Outcomes of subsequent pregnancy in women with peripartum cardiomyopathy: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: The primary concern for women who have experienced peripartum cardiomyopathy (PPCM) is the safety of a subsequent pregnancy (SSP). To maximie decision-making, facilitate effective patient counselling, and ultimately improve maternal and fetal outcomes as a whole, it is critical to comprehend the outcomes of SSP in women who have previously experienced PPCM. This study aimed to evaluate the outcomes of SSP in women with PPCM. METHODS: Three databases (PubMed, Scopus, and ScienceDirect) were used to identify relevant studies prior to 17 October 2023. A total of 662 studies were reviewed. Following the abstract and full-text screenings, 18 observational studies were included, out of which 2 were deemed suitable for inclusion in this meta-analysis. The quality assessment was conducted using the Newcastle-Ottawa Scale. RESULTS: This study has a total of 487 SSPs. Although recovered left ventricular (LV) function before entering SSP has the potential to be a beneficial prognostic factor, recovered LV function still has a substantial risk of relapse. The mortality rate of PPCM in an SSP ranged from 0% to 55.5%. Persistent LV dysfunction was significantly associated with an increased mortality rate (OR 13.17; 95% CI 1.54 to 112.28; p=0.02) and lower LV ejection fraction (MD -12.88; 95% CI -21.67 to -4.09; p=0.004). Diastolic and right ventricular functions remained unchanged before SSP and at follow-up. The majority of the SSP was observed alongside hypertension, while pre-eclampsia emerged as the predominant hypertensive complication in most studies. CONCLUSION: SSP increases the risk of relapse and mortality in women with a previous history of PPCM. Persistent LV dysfunction prior to the SSP has a higher mortality risk compared with recovered LV function. SSP was also associated with the worsening of LV echocardiography parameters.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.033 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".