Intracranial hemorrhage in posterior reversible encephalopathy syndrome: a systematic review & meta-analysis
Bibliographic record
Abstract
Background: Posterior reversible encephalopathy syndrome (PRES) is a clinical-radiographic phenomenon characterized by vasogenic edema, predominantly affecting the posterior regions of the brain. The hemorrhagic variant of PRES has been increasingly recognized, complicating the clinical picture and prognosis. Methods: This meta-analysis was conducted in accordance with PRISMA guidelines. Observational studies, case reports/series were included. Extracted data included demographics, clinical presentations, imaging findings, and outcomes. A random-effects model to pool the incidence rate of hemorrhagic PRES, and heterogeneity was assessed using the I 2 statistic. The Joanna Briggs Institute scale for case reports/series and the New Castle Ottawa scale for cohort studies were used for quality and risk of bias assessment. Results: A total of 63 individual records and 12 cohort studies were reviewed. Hypertension at arrival was seen in > 90% of cases. 60.3% of cases occurred in women and the average age was 39.3, with a 12.7% mortality rate. The incidence rate of hemorrhagic PRES was found to be approximately 17%, with significant heterogeneity among the included studies (I 2 = 67%). Seizures (31.7%), headaches (33.3%), and altered mental status (30.1%) were the most reported symptoms. Hypertension (31.7%), immunosuppressive therapy (23.8%), and coagulopathy (11.1%) were identified as the most common risk factors. Hemorrhagic findings included intraparenchymal hemorrhage (77.7%), subarachnoid hemorrhage (15.8%), and microhemorrhages (6.3%). Conclusions: Hemorrhagic PRES is a significant clinical concern, occurring in approximately 17% of PRES cases and is often associated with poorer outcomes. We highlight the importance of early recognition, aggressive blood pressure control, and careful monitoring in high-risk patients.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.004 | 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".