Occurrence and determinants of trimethoprim/sulfamethoxazole use in pregnancy
Bibliographic record
Abstract
OBJECTIVE: To estimate the rate of prescription trimethoprim/sulfamethoxazole use in pregnancy, and to analyse the association between maternal characteristics and use of trimethoprim/sulfamethoxazole in pregnancy. METHODS: A population-based study was conducted based on a 50% random sample of women who gave a birth in Saskatchewan between 1 January 1997 and 31 December 2000. The rate of trimethoprim/sulfamethoxazole use during pregnancy was estimated. The exposure in each trimester was also estimated. Associations between maternal characteristics and pregnancy trimethoprim/sulfamethoxazole use were evaluated using multiple logistical regression with adjusted odds ratios (ORs) and 95% confidence intervals (CIs) as the association measures. RESULTS: A total of 18,575 women who gave a birth in Saskatchewan during the study period were included in the analysis. Among them, 596 (3.2%) had at least 1 prescription for trimethoprim/sulfamethoxazole during pregnancy, 389 (2.1%) in the first trimester, 208 (1.1%) in the second trimester, and 195 (1.1%) in the third trimester. Women with chronic health conditions (6.2%) had a 2-fold increased risk of exposure compared to women without a chronic health condition (2.8%). Younger women (<20 years) with parity >/=3 and women on Saskatchewan assistance plan were also at increased risk. There were variations in exposure by trimester. For example, teenage women without chronic health conditions were at increased risk of use in the second and third trimester. CONCLUSIONS: Some 3.2% of women are exposed to trimethoprim/sulfamethoxazole during pregnancy. Women with chronic health problems, of younger age, and of lower socioeconomic status are at elevated risk of exposure to trimethoprim/sulfamethoxazole 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".