Failure of fertility therapy and subsequent adverse cardiovascular events
Bibliographic record
Abstract
BACKGROUND: Infertility may indicate an underlying predisposition toward premature cardiovascular disease, yet little is known about potential long-term cardiovascular events following fertility therapy. We investigated whether failure of fertility therapy is associated with subsequent adverse cardiovascular events. METHODS: We performed a population-based cohort analysis of women who received gonadotropin-based fertility therapy between Apr. 1, 1993, and Mar. 31, 2011, distinguishing those who subsequently gave birth and those who did not. Using multivariable Poisson regression models, we estimated the relative rate ratio of adverse cardiovascular events associated with fertility therapy failure, accounting for age, year, baseline risk factors, health care history and number of fertility cycles. The primary outcome was subsequent treatment for nonfatal coronary ischemia, stroke, transient ischemic attack, heart failure or thromboembolism. RESULTS: Of 28 442 women who received fertility therapy, 9349 (32.9%) subsequently gave birth and 19 093 (67.1%) did not. The median number of fertility treatments was 3 (interquartile range 1–5). We identified 2686 cardiovascular events over a median 8.4 years of follow-up. The annual rate of cardiovascular events was 19% higher among women who did not give birth after fertility therapy than among those who did (1.08 v. 0.91 per 100 patient-years, p < 0.001), equivalent to a 21% relative increase in the annual rate (95% confidence interval 13%–30%). We observed no association between event rates and number of treatment cycles. INTERPRETATION: Fertility therapy failure was associated with an increased risk of long-term adverse cardiovascular events. These women merit surveillance for subsequent cardiovascular events.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".