In‐Hospital Complications in Pregnancies Conceived by Assisted Reproductive Technology
Bibliographic record
Abstract
Background Assisted reproductive technology (ART) has emerged as a common treatment option for infertility, a problem that affects an estimated 48 million couples worldwide. Advancing maternal age with increasing prepregnancy cardiovascular risk factors, such as chronic hypertension, obesity, and diabetes, has raised concerns about pregnancy complications associated with ART. However, in‐hospital complications following pregnancies conceived by ART are poorly described. Methods and Results To assess the patient characteristics, obstetric outcomes, vascular complications and temporal trends of pregnancies conceived by ART, we analyzed hospital deliveries conceived with or without ART between January 1, 2008, and December 31, 2016, from the United States National Inpatient Sample database. We included 106 248 deliveries conceived with ART and 34 167 246 deliveries conceived without ART. Women who conceived with ART were older (35 versus 28 years; P <0.0001) and had more comorbidities. ART‐conceived pregnancies were independently associated with vascular complications (acute kidney injury: adjusted odds ratio [aOR], 2.52; 95% CI 1.99–3.19; and arrhythmia: aOR, 1.65; 95% CI, 1.46–1.86), and adverse obstetric outcomes (placental abruption: aOR, 1.57; 95% CI, 1.41–1.74; cesarean delivery: aOR, 1.38; 95% CI, 1.33–1.43; and preterm birth: aOR, 1.26; 95% CI, 1.20–1.32), including in subgroups without cardiovascular disease risk factors or without multifetal pregnancies. Higher hospital charges ($18 705 versus $11 983; P <0.0001) were incurred compared with women who conceived without ART. Conclusions Pregnancies conceived by ART have higher risks of adverse obstetric outcomes and vascular complications compared with spontaneous conception. Clinicians should have detailed discussions on the associated complications of ART in women during prepregnancy counseling.
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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 | 0.001 |
| Research integrity | 0.000 | 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".