User login
Examining the safety of lipid-lowering drugs in pregnancy
Lipid-lowering medications are some of the most commonly prescribed drugs in the United States. But while much is known about their general safety, the data are limited when it comes to pregnancy and breastfeeding.
Antilipemic agents are a pharmacologic class that contains 18 drugs. The class is divided into eight subclasses: bile acid sequestrants; fibric acid derivatives, HMG-CoA inhibitors; immunoglobulins; monoclonal antibodies; oligonucleotide inhibitors; vitamins; as well as two miscellaneous drugs, ezetimibe (Zetia) and lomitapide (Juxtapid). Another antilipemic – dextrothyroxine – has been removed from the market by the manufacturer.
Bile acid sequestrants
Bile acid sequestrants include cholestyramine (Prevalite, Questran), colesevelam (Welchol), and colestipol (Colestid). These drugs have the potential to cause fetal toxicity. This assessment is based on their mechanism of action. These agents are not absorbed systemically, or absorption is very poor and they bind bile acids into a nonabsorbable complex. This action can reduce intestinal absorption of fat-soluble vitamins A, D, E, and K.
Reports of fetal harm have not been located for the other two agents in this class, but there is only one case report involving five women for colesevelam and no reports for colestipol. Nevertheless, both of these drugs have the potential to cause fetal hemorrhage if they are taken for prolonged periods in pregnancy.
Fibric acid derivatives
The fibric acid derivatives subclass includes fenofibrate (Tricor, Lofibra) and gemfibrozil (Lopid).
Six reports, involving 13 pregnancies, have described the use of gemfibrozil during all phases of pregnancy. No teratogenic effects were observed in these cases. In one woman, similar concentrations of gemfibrozil and its active metabolite were found in the umbilical vein and artery at levels within the normal reference for adults.
Statins
There are seven HMG-CoA inhibitors, known as statins: atorvastatin (Lipitor), fluvastatin (Lescol), lovastatin (Mevacor), pitavastatin (Livalo), pravastatin (Pravachol), rosuvastatin (Crestor), and simvastatin (Zocor).
The interruption of cholesterol-lowering therapy during pregnancy should have no effect on the long-term treatment of hyperlipidemia. Moreover, cholesterol and products synthesized by cholesterol are important during fetal development as shown by the rise in maternal cholesterol levels during pregnancy. Although the potential for embryo-fetal harm has not been clearly documented, and that potential may eventually be confirmed as low, the use of these agents in the first trimester are best classified as contraindicated.
One consideration in estimating the embryo-fetal risk of statins is their classification as either lipophilic or hydrophilic. Three of the seven statins are hydrophilic (fluvastatin, pravastatin, and rosuvastatin); the remaining four agents are lipophilic. In a 2004 review of 70 reports, all adverse birth outcomes were reported following exposure to lipophilic statins (atorvastatin, lovastatin, or simvastatin) and none with the hydrophilic pravastatin. The authors stated that the findings were due to the fact that lipophilic agents equilibrate between maternal and embryonic compartments, whereas pravastatin is minimally present in the embryo.3 If this is indeed the case, and a statin must be used during pregnancy, fluvastatin, pravastatin, or rosuvastatin appears to be best.
Pravastatin also has been used for the prevention and treatment of preeclampsia.5,6 Although the teratogenic potential of these agents has not been fully determined, the risk for birth defects, if any, appears to be low even when exposure occurs during organogenesis.7,8,9 Nevertheless, avoiding these products during the first trimester appears to be best.
Immunoglobulins
The only immunoglobulin in the antilipemic class is evolocumab (Repatha), which has no human pregnancy data. It is an immunoglobulin G2 that is indicated as an adjunct to diet and maximally tolerated statin therapy. It is also indicated as an adjunct to diet and other low-density lipoprotein–lowering therapies in patients with homozygous familial hypercholesterolemia who require additional lowering. No adverse embryo-fetal effects were observed in monkeys. Because statins are contraindicated in the first trimester, the drug, if combined with a statin, can also be classified as contraindicated. However, if the drug is used alone, the embryo-fetal risk appears to be low based on the animal data.
Monoclonal antibodies
The protein alirocumab (Praluent) is a human monoclonal antibody. It is indicated as an adjunct to diet and maximally tolerated statin therapy for the treatment of adults with heterozygous familial hypercholesterolemia or clinical atherosclerotic cardiovascular disease. There are no human pregnancy data. The animal data in rats and monkeys suggest low embryo-fetal risk. However, suppression of the humoral immune response to keyhole hemocyanin antigen was observed in infant monkeys at 4-6 months of age. The significance of this in human infants is apparently unknown. Because statins are contraindicated in the first trimester, the drug should not be used with these agents during that period.
Oligonucleotide inhibitors
No reports describing the use of mipomersen (Kynamro), an oligonucleotide inhibitor of apolipoprotein B-100 synthesis, in human pregnancy have been located. The drug is indicated as an adjunct to lipid-lowering medications and diet to reduce low-density lipoprotein cholesterol, apolipoprotein B, total cholesterol, and non–high-density lipoprotein cholesterol in patients with homozygous familial hypercholesterolemia. It has a very long (1-2 months) elimination half-life. The drug caused fetal toxicity in rats, but not in mice or rabbits.
Vitamins
Niacin is a water-soluble B complex vitamin that is converted in vivo to niacinamide. Niacin has no known embryo-fetal risk.
Miscellaneous agents
The two agents in the miscellaneous category are ezetimibe and lomitapide. Ezetimibe is indicated, either alone or in combination with a statin, as adjunctive therapy to diet for the reduction of cholesterol and triglycerides. Statins are contraindicated in the first trimester, but ezetimibe alone could be used during that period if treatment of the mother was mandated. The drug caused no problems in rabbits, but in rats, a dose 10 times the human exposure increased the incidence of skeletal abnormalities. In one report, a woman with homozygous familial hypercholesterolemia was treated with direct adsorption of lipoprotein apheresis, ezetimibe, and rosuvastatin. When pregnancy was discovered (gestational age not specified), the two drugs were stopped but biweekly apheresis was continued. At 37 weeks’ gestation, the patient gave birth to a healthy 2,400-g male infant.10
There are no human pregnancy data with lomitapide. It is indicated as an adjunct to a low-fat diet and other lipid-lowering treatments, including low-density lipoprotein apheresis where available, to reduce LDL cholesterol, total cholesterol, apolipoprotein B, and non–high-density lipoprotein cholesterol in patients with homozygous familial hypercholesterolemia. At doses less than 10 times the human dose, the drug caused congenital malformations and embryo-fetal death in rats, rabbits, and ferrets. The manufacturer classifies the drug as contraindicated in pregnancy because of the animal data.
Breastfeeding
Only niacin, pravastatin, and rosuvastatin have data regarding human milk concentrations. Niacin and its active form – niacinamide – are excreted into breast milk.
The average peak milk level in 11 lactating women given pravastatin 20 mg twice daily for 2.5 days was 3.9 mcg/L, whereas the level for the active metabolite was 2.1 mcg/L. Based on these data, a fully breastfed infant would receive daily about 1.4% of the mother’s weight-adjusted dose.11
A 31-year-old woman was treated with rosuvastatin for familial hypercholesterolemia while breastfeeding her infant. The drug was stopped during breastfeeding but was restarted at 33 days post partum. Breast milk concentrations of the drug were 1.2 times serum levels (about 22 ng/mL vs. 18 ng/mL). Unfortunately, no information was provided on the status of the nursing infant.12
Three of the above agents have high molecular weights - alirocumab, evolocumab, and mipomersen - and are probably not excreted into mature breast milk. Moreover, colesevelam is not absorbed, and very small amounts of colestipol are absorbed by mothers. Several antilipemic agents have characteristics (for example, low molecular weight or long elimination half-life) that suggest they will be excreted into breast milk: ezetimibe, fenofibric acid (active metabolite of fenofibrate), gemfibrozil, lomitapide, and all the statins.
Taken in sum, all of the antilipemics, with the exception of niacin, have the potential to cause a deficiency of fat-soluble vitamins (A, D, E, K) in mother’s milk and in the nursing infant. Deficiency is a concern for all of these vitamins, but especially for vitamin K, because it could cause bruising, petechiae, hematomas, and bleeding in the nursing infant. In addition, antilipemics could cause low levels in milk of cholesterol and lipids, which are required by a nursing infant. Consequently, they should not be used by mothers who are breastfeeding an infant.
References
1. Br J Obstet Gynaecol. 1995 Feb;102(2):169-70.
2. J Matern Fetal Neonatal Med. 2015 May;28(8):954-8.
3. Am J Med Genet A. 2004 Dec 15;131(3):287-98.
4. J Clin Invest. 2016 Aug 1;126(8):2933-40.
5. Hypertension. 2015 Sep;66(3):687-97.
6. Am J Obstet Gynecol. 2016 Jun;214(6):720.e1-720.e17.
7. Birth Defects Res A Clin Mol Teratol. 2005 Nov;73(11):888-96.
8. Reprod Toxicol. 2008 Oct;26(2):175-7.
9. Ann Pharmacother. 2012 Oct;46(10):1419-24.
10. Open Cardiovasc Med J. 2015 Dec 29;9:114-7.
11. J Clin Pharmacol. 1988;28:942.
12. Am J Med. 2013 Sep;126(9):e7-e8.
Mr. Briggs is clinical professor of pharmacy at the University of California, San Francisco, and adjunct professor of pharmacy at the University of Southern California, Los Angeles, and Washington State University, Spokane. He is coauthor of “Drugs in Pregnancy and Lactation,” and coeditor of “Diseases, Complications, and Drug Therapy in Obstetrics.” He has no relevant financial disclosures.
Lipid-lowering medications are some of the most commonly prescribed drugs in the United States. But while much is known about their general safety, the data are limited when it comes to pregnancy and breastfeeding.
Antilipemic agents are a pharmacologic class that contains 18 drugs. The class is divided into eight subclasses: bile acid sequestrants; fibric acid derivatives, HMG-CoA inhibitors; immunoglobulins; monoclonal antibodies; oligonucleotide inhibitors; vitamins; as well as two miscellaneous drugs, ezetimibe (Zetia) and lomitapide (Juxtapid). Another antilipemic – dextrothyroxine – has been removed from the market by the manufacturer.
Bile acid sequestrants
Bile acid sequestrants include cholestyramine (Prevalite, Questran), colesevelam (Welchol), and colestipol (Colestid). These drugs have the potential to cause fetal toxicity. This assessment is based on their mechanism of action. These agents are not absorbed systemically, or absorption is very poor and they bind bile acids into a nonabsorbable complex. This action can reduce intestinal absorption of fat-soluble vitamins A, D, E, and K.
Reports of fetal harm have not been located for the other two agents in this class, but there is only one case report involving five women for colesevelam and no reports for colestipol. Nevertheless, both of these drugs have the potential to cause fetal hemorrhage if they are taken for prolonged periods in pregnancy.
Fibric acid derivatives
The fibric acid derivatives subclass includes fenofibrate (Tricor, Lofibra) and gemfibrozil (Lopid).
Six reports, involving 13 pregnancies, have described the use of gemfibrozil during all phases of pregnancy. No teratogenic effects were observed in these cases. In one woman, similar concentrations of gemfibrozil and its active metabolite were found in the umbilical vein and artery at levels within the normal reference for adults.
Statins
There are seven HMG-CoA inhibitors, known as statins: atorvastatin (Lipitor), fluvastatin (Lescol), lovastatin (Mevacor), pitavastatin (Livalo), pravastatin (Pravachol), rosuvastatin (Crestor), and simvastatin (Zocor).
The interruption of cholesterol-lowering therapy during pregnancy should have no effect on the long-term treatment of hyperlipidemia. Moreover, cholesterol and products synthesized by cholesterol are important during fetal development as shown by the rise in maternal cholesterol levels during pregnancy. Although the potential for embryo-fetal harm has not been clearly documented, and that potential may eventually be confirmed as low, the use of these agents in the first trimester are best classified as contraindicated.
One consideration in estimating the embryo-fetal risk of statins is their classification as either lipophilic or hydrophilic. Three of the seven statins are hydrophilic (fluvastatin, pravastatin, and rosuvastatin); the remaining four agents are lipophilic. In a 2004 review of 70 reports, all adverse birth outcomes were reported following exposure to lipophilic statins (atorvastatin, lovastatin, or simvastatin) and none with the hydrophilic pravastatin. The authors stated that the findings were due to the fact that lipophilic agents equilibrate between maternal and embryonic compartments, whereas pravastatin is minimally present in the embryo.3 If this is indeed the case, and a statin must be used during pregnancy, fluvastatin, pravastatin, or rosuvastatin appears to be best.
Pravastatin also has been used for the prevention and treatment of preeclampsia.5,6 Although the teratogenic potential of these agents has not been fully determined, the risk for birth defects, if any, appears to be low even when exposure occurs during organogenesis.7,8,9 Nevertheless, avoiding these products during the first trimester appears to be best.
Immunoglobulins
The only immunoglobulin in the antilipemic class is evolocumab (Repatha), which has no human pregnancy data. It is an immunoglobulin G2 that is indicated as an adjunct to diet and maximally tolerated statin therapy. It is also indicated as an adjunct to diet and other low-density lipoprotein–lowering therapies in patients with homozygous familial hypercholesterolemia who require additional lowering. No adverse embryo-fetal effects were observed in monkeys. Because statins are contraindicated in the first trimester, the drug, if combined with a statin, can also be classified as contraindicated. However, if the drug is used alone, the embryo-fetal risk appears to be low based on the animal data.
Monoclonal antibodies
The protein alirocumab (Praluent) is a human monoclonal antibody. It is indicated as an adjunct to diet and maximally tolerated statin therapy for the treatment of adults with heterozygous familial hypercholesterolemia or clinical atherosclerotic cardiovascular disease. There are no human pregnancy data. The animal data in rats and monkeys suggest low embryo-fetal risk. However, suppression of the humoral immune response to keyhole hemocyanin antigen was observed in infant monkeys at 4-6 months of age. The significance of this in human infants is apparently unknown. Because statins are contraindicated in the first trimester, the drug should not be used with these agents during that period.
Oligonucleotide inhibitors
No reports describing the use of mipomersen (Kynamro), an oligonucleotide inhibitor of apolipoprotein B-100 synthesis, in human pregnancy have been located. The drug is indicated as an adjunct to lipid-lowering medications and diet to reduce low-density lipoprotein cholesterol, apolipoprotein B, total cholesterol, and non–high-density lipoprotein cholesterol in patients with homozygous familial hypercholesterolemia. It has a very long (1-2 months) elimination half-life. The drug caused fetal toxicity in rats, but not in mice or rabbits.
Vitamins
Niacin is a water-soluble B complex vitamin that is converted in vivo to niacinamide. Niacin has no known embryo-fetal risk.
Miscellaneous agents
The two agents in the miscellaneous category are ezetimibe and lomitapide. Ezetimibe is indicated, either alone or in combination with a statin, as adjunctive therapy to diet for the reduction of cholesterol and triglycerides. Statins are contraindicated in the first trimester, but ezetimibe alone could be used during that period if treatment of the mother was mandated. The drug caused no problems in rabbits, but in rats, a dose 10 times the human exposure increased the incidence of skeletal abnormalities. In one report, a woman with homozygous familial hypercholesterolemia was treated with direct adsorption of lipoprotein apheresis, ezetimibe, and rosuvastatin. When pregnancy was discovered (gestational age not specified), the two drugs were stopped but biweekly apheresis was continued. At 37 weeks’ gestation, the patient gave birth to a healthy 2,400-g male infant.10
There are no human pregnancy data with lomitapide. It is indicated as an adjunct to a low-fat diet and other lipid-lowering treatments, including low-density lipoprotein apheresis where available, to reduce LDL cholesterol, total cholesterol, apolipoprotein B, and non–high-density lipoprotein cholesterol in patients with homozygous familial hypercholesterolemia. At doses less than 10 times the human dose, the drug caused congenital malformations and embryo-fetal death in rats, rabbits, and ferrets. The manufacturer classifies the drug as contraindicated in pregnancy because of the animal data.
Breastfeeding
Only niacin, pravastatin, and rosuvastatin have data regarding human milk concentrations. Niacin and its active form – niacinamide – are excreted into breast milk.
The average peak milk level in 11 lactating women given pravastatin 20 mg twice daily for 2.5 days was 3.9 mcg/L, whereas the level for the active metabolite was 2.1 mcg/L. Based on these data, a fully breastfed infant would receive daily about 1.4% of the mother’s weight-adjusted dose.11
A 31-year-old woman was treated with rosuvastatin for familial hypercholesterolemia while breastfeeding her infant. The drug was stopped during breastfeeding but was restarted at 33 days post partum. Breast milk concentrations of the drug were 1.2 times serum levels (about 22 ng/mL vs. 18 ng/mL). Unfortunately, no information was provided on the status of the nursing infant.12
Three of the above agents have high molecular weights - alirocumab, evolocumab, and mipomersen - and are probably not excreted into mature breast milk. Moreover, colesevelam is not absorbed, and very small amounts of colestipol are absorbed by mothers. Several antilipemic agents have characteristics (for example, low molecular weight or long elimination half-life) that suggest they will be excreted into breast milk: ezetimibe, fenofibric acid (active metabolite of fenofibrate), gemfibrozil, lomitapide, and all the statins.
Taken in sum, all of the antilipemics, with the exception of niacin, have the potential to cause a deficiency of fat-soluble vitamins (A, D, E, K) in mother’s milk and in the nursing infant. Deficiency is a concern for all of these vitamins, but especially for vitamin K, because it could cause bruising, petechiae, hematomas, and bleeding in the nursing infant. In addition, antilipemics could cause low levels in milk of cholesterol and lipids, which are required by a nursing infant. Consequently, they should not be used by mothers who are breastfeeding an infant.
References
1. Br J Obstet Gynaecol. 1995 Feb;102(2):169-70.
2. J Matern Fetal Neonatal Med. 2015 May;28(8):954-8.
3. Am J Med Genet A. 2004 Dec 15;131(3):287-98.
4. J Clin Invest. 2016 Aug 1;126(8):2933-40.
5. Hypertension. 2015 Sep;66(3):687-97.
6. Am J Obstet Gynecol. 2016 Jun;214(6):720.e1-720.e17.
7. Birth Defects Res A Clin Mol Teratol. 2005 Nov;73(11):888-96.
8. Reprod Toxicol. 2008 Oct;26(2):175-7.
9. Ann Pharmacother. 2012 Oct;46(10):1419-24.
10. Open Cardiovasc Med J. 2015 Dec 29;9:114-7.
11. J Clin Pharmacol. 1988;28:942.
12. Am J Med. 2013 Sep;126(9):e7-e8.
Mr. Briggs is clinical professor of pharmacy at the University of California, San Francisco, and adjunct professor of pharmacy at the University of Southern California, Los Angeles, and Washington State University, Spokane. He is coauthor of “Drugs in Pregnancy and Lactation,” and coeditor of “Diseases, Complications, and Drug Therapy in Obstetrics.” He has no relevant financial disclosures.
