Influence of Hypertensive Disorders of Pregnancy on Phenotype and Recovery in Peripartum Cardiomyopathy [27L]
Bibliographic record
Abstract
INTRODUCTION: Peripartum cardiomyopathy (PPCM) and cardiomyopathy secondary to hypertensive disorders of pregnancy (HDP) are considered to represent distinct cardiac entities (i.e. dilated vs hypertrophic cardiomyopathy). The goal of this systematic review and meta-analysis was to determine if HDP alters the odds of recovery and if baseline left ventricle characteristics are significantly different. METHODS: Ovid Medline, EMBASE, CENTRAL and Scopus were searched for combinations of the following: hypertension, preeclampsia, cardiomyopathy, peripartum, postpartum or puerperium. Articles describing initial left ventricular ejection fraction (LVEF), odds of recovery (EF >50%) or end diastolic diameter (EDD) amongst those with PPCM were included. Two raters analyzed abstracts and full text to determine eligibility and risk of bias. Risk of bias was determined using the Newcastle-Ottawa scale and the DerSimonian-Laird method was used to combine odds ratios. RESULTS: 1838 articles were identified and 148 full text articles were reviewed for eligibility, with 11 observational studies meeting criteria. There was substantial agreement for selection (K: 0.817) and for risk of bias (K: 0.633) between raters. There was no significant difference (mean: 1.837%, 95% CI-4.882, 1.282) in baseline LVEF or EDD (1.837 cm, 95% CI-1.104, 4.778) between patients who developed PPCM +/- HDP. Further, recovery rates between groups were similar with OR of 1.870 (95% CI 0.854, 4.094) and a moderate degree of heterogeneity. CONCLUSION: Counseling regarding eventual recovery of LVEF after PPCM should not be altered due to the presence of HDP; it is unlikely that a phenotypic difference exists in the cardiomyopathy induced by HDP compared to idiopathic PPCM.
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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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.017 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".