Bacterial Profile and asymptomatic bacteriuria among pregnant women in Africa: A systematic review and meta analysis
Bibliographic record
Abstract
Background: Different physiologic changes that occur during pregnancy, such as Hydroureter, dilatation of the renal pelvis, glycosuria and aminoaciduria, and low urine production predispose pregnant women for ascending urinary tract infection. Globally, 2% to 15% of the pregnant women have urinary tract infection without specific symptoms. Therefore, this study aimed to estimate the prevalence of asymptomatic bacteriuria (ABU) in pregnant women in Africa. Methods: Systematic search of published studies done on PubMed, EMBASE, Web of Science, SCOPUS, Psy-chInfo, CINAHL, and google scholar for gray literature. All published observational studies until October 30, 2020 were included. This meta-analysis follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Quality of studies was assessed by modified Newcastle-Ottawa Scale (NOS). Meta-analysis was carried out using a random-effects method with the double arcsine transformation approach using the STATA TM Version 14 software. Trim and fill analysis was done to correct presence of significant publication bias. The study protocol is prospectively registered on PROSPERO, registration number CRD42020212601. Findings: From 3393 obtained studies, 48 studies from 12 African countries involving 15, 664 pregnant women included in this Meta-analysis. The overall pooled prevalence of asymptomatic bacteriuria among pregnant women in Africa after correction for publication bias by trim and fill analysis was found to be 11.1% (95% CI: 7.8, 14.4). The most common bacterial isolates involved in the etiology of ABU was Escherichia coli with pooled prevalence 33.4% (95% CI: 27.3 -39.4) Interpretation: Asymptomatic bacteriuria is substantial among pregnant women in Africa. Therefore, all pregnant women should be tested for the presence of asymptomatic bacteriuria. A screening program must be based not only on the incidence but also on a cost-efficacy evaluation and a microbiological evaluation.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".