Urinary Tract Infections among HIV-Positive Pregnant Women in Mwanza City, Tanzania, Are High and Predicted by Low CD4+ Count
Bibliographic record
Abstract
Introduction. Urinary tract infection (UTI) among pregnant women can lead to adverse maternal and foetal outcomes. UTI has been widely studied in the general obstetric population in Tanzania; the present study evaluated the magnitude, antimicrobial resistance, and predictors of UTI among HIV-positive pregnant women.Methods. Between March and May 2016 midstream urine samples from 234 women attending prevention of mother to child transmission of HIV (PMTCT) clinics were analyzed using standard methods. Data was analyzed by STATA version 11.0.Results. The prevalence of UTI was 21.4%, 50/234 [95% CI: 16.1–26.6]. The asymptomatically significant bacteriuria was higher than symptomatically significant bacteriuria (16.6% versus 4.7%, p<0.001 ). On multivariable logistic regression analysis, single marital status (OR: 2.6, 95% CI: 1.1–6.1, and p=0.026 ), low CD4+ counts of <200/μL (OR: 2.9, 95% CI: 1.1–7.7, and p=0.031 ), and having UTI symptoms (OR: 2.5, 95% CI: 1.1–6.0, and p=0.03 ) were independent predictors of UTI.Escherichia colipredominated (57.7%) and exhibited a low prevalence of resistance to nitrofurantoin (16.7%), gentamicin (10.0%), and ceftriaxone (13.3%). Four (13.3%) of these were extended-spectrum beta-lactamase producers.Conclusions. A considerable proportion of HIV-positive pregnant women in Mwanza have significant bacteriuria which calls for the need to introduce routine UTI screening at PMTCT clinics to guide specific treatment and prevent associated complications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".