Trends in anti-infective drugs use in pregnancy.
Bibliographic record
Abstract
BACKGROUND: Development of knowledge in understanding the use of anti-infective drugs during pregnancy has been limited by difficulties in testing medications in pregnant women and lack of evidence-based data. Overuse of broad spectra agents is associated with development and spread of bacterial resistance, a problem that is faced as a significant threat to the public health. OBJECTIVES: To describe trends in use of general and broad spectrum anti-infective drugs during pregnancy. METHODS: We used the Quebec Pregnancy Registry to analyse trends for use of oral anti-infectives dispensed during pregnancy for the five-year period comprised between January 1998 and December 2002. Trends in use were assessed for classes of anti-infectives and for broad-spectrum drugs. Descriptive statistics were used to summarize the characteristics of the study population. Annual trends for the use of anti-infective drugs were analyzed using the Cochran-Armitage test. RESULTS: The use of anti-infective drugs and broad spectrum agents during pregnancy decreased from 1998 to 2002 (p ≤ 0.05 for trends). The classes that showed increasing trend for use were: macrolides, quinolones, tetracyclines, urinary anti-infective drugs and antimycotics. Use of penicillins and sulfonamides decreased. Azithromycin showed a remarkable increase in its use: 0.04% of all anti-infective prescriptions in 1998, compared to 10.16% in 2002. CONCLUSIONS: Decrease in the use of broad-spectrum drugs may have been caused by a positive impact of data issued from evidence in everyday life clinical practice. More data is needed to evaluate the impact of the knowledge transfer from evidence-based studies on prescription's trends during pregnancy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".