Impact of Intrapartum Azithromycin on the Carriage and Antibiotic Resistance of <i>Escherichia coli</i> and <i>Klebsiella pneumoniae</i> in Mothers and Their Newborns: A Substudy of a Randomized, Double-Blind Trial Conducted in The Gambia and Burkina Faso
Bibliographic record
Abstract
BACKGROUND: Limited data exist on the effects of intrapartum azithromycin on the prevalence of carriage and antibiotic resistance of Enterobacterales. METHODS: We conducted a randomized trial in The Gambia and Burkina Faso where women received intrapartum azithromycin (2 g) or placebo. We determined the impact of treatment on the prevalence of carriage and antibiotic resistance of Escherichia coli and Klebsiella pneumoniae by analyzing rectal swabs (RS), nasopharyngeal swabs (NPS), breast milk, and rectovaginal swabs (RVS). Bacteria were isolated microbiologically; antibiotic susceptibility was confirmed with an E-test. Prevalence ratios (PRs) with 95% confidence intervals (CIs) were used for comparison between arms. RESULTS: In infants, E. coli carriage in RS was lower in the intervention than in the placebo arm at day 6 (63.0% vs 75.2%; PR, 0.84; 95% CI, .75-.95) and day 28 (52.7% vs 70.4%; 0.75; 0.64-0.87) post-intervention. Prevalence of azithromycin-resistant E. coli was higher in the azithromycin arm at day 6 (13.4% vs 3.6%; 3.75; 1.83-7.69) and day 28 (16.4% vs 9.6%; 1.71; 1.05-2.79). For K. pneumoniae, carriage in RS was higher in the intervention than in the placebo arm at day 6 (49.6% vs 37.2%, 1.33; 1.08-1.64) and day 28 (53.6% vs 32.9%, 1.63; 1.31-2.03). Prevalence of azithromycin-resistant K. pneumoniae was higher in the azithromycin arm at day 28 (7.3% vs 2.1%; 3.49; 1.30-9.37). No differences were observed for other sample types. CONCLUSIONS: Intrapartum azithromycin decreased E. coli carriage but increased both K. pneumoniae carriage and azithromycin resistance in both bacteria. These data need to be considered together with efficacy results to balance the potential short- and long-term impact of the intervention. Clinical Trials Registration. www.clinicaltrials.gov: NCT03199547.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".