NoMicro classifier accurately predicts UTI in primary care without microscopy.
A study published in the January/February issue of the Annals of Family Medicine has found that the NoMicro classifier is accurate for evaluating urine cultures in cases of suspected urinary tract infection in the primary care setting without the need for microscopy. Gurpreet Dhanda, M.D., and colleagues from the University of Kansas Medical Center redesigned a classifier (NoMicro) that does not depend on urine microscopy and used machine learning prediction models for urine cultures both internally (emergency department data set) and externally (primary care data set).
The primary outcome was pathogenic urine culture growing ≥100,000 colony-forming units and the predictor variables were: age; gender; dipstick urinalysis nitrites, leukocytes, clarity, glucose, protein, and blood; dysuria; abdominal pain; and history of urinary tract infection. The researchers found that removal of microscopy features did not severely compromise performance under internal validation (receiver operating characteristic area under the curve [ROC-AUC], 0.86 and 0.88 for NoMicro/XGBoost and NeedMicro, respectively). In external validation, excellent performance was also achieved (NoMicro/random forests ROC-AUC, 0.85).
The authors suggest that NoMicro/random forests can be used to safely withhold antibiotics for low-risk patients, thereby avoiding antibiotic overuse. They believe that the NoMicro classifier appears appropriate for primary care and prospective trials to adjudicate the balance of benefits and harms of using the NoMicro classifier are appropriate.
In conclusion, the NoMicro classifier appears to be an accurate and reliable tool for evaluating urine cultures in cases of suspected urinary tract infection in the primary care setting. It may be used to safely withhold antibiotics for low-risk patients, thereby avoiding antibiotic overuse. Further research is needed to determine the effectiveness of the NoMicro classifier in the primary care setting.
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