Hypertensive disorders of pregnancy increase the risk of future ophthalmic disorders: a systematic review and meta-analysis
Bibliographic record
Abstract
Whilst 30-60% of women with hypertensive disorders of pregnancy (HDP) suffer from ocular manifestations, longer term ophthalmic sequelae are unclear. We performed a systematic review and meta-analysis assessing the relationship between HDP and future ophthalmic morbidity, specifically retinal disorders (primary outcome) and/or other ophthalmic disorders (secondary outcomes). Four databases were searched until February 2025. Studies were screened according to inclusion/exclusion criteria, and quality assessed using the Newcastle-Ottawa scale. Random-effects was performed using generic inverse variance method, producing pooled odds ratios (ORs) with 95% confidence intervals (Cis). Eight studies were included (2 174 991 women; 5.40% HDP), typically of good (n = 4) to fair (n = 2) quality. Meta-analysis for retinal detachment and diabetic retinopathy were performed using two studies (n = 1 211 724; 6% HDP). Preeclamptic women had near double odds of retinal detachment (1.87; 95% CI 1.57-2.22; I2 = 0%) and over six times the odds of diabetic retinopathy (6.57; 95% CI 3.41-12.65; I2 = 51%). Studies reported generally poorer ophthalmic outcomes in women with HDP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.031 |
| 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 | 0.001 |
| 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".