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TOPLINE:
Compared with other urine analysis methods, urine Gram stain has a moderate predictive value for detecting gram-negative bacteria in urine culture but does not significantly improve urinary tract infection (UTI) diagnosis in the emergency department (ED).
METHODOLOGY:
- Researchers conducted an observational cohort study at the University Medical Center Groningen in the Netherlands, encompassing 1358 episodes across 1136 patients suspected of having a UTI.
- The study included the following predefined subgroups: patients using urinary catheters and patients with leukopenia (< 4.0×10⁹ leucocytes/L). Urine dipstick nitrite, automated urinalysis, Gram stain, and urine cultures were performed on urine samples collected from patients presenting at the ED.
- The sensitivity and specificity of Gram stain for “many” bacteria (quantified as > 15/high power field) were compared with those of urine dipstick nitrite and automated bacterial counting in urinalysis.
TAKEAWAY:
- The sensitivity and specificity of Gram stain for “many” bacteria were 51.3% and 91.0%, respectively, with an accuracy of 76.8%.
- Gram stain showed a positive predictive value (PPV) of 84.7% for gram-negative rods in urine culture; however, the PPV was only 38.4% for gram-positive cocci.
- In the catheter subgroup, the presence of monomorphic bacteria quantified as “many” had a higher PPV for diagnosing a UTI than the presence of polymorphic bacteria with the same quantification.
- The overall performance of Gram stain in diagnosing a UTI in the ED was comparable to that of automated bacterial counting in urinalysis but better than that of urine dipstick nitrite.
IN PRACTICE:
“With the exception of a moderate prediction of gram-negative bacteria in the UC [urine culture], urine GS [Gram stain] does not improve UTI diagnosis at the ED compared to other urine parameters,” the authors wrote.
SOURCE:
The study was led by Stephanie J.M. Middelkoop, University of Groningen, University Medical Center Groningen, the Netherlands. It was published online on August 16, 2024, in Infectious Diseases.
LIMITATIONS:
The study’s limitations included a small sample size within the leukopenia subgroup, which may have affected the generalizability of the findings. Additionally, the potential influence of refrigeration of urine samples on bacterial growth could have affected the results. In this study, indwelling catheters were not replaced before urine sample collection, which may have affected the accuracy of UTI diagnosis in patients using catheters.
DISCLOSURES:
No conflicts of interest were disclosed by the authors.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Compared with other urine analysis methods, urine Gram stain has a moderate predictive value for detecting gram-negative bacteria in urine culture but does not significantly improve urinary tract infection (UTI) diagnosis in the emergency department (ED).
METHODOLOGY:
- Researchers conducted an observational cohort study at the University Medical Center Groningen in the Netherlands, encompassing 1358 episodes across 1136 patients suspected of having a UTI.
- The study included the following predefined subgroups: patients using urinary catheters and patients with leukopenia (< 4.0×10⁹ leucocytes/L). Urine dipstick nitrite, automated urinalysis, Gram stain, and urine cultures were performed on urine samples collected from patients presenting at the ED.
- The sensitivity and specificity of Gram stain for “many” bacteria (quantified as > 15/high power field) were compared with those of urine dipstick nitrite and automated bacterial counting in urinalysis.
TAKEAWAY:
- The sensitivity and specificity of Gram stain for “many” bacteria were 51.3% and 91.0%, respectively, with an accuracy of 76.8%.
- Gram stain showed a positive predictive value (PPV) of 84.7% for gram-negative rods in urine culture; however, the PPV was only 38.4% for gram-positive cocci.
- In the catheter subgroup, the presence of monomorphic bacteria quantified as “many” had a higher PPV for diagnosing a UTI than the presence of polymorphic bacteria with the same quantification.
- The overall performance of Gram stain in diagnosing a UTI in the ED was comparable to that of automated bacterial counting in urinalysis but better than that of urine dipstick nitrite.
IN PRACTICE:
“With the exception of a moderate prediction of gram-negative bacteria in the UC [urine culture], urine GS [Gram stain] does not improve UTI diagnosis at the ED compared to other urine parameters,” the authors wrote.
SOURCE:
The study was led by Stephanie J.M. Middelkoop, University of Groningen, University Medical Center Groningen, the Netherlands. It was published online on August 16, 2024, in Infectious Diseases.
LIMITATIONS:
The study’s limitations included a small sample size within the leukopenia subgroup, which may have affected the generalizability of the findings. Additionally, the potential influence of refrigeration of urine samples on bacterial growth could have affected the results. In this study, indwelling catheters were not replaced before urine sample collection, which may have affected the accuracy of UTI diagnosis in patients using catheters.
DISCLOSURES:
No conflicts of interest were disclosed by the authors.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Compared with other urine analysis methods, urine Gram stain has a moderate predictive value for detecting gram-negative bacteria in urine culture but does not significantly improve urinary tract infection (UTI) diagnosis in the emergency department (ED).
METHODOLOGY:
- Researchers conducted an observational cohort study at the University Medical Center Groningen in the Netherlands, encompassing 1358 episodes across 1136 patients suspected of having a UTI.
- The study included the following predefined subgroups: patients using urinary catheters and patients with leukopenia (< 4.0×10⁹ leucocytes/L). Urine dipstick nitrite, automated urinalysis, Gram stain, and urine cultures were performed on urine samples collected from patients presenting at the ED.
- The sensitivity and specificity of Gram stain for “many” bacteria (quantified as > 15/high power field) were compared with those of urine dipstick nitrite and automated bacterial counting in urinalysis.
TAKEAWAY:
- The sensitivity and specificity of Gram stain for “many” bacteria were 51.3% and 91.0%, respectively, with an accuracy of 76.8%.
- Gram stain showed a positive predictive value (PPV) of 84.7% for gram-negative rods in urine culture; however, the PPV was only 38.4% for gram-positive cocci.
- In the catheter subgroup, the presence of monomorphic bacteria quantified as “many” had a higher PPV for diagnosing a UTI than the presence of polymorphic bacteria with the same quantification.
- The overall performance of Gram stain in diagnosing a UTI in the ED was comparable to that of automated bacterial counting in urinalysis but better than that of urine dipstick nitrite.
IN PRACTICE:
“With the exception of a moderate prediction of gram-negative bacteria in the UC [urine culture], urine GS [Gram stain] does not improve UTI diagnosis at the ED compared to other urine parameters,” the authors wrote.
SOURCE:
The study was led by Stephanie J.M. Middelkoop, University of Groningen, University Medical Center Groningen, the Netherlands. It was published online on August 16, 2024, in Infectious Diseases.
LIMITATIONS:
The study’s limitations included a small sample size within the leukopenia subgroup, which may have affected the generalizability of the findings. Additionally, the potential influence of refrigeration of urine samples on bacterial growth could have affected the results. In this study, indwelling catheters were not replaced before urine sample collection, which may have affected the accuracy of UTI diagnosis in patients using catheters.
DISCLOSURES:
No conflicts of interest were disclosed by the authors.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.