Lipid-lowering medications are some of the most commonly prescribed drugs in the United States. But while much is known about their general safety, the data are limited when it comes to pregnancy and breastfeeding.
Antilipemic agents are a pharmacologic class that contains 18 drugs. The class is divided into eight subclasses: bile acid sequestrants; fibric acid derivatives, HMG-CoA inhibitors; immunoglobulins; monoclonal antibodies; oligonucleotide inhibitors; vitamins; as well as two miscellaneous drugs, ezetimibe (Zetia) and lomitapide (Juxtapid). Another antilipemic – dextrothyroxine – has been removed from the market by the manufacturer.
Bile acid sequestrants
Bile acid sequestrants include cholestyramine (Prevalite, Questran), colesevelam (Welchol), and colestipol (Colestid). These drugs have the potential to cause fetal toxicity. This assessment is based on their mechanism of action. These agents are not absorbed systemically, or absorption is very poor and they bind bile acids into a nonabsorbable complex. This action can reduce intestinal absorption of fat-soluble vitamins A, D, E, and K.
Reports of fetal harm have not been located for the other two agents in this class, but there is only one case report involving five women for colesevelam and no reports for colestipol. Nevertheless, both of these drugs have the potential to cause fetal hemorrhage if they are taken for prolonged periods in pregnancy.
Fibric acid derivatives
The fibric acid derivatives subclass includes fenofibrate (Tricor, Lofibra) and gemfibrozil (Lopid).
Six reports, involving 13 pregnancies, have described the use of gemfibrozil during all phases of pregnancy. No teratogenic effects were observed in these cases. In one woman, similar concentrations of gemfibrozil and its active metabolite were found in the umbilical vein and artery at levels within the normal reference for adults.
Statins
There are seven HMG-CoA inhibitors, known as statins: atorvastatin (Lipitor), fluvastatin (Lescol), lovastatin (Mevacor), pitavastatin (Livalo), pravastatin (Pravachol), rosuvastatin (Crestor), and simvastatin (Zocor).
The interruption of cholesterol-lowering therapy during pregnancy should have no effect on the long-term treatment of hyperlipidemia. Moreover, cholesterol and products synthesized by cholesterol are important during fetal development as shown by the rise in maternal cholesterol levels during pregnancy. Although the potential for embryo-fetal harm has not been clearly documented, and that potential may eventually be confirmed as low, the use of these agents in the first trimester are best classified as contraindicated.
One consideration in estimating the embryo-fetal risk of statins is their classification as either lipophilic or hydrophilic. Three of the seven statins are hydrophilic (fluvastatin, pravastatin, and rosuvastatin); the remaining four agents are lipophilic. In a 2004 review of 70 reports, all adverse birth outcomes were reported following exposure to lipophilic statins (atorvastatin, lovastatin, or simvastatin) and none with the hydrophilic pravastatin. The authors stated that the findings were due to the fact that lipophilic agents equilibrate between maternal and embryonic compartments, whereas pravastatin is minimally present in the embryo.3 If this is indeed the case, and a statin must be used during pregnancy, fluvastatin, pravastatin, or rosuvastatin appears to be best.
Pravastatin also has been used for the prevention and treatment of preeclampsia.5,6 Although the teratogenic potential of these agents has not been fully determined, the risk for birth defects, if any, appears to be low even when exposure occurs during organogenesis.7,8,9 Nevertheless, avoiding these products during the first trimester appears to be best.
Immunoglobulins
The only immunoglobulin in the antilipemic class is evolocumab (Repatha), which has no human pregnancy data. It is an immunoglobulin G2 that is indicated as an adjunct to diet and maximally tolerated statin therapy. It is also indicated as an adjunct to diet and other low-density lipoprotein–lowering therapies in patients with homozygous familial hypercholesterolemia who require additional lowering. No adverse embryo-fetal effects were observed in monkeys. Because statins are contraindicated in the first trimester, the drug, if combined with a statin, can also be classified as contraindicated. However, if the drug is used alone, the embryo-fetal risk appears to be low based on the animal data.
Monoclonal antibodies
The protein alirocumab (Praluent) is a human monoclonal antibody. It is indicated as an adjunct to diet and maximally tolerated statin therapy for the treatment of adults with heterozygous familial hypercholesterolemia or clinical atherosclerotic cardiovascular disease. There are no human pregnancy data. The animal data in rats and monkeys suggest low embryo-fetal risk. However, suppression of the humoral immune response to keyhole hemocyanin antigen was observed in infant monkeys at 4-6 months of age. The significance of this in human infants is apparently unknown. Because statins are contraindicated in the first trimester, the drug should not be used with these agents during that period.
Oligonucleotide inhibitors
No reports describing the use of mipomersen (Kynamro), an oligonucleotide inhibitor of apolipoprotein B-100 synthesis, in human pregnancy have been located. The drug is indicated as an adjunct to lipid-lowering medications and diet to reduce low-density lipoprotein cholesterol, apolipoprotein B, total cholesterol, and non–high-density lipoprotein cholesterol in patients with homozygous familial hypercholesterolemia. It has a very long (1-2 months) elimination half-life. The drug caused fetal toxicity in rats, but not in mice or rabbits.
Vitamins
Niacin is a water-soluble B complex vitamin that is converted in vivo to niacinamide. Niacin has no known embryo-fetal risk.
Miscellaneous agents
The two agents in the miscellaneous category are ezetimibe and lomitapide. Ezetimibe is indicated, either alone or in combination with a statin, as adjunctive therapy to diet for the reduction of cholesterol and triglycerides. Statins are contraindicated in the first trimester, but ezetimibe alone could be used during that period if treatment of the mother was mandated. The drug caused no problems in rabbits, but in rats, a dose 10 times the human exposure increased the incidence of skeletal abnormalities. In one report, a woman with homozygous familial hypercholesterolemia was treated with direct adsorption of lipoprotein apheresis, ezetimibe, and rosuvastatin. When pregnancy was discovered (gestational age not specified), the two drugs were stopped but biweekly apheresis was continued. At 37 weeks’ gestation, the patient gave birth to a healthy 2,400-g male infant.10
There are no human pregnancy data with lomitapide. It is indicated as an adjunct to a low-fat diet and other lipid-lowering treatments, including low-density lipoprotein apheresis where available, to reduce LDL cholesterol, total cholesterol, apolipoprotein B, and non–high-density lipoprotein cholesterol in patients with homozygous familial hypercholesterolemia. At doses less than 10 times the human dose, the drug caused congenital malformations and embryo-fetal death in rats, rabbits, and ferrets. The manufacturer classifies the drug as contraindicated in pregnancy because of the animal data.
Breastfeeding
Only niacin, pravastatin, and rosuvastatin have data regarding human milk concentrations. Niacin and its active form – niacinamide – are excreted into breast milk.
The average peak milk level in 11 lactating women given pravastatin 20 mg twice daily for 2.5 days was 3.9 mcg/L, whereas the level for the active metabolite was 2.1 mcg/L. Based on these data, a fully breastfed infant would receive daily about 1.4% of the mother’s weight-adjusted dose.11
A 31-year-old woman was treated with rosuvastatin for familial hypercholesterolemia while breastfeeding her infant. The drug was stopped during breastfeeding but was restarted at 33 days post partum. Breast milk concentrations of the drug were 1.2 times serum levels (about 22 ng/mL vs. 18 ng/mL). Unfortunately, no information was provided on the status of the nursing infant.12
Three of the above agents have high molecular weights - alirocumab, evolocumab, and mipomersen - and are probably not excreted into mature breast milk. Moreover, colesevelam is not absorbed, and very small amounts of colestipol are absorbed by mothers. Several antilipemic agents have characteristics (for example, low molecular weight or long elimination half-life) that suggest they will be excreted into breast milk: ezetimibe, fenofibric acid (active metabolite of fenofibrate), gemfibrozil, lomitapide, and all the statins.
Taken in sum, all of the antilipemics, with the exception of niacin, have the potential to cause a deficiency of fat-soluble vitamins (A, D, E, K) in mother’s milk and in the nursing infant. Deficiency is a concern for all of these vitamins, but especially for vitamin K, because it could cause bruising, petechiae, hematomas, and bleeding in the nursing infant. In addition, antilipemics could cause low levels in milk of cholesterol and lipids, which are required by a nursing infant. Consequently, they should not be used by mothers who are breastfeeding an infant.
References
1. Br J Obstet Gynaecol. 1995 Feb;102(2):169-70.
2. J Matern Fetal Neonatal Med. 2015 May;28(8):954-8.
3. Am J Med Genet A. 2004 Dec 15;131(3):287-98.
4. J Clin Invest. 2016 Aug 1;126(8):2933-40.
5. Hypertension. 2015 Sep;66(3):687-97.
6. Am J Obstet Gynecol. 2016 Jun;214(6):720.e1-720.e17.
7. Birth Defects Res A Clin Mol Teratol. 2005 Nov;73(11):888-96.
8. Reprod Toxicol. 2008 Oct;26(2):175-7.
9. Ann Pharmacother. 2012 Oct;46(10):1419-24.
10. Open Cardiovasc Med J. 2015 Dec 29;9:114-7.
11. J Clin Pharmacol. 1988;28:942.
12. Am J Med. 2013 Sep;126(9):e7-e8.
Mr. Briggs is clinical professor of pharmacy at the University of California, San Francisco, and adjunct professor of pharmacy at the University of Southern California, Los Angeles, and Washington State University, Spokane. He is coauthor of “Drugs in Pregnancy and Lactation,” and coeditor of “Diseases, Complications, and Drug Therapy in Obstetrics.” He has no relevant financial disclosures.
Alarming gaps in gestational diabetes care
BY E. ALBERT REECE, MD, PhD, MBA
Much attention has been given in the media to the incidence of prediabetes in the general population. The Centers for Disease Control and Prevention estimates that approximately 86 million adults have prediabetes, and that the incidence of this condition is similar across racial and ethnic groups. Indeed, the seriousness of this public health concern prompted the Centers for Medicare & Medicaid Services to expand Medicare coverage for interventions for people with prediabetes, a move that was finalized in November 2016.
Despite a widespread focus on the need to prevent prediabetes from becoming type 2 diabetes, women diagnosed with gestational diabetes mellitus (GDM), which accounts for about 9% of women in the United States, may not be receiving critical advice and care.
The investigators analyzed data collected via the National Health and Nutrition Examination Survey from 2007-2012, and identified 284 women with a history of GDM. Only 67% of these women received diabetes screening, and approximately one-third of women included in the study had undiagnosed prediabetes and diabetes. The authors concluded that prediabetes in women who have had GDM may be underdiagnosed. They argued that women with GDM should be encouraged to have additional health visits and screenings to prevent the development of prediabetes or diabetes. Considering the fact that a number of studies have shown that GDM predisposes a woman to developing type 2 diabetes, the University of Illinois findings are alarming.
As ob.gyns., we have increasingly become a woman’s only health care practitioner. Although individuals may skip annual exams with a primary care physician, during which blood work is typically drawn, many women will see their ob.gyn. for regular check-ups. Therefore, we have a unique role to play in our patients’ lifelong health. This is especially important during pregnancy, when it may be easy to focus only on the mother’s health as it pertains to the health of the baby, rather than her health in pregnancy as it may affect her long-term well-being.
We have invited Robert Ratner, MD, the chief scientific and medical officer at the American Diabetes Association, to discuss the need to carefully follow up with patients who have had GDM and to educate them about their risk for developing type 2 diabetes later in life.
Dr. Reece, who specializes in maternal-fetal medicine, is vice president for medical affairs at the University of Maryland, Baltimore, as well as the John Z. and Akiko K. Bowers Distinguished Professor and dean of the school of medicine. Dr. Reece said he had no relevant financial disclosures. He is the medical editor of this column. Contact him at [email protected].
Why postpartum GDM follow-up is so important
BY ROBERT E. RATNER, MD
Much of the attention paid to diagnosing gestational diabetes has focused on the fetus and on babies being born very large. However, it is important to appreciate that the original definitions of the condition were based entirely on the long-term outcomes of the mother.
John O’Sullivan, MD, and statistician Claire Mahan published diagnostic criteria in 1964 after performing 3-hour oral glucose tolerance tests (OGTTs) in more than 500 unselected women during their pregnancies, and then following these women and babies out as far as 23 years. Retrospectively, Dr. O’Sullivan and Ms. Mahan defined gestational diabetes mellitus (GDM) as glucose values exceeding two standard deviations above the mean on two out of four OGTT values. 
They came to their conclusions after tracking the later development of diabetes outside of pregnancy. More than 20 years later, 70% of women with the higher OGTT values had developed type 2 diabetes, compared with approximately 10% of women who did not have higher values during pregnancy. The O’Sullivan criteria were established, essentially, based on their association with the development of diabetes after pregnancy. In addition to being a significant predictor of subsequent diabetes, a history of GDM also conferred a three- to fourfold increase in maternal mortality.
Fifty-some years later, these findings have been affirmed through additional research and are the crux of what drives the current recommendations for postpartum follow-up of women with a history of GDM.
Long-term maternal risks
Postpartum, the current recommendation from both the American Diabetes Association and the American College of Obstetricians and Gynecologists is that women with GDM be tested at 6-12 weeks after delivery to ensure that the diabetes has resolved.
This recommendation for initial postpartum testing carries with it a stipulation that’s different from subsequent postpartum testing. It says that postpartum testing at 6-12 weeks should be performed with either a fasting glucose test or a 2-hour OGTT. Since hemoglobin A1c may still be impacted by the rapid red blood cell turnover in pregnancy or blood loss at delivery, A1c testing lacks sensitivity for identifying diabetes during this window of time.
Initial postpartum testing also serves as a way to identify whether the diabetes during pregnancy was preexisting or purely secondary to the hormonal changes associated with the pregnancy.
If this first postpartum test shows diabetes, the patient most likely had preexisting diabetes, and therapy must be initiated immediately. In the case of a normal result, the patient remains at higher risk for the development of type 2 diabetes essentially for the rest of her life and should be tested at least every 3 years for the occurrence of the disease.
Much of the increased risk for different ethnic groups occurs within 5 years of the index pregnancy. This was shown in a systematic review led by Catherine Kim, MD; the review examined more than two dozen studies with follow-up of up to 28 years postpartum. The cumulative incidence of type 2 diabetes increased markedly in the first 5 years and then appeared to plateau after 10 years (Diabetes Care. 2002 Oct;25[10]:1862-8).
The best data on late-occurring diabetes following GDM comes from the multicenter National Institutes of Health–sponsored Diabetes Prevention Program (DPP) trial, which randomized more than 3,000 individuals with baseline impaired glucose tolerance – or prediabetes – to one of two interventions: metformin therapy or intensive lifestyle intervention, or to placebo.
Within this population, there were more than 1,700 women who had a previous live birth. Of these women, 350 reported a history of GDM at a mean of 12 years since the delivery of their first GDM pregnancy. The DPP gave us the opportunity, therefore, to look at a large group of women about 12 years away from their GDM pregnancy who had abnormal glucose levels but had not reached the level of type 2 diabetes, and compare them with women with similarly impaired glucose tolerance who did not have a history of GDM.
There were interesting similarities and differences. Women with a GDM history were on average 8 years younger than women without a GDM history, but they had comparable BMIs. In addition, within the placebo arm, we could observe the natural history of glucose intolerance in women with and without a history of GDM. Despite both groups entering the study with equivalent degrees of impaired glucose tolerance and similar BMI, women with a history of GDM had a 71% higher risk of developing diabetes during the 3-year intervention period than that of parous women without a history of GDM (J Clin Endocrinol Metab. 2008 Dec;93[12]:4774-9).
Clearly, there was something about the history of GDM that puts these women at greater risk for diabetes than women who had the same impaired glucose tolerance, but no GDM. The study demonstrated that GDM is an exceptionally strong predictor of the development of type 2 diabetes, even for those who manage to escape diabetes for the first 10 years.
Postpartum prevention
The DPP demonstrated, moreover, that intensive lifestyle therapy and metformin not only were both effective, but that they were equally effective, in delaying or preventing diabetes in women with impaired glucose tolerance and a history of GDM. Both reduced the risk by about 50% at 3 years. This was striking because in parous women without GDM, the reductions were 49% and 14%, respectively. Metformin thus appeared to be more effective in women with a history of GDM.
The effects of the interventions persisted over a 10-year follow up of the DPP population. In women with a history of GDM, the intensive lifestyle intervention and metformin reduced progression to diabetes by 35% and 40%, respectively, over 10 years (J Clin Endocrinol Metab. 2015 Apr;100[4]:1646-53).
Pregnancy presents a stress test for beta cell function, and gestational diabetes clearly is a harbinger of further deterioration in beta-cell function and metabolic abnormalities in the mother. Because of these risks and because early intervention makes a difference, surveillance is critically important. Most women see their ob.gyn. as their primary care physician in the 10 years following a pregnancy – the time when more than 50% of all cases of subsequent diabetes will occur – and many continue to see their ob.gyns. in the longer term, as their risk continues to linger.
Immediately after a pregnancy with GDM, ob.gyns. can counsel women not only about their risks of developing type 2 diabetes and the importance of screening, but also about the beneficial impact of lifestyle modification, caloric restriction and weight loss if necessary, and increased exercise. Mothers should also know that GDM is a family affair, and that lifestyle changes that are beneficial for the mother will be equally beneficial for the baby.
The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study taught us that there are continuous linear relationships between maternal glucose and adverse fetal outcomes like birth weight and percent body fat greater than the 90th percentile. Longitudinal studies of the Pima Indians showed us that offspring of women who had diabetes during pregnancy were more likely to be obese and more likely to develop diabetes than offspring of women who did not have diabetes during pregnancy. Even when GDM has been well treated and controlled, we should have heightened awareness to the potential risks in the fetus and the growing child and adolescent.
Patients who are found to have subsequent type 2 diabetes should know that aggressive therapy early on in the natural history of the disease reduces the risk of microvascular and macrovascular complications. And as the DPP has demonstrated, lifestyle interventions and metformin may also keep women who are found to have prediabetes outside of pregnancy from progressing on to diabetes.
