Key result
Prediction models for 30-day stroke readmission show modest discrimination with a 0.69 AUC.
Why the study?
Contemporary readmission rates, prediction model performance, and predictor domains for 30-day readmission after stroke had not been comprehensively synthesized.
What is the pooled 30-day readmission rate after stroke and the performance of contemporary prediction models?
Meta-Analysis (n=358,434)
What is the pooled 30-day readmission rate after stroke and the performance of contemporary prediction models?
Effect estimate: Pooled AUC 0.69 (95% CI 0.64-0.75)
Current prediction models for 30-day readmission after stroke demonstrate only modest discrimination (pooled AUC 0.69), highlighting the need for models that incorporate broader clinical, functional, and social determinants.
Moderate discrimination limits reliable risk stratification for post-stroke readmission; leaves open the need for standardized predictors and higher-performing models.
Background: Thirty-day readmission after stroke remains common, yet contemporary readmission rates, prediction model performance, and predictor domains have not been comprehensively synthesized. Methods: Following PRISMA guidelines, we searched PubMed, Embase, Web of Science, Scopus, and Google Scholar for studies published between 1 January 2021 and 9 October 2025. Readmission proportions and model discrimination, measured by area under the receiver operating characteristic curve (AUC), were pooled using random-effects meta-analysis. Heterogeneity was assessed using I2. Predictors were summarized across studies by domain. Results: Twenty studies met inclusion criteria: 15 studies comprising 358,434 patients contributed quantitative data, and 5 were included in qualitative synthesis only. The pooled proportion was 12.9% (95% CI: 10.1–15.8%), with subgroup estimates of 14.2% (95% CI: 11.9–16.6%) for all-cause and 3.6% (95% CI: 0.5–6.7%) for stroke-specific readmissions. Study-level AUCs ranged from 0.59 to 0.88, with a pooled AUC of 0.69 (95% CI: 0.64–0.75), indicating moderate discrimination. Substantial heterogeneity was observed (I2 > 98%, p < 0.001), and pooled estimates should be interpreted cautiously. Predictor selection was poorly standardized and largely driven by data availability, with inconsistent inclusion of key clinical and post-discharge domains such as stroke severity, functional status, discharge disposition, post-discharge care, and social determinants of health. Conclusions: Thirty-day readmission after stroke remains common, and currently available models demonstrate modest predictive discrimination; no consistently high-performing, broadly generalizable prediction model has yet emerged. Improving prediction will require broader predictors capturing stroke severity, care transitions, follow-up, and patient context, along with external validation and integration into clinical workflows.
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Kalra et al. (2026) conducted a meta-analysis in Stroke (n=358,434). Prediction models was evaluated on 30-day readmission proportion (Pooled AUC 0.69, 95% CI 0.64-0.75). Prediction models for 30-day readmission after stroke demonstrated modest discrimination with a pooled AUC of 0.69 (95% CI 0.64-0.75), alongside a pooled 30-day readmission proportion of 12.9%.
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