SynthesisPeerJ2026
Risk prediction models for sepsis-associated encephalopathy: a systematic evaluation and meta-analysis.
Synthesis in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Research Advances in the Pathogenesis of Sepsis-Associated Encephalopathy.International journal of molecular sciences · 2026Review
- Early Clinical, Laboratory, and Imaging Correlates of Neurological Dysfunction in Adults Presenting to the Emergency Department with Sepsis: A Single-Center Retrospective Study.Juntendo medical journal · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The number of risk prediction models for sepsis-associated encephalopathy (SAE) is increasing, while the quality and applicability of these models in clinical practice and future research remain uncertain. Objective: To systematically review published studies on SAE risk prediction models. Design: Systematic review and meta-analysis of observational studies. Methods: A systematic search of PubMed, Web of Science, Embase, Wanfang, VIP, and CNKI databases was conducted from inception to April 2, 2025, to identify studies on SAE risk prediction models. Two independent reviewers screened the studies and extracted data. The Prediction model Risk Of Bias Assessment Tool (PROBAST) was applied to evaluate the risk of bias and applicability of the included studies. Results: A total of 1,994 studies were identified, and 10 were included after screening. The reported incidence of SAE ranged from 15.16% to 63.3%. Age and Sequential Organ Failure Assessment (SOFA) score are the most frequently adopted factors with significant predictive value, both of which were incorporated into five models. Both the SOFA score and age were significantly associated with SAE. In studies with available data, the odds ratio (OR) for age ranged from 1.084 to 1.018, while that for SOFA score ranged from 1.246 to 2.416. The area under the receiver operating characteristic curve (AUC) for the 10 studies ranged from 0.743 to 0.975. All studies were found to have a high risk of bias, primarily due to inappropriate data sources and deficiencies in the analysis domain. The pooled AUC for the six validated models was 0.83 (95% confidence interval [0.77-0.89]), indicating fair discrimination. Conclusion: Although the included studies reported some discrimination in the SAE prediction models, all were found to have a high risk of bias according to the PROBAST checklist. Registration: This study protocol was registered on PROSPERO (registration number: CRD420251012485).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.