Identifying pregnancies in insurance claims data: Methods and application to retinoid teratogenic surveillance
Bibliographic record
Abstract
PURPOSE: The purpose of the study is to develop an algorithm to identify pregnancies in administrative databases and apply it to assess pregnancy rates and outcomes in women prescribed isotretinoin or tretinoin. METHODS: Using the 2011 to 2015 Truven Health MarketScan Database, we identified pregnancies, including losses and terminations. In a cohort design, nonpregnant women filling a prescription for isotretinoin or tretinoin were matched to five women without either prescription. Women were followed for 365 days or until conception, medication discontinuation, or enrollment discontinuation ("prescription episode"). Rates of pregnancy, risks of pregnancy losses, and prevalence of infant malformations at birth were assessed by exposure. RESULTS: We identified 2 179 192 livebirths, 8434 stillbirths, 2521 mixed births, 415 110 spontaneous abortions, 124 556 elective terminations, and 8974 unspecified abortions. There were 86 834 isotretinoin and 973 587 tretinoin episodes, matched to 5 302 105 unexposed women. Pregnancy rates were 3 (isotretinoin), 19 (tretinoin), and 34 (unexposed) per 1000 person-years. Risk of spontaneous pregnancy losses were similar; however, terminations were more common in the isotretinoin-exposed (28% [95% CI: 21%-36%]) than the tretinoin-exposed (10% [95% CI: 9%-11%]) or unexposed pregnancies (6%). Malformations occurred in 4.5% (95% CI: 3.5%-5.6%) of the tretinoin-exposed pregnancies and 4.2% of the unexposed pregnancies (adjusted odds ratio: 1.16 [95% CI: 0.85-1.58]); isotretinoin-exposed births were too few to assess malformations. CONCLUSIONS: Administrative databases can complement risk evaluation and mitigation strategies (REMS) for known teratogens and contribute to safety surveillance for other medications. Here, isotretinoin-exposed pregnancy rates were low, but existent, and many pregnancies were terminated. Tretinoin exposure was not associated with a meaningfully elevated risk of losses or malformations as compared with unexposed pregnancies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".