Microbiology of Urinary Tract Infections in Gaborone, Botswana
Bibliographic record
Abstract
OBJECTIVE: The microbiology and epidemiology of UTI pathogens are largely unknown in Botswana, a high prevalence HIV setting. Using laboratory data from the largest referral hospital and a private hospital, we describe the major pathogens causing UTI and their antimicrobial resistance patterns. METHODS: This retrospective study examined antimicrobial susceptibility data for urine samples collected at Princess Marina Hospital (PMH), Bokamoso Private Hospital (BPH), or one of their affiliated outpatient clinics. A urine sample was included in our dataset if it demonstrated pure growth of a single organism and accompanying antimicrobial susceptibility and subject demographic data were available. RESULTS: A total of 744 samples were included. Greater than 10% resistance was observed for amoxicillin, co-trimoxazole, amoxicillin-clavulanate, and ciprofloxacin. Resistance of E. coli isolates to ampicillin and co-trimoxazole was greater than 60% in all settings. HIV status did not significantly impact the microbiology of UTIs, but did impact antimicrobial resistance to co-trimoxazole. CONCLUSIONS: Data suggests that antimicrobial resistance has already emerged to most oral antibiotics, making empiric management of outpatient UTIs challenging. Ampicillin, co-trimoxazole, and ciprofloxacin should not be used as empiric treatment for UTI in this context. Nitrofurantoin could be used for simple cystitis; aminoglycosides for uncomplicated UTI in inpatients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".