Rheumatic Heart Disease in Pregnancy [22D]
Bibliographic record
Abstract
INTRODUCTION: The objective of the study was to examine the obstetrical outcomes of pregnancies in women with rheumatic heart disease (RHD) and the rate of associated chronic diseases. METHODS: The nationwide inpatient sample (NIS) database was queried for all birth related admissions between 2008 and 2012. The data were weighted by the NIS weight code provided. Women with RHD were identified and compared to women without RHD. The prevalence of relevant medical conditions and common obstetrical outcomes were compared between the two groups using logistic regressions. RESULTS: From 2008 to 2012, we identified 19,828,389 deliveries, 623 of those were among women with RHD. Interestingly, women with RHD tend to be from a lower socioeconomic class, be on Medicaid, and to be of ethnic origins other than white (P<.05). These women had a higher frequency of associated chronic medical illnesses including chronic hypertension OR=153.87 (4.02–6.78), cardiac arrhythmia OR=15.31 (1.72–5.14), congestive heart failure OR=619 (70.91–169.03), and thrombocytopenia OR=24 (1.95–4.71). After adjusting for baseline characteristics and preexisting diabetes and hypertension, patients with RHD tend to have a higher risk of developing preeclampsia OR=24.92 (1.56–2.75), have more preterm premature rupture of membranes OR=24.63 (1.57–2.81), develop gestational diabetes OR=9.29 (1.16–1.96) and to develop urinary tract infections OR=19.22 (1.76–4.38). Furthermore, they are at a higher risk of cesarean delivery OR=8.91 (1.10–1.58), instrumental delivery OR=28.74 (2.52–7.30), and stillbirth OR=6.37 (1.2–4.16). CONCLUSION: Pregnancy in patients with RHD carries significant risks to the mother and the fetus. This information will allow for better counseling of women with RHD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".