Terry L. Kamps

 

Infection and infection sites have been found to be associated with a significant increased risk of venous thromboembolism, according to results of a population-based, matched, case-control analysis of medical records covering the 13-year period 1988-2000.

Dr. Kevin P. Cohoon and his colleagues at the Mayo Clinic, Rochester, Minn., developed models using conditional logistic regression analysis to stratify the risk associated with specific infections and infection sites.

Courtesy Wikimedia Commons/Walter Serra, Giuseppe De Iaco, Claudio Reverberi, and Tiziano Gherli/Creative Commons License

A total of 1,303 individuals, mean age of 65.2 years, with a first lifetime objectively diagnosed deep vein thrombosis and/or pulmonary embolism were identified and paired with 1,494 controls without venous thromboembolism (VTE), mean age of 64.9 years. The matches were based on sex, age, and an episode of medical care within 1 year of the case event date. The case population consisted of 55.6% women, compared with the control population consisting of 55.4% women.

Five hundred thirteen (39.4%) cases and 189 (12.7%) controls had an infection within the previous 92 days (odds ratio, 4.5; P less than .0001). Known VTE risk factors and potentially confounding variables were used in the adjusted univariate and multivariate models, as reported in the American Journal of Medicine (2017. doi: 10.1016/j.amjmed.2017.09.015).

Dr. Cohoon and his colleagues reported that univariate analysis showed “most infection sites were strongly associated with venous thromboembolism” and the adjusted multivariate model resulted in 2.4-fold (P less than .0001) higher odds for VTE incidence, compared with uninfected controls.

Adjusted multivariate analysis ranked the odds of VTE according to specific infections. Dr. Cohoon and his colleagues reported that this modeling showed that the “highest magnitude of risk, compared with no infection, was imparted by intra-abdominal infection (OR, 18) followed by oral infection (OR, 12), systematic blood stream infection (OR, 11), lower respiratory infection such as pneumonia (OR, 3.6), and symptomatic urinary tract infection (OR, 2.2).”

The researchers concluded that their findings may allow for further refinement of inpatient VTE risk-prediction models such as the Padua prediction score and “future studies are required to assess the utility of venous thromboembolism prophylaxis among outpatients with high venous thromboembolism risk infections.”

The authors reported that they had no conflicts of interest.

 

 

Infection and infection sites have been found to be associated with a significant increased risk of venous thromboembolism, according to results of a population-based, matched, case-control analysis of medical records covering the 13-year period 1988-2000.

Dr. Kevin P. Cohoon and his colleagues at the Mayo Clinic, Rochester, Minn., developed models using conditional logistic regression analysis to stratify the risk associated with specific infections and infection sites.

Courtesy Wikimedia Commons/Walter Serra, Giuseppe De Iaco, Claudio Reverberi, and Tiziano Gherli/Creative Commons License

A total of 1,303 individuals, mean age of 65.2 years, with a first lifetime objectively diagnosed deep vein thrombosis and/or pulmonary embolism were identified and paired with 1,494 controls without venous thromboembolism (VTE), mean age of 64.9 years. The matches were based on sex, age, and an episode of medical care within 1 year of the case event date. The case population consisted of 55.6% women, compared with the control population consisting of 55.4% women.

Five hundred thirteen (39.4%) cases and 189 (12.7%) controls had an infection within the previous 92 days (odds ratio, 4.5; P less than .0001). Known VTE risk factors and potentially confounding variables were used in the adjusted univariate and multivariate models, as reported in the American Journal of Medicine (2017. doi: 10.1016/j.amjmed.2017.09.015).

Dr. Cohoon and his colleagues reported that univariate analysis showed “most infection sites were strongly associated with venous thromboembolism” and the adjusted multivariate model resulted in 2.4-fold (P less than .0001) higher odds for VTE incidence, compared with uninfected controls.

Adjusted multivariate analysis ranked the odds of VTE according to specific infections. Dr. Cohoon and his colleagues reported that this modeling showed that the “highest magnitude of risk, compared with no infection, was imparted by intra-abdominal infection (OR, 18) followed by oral infection (OR, 12), systematic blood stream infection (OR, 11), lower respiratory infection such as pneumonia (OR, 3.6), and symptomatic urinary tract infection (OR, 2.2).”

The researchers concluded that their findings may allow for further refinement of inpatient VTE risk-prediction models such as the Padua prediction score and “future studies are required to assess the utility of venous thromboembolism prophylaxis among outpatients with high venous thromboembolism risk infections.”

The authors reported that they had no conflicts of interest.

 

 

Infection and infection sites have been found to be associated with a significant increased risk of venous thromboembolism, according to results of a population-based, matched, case-control analysis of medical records covering the 13-year period 1988-2000.

Dr. Kevin P. Cohoon and his colleagues at the Mayo Clinic, Rochester, Minn., developed models using conditional logistic regression analysis to stratify the risk associated with specific infections and infection sites.

Courtesy Wikimedia Commons/Walter Serra, Giuseppe De Iaco, Claudio Reverberi, and Tiziano Gherli/Creative Commons License

A total of 1,303 individuals, mean age of 65.2 years, with a first lifetime objectively diagnosed deep vein thrombosis and/or pulmonary embolism were identified and paired with 1,494 controls without venous thromboembolism (VTE), mean age of 64.9 years. The matches were based on sex, age, and an episode of medical care within 1 year of the case event date. The case population consisted of 55.6% women, compared with the control population consisting of 55.4% women.

Five hundred thirteen (39.4%) cases and 189 (12.7%) controls had an infection within the previous 92 days (odds ratio, 4.5; P less than .0001). Known VTE risk factors and potentially confounding variables were used in the adjusted univariate and multivariate models, as reported in the American Journal of Medicine (2017. doi: 10.1016/j.amjmed.2017.09.015).

Dr. Cohoon and his colleagues reported that univariate analysis showed “most infection sites were strongly associated with venous thromboembolism” and the adjusted multivariate model resulted in 2.4-fold (P less than .0001) higher odds for VTE incidence, compared with uninfected controls.

Adjusted multivariate analysis ranked the odds of VTE according to specific infections. Dr. Cohoon and his colleagues reported that this modeling showed that the “highest magnitude of risk, compared with no infection, was imparted by intra-abdominal infection (OR, 18) followed by oral infection (OR, 12), systematic blood stream infection (OR, 11), lower respiratory infection such as pneumonia (OR, 3.6), and symptomatic urinary tract infection (OR, 2.2).”

The researchers concluded that their findings may allow for further refinement of inpatient VTE risk-prediction models such as the Padua prediction score and “future studies are required to assess the utility of venous thromboembolism prophylaxis among outpatients with high venous thromboembolism risk infections.”

The authors reported that they had no conflicts of interest.