Impact of Obstetric Complications in Subjects at Clinical High Risk for Psychosis: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
INTRODUCTION: Exposure to obstetric complications (OCs) increases the risk of developing psychosis and schizophrenia in offspring. However, studies with subjects at clinical high risk for psychosis (CHR) have reported inconsistent results. We conducted a systematic review and meta-analysis to evaluate the prevalence of OCs among CHR subjects and controls and examine their impact on the transition to psychosis. METHODS: Four databases (Web of Science, PubMed, Latindex, and Dialnet) were systematically searched for articles published between 1995 and June 6, 2024. The risk of bias was assessed using the Newcastle-Ottawa scale. Articles providing data on OCs in CHR subjects were included. RESULTS: A total of 6037 records were retrieved through systematic and citation searches. Nine articles met the inclusion criteria for our systematic review and provided data for meta-analysis. A total of 555 CHR participants were included. Meta-analysis showed a significantly higher prevalence of OCs in CHR subjects versus controls: RR = 1.45 (95% CI: 1.16, 1.81), (Z = 3.27, p = 0.0011). Data from three longitudinal studies assessed transition to psychosis and our meta-analysis found a trend toward an increased risk of transition in CHR subjects with a history of OCs compared to others: RR = 2.05 (95% CI: 0.98, 4.26), Z = 1.91, p = 0.056. CONCLUSIONS: CHR for psychosis was associated with OCs, though their role in the transition to psychosis requires further study. OCs should be recorded and analyzed in CHR individuals, considering their potential clinical implications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".