Dr. Ratner is the chief scientific and medical officer for the American Diabetes Association. He reported having no financial disclosures relevant to this Master Class.
BY E. ALBERT REECE, MD, PhD, MBA
Much attention has been given in the media to the incidence of prediabetes in the general population. The Centers for Disease Control and Prevention estimates that approximately 86 million adults have prediabetes, and that the incidence of this condition is similar across racial and ethnic groups. Indeed, the seriousness of this public health concern prompted the Centers for Medicare & Medicaid Services to expand Medicare coverage for interventions for people with prediabetes, a move that was finalized in November 2016.
Despite a widespread focus on the need to prevent prediabetes from becoming type 2 diabetes, women diagnosed with gestational diabetes mellitus (GDM), which accounts for about 9% of women in the United States, may not be receiving critical advice and care.
The investigators analyzed data collected via the National Health and Nutrition Examination Survey from 2007-2012, and identified 284 women with a history of GDM. Only 67% of these women received diabetes screening, and approximately one-third of women included in the study had undiagnosed prediabetes and diabetes. The authors concluded that prediabetes in women who have had GDM may be underdiagnosed. They argued that women with GDM should be encouraged to have additional health visits and screenings to prevent the development of prediabetes or diabetes. Considering the fact that a number of studies have shown that GDM predisposes a woman to developing type 2 diabetes, the University of Illinois findings are alarming.
As ob.gyns., we have increasingly become a woman’s only health care practitioner. Although individuals may skip annual exams with a primary care physician, during which blood work is typically drawn, many women will see their ob.gyn. for regular check-ups. Therefore, we have a unique role to play in our patients’ lifelong health. This is especially important during pregnancy, when it may be easy to focus only on the mother’s health as it pertains to the health of the baby, rather than her health in pregnancy as it may affect her long-term well-being.
We have invited Robert Ratner, MD, the chief scientific and medical officer at the American Diabetes Association, to discuss the need to carefully follow up with patients who have had GDM and to educate them about their risk for developing type 2 diabetes later in life.
Dr. Reece, who specializes in maternal-fetal medicine, is vice president for medical affairs at the University of Maryland, Baltimore, as well as the John Z. and Akiko K. Bowers Distinguished Professor and dean of the school of medicine. Dr. Reece said he had no relevant financial disclosures. He is the medical editor of this column. Contact him at [email protected].
Why postpartum GDM follow-up is so important
BY ROBERT E. RATNER, MD
Much of the attention paid to diagnosing gestational diabetes has focused on the fetus and on babies being born very large. However, it is important to appreciate that the original definitions of the condition were based entirely on the long-term outcomes of the mother.
John O’Sullivan, MD, and statistician Claire Mahan published diagnostic criteria in 1964 after performing 3-hour oral glucose tolerance tests (OGTTs) in more than 500 unselected women during their pregnancies, and then following these women and babies out as far as 23 years. Retrospectively, Dr. O’Sullivan and Ms. Mahan defined gestational diabetes mellitus (GDM) as glucose values exceeding two standard deviations above the mean on two out of four OGTT values.
They came to their conclusions after tracking the later development of diabetes outside of pregnancy. More than 20 years later, 70% of women with the higher OGTT values had developed type 2 diabetes, compared with approximately 10% of women who did not have higher values during pregnancy. The O’Sullivan criteria were established, essentially, based on their association with the development of diabetes after pregnancy. In addition to being a significant predictor of subsequent diabetes, a history of GDM also conferred a three- to fourfold increase in maternal mortality.
Fifty-some years later, these findings have been affirmed through additional research and are the crux of what drives the current recommendations for postpartum follow-up of women with a history of GDM.
Long-term maternal risks
Postpartum, the current recommendation from both the American Diabetes Association and the American College of Obstetricians and Gynecologists is that women with GDM be tested at 6-12 weeks after delivery to ensure that the diabetes has resolved.
This recommendation for initial postpartum testing carries with it a stipulation that’s different from subsequent postpartum testing. It says that postpartum testing at 6-12 weeks should be performed with either a fasting glucose test or a 2-hour OGTT. Since hemoglobin A1c may still be impacted by the rapid red blood cell turnover in pregnancy or blood loss at delivery, A1c testing lacks sensitivity for identifying diabetes during this window of time.
Initial postpartum testing also serves as a way to identify whether the diabetes during pregnancy was preexisting or purely secondary to the hormonal changes associated with the pregnancy.
If this first postpartum test shows diabetes, the patient most likely had preexisting diabetes, and therapy must be initiated immediately. In the case of a normal result, the patient remains at higher risk for the development of type 2 diabetes essentially for the rest of her life and should be tested at least every 3 years for the occurrence of the disease.
Much of the increased risk for different ethnic groups occurs within 5 years of the index pregnancy. This was shown in a systematic review led by Catherine Kim, MD; the review examined more than two dozen studies with follow-up of up to 28 years postpartum. The cumulative incidence of type 2 diabetes increased markedly in the first 5 years and then appeared to plateau after 10 years (Diabetes Care. 2002 Oct;25[10]:1862-8).
The best data on late-occurring diabetes following GDM comes from the multicenter National Institutes of Health–sponsored Diabetes Prevention Program (DPP) trial, which randomized more than 3,000 individuals with baseline impaired glucose tolerance – or prediabetes – to one of two interventions: metformin therapy or intensive lifestyle intervention, or to placebo.
Within this population, there were more than 1,700 women who had a previous live birth. Of these women, 350 reported a history of GDM at a mean of 12 years since the delivery of their first GDM pregnancy. The DPP gave us the opportunity, therefore, to look at a large group of women about 12 years away from their GDM pregnancy who had abnormal glucose levels but had not reached the level of type 2 diabetes, and compare them with women with similarly impaired glucose tolerance who did not have a history of GDM.
There were interesting similarities and differences. Women with a GDM history were on average 8 years younger than women without a GDM history, but they had comparable BMIs. In addition, within the placebo arm, we could observe the natural history of glucose intolerance in women with and without a history of GDM. Despite both groups entering the study with equivalent degrees of impaired glucose tolerance and similar BMI, women with a history of GDM had a 71% higher risk of developing diabetes during the 3-year intervention period than that of parous women without a history of GDM (J Clin Endocrinol Metab. 2008 Dec;93[12]:4774-9).
Clearly, there was something about the history of GDM that puts these women at greater risk for diabetes than women who had the same impaired glucose tolerance, but no GDM. The study demonstrated that GDM is an exceptionally strong predictor of the development of type 2 diabetes, even for those who manage to escape diabetes for the first 10 years.
Postpartum prevention
The DPP demonstrated, moreover, that intensive lifestyle therapy and metformin not only were both effective, but that they were equally effective, in delaying or preventing diabetes in women with impaired glucose tolerance and a history of GDM. Both reduced the risk by about 50% at 3 years. This was striking because in parous women without GDM, the reductions were 49% and 14%, respectively. Metformin thus appeared to be more effective in women with a history of GDM.
The effects of the interventions persisted over a 10-year follow up of the DPP population. In women with a history of GDM, the intensive lifestyle intervention and metformin reduced progression to diabetes by 35% and 40%, respectively, over 10 years (J Clin Endocrinol Metab. 2015 Apr;100[4]:1646-53).
Pregnancy presents a stress test for beta cell function, and gestational diabetes clearly is a harbinger of further deterioration in beta-cell function and metabolic abnormalities in the mother. Because of these risks and because early intervention makes a difference, surveillance is critically important. Most women see their ob.gyn. as their primary care physician in the 10 years following a pregnancy – the time when more than 50% of all cases of subsequent diabetes will occur – and many continue to see their ob.gyns. in the longer term, as their risk continues to linger.
Immediately after a pregnancy with GDM, ob.gyns. can counsel women not only about their risks of developing type 2 diabetes and the importance of screening, but also about the beneficial impact of lifestyle modification, caloric restriction and weight loss if necessary, and increased exercise. Mothers should also know that GDM is a family affair, and that lifestyle changes that are beneficial for the mother will be equally beneficial for the baby.
The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study taught us that there are continuous linear relationships between maternal glucose and adverse fetal outcomes like birth weight and percent body fat greater than the 90th percentile. Longitudinal studies of the Pima Indians showed us that offspring of women who had diabetes during pregnancy were more likely to be obese and more likely to develop diabetes than offspring of women who did not have diabetes during pregnancy. Even when GDM has been well treated and controlled, we should have heightened awareness to the potential risks in the fetus and the growing child and adolescent.
Patients who are found to have subsequent type 2 diabetes should know that aggressive therapy early on in the natural history of the disease reduces the risk of microvascular and macrovascular complications. And as the DPP has demonstrated, lifestyle interventions and metformin may also keep women who are found to have prediabetes outside of pregnancy from progressing on to diabetes.
Dr. Ratner is the chief scientific and medical officer for the American Diabetes Association. He reported having no financial disclosures relevant to this Master Class.
BY E. ALBERT REECE, MD, PhD, MBA
Much attention has been given in the media to the incidence of prediabetes in the general population. The Centers for Disease Control and Prevention estimates that approximately 86 million adults have prediabetes, and that the incidence of this condition is similar across racial and ethnic groups. Indeed, the seriousness of this public health concern prompted the Centers for Medicare & Medicaid Services to expand Medicare coverage for interventions for people with prediabetes, a move that was finalized in November 2016.
Despite a widespread focus on the need to prevent prediabetes from becoming type 2 diabetes, women diagnosed with gestational diabetes mellitus (GDM), which accounts for about 9% of women in the United States, may not be receiving critical advice and care.
The investigators analyzed data collected via the National Health and Nutrition Examination Survey from 2007-2012, and identified 284 women with a history of GDM. Only 67% of these women received diabetes screening, and approximately one-third of women included in the study had undiagnosed prediabetes and diabetes. The authors concluded that prediabetes in women who have had GDM may be underdiagnosed. They argued that women with GDM should be encouraged to have additional health visits and screenings to prevent the development of prediabetes or diabetes. Considering the fact that a number of studies have shown that GDM predisposes a woman to developing type 2 diabetes, the University of Illinois findings are alarming.
As ob.gyns., we have increasingly become a woman’s only health care practitioner. Although individuals may skip annual exams with a primary care physician, during which blood work is typically drawn, many women will see their ob.gyn. for regular check-ups. Therefore, we have a unique role to play in our patients’ lifelong health. This is especially important during pregnancy, when it may be easy to focus only on the mother’s health as it pertains to the health of the baby, rather than her health in pregnancy as it may affect her long-term well-being.
We have invited Robert Ratner, MD, the chief scientific and medical officer at the American Diabetes Association, to discuss the need to carefully follow up with patients who have had GDM and to educate them about their risk for developing type 2 diabetes later in life.
Dr. Reece, who specializes in maternal-fetal medicine, is vice president for medical affairs at the University of Maryland, Baltimore, as well as the John Z. and Akiko K. Bowers Distinguished Professor and dean of the school of medicine. Dr. Reece said he had no relevant financial disclosures. He is the medical editor of this column. Contact him at [email protected].
Why postpartum GDM follow-up is so important
BY ROBERT E. RATNER, MD
Much of the attention paid to diagnosing gestational diabetes has focused on the fetus and on babies being born very large. However, it is important to appreciate that the original definitions of the condition were based entirely on the long-term outcomes of the mother.
John O’Sullivan, MD, and statistician Claire Mahan published diagnostic criteria in 1964 after performing 3-hour oral glucose tolerance tests (OGTTs) in more than 500 unselected women during their pregnancies, and then following these women and babies out as far as 23 years. Retrospectively, Dr. O’Sullivan and Ms. Mahan defined gestational diabetes mellitus (GDM) as glucose values exceeding two standard deviations above the mean on two out of four OGTT values.
They came to their conclusions after tracking the later development of diabetes outside of pregnancy. More than 20 years later, 70% of women with the higher OGTT values had developed type 2 diabetes, compared with approximately 10% of women who did not have higher values during pregnancy. The O’Sullivan criteria were established, essentially, based on their association with the development of diabetes after pregnancy. In addition to being a significant predictor of subsequent diabetes, a history of GDM also conferred a three- to fourfold increase in maternal mortality.
Fifty-some years later, these findings have been affirmed through additional research and are the crux of what drives the current recommendations for postpartum follow-up of women with a history of GDM.
Long-term maternal risks
Postpartum, the current recommendation from both the American Diabetes Association and the American College of Obstetricians and Gynecologists is that women with GDM be tested at 6-12 weeks after delivery to ensure that the diabetes has resolved.
This recommendation for initial postpartum testing carries with it a stipulation that’s different from subsequent postpartum testing. It says that postpartum testing at 6-12 weeks should be performed with either a fasting glucose test or a 2-hour OGTT. Since hemoglobin A1c may still be impacted by the rapid red blood cell turnover in pregnancy or blood loss at delivery, A1c testing lacks sensitivity for identifying diabetes during this window of time.
Initial postpartum testing also serves as a way to identify whether the diabetes during pregnancy was preexisting or purely secondary to the hormonal changes associated with the pregnancy.
If this first postpartum test shows diabetes, the patient most likely had preexisting diabetes, and therapy must be initiated immediately. In the case of a normal result, the patient remains at higher risk for the development of type 2 diabetes essentially for the rest of her life and should be tested at least every 3 years for the occurrence of the disease.
Much of the increased risk for different ethnic groups occurs within 5 years of the index pregnancy. This was shown in a systematic review led by Catherine Kim, MD; the review examined more than two dozen studies with follow-up of up to 28 years postpartum. The cumulative incidence of type 2 diabetes increased markedly in the first 5 years and then appeared to plateau after 10 years (Diabetes Care. 2002 Oct;25[10]:1862-8).
The best data on late-occurring diabetes following GDM comes from the multicenter National Institutes of Health–sponsored Diabetes Prevention Program (DPP) trial, which randomized more than 3,000 individuals with baseline impaired glucose tolerance – or prediabetes – to one of two interventions: metformin therapy or intensive lifestyle intervention, or to placebo.
Within this population, there were more than 1,700 women who had a previous live birth. Of these women, 350 reported a history of GDM at a mean of 12 years since the delivery of their first GDM pregnancy. The DPP gave us the opportunity, therefore, to look at a large group of women about 12 years away from their GDM pregnancy who had abnormal glucose levels but had not reached the level of type 2 diabetes, and compare them with women with similarly impaired glucose tolerance who did not have a history of GDM.
There were interesting similarities and differences. Women with a GDM history were on average 8 years younger than women without a GDM history, but they had comparable BMIs. In addition, within the placebo arm, we could observe the natural history of glucose intolerance in women with and without a history of GDM. Despite both groups entering the study with equivalent degrees of impaired glucose tolerance and similar BMI, women with a history of GDM had a 71% higher risk of developing diabetes during the 3-year intervention period than that of parous women without a history of GDM (J Clin Endocrinol Metab. 2008 Dec;93[12]:4774-9).
Clearly, there was something about the history of GDM that puts these women at greater risk for diabetes than women who had the same impaired glucose tolerance, but no GDM. The study demonstrated that GDM is an exceptionally strong predictor of the development of type 2 diabetes, even for those who manage to escape diabetes for the first 10 years.
Postpartum prevention
The DPP demonstrated, moreover, that intensive lifestyle therapy and metformin not only were both effective, but that they were equally effective, in delaying or preventing diabetes in women with impaired glucose tolerance and a history of GDM. Both reduced the risk by about 50% at 3 years. This was striking because in parous women without GDM, the reductions were 49% and 14%, respectively. Metformin thus appeared to be more effective in women with a history of GDM.
The effects of the interventions persisted over a 10-year follow up of the DPP population. In women with a history of GDM, the intensive lifestyle intervention and metformin reduced progression to diabetes by 35% and 40%, respectively, over 10 years (J Clin Endocrinol Metab. 2015 Apr;100[4]:1646-53).
Pregnancy presents a stress test for beta cell function, and gestational diabetes clearly is a harbinger of further deterioration in beta-cell function and metabolic abnormalities in the mother. Because of these risks and because early intervention makes a difference, surveillance is critically important. Most women see their ob.gyn. as their primary care physician in the 10 years following a pregnancy – the time when more than 50% of all cases of subsequent diabetes will occur – and many continue to see their ob.gyns. in the longer term, as their risk continues to linger.
Immediately after a pregnancy with GDM, ob.gyns. can counsel women not only about their risks of developing type 2 diabetes and the importance of screening, but also about the beneficial impact of lifestyle modification, caloric restriction and weight loss if necessary, and increased exercise. Mothers should also know that GDM is a family affair, and that lifestyle changes that are beneficial for the mother will be equally beneficial for the baby.
The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study taught us that there are continuous linear relationships between maternal glucose and adverse fetal outcomes like birth weight and percent body fat greater than the 90th percentile. Longitudinal studies of the Pima Indians showed us that offspring of women who had diabetes during pregnancy were more likely to be obese and more likely to develop diabetes than offspring of women who did not have diabetes during pregnancy. Even when GDM has been well treated and controlled, we should have heightened awareness to the potential risks in the fetus and the growing child and adolescent.
Patients who are found to have subsequent type 2 diabetes should know that aggressive therapy early on in the natural history of the disease reduces the risk of microvascular and macrovascular complications. And as the DPP has demonstrated, lifestyle interventions and metformin may also keep women who are found to have prediabetes outside of pregnancy from progressing on to diabetes.
Dr. Ratner is the chief scientific and medical officer for the American Diabetes Association. He reported having no financial disclosures relevant to this Master Class.
Critical Care Commentary
According to IBM, over 2 quintillion bytes of data are generated every day (that’s a 2 with 18 zeros!), with over 90% of the data in the world today generated in the past 2 years alone.
In our private lives, much of this information is generated through online shopping, web surfing, and popular websites such as Facebook and Twitter. Companies are making incredible efforts to collect these data and to use it to improve how they relate to customers and, ultimately, to make more money. For example, companies like Google, Amazon, Facebook, and Netflix collect enormous amounts of data and then use algorithms to provide real-time suggestions for what their customers might want to rent, buy, or click on. These algorithms, which companies use for anything from predicting customer behavior to facial recognition, were developed in the field of machine learning, a branch of computer science that focuses on how to learn from data.
Big data and critical care
Although the “big data” revolution has proliferated across the private sector, medicine has been slow to utilize the data we painstakingly collect in hospitals every day in order to improve patient care.
