SynthesisBrain and behavior2026
Prediction Models for Acute Kidney Injury in Stroke Patients: A Systematic Review.
Synthesis in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Prediction Models for Acute Kidney Injury in Stroke Patients: A Systematic Review.Brain and behavior · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
introductionTo systematically identify and synthesize the research on prediction models for acute kidney injury (AKI) in stroke patients.
methodsCNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, Embase, and Web of Science were searched from inception to April 26, 2025. The fundamental characteristics of the included studies were extracted, including model construction, predictors, model performance, and presentation methods.
resultsA total of 35 prediction models were identified in this systematic review, with area under the curve (AUC) values ranging from 0.428 to 1.000. Seven studies performed external validation. Common predictors included hypertension, serum creatinine levels, age, diuretic use, mechanical ventilation, and the National Institutes of Health Stroke Scale score (NIHSS).
conclusionsThe risk prediction model for AKI in stroke patients still needs to be developed. Despite demonstrating promising predictive capability, the models exhibited significant performance variability and an overall high risk of bias. Future research requires standardized development and validation of models to develop reliable prediction tools with minimal bias and enhanced applicability.
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What OpenQuestion holds
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 OpenQuestion graph.