Hypertensive disorders of pregnancy and the long-term risk of maternal retinal disease: a systematic review protocol
Bibliographic record
Abstract
Background Previous studies have established an association between hypertensive disorders of pregnancy (HDP) (e.g. preeclampsia, gestational hypertension) and maternal cardiovascular disease, renal disease, and cerebrovascular disease. There is relatively little known about the association between HDP and maternal retinal disease, despite many retinal disorders having an underlying vascular aetiology. Existing research which has focused on HDP and future maternal ophthalmic outcomes is scarce, and findings are inconsistent. Objective This systematic review will examine the available evidence on the association between HDP and long-term maternal retinal disease and other forms of ophthalmic disease. Methods and analysis We will include cohort, cross-sectional, and case-control studies in which women had a known diagnosis of HDP (including preeclampsia, gestational hypertension) and where measures of association with maternal retinal disease or other ophthalmic disease were reported after at least 6 months postpartum. A systematic search of PubMed, Embase, Web of Science, and Cochrane Library will be conducted following a detailed search strategy until end of September 2024. Two authors will independently review titles and abstracts of all eligible studies, extract data using pre-defined, standardised data extraction tools, and assess the quality of each study using the Newcastle-Ottawa Scale. We will use random-effects meta-analysis for each exposure-outcome association where possible, and we will calculate overall pooled estimates using the generic inverse variance method. PROSPERO registration CRD42024589508
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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 | 0.038 | 0.051 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.013 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.085 | 0.007 |
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".