Clinicians typically rely on their intuition and the few clinical trials that their patients would have been included in to make decisions, and evidence-based clinical decision support tools are often not available or not used. The tools and scores we have at our disposal are often oversimplified so that they can be calculated by hand and usually rely on the clinician to manually gather information from the electronic health record (EHR) to calculate the score. However, this is starting to change. From partnerships between IBM Watson and hospitals, to groups developing and implementing clinical decision support tools in the EHR, it is clear that hospitals are becoming increasingly interested in learning from and using the enormous amount of data that are just sitting in the hospital records.
Although there are many areas in medicine that stand to benefit from harnessing the data available in the EHR to improve patient care, critical care should be one of the specialties that benefits the most. With the variety and frequency of monitoring that critically ill patients receive, there are large swaths of data available to collect, analyze, and harness to improve patient care. The current glut of information results in data overload and alarm fatigue for today’s clinicians, but intelligent use of these data holds promise for making care safer and more efficient and effective.
Groups have already begun using these data to develop tools to identify patients with ARDS (Herasevich V, et al. Intensive Care Med. 2009;35[6]:1018-23), patients at risk of adverse drug reactions (Harinstein LM, et al. J Crit Care. 2012;27[3]:242-9), and those with sepsis (Tafelski S, et al. J Int Med Res. 2010;38:1605-16).
Furthermore, groups have begun “crowdsourcing” critical care problems by making large datasets publicly available, such as the Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC) database, which now holds clinical data from over 40,000 ICU stays from Beth Israel Deaconess Medical Center. Continued efforts to utilize data from patients in the ICU have the potential to revolutionize the care in hospitals today.
An important area of critical care that has seen a rapid rise in the use of EHR data to create decision support tools is in the early detection of critical illness. Given that many in-hospital cardiac arrests occur outside the ICU and delays in transferring critically ill patients to the ICU increase morbidity and mortality (Churpek MM, et al. J Hosp Med. 2016;11[11]:757-62), detecting critical illness early is incredibly important.
For millennia, clinicians have relied on their intuition and experience to determine which patients have a poor prognosis or need increased levels of care. In the 1990s, rapid response teams (RRTs) were developed, with the goal of identifying and treating critical illness earlier. Along with them came early warning scores, which are objective tools that typically use vital sign abnormalities to detect patients at high risk of clinical deterioration. RRTs and the early warning scores used to activate them have proliferated around the world, including in the United States, and scores like the Modified Early Warning Score (MEWS) are available for automatic calculation in the EHR.
However, taking a tool such as the MEWS that can easily be calculated by hand and making our expensive EHRs calculate it is a lot like buying a Ferrari just to drive it around the parking lot. There is no reason to limit our decision support tools to simple algorithms with only a few variables, especially when patients’ lives are at stake.
Several groups around the country have, therefore, begun to utilize other variables in the EHR, such as laboratory values, to create integrated decision support tools for the early identification of critical illness. For example, Kollef and colleagues developed a statistical model to identify critical illness and implemented it on the wards to activate their RRT, which resulted in decreased lengths of stay in the intervention group (Kollef MH, et al. J Hosp Med. 2014;9[7]:424-9).
Escobar et al. developed a model to predict ICU transfer or non-DNR deaths in the Kaiser system and found it to be more accurate than the MEWS in a validation cohort (Escobar GJ, et al. J Hosp Med. 2012;7[5]:388-95). A clinical trial of their system is ongoing.
Finally, our group developed a model called eCART in a multicenter study of over 250,000 patients and has since implemented it in our hospital. An early “black-box” study found that eCART detected more patients who went on to experience a cardiac arrest or ICU transfer than our usual care RRT and it did so 24 hours earlier (Kang MA, et al. Crit Care Med. 2016;44[8]:1468-73). These scores and many more will likely become commonplace in hospitals to provide an objective and accurate way to identify critically ill patients earlier, which may result in decreased preventable morbidity and mortality.
Future directions
There are several important future directions at the intersection of big data and critical care.
First, efforts to collect, store, and share the highly granular data in the ICU are paramount for successful and generalizable research collaborations. Although there are often institutional barriers to data sharing to surmount, efforts such as the MIMIC database provide a roadmap for how ICU data can be shared and problems “crowdsourced” in order to allow researchers access to these data for high quality research.
Second, efforts to fuse randomized controlled trials with big data, such as randomized, embedded, multifactorial, adaptive platform (REMAP) trials, have the potential to greatly enhance the way trials are done in the future. REMAP trials would be embedded in the EHR, provide the ability to study multiple therapies at once, and adapt the randomization scheme to ensure that patients are not harmed by interventions that are clearly detrimental while the study is ongoing (Angus DC. JAMA. 2015;314[8]:767-8).
Finally, it is important that we move beyond the classic statistical methods that are commonly used to develop decision support tools and increase our use of more modern machine learning techniques that companies in the private sector use every day. For example, our group found that classic regression methods were the least accurate of all the methods we studied for detecting clinical deterioration on the wards (Churpek MM, et al. Crit Care Med. 2016;44[2]:368-74). In the future, methods such as the random forest and neural network should become commonplace in the critical care literature.
The big data revolution is here, both in our private lives and in the hospital. The future will bring continued efforts to use data to identify critical illness earlier, improve the care of patients in the ICU, and implement smarter and more efficient clinical trials. This should rapidly increase the generation and utilization of new knowledge and will have a profound impact on the way we care for critically ill patients.
Dr. Churpek is assistant professor, section of pulmonary and critical care medicine, department of medicine at University of Chicago.
Editor’s comment
Why should busy ICU clinicians bother with big data? Isn’t this simply a “flash in the pan” phenomenon that has sprung up in the aftermath of the electronic medical records (EMRs) mandated by the Affordable Care Act? Are concerns valid that clinical data–based algorithms will lead to an endless stream of alerts akin to the ubiquitous pop-up ads for mortgage refinancing, herbal Viagra, and online gambling that has resulted from commercial data mining?
In this Critical Care Commentary, Dr. Matthew Churpek convincingly outlines the potential inherent in the big data generated by our collective ICUs. These benefits are manifesting themselves not just in the data populated within the EMR – but also in the novel ways we can now design and execute studies. And for those who aren’t yet convinced, recall that payers already use the treasure trove of information within our EMRs against us in the forms of self-serving quality metrics, punitive reimbursement, and unvalidated hospital comparison sites.
Lee E. Morrow, MD, FCCP, is the editor of the Critical Care Commentary section of CHEST Physician.
According to IBM, over 2 quintillion bytes of data are generated every day (that’s a 2 with 18 zeros!), with over 90% of the data in the world today generated in the past 2 years alone.
In our private lives, much of this information is generated through online shopping, web surfing, and popular websites such as Facebook and Twitter. Companies are making incredible efforts to collect these data and to use it to improve how they relate to customers and, ultimately, to make more money. For example, companies like Google, Amazon, Facebook, and Netflix collect enormous amounts of data and then use algorithms to provide real-time suggestions for what their customers might want to rent, buy, or click on. These algorithms, which companies use for anything from predicting customer behavior to facial recognition, were developed in the field of machine learning, a branch of computer science that focuses on how to learn from data.
Big data and critical care
Although the “big data” revolution has proliferated across the private sector, medicine has been slow to utilize the data we painstakingly collect in hospitals every day in order to improve patient care.
Clinicians typically rely on their intuition and the few clinical trials that their patients would have been included in to make decisions, and evidence-based clinical decision support tools are often not available or not used. The tools and scores we have at our disposal are often oversimplified so that they can be calculated by hand and usually rely on the clinician to manually gather information from the electronic health record (EHR) to calculate the score. However, this is starting to change. From partnerships between IBM Watson and hospitals, to groups developing and implementing clinical decision support tools in the EHR, it is clear that hospitals are becoming increasingly interested in learning from and using the enormous amount of data that are just sitting in the hospital records.
Although there are many areas in medicine that stand to benefit from harnessing the data available in the EHR to improve patient care, critical care should be one of the specialties that benefits the most. With the variety and frequency of monitoring that critically ill patients receive, there are large swaths of data available to collect, analyze, and harness to improve patient care. The current glut of information results in data overload and alarm fatigue for today’s clinicians, but intelligent use of these data holds promise for making care safer and more efficient and effective.
Groups have already begun using these data to develop tools to identify patients with ARDS (Herasevich V, et al. Intensive Care Med. 2009;35[6]:1018-23), patients at risk of adverse drug reactions (Harinstein LM, et al. J Crit Care. 2012;27[3]:242-9), and those with sepsis (Tafelski S, et al. J Int Med Res. 2010;38:1605-16).
Furthermore, groups have begun “crowdsourcing” critical care problems by making large datasets publicly available, such as the Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC) database, which now holds clinical data from over 40,000 ICU stays from Beth Israel Deaconess Medical Center. Continued efforts to utilize data from patients in the ICU have the potential to revolutionize the care in hospitals today.
An important area of critical care that has seen a rapid rise in the use of EHR data to create decision support tools is in the early detection of critical illness. Given that many in-hospital cardiac arrests occur outside the ICU and delays in transferring critically ill patients to the ICU increase morbidity and mortality (Churpek MM, et al. J Hosp Med. 2016;11[11]:757-62), detecting critical illness early is incredibly important.
For millennia, clinicians have relied on their intuition and experience to determine which patients have a poor prognosis or need increased levels of care. In the 1990s, rapid response teams (RRTs) were developed, with the goal of identifying and treating critical illness earlier. Along with them came early warning scores, which are objective tools that typically use vital sign abnormalities to detect patients at high risk of clinical deterioration. RRTs and the early warning scores used to activate them have proliferated around the world, including in the United States, and scores like the Modified Early Warning Score (MEWS) are available for automatic calculation in the EHR.
However, taking a tool such as the MEWS that can easily be calculated by hand and making our expensive EHRs calculate it is a lot like buying a Ferrari just to drive it around the parking lot. There is no reason to limit our decision support tools to simple algorithms with only a few variables, especially when patients’ lives are at stake.
Several groups around the country have, therefore, begun to utilize other variables in the EHR, such as laboratory values, to create integrated decision support tools for the early identification of critical illness. For example, Kollef and colleagues developed a statistical model to identify critical illness and implemented it on the wards to activate their RRT, which resulted in decreased lengths of stay in the intervention group (Kollef MH, et al. J Hosp Med. 2014;9[7]:424-9).
Escobar et al. developed a model to predict ICU transfer or non-DNR deaths in the Kaiser system and found it to be more accurate than the MEWS in a validation cohort (Escobar GJ, et al. J Hosp Med. 2012;7[5]:388-95). A clinical trial of their system is ongoing.
Finally, our group developed a model called eCART in a multicenter study of over 250,000 patients and has since implemented it in our hospital. An early “black-box” study found that eCART detected more patients who went on to experience a cardiac arrest or ICU transfer than our usual care RRT and it did so 24 hours earlier (Kang MA, et al. Crit Care Med. 2016;44[8]:1468-73). These scores and many more will likely become commonplace in hospitals to provide an objective and accurate way to identify critically ill patients earlier, which may result in decreased preventable morbidity and mortality.
Future directions
There are several important future directions at the intersection of big data and critical care.
First, efforts to collect, store, and share the highly granular data in the ICU are paramount for successful and generalizable research collaborations. Although there are often institutional barriers to data sharing to surmount, efforts such as the MIMIC database provide a roadmap for how ICU data can be shared and problems “crowdsourced” in order to allow researchers access to these data for high quality research.
Second, efforts to fuse randomized controlled trials with big data, such as randomized, embedded, multifactorial, adaptive platform (REMAP) trials, have the potential to greatly enhance the way trials are done in the future. REMAP trials would be embedded in the EHR, provide the ability to study multiple therapies at once, and adapt the randomization scheme to ensure that patients are not harmed by interventions that are clearly detrimental while the study is ongoing (Angus DC. JAMA. 2015;314[8]:767-8).
Finally, it is important that we move beyond the classic statistical methods that are commonly used to develop decision support tools and increase our use of more modern machine learning techniques that companies in the private sector use every day. For example, our group found that classic regression methods were the least accurate of all the methods we studied for detecting clinical deterioration on the wards (Churpek MM, et al. Crit Care Med. 2016;44[2]:368-74). In the future, methods such as the random forest and neural network should become commonplace in the critical care literature.
The big data revolution is here, both in our private lives and in the hospital. The future will bring continued efforts to use data to identify critical illness earlier, improve the care of patients in the ICU, and implement smarter and more efficient clinical trials. This should rapidly increase the generation and utilization of new knowledge and will have a profound impact on the way we care for critically ill patients.
Dr. Churpek is assistant professor, section of pulmonary and critical care medicine, department of medicine at University of Chicago.
Editor’s comment
Why should busy ICU clinicians bother with big data? Isn’t this simply a “flash in the pan” phenomenon that has sprung up in the aftermath of the electronic medical records (EMRs) mandated by the Affordable Care Act? Are concerns valid that clinical data–based algorithms will lead to an endless stream of alerts akin to the ubiquitous pop-up ads for mortgage refinancing, herbal Viagra, and online gambling that has resulted from commercial data mining?
In this Critical Care Commentary, Dr. Matthew Churpek convincingly outlines the potential inherent in the big data generated by our collective ICUs. These benefits are manifesting themselves not just in the data populated within the EMR – but also in the novel ways we can now design and execute studies. And for those who aren’t yet convinced, recall that payers already use the treasure trove of information within our EMRs against us in the forms of self-serving quality metrics, punitive reimbursement, and unvalidated hospital comparison sites.
Lee E. Morrow, MD, FCCP, is the editor of the Critical Care Commentary section of CHEST Physician.
According to IBM, over 2 quintillion bytes of data are generated every day (that’s a 2 with 18 zeros!), with over 90% of the data in the world today generated in the past 2 years alone.
In our private lives, much of this information is generated through online shopping, web surfing, and popular websites such as Facebook and Twitter. Companies are making incredible efforts to collect these data and to use it to improve how they relate to customers and, ultimately, to make more money. For example, companies like Google, Amazon, Facebook, and Netflix collect enormous amounts of data and then use algorithms to provide real-time suggestions for what their customers might want to rent, buy, or click on. These algorithms, which companies use for anything from predicting customer behavior to facial recognition, were developed in the field of machine learning, a branch of computer science that focuses on how to learn from data.
Big data and critical care
Although the “big data” revolution has proliferated across the private sector, medicine has been slow to utilize the data we painstakingly collect in hospitals every day in order to improve patient care.
Clinicians typically rely on their intuition and the few clinical trials that their patients would have been included in to make decisions, and evidence-based clinical decision support tools are often not available or not used. The tools and scores we have at our disposal are often oversimplified so that they can be calculated by hand and usually rely on the clinician to manually gather information from the electronic health record (EHR) to calculate the score. However, this is starting to change. From partnerships between IBM Watson and hospitals, to groups developing and implementing clinical decision support tools in the EHR, it is clear that hospitals are becoming increasingly interested in learning from and using the enormous amount of data that are just sitting in the hospital records.
Although there are many areas in medicine that stand to benefit from harnessing the data available in the EHR to improve patient care, critical care should be one of the specialties that benefits the most. With the variety and frequency of monitoring that critically ill patients receive, there are large swaths of data available to collect, analyze, and harness to improve patient care. The current glut of information results in data overload and alarm fatigue for today’s clinicians, but intelligent use of these data holds promise for making care safer and more efficient and effective.
Groups have already begun using these data to develop tools to identify patients with ARDS (Herasevich V, et al. Intensive Care Med. 2009;35[6]:1018-23), patients at risk of adverse drug reactions (Harinstein LM, et al. J Crit Care. 2012;27[3]:242-9), and those with sepsis (Tafelski S, et al. J Int Med Res. 2010;38:1605-16).
Furthermore, groups have begun “crowdsourcing” critical care problems by making large datasets publicly available, such as the Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC) database, which now holds clinical data from over 40,000 ICU stays from Beth Israel Deaconess Medical Center. Continued efforts to utilize data from patients in the ICU have the potential to revolutionize the care in hospitals today.
An important area of critical care that has seen a rapid rise in the use of EHR data to create decision support tools is in the early detection of critical illness. Given that many in-hospital cardiac arrests occur outside the ICU and delays in transferring critically ill patients to the ICU increase morbidity and mortality (Churpek MM, et al. J Hosp Med. 2016;11[11]:757-62), detecting critical illness early is incredibly important.
For millennia, clinicians have relied on their intuition and experience to determine which patients have a poor prognosis or need increased levels of care. In the 1990s, rapid response teams (RRTs) were developed, with the goal of identifying and treating critical illness earlier. Along with them came early warning scores, which are objective tools that typically use vital sign abnormalities to detect patients at high risk of clinical deterioration. RRTs and the early warning scores used to activate them have proliferated around the world, including in the United States, and scores like the Modified Early Warning Score (MEWS) are available for automatic calculation in the EHR.
However, taking a tool such as the MEWS that can easily be calculated by hand and making our expensive EHRs calculate it is a lot like buying a Ferrari just to drive it around the parking lot. There is no reason to limit our decision support tools to simple algorithms with only a few variables, especially when patients’ lives are at stake.
Several groups around the country have, therefore, begun to utilize other variables in the EHR, such as laboratory values, to create integrated decision support tools for the early identification of critical illness. For example, Kollef and colleagues developed a statistical model to identify critical illness and implemented it on the wards to activate their RRT, which resulted in decreased lengths of stay in the intervention group (Kollef MH, et al. J Hosp Med. 2014;9[7]:424-9).
Escobar et al. developed a model to predict ICU transfer or non-DNR deaths in the Kaiser system and found it to be more accurate than the MEWS in a validation cohort (Escobar GJ, et al. J Hosp Med. 2012;7[5]:388-95). A clinical trial of their system is ongoing.
Finally, our group developed a model called eCART in a multicenter study of over 250,000 patients and has since implemented it in our hospital. An early “black-box” study found that eCART detected more patients who went on to experience a cardiac arrest or ICU transfer than our usual care RRT and it did so 24 hours earlier (Kang MA, et al. Crit Care Med. 2016;44[8]:1468-73). These scores and many more will likely become commonplace in hospitals to provide an objective and accurate way to identify critically ill patients earlier, which may result in decreased preventable morbidity and mortality.
Future directions
There are several important future directions at the intersection of big data and critical care.
First, efforts to collect, store, and share the highly granular data in the ICU are paramount for successful and generalizable research collaborations. Although there are often institutional barriers to data sharing to surmount, efforts such as the MIMIC database provide a roadmap for how ICU data can be shared and problems “crowdsourced” in order to allow researchers access to these data for high quality research.
