Molecular Diagnostic Methods Versus Conventional Urine Culture for Diagnosis and Treatment of Urinary Tract Infection: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Context: Urine culture has low sensitivity in the diagnosis of urinary tract infection (UTI). Next-generation sequencing (NGS) and polymerase chain reaction (PCR) are culture-independent molecular methods available for commercial use to diagnose UTI. Objective: To systematically evaluate the evidence comparing the diagnostic and therapeutic values of molecular diagnostic methods to urine culture in the management of UTI in adults. Evidence acquisition: We performed a critical review of Embase, Ovid, and PubMed in February 2022 according to the Preferred Reporting Items for Systematic Review and Meta-analyses statement. Studies involving pregnant women, ureteral stones, ureteral stents, and percutaneous nephrostomy tubes were excluded. Risk of bias and methodological quality were assessed using the Cochrane risk of bias tool and Newcastle Ottawa Scale. Fifteen publications were selected for inclusion. Evidence synthesis: Included reports compared NGS (nine studies) and PCR (six studies) to urine culture. A meta-analysis of seven similar studies utilizing NGS demonstrates that NGS is more sensitive in the identification of urinary bacteria and detects greater species diversity per urine sample than culture. PCR protocols designed to detect a diverse range of microbes had increased sensitivity and species diversity compared with culture. Phenotypic and genotypic resistomes are concordant in approximately 85% of cases. There is insufficient evidence to compare patient symptomatic responses to antibiotic therapy guided by molecular testing versus standard susceptibility testing. Conclusions: Moderately strong evidence exists that molecular diagnostics demonstrate increased sensitivity in detecting urinary bacteria at the expense of poor specificity in controls. Additional data comparing patient symptoms and cure rates following antibiotic selection directed by molecular methods compared with culture are needed to elucidate their place in UTI care. Patient summary: We compare culture-independent molecular methods with urine culture in the management of urinary tract infection. We found good evidence that molecular methods detect more bacteria than culture; however, the clinical implications to support their routine use are unclear.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.023 | 0.036 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".