Safety, effectiveness and sustainability of a laboratory intervention to de-adopt culture of midstream urine samples among hospitalized patients
Bibliographic record
Abstract
OBJECTIVE: To assess the safety, sustainability, and effectiveness of a laboratory intervention to reduce processing of midstream urine (MSU) cultures. DESIGN: Prospective observational cohort. SETTING: Medical and surgical inpatients in a tertiary-care hospital. PARTICIPANTS: The study included 1,678 adult inpatients with an order for MSU culture. METHODS: From 2013 to 2019, ordered MSU cultures were not processed unless the laboratory was called. Patients were interviewed on days 0 and 4; from 2017 to 2019, day-30 follow-up was added. Primary outcome was serious adverse events due to not processing MSU cultures. Secondary outcomes were nonserious adverse events due to not processing MSU cultures, rates of MSU cultures submitted, proportion of MSU cultures processed, proportion of patients prescribed urinary tract infection (UTI)-directed antibiotics, and laboratory workload. RESULTS: Among 912 and 459 patients followed to days 4 and 30, respectively, no serious adverse events attributable to not processing MSU cultures were identified. However, 6 patients (0.66%) had prolonged urinary symptoms potentially associated with not processing MSU cultures. We estimated that 4 patients missed having empiric antibiotics stopped in response to negative MSU cultures, and 99 antibiotic courses for asymptomatic bacteriuria (ASB) and 8 antibiotic-associated adverse events were avoided. The rate of submitted MSU samples and proportion of patients receiving empiric UTI-directed antibiotics did not change. The proportion of MSU cultures processed declined from 59% to 49% (P < .0001), and total laboratory workload was reduced by 185 hours. CONCLUSIONS: De-adopting the processing of MSU cultures from medical and surgical inpatient units is safe and sustainable, and it reduces antibiotic prescriptions for ASB at a cost of prolonged urinary symptoms in a small proportion of patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".