Second, efforts to fuse randomized controlled trials with big data, such as randomized, embedded, multifactorial, adaptive platform (REMAP) trials, have the potential to greatly enhance the way trials are done in the future. REMAP trials would be embedded in the EHR, provide the ability to study multiple therapies at once, and adapt the randomization scheme to ensure that patients are not harmed by interventions that are clearly detrimental while the study is ongoing (Angus DC. JAMA. 2015;314[8]:767-8).
Finally, it is important that we move beyond the classic statistical methods that are commonly used to develop decision support tools and increase our use of more modern machine learning techniques that companies in the private sector use every day. For example, our group found that classic regression methods were the least accurate of all the methods we studied for detecting clinical deterioration on the wards (Churpek MM, et al. Crit Care Med. 2016;44[2]:368-74). In the future, methods such as the random forest and neural network should become commonplace in the critical care literature.
The big data revolution is here, both in our private lives and in the hospital. The future will bring continued efforts to use data to identify critical illness earlier, improve the care of patients in the ICU, and implement smarter and more efficient clinical trials. This should rapidly increase the generation and utilization of new knowledge and will have a profound impact on the way we care for critically ill patients.
Dr. Churpek is assistant professor, section of pulmonary and critical care medicine, department of medicine at University of Chicago.
Editor’s comment
Why should busy ICU clinicians bother with big data? Isn’t this simply a “flash in the pan” phenomenon that has sprung up in the aftermath of the electronic medical records (EMRs) mandated by the Affordable Care Act? Are concerns valid that clinical data–based algorithms will lead to an endless stream of alerts akin to the ubiquitous pop-up ads for mortgage refinancing, herbal Viagra, and online gambling that has resulted from commercial data mining?
In this Critical Care Commentary, Dr. Matthew Churpek convincingly outlines the potential inherent in the big data generated by our collective ICUs. These benefits are manifesting themselves not just in the data populated within the EMR – but also in the novel ways we can now design and execute studies. And for those who aren’t yet convinced, recall that payers already use the treasure trove of information within our EMRs against us in the forms of self-serving quality metrics, punitive reimbursement, and unvalidated hospital comparison sites.
Lee E. Morrow, MD, FCCP, is the editor of the Critical Care Commentary section of CHEST Physician.
Thank You to Our 2016 Peer Reviewers
The editors of Emergency Medicine acknowledge the help of the journal’s editorial board members, other emergency physicians, and colleagues in other specialties who reviewed manuscripts in 2016. On behalf of our readers, who are the beneficiaries of your efforts, we thank you.
Alfred Z. Abuhamad, MD
Department of Obstetrics and Gynecology
Eastern Virginia Medical School
John E. Arbo, MD
Division of Emergency Medicine and Pulmonary Critical Care Medicine
Weill Cornell Medical College, Cornell University
David P. Calfee, MD
Division of Infectious Diseases
Weill Cornell Medical College, Cornell University
Richard M. Cantor, MD, FAAP, FACEP
Emergency Department, Pediatrics
Upstate Medical University
Wallace A. Carter, MD, FACEP
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Sunday Clark, ScD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Theodore R. Delbridge, MD
Department of Emergency
Medicine East Carolina University, Brody School of Medicine
Joseph J. Fins, MD
Division of Medical Ethics Internal Medicine
Weill Cornell Medical College, Cornell University
Ron W. Flenner, MD
Department of Internal Medicine
Eastern Virginia Medical School
E. John Gallagher, MD
Department of Emergency Medicine
Albert Einstein College of Medicine
Marianne Gausche-Hill, MD
Department of Emergency Medicine
Harbor-UCLA Medical Center
Keith D. Hentel, MD
Department of Radiology
Weill Cornell Medical College, Cornell University
Barry J. Knapp, MD
Department of Emergency Medicine
Eastern Virginia Medical School
Richard I. Lapin, MD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Anthony C. Mustalish, MD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Lewis S. Nelson, MD
Department of Emergency Medicine
Rutgers New Jersey Medical School
Debra Perina, MD
Department of Emergency Medicine
University of Virginia, Charlottesville
Constance Peterson, MA
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Shari L. Platt, MD, FAAP
Division of Pediatric Emergency Medicine
Weill Cornell Medical College, Cornell University
Rama B. Rao, MD
Division of Toxicology
Weill Cornell Medical College, Cornell University
Earl J. Reisdorff, MD
Executive Director
American Board of Emergency Medicine
Thomas M. Scalea, MD, FACS, FCCM
Program in Trauma
University of Maryland School of Medicine
Edward J. Schenk, MD
Pulmonary Critical Care Medicine
Weill Cornell Medical College, Cornell University
Christopher K. Schott, MD, MS
Department of Emergency Medicine and Critical Care Medicine
University of Pittsburgh
Adam J Singer, MD
Department of Emergency Medicine
Stony Brook University and Medical Center
Sarah A. Stahmer, MD, FACEP
Division of Emergency Medicine
Duke University Medical Center
Michael E. Stern, MD
Division of Geriatric Emergency Medicine
Weill Cornell Medical College, Cornell University
Susan Stone, MD
Emergency Medicine/Palliative Care
University of California, Los Angeles
Todd Taylor, MD
Department of Emergency Medicine
Emory University School of Medicine
The editors of Emergency Medicine acknowledge the help of the journal’s editorial board members, other emergency physicians, and colleagues in other specialties who reviewed manuscripts in 2016. On behalf of our readers, who are the beneficiaries of your efforts, we thank you.
Alfred Z. Abuhamad, MD
Department of Obstetrics and Gynecology
Eastern Virginia Medical School
John E. Arbo, MD
Division of Emergency Medicine and Pulmonary Critical Care Medicine
Weill Cornell Medical College, Cornell University
David P. Calfee, MD
Division of Infectious Diseases
Weill Cornell Medical College, Cornell University
Richard M. Cantor, MD, FAAP, FACEP
Emergency Department, Pediatrics
Upstate Medical University
Wallace A. Carter, MD, FACEP
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Sunday Clark, ScD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Theodore R. Delbridge, MD
Department of Emergency
Medicine East Carolina University, Brody School of Medicine
Joseph J. Fins, MD
Division of Medical Ethics Internal Medicine
Weill Cornell Medical College, Cornell University
Ron W. Flenner, MD
Department of Internal Medicine
Eastern Virginia Medical School
E. John Gallagher, MD
Department of Emergency Medicine
Albert Einstein College of Medicine
Marianne Gausche-Hill, MD
Department of Emergency Medicine
Harbor-UCLA Medical Center
Keith D. Hentel, MD
Department of Radiology
Weill Cornell Medical College, Cornell University
Barry J. Knapp, MD
Department of Emergency Medicine
Eastern Virginia Medical School
Richard I. Lapin, MD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Anthony C. Mustalish, MD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Lewis S. Nelson, MD
Department of Emergency Medicine
Rutgers New Jersey Medical School
Debra Perina, MD
Department of Emergency Medicine
University of Virginia, Charlottesville
Constance Peterson, MA
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Shari L. Platt, MD, FAAP
Division of Pediatric Emergency Medicine
Weill Cornell Medical College, Cornell University
Rama B. Rao, MD
Division of Toxicology
Weill Cornell Medical College, Cornell University
Earl J. Reisdorff, MD
Executive Director
American Board of Emergency Medicine
Thomas M. Scalea, MD, FACS, FCCM
Program in Trauma
University of Maryland School of Medicine
Edward J. Schenk, MD
Pulmonary Critical Care Medicine
Weill Cornell Medical College, Cornell University
Christopher K. Schott, MD, MS
Department of Emergency Medicine and Critical Care Medicine
University of Pittsburgh
Adam J Singer, MD
Department of Emergency Medicine
Stony Brook University and Medical Center
Sarah A. Stahmer, MD, FACEP
Division of Emergency Medicine
Duke University Medical Center
Michael E. Stern, MD
Division of Geriatric Emergency Medicine
Weill Cornell Medical College, Cornell University
Susan Stone, MD
Emergency Medicine/Palliative Care
University of California, Los Angeles
Todd Taylor, MD
Department of Emergency Medicine
Emory University School of Medicine
The editors of Emergency Medicine acknowledge the help of the journal’s editorial board members, other emergency physicians, and colleagues in other specialties who reviewed manuscripts in 2016. On behalf of our readers, who are the beneficiaries of your efforts, we thank you.
Alfred Z. Abuhamad, MD
Department of Obstetrics and Gynecology
Eastern Virginia Medical School
John E. Arbo, MD
Division of Emergency Medicine and Pulmonary Critical Care Medicine
Weill Cornell Medical College, Cornell University
David P. Calfee, MD
Division of Infectious Diseases
Weill Cornell Medical College, Cornell University
Richard M. Cantor, MD, FAAP, FACEP
Emergency Department, Pediatrics
Upstate Medical University
Wallace A. Carter, MD, FACEP
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Sunday Clark, ScD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Theodore R. Delbridge, MD
Department of Emergency
Medicine East Carolina University, Brody School of Medicine
Joseph J. Fins, MD
Division of Medical Ethics Internal Medicine
Weill Cornell Medical College, Cornell University
Ron W. Flenner, MD
Department of Internal Medicine
Eastern Virginia Medical School
E. John Gallagher, MD
Department of Emergency Medicine
Albert Einstein College of Medicine
Marianne Gausche-Hill, MD
Department of Emergency Medicine
Harbor-UCLA Medical Center
Keith D. Hentel, MD
Department of Radiology
Weill Cornell Medical College, Cornell University
Barry J. Knapp, MD
Department of Emergency Medicine
Eastern Virginia Medical School
Richard I. Lapin, MD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Anthony C. Mustalish, MD
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Lewis S. Nelson, MD
Department of Emergency Medicine
Rutgers New Jersey Medical School
Debra Perina, MD
Department of Emergency Medicine
University of Virginia, Charlottesville
Constance Peterson, MA
Department of Emergency Medicine
Weill Cornell Medical College, Cornell University
Shari L. Platt, MD, FAAP
Division of Pediatric Emergency Medicine
Weill Cornell Medical College, Cornell University
Rama B. Rao, MD
Division of Toxicology
Weill Cornell Medical College, Cornell University
Earl J. Reisdorff, MD
Executive Director
American Board of Emergency Medicine
Thomas M. Scalea, MD, FACS, FCCM
Program in Trauma
University of Maryland School of Medicine
Edward J. Schenk, MD
Pulmonary Critical Care Medicine
Weill Cornell Medical College, Cornell University
Christopher K. Schott, MD, MS
Department of Emergency Medicine and Critical Care Medicine
University of Pittsburgh
Adam J Singer, MD
Department of Emergency Medicine
Stony Brook University and Medical Center
Sarah A. Stahmer, MD, FACEP
Division of Emergency Medicine
Duke University Medical Center
Michael E. Stern, MD
Division of Geriatric Emergency Medicine
Weill Cornell Medical College, Cornell University
Susan Stone, MD
Emergency Medicine/Palliative Care
University of California, Los Angeles
Todd Taylor, MD
Department of Emergency Medicine
Emory University School of Medicine
A Holiday Visit to the ED (With Apologies to Clement Clarke Moore)
‘Twas the night before New Year, when all through the land
Every ED was busy—Can you give us a hand?
Treating chest pains, and traumas, and hot swollen knees,
While clinics were shuttered, along with UCs.
The handoffs were done with hardly a frown,
In hopes that the volume soon would slow down.
Babies were nestled all snug in a sheet,
Watching sutures applied to their hands and their feet.
And amateur athletes unpadded, uncapped,
Had brains that were rattled after balls had been snapped.
When out on the deck there arose such a clatter
We sprang from the doc box to help with the matter.
To Resusc room 1 we flew in a flash,
Tearing open the curtain before the patient could crash.
The leads on the breast of the now-fallen fellow,
Made lustrous white circles near sclerae bright yellow.
When what to our wondering ears did we hear,
But an overhead page that inspired some fear:
Notifications of a Level 1 trauma,
And several ODs, to add to the drama.
More rapid than eagles the new patients came,
All victims of poisons with rather strange names:
Poinsettia, and holly, and dried mistletoe,
Angel hair, leaded tinsel, polyacrylate snow.
And a man who was tarnished with ashes and soot,
With a cherry red color from his head to his foot.
Smoke inhalation and a toxic epoxide?
Or alcohol, cyanide, carbon monoxide?
But “Holiday Poisonings” on the pages ahead,
Soon reassured us we had nothing to dread…
When patients were discharged to families waiting,
They promised to give us all a good rating.
So to all EMTs, NPs, and PAs,
RNs, and EPs who work holidays,
And to all ED staffs who “fight the good fight,”
Have a Happy New Year, and a nice quiet night!
—Neal Flomenbaum, MD
‘Twas the night before New Year, when all through the land
Every ED was busy—Can you give us a hand?
Treating chest pains, and traumas, and hot swollen knees,
While clinics were shuttered, along with UCs.
The handoffs were done with hardly a frown,
In hopes that the volume soon would slow down.
Babies were nestled all snug in a sheet,
Watching sutures applied to their hands and their feet.
And amateur athletes unpadded, uncapped,
Had brains that were rattled after balls had been snapped.
When out on the deck there arose such a clatter
We sprang from the doc box to help with the matter.
To Resusc room 1 we flew in a flash,
Tearing open the curtain before the patient could crash.
The leads on the breast of the now-fallen fellow,
Made lustrous white circles near sclerae bright yellow.
When what to our wondering ears did we hear,
But an overhead page that inspired some fear:
Notifications of a Level 1 trauma,
And several ODs, to add to the drama.
More rapid than eagles the new patients came,
All victims of poisons with rather strange names:
Poinsettia, and holly, and dried mistletoe,
Angel hair, leaded tinsel, polyacrylate snow.
And a man who was tarnished with ashes and soot,
With a cherry red color from his head to his foot.
Smoke inhalation and a toxic epoxide?
Or alcohol, cyanide, carbon monoxide?
But “Holiday Poisonings” on the pages ahead,
Soon reassured us we had nothing to dread…
When patients were discharged to families waiting,
They promised to give us all a good rating.
So to all EMTs, NPs, and PAs,
RNs, and EPs who work holidays,
And to all ED staffs who “fight the good fight,”
Have a Happy New Year, and a nice quiet night!
—Neal Flomenbaum, MD
‘Twas the night before New Year, when all through the land
Every ED was busy—Can you give us a hand?
Treating chest pains, and traumas, and hot swollen knees,
While clinics were shuttered, along with UCs.
The handoffs were done with hardly a frown,
In hopes that the volume soon would slow down.
Babies were nestled all snug in a sheet,
Watching sutures applied to their hands and their feet.
And amateur athletes unpadded, uncapped,
Had brains that were rattled after balls had been snapped.
When out on the deck there arose such a clatter
We sprang from the doc box to help with the matter.
To Resusc room 1 we flew in a flash,
Tearing open the curtain before the patient could crash.
The leads on the breast of the now-fallen fellow,
Made lustrous white circles near sclerae bright yellow.
When what to our wondering ears did we hear,
But an overhead page that inspired some fear:
Notifications of a Level 1 trauma,
And several ODs, to add to the drama.
More rapid than eagles the new patients came,
All victims of poisons with rather strange names:
Poinsettia, and holly, and dried mistletoe,
Angel hair, leaded tinsel, polyacrylate snow.
And a man who was tarnished with ashes and soot,
With a cherry red color from his head to his foot.
Smoke inhalation and a toxic epoxide?
Or alcohol, cyanide, carbon monoxide?
But “Holiday Poisonings” on the pages ahead,
Soon reassured us we had nothing to dread…
When patients were discharged to families waiting,
They promised to give us all a good rating.
So to all EMTs, NPs, and PAs,
RNs, and EPs who work holidays,
And to all ED staffs who “fight the good fight,”
Have a Happy New Year, and a nice quiet night!
—Neal Flomenbaum, MD
Using the Blanch Sign to Differentiate Weathering Nodules From Auricular Tophaceous Gout
To the Editor:
We commend the recent report by Smith et al (Cutis. 2016;97:166, 175-176) that described multiple white nodules on the bilateral helical rims of the ears in a 40-year-old man, which was determined to be bilateral auricular tophaceous gout. Furthermore, we appreciate the inclusion of weathering nodules in the differential diagnosis and wish to share our experience with these lesions.
Auricular tophaceous gout and weathering nodules are clinically similar. Weathering nodules may appear as single or multiple, 2 to 3 mm in diameter and 1 to 2 mm in height, white to flesh-colored papules usually found on the helical rim of the ear (Figure 1).1 We recently described 10 patients with weathering nodules and their associated risk factors.2 We observed that the weathering nodules will blanch upon the application of pressure to the adjacent helical rim; a positive “blanch sign” may be used to differentiate weathering nodules from auricular tophaceous gout and other lesions of the ear (Figure 2). Furthermore, patients with weathering nodules typically exhibit a history of sun exposure and often have other cutaneous findings such as actinic keratoses. The pathogenesis of weathering nodules was previously thought to rely solely on actinic damage; however, we reported a pediatric case of weathering nodules that presented following radiotherapy to the ears.2
In summary, weathering nodules should be included in the differential diagnosis of auricular tophaceous gout. In addition, a positive blanch sign may be a useful clinical tool in differentiating weathering nodules from other ear lesions.
- Kavanagh GM, Bradfield JW, Collins CM, et al. Weathering nodules of the ear: a clinicopathological study. Br J Dermatol. 1996;135:550-554.
- Udkoff J, Cohen PR. Weathering nodules: a report of ten individuals with weathering nodules and review of the literature. Indian J Dermatol. 2016;61:433-436.
To the Editor:
We commend the recent report by Smith et al (Cutis. 2016;97:166, 175-176) that described multiple white nodules on the bilateral helical rims of the ears in a 40-year-old man, which was determined to be bilateral auricular tophaceous gout. Furthermore, we appreciate the inclusion of weathering nodules in the differential diagnosis and wish to share our experience with these lesions.
Auricular tophaceous gout and weathering nodules are clinically similar. Weathering nodules may appear as single or multiple, 2 to 3 mm in diameter and 1 to 2 mm in height, white to flesh-colored papules usually found on the helical rim of the ear (Figure 1).1 We recently described 10 patients with weathering nodules and their associated risk factors.2 We observed that the weathering nodules will blanch upon the application of pressure to the adjacent helical rim; a positive “blanch sign” may be used to differentiate weathering nodules from auricular tophaceous gout and other lesions of the ear (Figure 2). Furthermore, patients with weathering nodules typically exhibit a history of sun exposure and often have other cutaneous findings such as actinic keratoses. The pathogenesis of weathering nodules was previously thought to rely solely on actinic damage; however, we reported a pediatric case of weathering nodules that presented following radiotherapy to the ears.2
In summary, weathering nodules should be included in the differential diagnosis of auricular tophaceous gout. In addition, a positive blanch sign may be a useful clinical tool in differentiating weathering nodules from other ear lesions.
