Urinary Tract Infections and Preeclampsia among Pregnant Women Attending Two Hospitals in Mwanza City, Tanzania: A 1:2 Matched Case-Control Study
Bibliographic record
Abstract
Urinary tract infection (UTI) and preeclampsia are common among pregnant women and are associated with adverse maternal-fetal and neonatal outcomes. Despite this, limited information exists on the association between UTIs and preeclampsia in Tanzania to guide specific management and thereby averting the adverse outcomes. A 1:2 matched case-control study (by age and gravidity) involving 131 pregnant women with preeclampsia (cases) and 262 without preeclampsia (controls) was conducted. Sociodemographic and clinical information was collected using a questionnaire. Midstream urine samples were collected during admission for culture and antimicrobial susceptibility testing (AST). Out of 393 pregnant women enrolled, 110 (28.0%), 95% CI: 23.8%-32.7%, had significant bacteriuria [cases: 50.4% (66/131) and control: 16.8% (44/262)]. Pregnant women with preeclampsia had 7.7 odds of having significant bacteriuria than those without preeclampsia [OR=7.7, 95% CI (4.11-14.49); p-value <0.001]. Escherichia coli , 50 (45.5%), and Klebsiella spp., 25 (23.6%), predominated, and resistance to gentamicin, ceftriaxone, and piperacillin-tazobactam ranged from 9.0% to 29.0% in these dominant species. Extended spectrum beta lactamases (ESBL) production in Escherichia coli and Klebsiella spp. was 18.0% (9/50) and 15.4% (4/26), respectively. Routine urine culture and AST among pregnant women with preeclampsia should be introduced in the antenatal clinics to ensure prompt management. Delineation of maternal-fetal and neonatal outcomes among pregnant women with preeclampsia and UTIs would be of interest in future studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".