Key result
CHA2DS2-VASc shows only modest discrimination for ischemic stroke in AF patients with kidney disease.
Why the study?
To evaluate stroke and bleeding prediction models in patients with AF undergoing dialysis or with CKD, provide pooled estimates, and assess their risk of bias.
What is the predictive performance of standard stroke and bleeding risk prediction models in patients with atrial fibrillation and chronic kidney disease or undergoing dialysis?
Systematic Review (n=627,199)
What is the predictive performance of standard stroke and bleeding risk prediction models in patients with atrial fibrillation and chronic kidney disease or undergoing dialysis?
Effect estimate: c-statistic 0.65 (95% CI 0.61-0.69)
Commonly used prediction models for stroke and bleeding in atrial fibrillation show modest discrimination in patients with CKD or on dialysis, similar to their performance in the general population, thereby supporting their continued clinical use in this high-risk subgroup.
May support continued use in AF with CKD; leaves open kidney-specific models given high bias and heterogeneity.
Rationale & Objective: HAGES model scores in patients with AF undergoing dialysis or with CKD, (2) provide pooled estimates, and (3) assess their risk of bias (ROB). Study Design: Systematic review and meta-analysis. Setting & Participants: We searched Web of Science, PubMed, MEDLINE, Embase, Emcare, PMC, Cochrane Library, and Academic Search Premier for studies externally validating IS and bleeding prediction models in patients with AF undergoing dialysis or with CKD. Exposures: AF and CKD or dialysis. Outcomes: IS and bleeding. Analytical Approach: Eligible studies were reviewed, discrimination was pooled using random-effects meta-analysis, calibration was calculated and plotted, and the ROB score was assessed using the prediction model ROB assessment tool. Results: HAGES model scores showed similar c-statistic scores predicting bleeding (0.55 and 0.56, respectively). Calibration was good in the most relevant high-risk group. Limitations: All studies were at high ROB scores, contained within- and between-study heterogeneity, and often merged scoring categories or populations, limiting comparability. Conclusions: Although modest, the discrimination of prediction models in patients with AF undergoing dialysis or with CKD is similar to patients with AF without CKD. Despite the described limitations, these models can be used in clinical practice for patients with CKD and patients undergoing dialysis.
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Langenhuijsen et al. (2025) conducted a systematic review in Atrial Fibrillation with Chronic Kidney Disease or Dialysis (n=627,199). Ischemic stroke and bleeding prediction models (CHA2DS2-VASc, CHADS2, HAS-BLED, HEMORR2HAGES) vs. Observed clinical events was evaluated on Ischemic stroke prediction discrimination (pooled c-statistic) for the CHA2DS2-VASc model in combined CKD and dialysis patients (c-statistic 0.65, 95% CI 0.61-0.69). In patients with atrial fibrillation and kidney disease or dialysis, the CHA2DS2-VASc and CHADS2 prediction models demonstrated modest discrimination for ischemic stroke with pooled c-statistics of 0.65 and 0.68, respectively.
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