To the Editor:
We commend the recent report by Smith et al (Cutis. 2016;97:166, 175-176) that described multiple white nodules on the bilateral helical rims of the ears in a 40-year-old man, which was determined to be bilateral auricular tophaceous gout. Furthermore, we appreciate the inclusion of weathering nodules in the differential diagnosis and wish to share our experience with these lesions.
Auricular tophaceous gout and weathering nodules are clinically similar. Weathering nodules may appear as single or multiple, 2 to 3 mm in diameter and 1 to 2 mm in height, white to flesh-colored papules usually found on the helical rim of the ear (Figure 1).1 We recently described 10 patients with weathering nodules and their associated risk factors.2 We observed that the weathering nodules will blanch upon the application of pressure to the adjacent helical rim; a positive “blanch sign” may be used to differentiate weathering nodules from auricular tophaceous gout and other lesions of the ear (Figure 2). Furthermore, patients with weathering nodules typically exhibit a history of sun exposure and often have other cutaneous findings such as actinic keratoses. The pathogenesis of weathering nodules was previously thought to rely solely on actinic damage; however, we reported a pediatric case of weathering nodules that presented following radiotherapy to the ears.2
In summary, weathering nodules should be included in the differential diagnosis of auricular tophaceous gout. In addition, a positive blanch sign may be a useful clinical tool in differentiating weathering nodules from other ear lesions.
- Kavanagh GM, Bradfield JW, Collins CM, et al. Weathering nodules of the ear: a clinicopathological study. Br J Dermatol. 1996;135:550-554.
- Udkoff J, Cohen PR. Weathering nodules: a report of ten individuals with weathering nodules and review of the literature. Indian J Dermatol. 2016;61:433-436.
- Kavanagh GM, Bradfield JW, Collins CM, et al. Weathering nodules of the ear: a clinicopathological study. Br J Dermatol. 1996;135:550-554.
- Udkoff J, Cohen PR. Weathering nodules: a report of ten individuals with weathering nodules and review of the literature. Indian J Dermatol. 2016;61:433-436.
How Can We Say Thank You?
And remember: you must never, under any circumstances, despair. To hope and to act, these are our duties in misfortune.
—Boris Pasternak, Doctor Zhivago
This editorial is being written on Veterans Day. Likely you will read it when the stores and streets are lined with holiday decorations. Thanksgiving will have come and gone. All these celebrations have the common themes of giving and gratitude, and among the many requests clamoring for your attention at this season are care package collections for active-duty service members and donations for disadvantaged veterans. These efforts are well intentioned on the part of givers and appreciated on the part of those who receive them. Yet these themes remind me of the hackneyed saying we likely have all heard, and many of us have said: Thank you for your service.
Many of you may recall the controversy that emerged surrounding this seemingly innocuous cliché. It has had an Internet resurgence on this day set out to honor those who wore or are in uniform.1 For those who don’t remember the phenomenon, I will briefly summarize. A journalist was interviewing a combat veteran from Afghanistan on a different subject but knowing he had been in the military and the reporter thinking he was being kind and respectful, like so many of us, thanked him for his service. The astute journalist could tell from the expression on the veteran’s face that the comment had touched a wound he never expected to open. But he cared enough to try and understand how the veteran heard these words from out of the depths of his memories of war.
The emotions that emerged from the interview and the online blogs and comments that followed reflect the toll that war takes: anger, anguish, alienation, which these “have a nice day” words seem to evoke, even though they are never meant to create distance, dismissal, or dishonor. This interaction was a painful one for the veteran, and even for the journalist, and created what psychologists call cognitive dissonance, “a condition of conflict or anxiety resulting from inconsistency between belief and action.”2
The reason those 5 words strike a raw nerve in some—but by no means all—who were or are in the armed forces is that those to whom they are spoken know in a deep and personal way, that we who say them usually do not know what we are talking about. I can see this reaction when I watch several of my VA colleagues who actually are combat veterans say the words but from a different theory of mind, a theory of mind they share. Theory of mind is another psychological concept that is at the core of interpersonal and communication skills, the ability to see and feel the world as another person sees it. When someone who has never fought or even served says “thank you for your service,” some veterans feel that their individual experience of combat or even of being in the military is being expressed inauthentically, even perhaps insincerely.
“To these vets, thanking soldiers for their service symbolizes the ease of sending a volunteer army to wage war at great distance—physically, spiritually, economically,” journalist Matt Richtel writes. “It raises questions of the meaning of patriotism, shared purpose and, pointedly, what you’re supposed to say to those who put their lives on the line and are uncomfortable about being thanked for it.”2
My father, a World War II combat veteran and career army physician, told me when I was young that there were 3 experiences that could never be understood unless you lived them: pregnancy, medical school, and combat. I’m not sure why or how he chose these although I am sure they were not original, but having gone through the second, I believe it was because these events are of such personal intensity, such immediate contact with the human condition in all its suffering and resilience that they cannot be faithfully replicated in any in vitro simulation but only in vivo.
Which brings me to the title of the column. How can we say thank you to our friends and family members, our coworkers, and our patients who went to war and returned, who enlisted ready to go into combat even if the fates did not send them? Reading the comments of these men and women in response to the superficial phrase with which we habitually acknowledge their sacrifice leaves me wondering what to say to express our obligation to those who struggled through foreign tribulations while we remained safe at home. Their reflections offer some surprising suggestions that seem prophetic as we as a country process the results of the recent election with grief, triumph, or indifference.
We can say thank you through voting, donations, or advocacy as long as we act to promote the most fundamental good for humanity. We say thank you when we act to help a veteran to live a decent and rewarding life, to have a safe place to live, to grow through education, to share life with companions, and to find a job or another way to contribute to society. Actions to improve the living conditions of veterans now and a better future for those who leave the ranks are seeds of gratitude that come to fruition long after the empty phrases are forgotten.
We say thank you when we think and question long and hard until it hurts, until we too experience cognitive dissonance, until our theory of mind is stretched beyond its comfortable boundaries about the purpose of war in general and the justification for any particular conflict in which our government contemplates sending the young and brave to fight and die. Acting and thinking honor sacrifice as words never can.
1. Korzen DM. One veteran’s unease when hearing, “Thanks for your service.” Los Angeles Times. http://www.latimes.com /opinion/op-ed/la-oe-korzen-veterans-thank-you-20161111-story.html. Published November 11, 2016. Accessed November 14, 2016.
2. Richtel M. Please don’t thank me for my service.” The New York Times. http://www.nytimes .com/2015/02/22/sunday-review/please-dont-thank -me-for-my-service.html?_r=0. Published February 21, 2015. Accessed November 14, 2016.
And remember: you must never, under any circumstances, despair. To hope and to act, these are our duties in misfortune.
—Boris Pasternak, Doctor Zhivago
This editorial is being written on Veterans Day. Likely you will read it when the stores and streets are lined with holiday decorations. Thanksgiving will have come and gone. All these celebrations have the common themes of giving and gratitude, and among the many requests clamoring for your attention at this season are care package collections for active-duty service members and donations for disadvantaged veterans. These efforts are well intentioned on the part of givers and appreciated on the part of those who receive them. Yet these themes remind me of the hackneyed saying we likely have all heard, and many of us have said: Thank you for your service.
Many of you may recall the controversy that emerged surrounding this seemingly innocuous cliché. It has had an Internet resurgence on this day set out to honor those who wore or are in uniform.1 For those who don’t remember the phenomenon, I will briefly summarize. A journalist was interviewing a combat veteran from Afghanistan on a different subject but knowing he had been in the military and the reporter thinking he was being kind and respectful, like so many of us, thanked him for his service. The astute journalist could tell from the expression on the veteran’s face that the comment had touched a wound he never expected to open. But he cared enough to try and understand how the veteran heard these words from out of the depths of his memories of war.
The emotions that emerged from the interview and the online blogs and comments that followed reflect the toll that war takes: anger, anguish, alienation, which these “have a nice day” words seem to evoke, even though they are never meant to create distance, dismissal, or dishonor. This interaction was a painful one for the veteran, and even for the journalist, and created what psychologists call cognitive dissonance, “a condition of conflict or anxiety resulting from inconsistency between belief and action.”2
The reason those 5 words strike a raw nerve in some—but by no means all—who were or are in the armed forces is that those to whom they are spoken know in a deep and personal way, that we who say them usually do not know what we are talking about. I can see this reaction when I watch several of my VA colleagues who actually are combat veterans say the words but from a different theory of mind, a theory of mind they share. Theory of mind is another psychological concept that is at the core of interpersonal and communication skills, the ability to see and feel the world as another person sees it. When someone who has never fought or even served says “thank you for your service,” some veterans feel that their individual experience of combat or even of being in the military is being expressed inauthentically, even perhaps insincerely.
“To these vets, thanking soldiers for their service symbolizes the ease of sending a volunteer army to wage war at great distance—physically, spiritually, economically,” journalist Matt Richtel writes. “It raises questions of the meaning of patriotism, shared purpose and, pointedly, what you’re supposed to say to those who put their lives on the line and are uncomfortable about being thanked for it.”2
My father, a World War II combat veteran and career army physician, told me when I was young that there were 3 experiences that could never be understood unless you lived them: pregnancy, medical school, and combat. I’m not sure why or how he chose these although I am sure they were not original, but having gone through the second, I believe it was because these events are of such personal intensity, such immediate contact with the human condition in all its suffering and resilience that they cannot be faithfully replicated in any in vitro simulation but only in vivo.
Which brings me to the title of the column. How can we say thank you to our friends and family members, our coworkers, and our patients who went to war and returned, who enlisted ready to go into combat even if the fates did not send them? Reading the comments of these men and women in response to the superficial phrase with which we habitually acknowledge their sacrifice leaves me wondering what to say to express our obligation to those who struggled through foreign tribulations while we remained safe at home. Their reflections offer some surprising suggestions that seem prophetic as we as a country process the results of the recent election with grief, triumph, or indifference.
We can say thank you through voting, donations, or advocacy as long as we act to promote the most fundamental good for humanity. We say thank you when we act to help a veteran to live a decent and rewarding life, to have a safe place to live, to grow through education, to share life with companions, and to find a job or another way to contribute to society. Actions to improve the living conditions of veterans now and a better future for those who leave the ranks are seeds of gratitude that come to fruition long after the empty phrases are forgotten.
We say thank you when we think and question long and hard until it hurts, until we too experience cognitive dissonance, until our theory of mind is stretched beyond its comfortable boundaries about the purpose of war in general and the justification for any particular conflict in which our government contemplates sending the young and brave to fight and die. Acting and thinking honor sacrifice as words never can.
And remember: you must never, under any circumstances, despair. To hope and to act, these are our duties in misfortune.
—Boris Pasternak, Doctor Zhivago
This editorial is being written on Veterans Day. Likely you will read it when the stores and streets are lined with holiday decorations. Thanksgiving will have come and gone. All these celebrations have the common themes of giving and gratitude, and among the many requests clamoring for your attention at this season are care package collections for active-duty service members and donations for disadvantaged veterans. These efforts are well intentioned on the part of givers and appreciated on the part of those who receive them. Yet these themes remind me of the hackneyed saying we likely have all heard, and many of us have said: Thank you for your service.
Many of you may recall the controversy that emerged surrounding this seemingly innocuous cliché. It has had an Internet resurgence on this day set out to honor those who wore or are in uniform.1 For those who don’t remember the phenomenon, I will briefly summarize. A journalist was interviewing a combat veteran from Afghanistan on a different subject but knowing he had been in the military and the reporter thinking he was being kind and respectful, like so many of us, thanked him for his service. The astute journalist could tell from the expression on the veteran’s face that the comment had touched a wound he never expected to open. But he cared enough to try and understand how the veteran heard these words from out of the depths of his memories of war.
The emotions that emerged from the interview and the online blogs and comments that followed reflect the toll that war takes: anger, anguish, alienation, which these “have a nice day” words seem to evoke, even though they are never meant to create distance, dismissal, or dishonor. This interaction was a painful one for the veteran, and even for the journalist, and created what psychologists call cognitive dissonance, “a condition of conflict or anxiety resulting from inconsistency between belief and action.”2
The reason those 5 words strike a raw nerve in some—but by no means all—who were or are in the armed forces is that those to whom they are spoken know in a deep and personal way, that we who say them usually do not know what we are talking about. I can see this reaction when I watch several of my VA colleagues who actually are combat veterans say the words but from a different theory of mind, a theory of mind they share. Theory of mind is another psychological concept that is at the core of interpersonal and communication skills, the ability to see and feel the world as another person sees it. When someone who has never fought or even served says “thank you for your service,” some veterans feel that their individual experience of combat or even of being in the military is being expressed inauthentically, even perhaps insincerely.
“To these vets, thanking soldiers for their service symbolizes the ease of sending a volunteer army to wage war at great distance—physically, spiritually, economically,” journalist Matt Richtel writes. “It raises questions of the meaning of patriotism, shared purpose and, pointedly, what you’re supposed to say to those who put their lives on the line and are uncomfortable about being thanked for it.”2
My father, a World War II combat veteran and career army physician, told me when I was young that there were 3 experiences that could never be understood unless you lived them: pregnancy, medical school, and combat. I’m not sure why or how he chose these although I am sure they were not original, but having gone through the second, I believe it was because these events are of such personal intensity, such immediate contact with the human condition in all its suffering and resilience that they cannot be faithfully replicated in any in vitro simulation but only in vivo.
Which brings me to the title of the column. How can we say thank you to our friends and family members, our coworkers, and our patients who went to war and returned, who enlisted ready to go into combat even if the fates did not send them? Reading the comments of these men and women in response to the superficial phrase with which we habitually acknowledge their sacrifice leaves me wondering what to say to express our obligation to those who struggled through foreign tribulations while we remained safe at home. Their reflections offer some surprising suggestions that seem prophetic as we as a country process the results of the recent election with grief, triumph, or indifference.
We can say thank you through voting, donations, or advocacy as long as we act to promote the most fundamental good for humanity. We say thank you when we act to help a veteran to live a decent and rewarding life, to have a safe place to live, to grow through education, to share life with companions, and to find a job or another way to contribute to society. Actions to improve the living conditions of veterans now and a better future for those who leave the ranks are seeds of gratitude that come to fruition long after the empty phrases are forgotten.
We say thank you when we think and question long and hard until it hurts, until we too experience cognitive dissonance, until our theory of mind is stretched beyond its comfortable boundaries about the purpose of war in general and the justification for any particular conflict in which our government contemplates sending the young and brave to fight and die. Acting and thinking honor sacrifice as words never can.
1. Korzen DM. One veteran’s unease when hearing, “Thanks for your service.” Los Angeles Times. http://www.latimes.com /opinion/op-ed/la-oe-korzen-veterans-thank-you-20161111-story.html. Published November 11, 2016. Accessed November 14, 2016.
2. Richtel M. Please don’t thank me for my service.” The New York Times. http://www.nytimes .com/2015/02/22/sunday-review/please-dont-thank -me-for-my-service.html?_r=0. Published February 21, 2015. Accessed November 14, 2016.
1. Korzen DM. One veteran’s unease when hearing, “Thanks for your service.” Los Angeles Times. http://www.latimes.com /opinion/op-ed/la-oe-korzen-veterans-thank-you-20161111-story.html. Published November 11, 2016. Accessed November 14, 2016.
2. Richtel M. Please don’t thank me for my service.” The New York Times. http://www.nytimes .com/2015/02/22/sunday-review/please-dont-thank -me-for-my-service.html?_r=0. Published February 21, 2015. Accessed November 14, 2016.
The merits of buprenorphine for pregnant women with opioid use disorder; A possible solution to the ‘shrinking’ workforce
The merits of buprenorphine for pregnant women with opioid use disorder
Several medication-assisted treatments (MATs) for opioid use disorder were highlighted in “What clinicians need to know about treating opioid use disorder,” (Evidence-Based Reviews,
The landmark study, the Maternal Opioid Treatment: Human Experimental Research, a 2010 multicenter randomized controlled trial compared buprenorphine with methadone in pregnant women with opioid use disorder. The results revealed that neonates exposed to buprenorphine needed 89% less morphine to treat neonatal abstinence syndrome (NAS), 43% shorter hospital stay, and 58% shorter duration of medical treatment for NAS compared with those receiving methadone. Other advantages of buprenorphine over methadone are lower risk of overdose, fewer drug–drug interactions, and the option of receiving treatment in an outpatient setting, rather than a licensed treatment program, such as a methadone maintenance treatment program, which is more tightly controlled.1-3
The previous recommendation was to consider buprenorphine for patients who refused methadone or were unable to take it, or when a methadone treatment program wasn’t available. This study highlighted some clear advantages for treating this subpopulation with methadone instead of buprenorphine: only 18% of patients receiving methadone discontinued treatment, compared with 33% of those receiving buprenorphine,1-3 and methadone had a lower risk of diversion.3 The accepted practice has been to recommend methadone treatment for patients with mental, physical, or social stressors because of the structure of opioid treatment programs (OTP) (also known as methadone maintenance treatment programs). However, buprenorphine can be dispensed through an OTP, following the same stringent rules and regulations.4
The single agent, buprenorphine—not buprenorphine/naloxone—is recommended to prevent prenatal exposure to naloxone. It is thought that exposure to naloxone in utero might produce hormonal changes in the fetus.1,5 O'Connor et al5 noted methadone’s suitability during breast-feeding because of its low concentration in breast milk. Buprenorphine is excreted at breast milk to plasma ratio of 1:1, but because of buprenorphine’s poor oral bioavailability, infant exposure has little impact on the NAS score, therefore it’s suitable for breast-feeding mothers.5
Adegboyega Oyemade, MD, FAPA
Addiction Psychiatrist
Kaiser Permanente
Baltimore, Maryland
References
1. Lori W. Buprenorphine during pregnancy reduces neonate distress. https://www.drugabuse.gov/news-events/nida-notes/2012/07/buprenorphine- during-pregnancy-reduces-neonate-distress. Published July 6, 2016. Accessed September 9, 2016.
2. Jones HE, Kaltenbach K, Heil SH, et al. Neonatal abstinence syndrome after methadone or buprenorphine exposure. N Engl J Med. 2010;363(24):2320-2331.
3. ACOG Committee on Health Care for Underserved Women; American Society of Addiction Medicine. ACOG Committee Opinion No. 524: Opioid abuse, dependence, and addiction in pregnancy. Obest Gynecol. 2012;119(5):1070-1076.
4. Addiction Treatment Forum. Methadone vs. buprenorphine: how do OTPs and patients make the choice? http://atforum.com/2013/11/methadone-vs-buprenorphine-how-do-otps-and-patients-make-the-choice. Published November 15, 2013. Accessed September 9, 2016.
5. O’Connor A, Alto W, Musgrave K, et al. Observational study of buprenorphine treatment of opioid-dependent pregnancy women in a family medicine residency: reports on maternal and infant outcomes. J Am Board Fam Med. 2011;24(2):194-201.
A possible solution to the 'shrinking' workforce
I would like to offer another pragmatic, easy, and quick solution for dealing with the shrinking psychiatrist workforce (The psychiatry workforce pool is shrinking. What are we doing about it? From the Editor.
The United States is short approximately 45,000 psychiatrists.1 Burnout—a silent epidemic among physicians—is prevalent in psychiatry. What consumes time and leads to burn out? “Scut work.”
There are thousands of unmatched residency graduates.2 Most of these graduates have clinical experience in the United States. Psychiatry residency programs should give these unmatched graduates 6 months of training in psychiatry and use them as our primary workforce. These assistant physicians could be paired with 2 to 3 psychiatrists to perform the menial tasks, including, but not limited to, phone calls, prescriptions, prior authorizations, chart review, and other clinical and administrative paper work. This way, psychiatrists can focus on the interview, diagnoses, and treatment, major medical decision-making, and see more patients.
Employing assistant physicians to provide care has been suggested as a solution.3 Arkansas, Kansas, and Missouri have passed laws that allow medical school graduates who did not match with a residency program to work in underserved areas with a collaborating physician.
Because 1 out of 4 individuals have a mental illness and more of them are seeking help because of increasing awareness and the Affordable Care Act, the construct of “assistant physicians” could ease psychiatrists’ workload allowing them to deliver better care to more people.
Maju Mathew Koola, MD
Associate Professor
Department of Psychiatry and Behavioral Sciences
George Washington University
School of Medicine and Health Sciences
Washington, DC
References
1. Carlat D. 45,000 More psychiatrists, anyone? Psychiatric Times. http://www.psychiatrictimes.com/articles/45000-more-psychiatrists-anyone-0.Published August 3, 2010. Accessed November 11, 2016.
2. The Match: National Resident Matching Program. results and data: 2016 main residency match. http://www.nrmp.org/wp-content/uploads/2016/04/Main-Match-Results-and-Data-2016.pdf. Published April 2016. Accessed November 11, 2016.
3. Miller JG, Peterson DJ. Employing nurse practitioners and physician assistants to provide access to care as the psychiatrist shortage continues. Acad Psychiatry. 2015;39(6):685-686.
Concerns in psychiatry
The August 2016 editorial (Unresolved questions about the specialty lurk in the cortext of psychiatrists.
Denis F. Darko, MD
CEO
NeuroSci R&D Consultancy, LLC
Maple Grove, Minnesota
The merits of buprenorphine for pregnant women with opioid use disorder
Several medication-assisted treatments (MATs) for opioid use disorder were highlighted in “What clinicians need to know about treating opioid use disorder,” (Evidence-Based Reviews,
The landmark study, the Maternal Opioid Treatment: Human Experimental Research, a 2010 multicenter randomized controlled trial compared buprenorphine with methadone in pregnant women with opioid use disorder. The results revealed that neonates exposed to buprenorphine needed 89% less morphine to treat neonatal abstinence syndrome (NAS), 43% shorter hospital stay, and 58% shorter duration of medical treatment for NAS compared with those receiving methadone. Other advantages of buprenorphine over methadone are lower risk of overdose, fewer drug–drug interactions, and the option of receiving treatment in an outpatient setting, rather than a licensed treatment program, such as a methadone maintenance treatment program, which is more tightly controlled.1-3
The previous recommendation was to consider buprenorphine for patients who refused methadone or were unable to take it, or when a methadone treatment program wasn’t available. This study highlighted some clear advantages for treating this subpopulation with methadone instead of buprenorphine: only 18% of patients receiving methadone discontinued treatment, compared with 33% of those receiving buprenorphine,1-3 and methadone had a lower risk of diversion.3 The accepted practice has been to recommend methadone treatment for patients with mental, physical, or social stressors because of the structure of opioid treatment programs (OTP) (also known as methadone maintenance treatment programs). However, buprenorphine can be dispensed through an OTP, following the same stringent rules and regulations.4
The single agent, buprenorphine—not buprenorphine/naloxone—is recommended to prevent prenatal exposure to naloxone. It is thought that exposure to naloxone in utero might produce hormonal changes in the fetus.1,5 O'Connor et al5 noted methadone’s suitability during breast-feeding because of its low concentration in breast milk. Buprenorphine is excreted at breast milk to plasma ratio of 1:1, but because of buprenorphine’s poor oral bioavailability, infant exposure has little impact on the NAS score, therefore it’s suitable for breast-feeding mothers.5
Adegboyega Oyemade, MD, FAPA
Addiction Psychiatrist
Kaiser Permanente
Baltimore, Maryland
References
1. Lori W. Buprenorphine during pregnancy reduces neonate distress. https://www.drugabuse.gov/news-events/nida-notes/2012/07/buprenorphine- during-pregnancy-reduces-neonate-distress. Published July 6, 2016. Accessed September 9, 2016.
2. Jones HE, Kaltenbach K, Heil SH, et al. Neonatal abstinence syndrome after methadone or buprenorphine exposure. N Engl J Med. 2010;363(24):2320-2331.
3. ACOG Committee on Health Care for Underserved Women; American Society of Addiction Medicine. ACOG Committee Opinion No. 524: Opioid abuse, dependence, and addiction in pregnancy. Obest Gynecol. 2012;119(5):1070-1076.
4. Addiction Treatment Forum. Methadone vs. buprenorphine: how do OTPs and patients make the choice? http://atforum.com/2013/11/methadone-vs-buprenorphine-how-do-otps-and-patients-make-the-choice. Published November 15, 2013. Accessed September 9, 2016.
5. O’Connor A, Alto W, Musgrave K, et al. Observational study of buprenorphine treatment of opioid-dependent pregnancy women in a family medicine residency: reports on maternal and infant outcomes. J Am Board Fam Med. 2011;24(2):194-201.
A possible solution to the 'shrinking' workforce
I would like to offer another pragmatic, easy, and quick solution for dealing with the shrinking psychiatrist workforce (The psychiatry workforce pool is shrinking. What are we doing about it? From the Editor.
The United States is short approximately 45,000 psychiatrists.1 Burnout—a silent epidemic among physicians—is prevalent in psychiatry. What consumes time and leads to burn out? “Scut work.”
There are thousands of unmatched residency graduates.2 Most of these graduates have clinical experience in the United States. Psychiatry residency programs should give these unmatched graduates 6 months of training in psychiatry and use them as our primary workforce. These assistant physicians could be paired with 2 to 3 psychiatrists to perform the menial tasks, including, but not limited to, phone calls, prescriptions, prior authorizations, chart review, and other clinical and administrative paper work. This way, psychiatrists can focus on the interview, diagnoses, and treatment, major medical decision-making, and see more patients.
Employing assistant physicians to provide care has been suggested as a solution.3 Arkansas, Kansas, and Missouri have passed laws that allow medical school graduates who did not match with a residency program to work in underserved areas with a collaborating physician.
Because 1 out of 4 individuals have a mental illness and more of them are seeking help because of increasing awareness and the Affordable Care Act, the construct of “assistant physicians” could ease psychiatrists’ workload allowing them to deliver better care to more people.
Maju Mathew Koola, MD
Associate Professor
Department of Psychiatry and Behavioral Sciences
George Washington University
School of Medicine and Health Sciences
Washington, DC
References
1. Carlat D. 45,000 More psychiatrists, anyone? Psychiatric Times. http://www.psychiatrictimes.com/articles/45000-more-psychiatrists-anyone-0.Published August 3, 2010. Accessed November 11, 2016.
2. The Match: National Resident Matching Program. results and data: 2016 main residency match. http://www.nrmp.org/wp-content/uploads/2016/04/Main-Match-Results-and-Data-2016.pdf. Published April 2016. Accessed November 11, 2016.
3. Miller JG, Peterson DJ. Employing nurse practitioners and physician assistants to provide access to care as the psychiatrist shortage continues. Acad Psychiatry. 2015;39(6):685-686.
Concerns in psychiatry
The August 2016 editorial (Unresolved questions about the specialty lurk in the cortext of psychiatrists.
Denis F. Darko, MD
CEO
NeuroSci R&D Consultancy, LLC
Maple Grove, Minnesota
The merits of buprenorphine for pregnant women with opioid use disorder
Several medication-assisted treatments (MATs) for opioid use disorder were highlighted in “What clinicians need to know about treating opioid use disorder,” (Evidence-Based Reviews,
The landmark study, the Maternal Opioid Treatment: Human Experimental Research, a 2010 multicenter randomized controlled trial compared buprenorphine with methadone in pregnant women with opioid use disorder. The results revealed that neonates exposed to buprenorphine needed 89% less morphine to treat neonatal abstinence syndrome (NAS), 43% shorter hospital stay, and 58% shorter duration of medical treatment for NAS compared with those receiving methadone. Other advantages of buprenorphine over methadone are lower risk of overdose, fewer drug–drug interactions, and the option of receiving treatment in an outpatient setting, rather than a licensed treatment program, such as a methadone maintenance treatment program, which is more tightly controlled.1-3
The previous recommendation was to consider buprenorphine for patients who refused methadone or were unable to take it, or when a methadone treatment program wasn’t available. This study highlighted some clear advantages for treating this subpopulation with methadone instead of buprenorphine: only 18% of patients receiving methadone discontinued treatment, compared with 33% of those receiving buprenorphine,1-3 and methadone had a lower risk of diversion.3 The accepted practice has been to recommend methadone treatment for patients with mental, physical, or social stressors because of the structure of opioid treatment programs (OTP) (also known as methadone maintenance treatment programs). However, buprenorphine can be dispensed through an OTP, following the same stringent rules and regulations.4
The single agent, buprenorphine—not buprenorphine/naloxone—is recommended to prevent prenatal exposure to naloxone. It is thought that exposure to naloxone in utero might produce hormonal changes in the fetus.1,5 O'Connor et al5 noted methadone’s suitability during breast-feeding because of its low concentration in breast milk. Buprenorphine is excreted at breast milk to plasma ratio of 1:1, but because of buprenorphine’s poor oral bioavailability, infant exposure has little impact on the NAS score, therefore it’s suitable for breast-feeding mothers.5
Adegboyega Oyemade, MD, FAPA
Addiction Psychiatrist
Kaiser Permanente
Baltimore, Maryland
References
1. Lori W. Buprenorphine during pregnancy reduces neonate distress. https://www.drugabuse.gov/news-events/nida-notes/2012/07/buprenorphine- during-pregnancy-reduces-neonate-distress. Published July 6, 2016. Accessed September 9, 2016.
2. Jones HE, Kaltenbach K, Heil SH, et al. Neonatal abstinence syndrome after methadone or buprenorphine exposure. N Engl J Med. 2010;363(24):2320-2331.
3. ACOG Committee on Health Care for Underserved Women; American Society of Addiction Medicine. ACOG Committee Opinion No. 524: Opioid abuse, dependence, and addiction in pregnancy. Obest Gynecol. 2012;119(5):1070-1076.
4. Addiction Treatment Forum. Methadone vs. buprenorphine: how do OTPs and patients make the choice? http://atforum.com/2013/11/methadone-vs-buprenorphine-how-do-otps-and-patients-make-the-choice. Published November 15, 2013. Accessed September 9, 2016.
5. O’Connor A, Alto W, Musgrave K, et al. Observational study of buprenorphine treatment of opioid-dependent pregnancy women in a family medicine residency: reports on maternal and infant outcomes. J Am Board Fam Med. 2011;24(2):194-201.
A possible solution to the 'shrinking' workforce
I would like to offer another pragmatic, easy, and quick solution for dealing with the shrinking psychiatrist workforce (The psychiatry workforce pool is shrinking. What are we doing about it? From the Editor.
The United States is short approximately 45,000 psychiatrists.1 Burnout—a silent epidemic among physicians—is prevalent in psychiatry. What consumes time and leads to burn out? “Scut work.”
There are thousands of unmatched residency graduates.2 Most of these graduates have clinical experience in the United States. Psychiatry residency programs should give these unmatched graduates 6 months of training in psychiatry and use them as our primary workforce. These assistant physicians could be paired with 2 to 3 psychiatrists to perform the menial tasks, including, but not limited to, phone calls, prescriptions, prior authorizations, chart review, and other clinical and administrative paper work. This way, psychiatrists can focus on the interview, diagnoses, and treatment, major medical decision-making, and see more patients.
Employing assistant physicians to provide care has been suggested as a solution.3 Arkansas, Kansas, and Missouri have passed laws that allow medical school graduates who did not match with a residency program to work in underserved areas with a collaborating physician.
Because 1 out of 4 individuals have a mental illness and more of them are seeking help because of increasing awareness and the Affordable Care Act, the construct of “assistant physicians” could ease psychiatrists’ workload allowing them to deliver better care to more people.
Maju Mathew Koola, MD
Associate Professor
Department of Psychiatry and Behavioral Sciences
George Washington University
School of Medicine and Health Sciences
Washington, DC
References
1. Carlat D. 45,000 More psychiatrists, anyone? Psychiatric Times. http://www.psychiatrictimes.com/articles/45000-more-psychiatrists-anyone-0.Published August 3, 2010. Accessed November 11, 2016.
2. The Match: National Resident Matching Program. results and data: 2016 main residency match. http://www.nrmp.org/wp-content/uploads/2016/04/Main-Match-Results-and-Data-2016.pdf. Published April 2016. Accessed November 11, 2016.
3. Miller JG, Peterson DJ. Employing nurse practitioners and physician assistants to provide access to care as the psychiatrist shortage continues. Acad Psychiatry. 2015;39(6):685-686.
Concerns in psychiatry
The August 2016 editorial (Unresolved questions about the specialty lurk in the cortext of psychiatrists.
Denis F. Darko, MD
CEO
NeuroSci R&D Consultancy, LLC
Maple Grove, Minnesota
6 steps to take when a patient insists on that antibiotic
In this issue of JFP, Wiskirchen and colleagues discuss the appropriate use of antibiotics in outpatient settings, providing stewardship advice for several conditions we frequently see in primary care practice.
One of the symptoms for which we most frequently battle requests for antibiotics is acute cough. Despite the fact that more than 90% of cases of acute cough illness (aka acute bronchitis) are caused by viruses, the prescribing rate for it in the United States remains about 70%.1
Over the years, I’ve honed a “spiel” that I use with patients with acute cough illness to help keep my antibiotic prescribing to a minimum. It must be working; my prescribing rate is less than 20%. What follows are some of my catch phrases and techniques.
1. Acknowledge the patient’s misery. “Sounds like you have a really bad bug."
2. Tell the patient what he or she doesn’t have. “Your lungs sound good, and your throat does not look too bad, so that means you don’t have strep throat or pneumonia. That’s good news.”
3. Explain what viruses are “making the rounds.” If you have surveillance data, that’s even better. “I have seen several other patients with symptoms just like yours this week.” Over 25 years ago, Jon Temte, an FP from Wisconsin, drove down prescribing rates for acute bronchitis below 20% in family medicine residencies by providing feedback to physicians and patients about the viruses circulating in their communities.2
4. Set realistic expectations. Tell patients how long their cough is likely to last. The duration of the typical cough is (unfortunately) about 17 days.3 Most patients (and even some doctors) think a bad cold should be gone in 7 days.3
5. Choose your terms carefully. Don’t use the term “acute bronchitis.” It sounds bad and worthy of an antibiotic. “Chest cold” sounds much more benign; patients are less likely to think they need an antibiotic for a chest cold.4
6. When all else fails, consider a delayed prescription. I reserve this strategy for patients who are insistent on getting an antibiotic even though their illness is clearly viral. Randomized trials of the delayed strategy show that fewer than 50% of patients actually fill the prescription.5
Develop your own spiel to reduce unnecessary antibiotic prescribing. You’ll find that it works a good deal of the time.
1. Barnett ML, Linder JA. Antibiotic prescribing for adults with acute bronchitis in the United States, 1996-2010. JAMA. 2014;311:2020-2022.
2. Temte JL, Shult PA, Kirk CJ, et al. Effects of viral respiratory disease education and surveillance on antibiotic prescribing. Fam Med. 1999;31:101-106.
3. Ebell MH, Lundgren J, Youngpairoj S. How long does a cough last? Comparing patients’ expectations with data from a systematic review of the literature. Ann Fam Med. 2013;11:5-13.
4. Phillips TG, Hickner J. Calling acute bronchitis a chest cold may improve patient satisfaction with appropriate antibiotic use. J Am Board Fam Pract. 2005;18:459-463.
5. Spurling GK, Del Mar CB, Dooley L, et al. Delayed antibiotics for respiratory infections. Cochrane Database Syst Rev. 2013:CD004417.
John Hickner, MD, MSc
Editor-in-Chief
John Hickner, MD, MSc
Editor-in-Chief
John Hickner, MD, MSc
Editor-in-Chief
In this issue of JFP, Wiskirchen and colleagues discuss the appropriate use of antibiotics in outpatient settings, providing stewardship advice for several conditions we frequently see in primary care practice.
One of the symptoms for which we most frequently battle requests for antibiotics is acute cough. Despite the fact that more than 90% of cases of acute cough illness (aka acute bronchitis) are caused by viruses, the prescribing rate for it in the United States remains about 70%.1
Over the years, I’ve honed a “spiel” that I use with patients with acute cough illness to help keep my antibiotic prescribing to a minimum. It must be working; my prescribing rate is less than 20%. What follows are some of my catch phrases and techniques.
1. Acknowledge the patient’s misery. “Sounds like you have a really bad bug."
2. Tell the patient what he or she doesn’t have. “Your lungs sound good, and your throat does not look too bad, so that means you don’t have strep throat or pneumonia. That’s good news.”
3. Explain what viruses are “making the rounds.” If you have surveillance data, that’s even better. “I have seen several other patients with symptoms just like yours this week.” Over 25 years ago, Jon Temte, an FP from Wisconsin, drove down prescribing rates for acute bronchitis below 20% in family medicine residencies by providing feedback to physicians and patients about the viruses circulating in their communities.2
4. Set realistic expectations. Tell patients how long their cough is likely to last. The duration of the typical cough is (unfortunately) about 17 days.3 Most patients (and even some doctors) think a bad cold should be gone in 7 days.3
5. Choose your terms carefully. Don’t use the term “acute bronchitis.” It sounds bad and worthy of an antibiotic. “Chest cold” sounds much more benign; patients are less likely to think they need an antibiotic for a chest cold.4
6. When all else fails, consider a delayed prescription. I reserve this strategy for patients who are insistent on getting an antibiotic even though their illness is clearly viral. Randomized trials of the delayed strategy show that fewer than 50% of patients actually fill the prescription.5
Develop your own spiel to reduce unnecessary antibiotic prescribing. You’ll find that it works a good deal of the time.
In this issue of JFP, Wiskirchen and colleagues discuss the appropriate use of antibiotics in outpatient settings, providing stewardship advice for several conditions we frequently see in primary care practice.
One of the symptoms for which we most frequently battle requests for antibiotics is acute cough. Despite the fact that more than 90% of cases of acute cough illness (aka acute bronchitis) are caused by viruses, the prescribing rate for it in the United States remains about 70%.1
Over the years, I’ve honed a “spiel” that I use with patients with acute cough illness to help keep my antibiotic prescribing to a minimum. It must be working; my prescribing rate is less than 20%. What follows are some of my catch phrases and techniques.
1. Acknowledge the patient’s misery. “Sounds like you have a really bad bug."
2. Tell the patient what he or she doesn’t have. “Your lungs sound good, and your throat does not look too bad, so that means you don’t have strep throat or pneumonia. That’s good news.”
3. Explain what viruses are “making the rounds.” If you have surveillance data, that’s even better. “I have seen several other patients with symptoms just like yours this week.” Over 25 years ago, Jon Temte, an FP from Wisconsin, drove down prescribing rates for acute bronchitis below 20% in family medicine residencies by providing feedback to physicians and patients about the viruses circulating in their communities.2
4. Set realistic expectations. Tell patients how long their cough is likely to last. The duration of the typical cough is (unfortunately) about 17 days.3 Most patients (and even some doctors) think a bad cold should be gone in 7 days.3
5. Choose your terms carefully. Don’t use the term “acute bronchitis.” It sounds bad and worthy of an antibiotic. “Chest cold” sounds much more benign; patients are less likely to think they need an antibiotic for a chest cold.4
6. When all else fails, consider a delayed prescription. I reserve this strategy for patients who are insistent on getting an antibiotic even though their illness is clearly viral. Randomized trials of the delayed strategy show that fewer than 50% of patients actually fill the prescription.5
Develop your own spiel to reduce unnecessary antibiotic prescribing. You’ll find that it works a good deal of the time.
1. Barnett ML, Linder JA. Antibiotic prescribing for adults with acute bronchitis in the United States, 1996-2010. JAMA. 2014;311:2020-2022.
2. Temte JL, Shult PA, Kirk CJ, et al. Effects of viral respiratory disease education and surveillance on antibiotic prescribing. Fam Med. 1999;31:101-106.
3. Ebell MH, Lundgren J, Youngpairoj S. How long does a cough last? Comparing patients’ expectations with data from a systematic review of the literature. Ann Fam Med. 2013;11:5-13.
4. Phillips TG, Hickner J. Calling acute bronchitis a chest cold may improve patient satisfaction with appropriate antibiotic use. J Am Board Fam Pract. 2005;18:459-463.
5. Spurling GK, Del Mar CB, Dooley L, et al. Delayed antibiotics for respiratory infections. Cochrane Database Syst Rev. 2013:CD004417.
1. Barnett ML, Linder JA. Antibiotic prescribing for adults with acute bronchitis in the United States, 1996-2010. JAMA. 2014;311:2020-2022.
2. Temte JL, Shult PA, Kirk CJ, et al. Effects of viral respiratory disease education and surveillance on antibiotic prescribing. Fam Med. 1999;31:101-106.
3. Ebell MH, Lundgren J, Youngpairoj S. How long does a cough last? Comparing patients’ expectations with data from a systematic review of the literature. Ann Fam Med. 2013;11:5-13.
4. Phillips TG, Hickner J. Calling acute bronchitis a chest cold may improve patient satisfaction with appropriate antibiotic use. J Am Board Fam Pract. 2005;18:459-463.
5. Spurling GK, Del Mar CB, Dooley L, et al. Delayed antibiotics for respiratory infections. Cochrane Database Syst Rev. 2013:CD004417.
Mental Health: A Forgotten Facet of Primary Care
One of the biggest disparities in health care today is the separate treatment of mind and body, despite their known integration.1 While mental and behavioral health conditions are frequently diagnosed and treated within primary care settings, fragmentation persists between the mental and physical health care systems—creating barriers in the quality, outcome, and efficiency of care.2 Since half of Americans with mental health conditions go without essential care, reform of our nation’s mental health system is a priority issue for NPs and PAs and the patients we serve.
Some progress has been made to implement change—the Now Is the Time initiative, launched in 2013, increased federal funding for behavioral health care workforce training in an effort to support more providers in mental and substance use disorder treatment. The Affordable Care Act (ACA) has worked to improve behavioral health coverage for Americans in three ways: ending insurance company discrimination based on pre-existing conditions, requiring health insurance coverage for mental and substance use disorder services, and expanding mental health parity. This has improved coverage and access to mental and substance abuse services for more than 60 million Americans.3 In January 2016, President Obama proposed a $500 million investment to increase access to mental health care.4 The most recent presidential election creates an uncertain future for
Regardless, more work has to be done to guarantee that Americans have the access they need. Sadly, even with these advancements in behavioral health coverage, only about half of children and less than half of adults with diagnosable mental health disorders get the treatment they need.4 A 2016 report from the Rural Health Research Center revealed that more than 15 million Americans face behavioral health issues without access to the necessary care.5
Psychiatric providers (like most other specialists) tend to be located in urban areas, limiting access in rural areas and even some underserved urban communities. Only 43% of family physicians in this country provide mental health care.6 The team-based care that NPs and PAs provide has great potential for bridging this gap in mental health coverage.
NPs and PAs are an important but underutilized resource for improving mental health care access—but how can primary care NPs and PAs work to enhance the delivery of mental health care in our country? In the preprofessional area, it would be prudent to entice qualified individuals in the mental health field—particularly those who are licensed clinical social workers, licensed professional counselors, or marriage and family therapists—into NP and PA programs with preference.
Clinical rotations in behavioral health (BH)/psychiatry should be encouraged—even mandated—in professional education. We should ensure this content is taught in the didactic portion of NP/PA professional education, as well as bolstering psychiatric pharmacology in coursework.
Postprofessional education should encourage primary care NPs and PAs to gain additional self-directed education in BH/psychiatry. This can be achieved via a focused psychiatry “boot camp” (for PAs following the CAQ blueprint, found at www.nccpa.net/psychiatry) or a competency-based online postprofessional certificate in BH/psychiatry (such as—shameless plug—the one offered at my institution; www.atsu.edu/postgraduate-certificate-in-psychiatry-and-behavioral-health-online).7,8
This psychiatric background is fundamental throughout primary care but is crucial in community health centers, correctional health care centers, and Veterans Administration hospitals. Of course, in order to make a difference, we must remove the barriers that prevent psychiatric NPs and PAs from being considered mental health providers and adjust reimbursement accordingly.
Do you have ideas on how to increase the knowledge base of primary care NPs and PAs and enhance the provision of mental health services in this country? Will the political change in leadership in January 2017 increase opportunities to make a difference in mental health care? Please share your thoughts by contacting me at [email protected].
1. deGruy F. Mental health care in the primary care setting. In: Donaldson MS, Yordy KD, Lohr KN, Vanselow NA, eds. Primary Care: America’s Health in a New Era. Washington, DC: Institute of Medicine; 1996.
2. Simon GE, Katon WJ, VonKorff M, et al. Cost-effectiveness of a collaborative care program for primary care patients with persistent depression. Am J Psychiatry. 2001;158(10): 1638-1644.
3. Enomoto K. Improving access to mental health services - President’s FY 2017 Budget proposes new investments to increase access. http://abilitychicagoinfo.blogspot.com/2016/02/improving-access-to-mental-health.html. Accessed November 3, 2016.
4. Enomoto K. Improving access to mental health services. www.hhs.gov/blog/2016/02/09/improving-access-mental-health-services.html. Accessed November 3, 2016.
5. Rural Health Research Center. Supply and distribution of the behavioral health workforce in rural America. http://depts.washington.edu/fammed/rhrc/wp-content/uploads/sites/4/2016/09/RHRC_DB160_Larson.pdf. Accessed November 3, 2016.
6. Miller BF, Druss B. The role of family physicians in mental health care delivery in the United States: implications for health reform. J Am Board Fam Med. 2013;26(2): 111-113.
7. National Commission on Certification of Physician Assistants. Psychiatry CAQ. www.nccpa.net/psychiatry. Accessed November 3, 2016.
8. A.T. Still University. Postgraduate certificate in psychiatry and behavioral health online. www.atsu.edu/postgraduate-certificate-in-psychiatry-and-behavioral-health-online. Accessed November 3, 2016.
One of the biggest disparities in health care today is the separate treatment of mind and body, despite their known integration.1 While mental and behavioral health conditions are frequently diagnosed and treated within primary care settings, fragmentation persists between the mental and physical health care systems—creating barriers in the quality, outcome, and efficiency of care.2 Since half of Americans with mental health conditions go without essential care, reform of our nation’s mental health system is a priority issue for NPs and PAs and the patients we serve.
Some progress has been made to implement change—the Now Is the Time initiative, launched in 2013, increased federal funding for behavioral health care workforce training in an effort to support more providers in mental and substance use disorder treatment. The Affordable Care Act (ACA) has worked to improve behavioral health coverage for Americans in three ways: ending insurance company discrimination based on pre-existing conditions, requiring health insurance coverage for mental and substance use disorder services, and expanding mental health parity. This has improved coverage and access to mental and substance abuse services for more than 60 million Americans.3 In January 2016, President Obama proposed a $500 million investment to increase access to mental health care.4 The most recent presidential election creates an uncertain future for
Regardless, more work has to be done to guarantee that Americans have the access they need. Sadly, even with these advancements in behavioral health coverage, only about half of children and less than half of adults with diagnosable mental health disorders get the treatment they need.4 A 2016 report from the Rural Health Research Center revealed that more than 15 million Americans face behavioral health issues without access to the necessary care.5
Psychiatric providers (like most other specialists) tend to be located in urban areas, limiting access in rural areas and even some underserved urban communities. Only 43% of family physicians in this country provide mental health care.6 The team-based care that NPs and PAs provide has great potential for bridging this gap in mental health coverage.
NPs and PAs are an important but underutilized resource for improving mental health care access—but how can primary care NPs and PAs work to enhance the delivery of mental health care in our country? In the preprofessional area, it would be prudent to entice qualified individuals in the mental health field—particularly those who are licensed clinical social workers, licensed professional counselors, or marriage and family therapists—into NP and PA programs with preference.
Clinical rotations in behavioral health (BH)/psychiatry should be encouraged—even mandated—in professional education. We should ensure this content is taught in the didactic portion of NP/PA professional education, as well as bolstering psychiatric pharmacology in coursework.
Postprofessional education should encourage primary care NPs and PAs to gain additional self-directed education in BH/psychiatry. This can be achieved via a focused psychiatry “boot camp” (for PAs following the CAQ blueprint, found at www.nccpa.net/psychiatry) or a competency-based online postprofessional certificate in BH/psychiatry (such as—shameless plug—the one offered at my institution; www.atsu.edu/postgraduate-certificate-in-psychiatry-and-behavioral-health-online).7,8
This psychiatric background is fundamental throughout primary care but is crucial in community health centers, correctional health care centers, and Veterans Administration hospitals. Of course, in order to make a difference, we must remove the barriers that prevent psychiatric NPs and PAs from being considered mental health providers and adjust reimbursement accordingly.
Do you have ideas on how to increase the knowledge base of primary care NPs and PAs and enhance the provision of mental health services in this country? Will the political change in leadership in January 2017 increase opportunities to make a difference in mental health care? Please share your thoughts by contacting me at [email protected].
One of the biggest disparities in health care today is the separate treatment of mind and body, despite their known integration.1 While mental and behavioral health conditions are frequently diagnosed and treated within primary care settings, fragmentation persists between the mental and physical health care systems—creating barriers in the quality, outcome, and efficiency of care.2 Since half of Americans with mental health conditions go without essential care, reform of our nation’s mental health system is a priority issue for NPs and PAs and the patients we serve.
Some progress has been made to implement change—the Now Is the Time initiative, launched in 2013, increased federal funding for behavioral health care workforce training in an effort to support more providers in mental and substance use disorder treatment. The Affordable Care Act (ACA) has worked to improve behavioral health coverage for Americans in three ways: ending insurance company discrimination based on pre-existing conditions, requiring health insurance coverage for mental and substance use disorder services, and expanding mental health parity. This has improved coverage and access to mental and substance abuse services for more than 60 million Americans.3 In January 2016, President Obama proposed a $500 million investment to increase access to mental health care.4 The most recent presidential election creates an uncertain future for
Regardless, more work has to be done to guarantee that Americans have the access they need. Sadly, even with these advancements in behavioral health coverage, only about half of children and less than half of adults with diagnosable mental health disorders get the treatment they need.4 A 2016 report from the Rural Health Research Center revealed that more than 15 million Americans face behavioral health issues without access to the necessary care.5
Psychiatric providers (like most other specialists) tend to be located in urban areas, limiting access in rural areas and even some underserved urban communities. Only 43% of family physicians in this country provide mental health care.6 The team-based care that NPs and PAs provide has great potential for bridging this gap in mental health coverage.
NPs and PAs are an important but underutilized resource for improving mental health care access—but how can primary care NPs and PAs work to enhance the delivery of mental health care in our country? In the preprofessional area, it would be prudent to entice qualified individuals in the mental health field—particularly those who are licensed clinical social workers, licensed professional counselors, or marriage and family therapists—into NP and PA programs with preference.
Clinical rotations in behavioral health (BH)/psychiatry should be encouraged—even mandated—in professional education. We should ensure this content is taught in the didactic portion of NP/PA professional education, as well as bolstering psychiatric pharmacology in coursework.
Postprofessional education should encourage primary care NPs and PAs to gain additional self-directed education in BH/psychiatry. This can be achieved via a focused psychiatry “boot camp” (for PAs following the CAQ blueprint, found at www.nccpa.net/psychiatry) or a competency-based online postprofessional certificate in BH/psychiatry (such as—shameless plug—the one offered at my institution; www.atsu.edu/postgraduate-certificate-in-psychiatry-and-behavioral-health-online).7,8
This psychiatric background is fundamental throughout primary care but is crucial in community health centers, correctional health care centers, and Veterans Administration hospitals. Of course, in order to make a difference, we must remove the barriers that prevent psychiatric NPs and PAs from being considered mental health providers and adjust reimbursement accordingly.
Do you have ideas on how to increase the knowledge base of primary care NPs and PAs and enhance the provision of mental health services in this country? Will the political change in leadership in January 2017 increase opportunities to make a difference in mental health care? Please share your thoughts by contacting me at [email protected].
1. deGruy F. Mental health care in the primary care setting. In: Donaldson MS, Yordy KD, Lohr KN, Vanselow NA, eds. Primary Care: America’s Health in a New Era. Washington, DC: Institute of Medicine; 1996.
2. Simon GE, Katon WJ, VonKorff M, et al. Cost-effectiveness of a collaborative care program for primary care patients with persistent depression. Am J Psychiatry. 2001;158(10): 1638-1644.
3. Enomoto K. Improving access to mental health services - President’s FY 2017 Budget proposes new investments to increase access. http://abilitychicagoinfo.blogspot.com/2016/02/improving-access-to-mental-health.html. Accessed November 3, 2016.
4. Enomoto K. Improving access to mental health services. www.hhs.gov/blog/2016/02/09/improving-access-mental-health-services.html. Accessed November 3, 2016.
5. Rural Health Research Center. Supply and distribution of the behavioral health workforce in rural America. http://depts.washington.edu/fammed/rhrc/wp-content/uploads/sites/4/2016/09/RHRC_DB160_Larson.pdf. Accessed November 3, 2016.
6. Miller BF, Druss B. The role of family physicians in mental health care delivery in the United States: implications for health reform. J Am Board Fam Med. 2013;26(2): 111-113.
7. National Commission on Certification of Physician Assistants. Psychiatry CAQ. www.nccpa.net/psychiatry. Accessed November 3, 2016.
8. A.T. Still University. Postgraduate certificate in psychiatry and behavioral health online. www.atsu.edu/postgraduate-certificate-in-psychiatry-and-behavioral-health-online. Accessed November 3, 2016.
1. deGruy F. Mental health care in the primary care setting. In: Donaldson MS, Yordy KD, Lohr KN, Vanselow NA, eds. Primary Care: America’s Health in a New Era. Washington, DC: Institute of Medicine; 1996.
2. Simon GE, Katon WJ, VonKorff M, et al. Cost-effectiveness of a collaborative care program for primary care patients with persistent depression. Am J Psychiatry. 2001;158(10): 1638-1644.
3. Enomoto K. Improving access to mental health services - President’s FY 2017 Budget proposes new investments to increase access. http://abilitychicagoinfo.blogspot.com/2016/02/improving-access-to-mental-health.html. Accessed November 3, 2016.
4. Enomoto K. Improving access to mental health services. www.hhs.gov/blog/2016/02/09/improving-access-mental-health-services.html. Accessed November 3, 2016.
5. Rural Health Research Center. Supply and distribution of the behavioral health workforce in rural America. http://depts.washington.edu/fammed/rhrc/wp-content/uploads/sites/4/2016/09/RHRC_DB160_Larson.pdf. Accessed November 3, 2016.
6. Miller BF, Druss B. The role of family physicians in mental health care delivery in the United States: implications for health reform. J Am Board Fam Med. 2013;26(2): 111-113.
7. National Commission on Certification of Physician Assistants. Psychiatry CAQ. www.nccpa.net/psychiatry. Accessed November 3, 2016.
8. A.T. Still University. Postgraduate certificate in psychiatry and behavioral health online. www.atsu.edu/postgraduate-certificate-in-psychiatry-and-behavioral-health-online. Accessed November 3, 2016.