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. 2024 Nov 15;17(12):sfae347.
doi: 10.1093/ckj/sfae347. eCollection 2024 Dec.

Prediction models for ischemic stroke and bleeding in dialysis patients: a systematic review and meta-analysis

Christoforos K Travlos  1   2   3 , Adario Chirgwin-Dasgupta  4 , Emilie Trinh  1   2   3 , Allan D Sniderman  5 , Ahsan Alam  1   2   3 , Thomas A Mavrakanas  1   2   3
Affiliations

Prediction models for ischemic stroke and bleeding in dialysis patients: a systematic review and meta-analysis

Christoforos K Travlos et al. Clin Kidney J. .

Abstract

Background: Patients with kidney failure on maintenance dialysis have a high stroke and bleeding risk. Multivariable prediction models can be used to estimate the risk of ischemic stroke and bleeding. A systematic review and meta-analysis was performed to determine the performance of the existing models in patients on dialysis.

Methods: MEDLINE and Embase databases were searched, from inception through 12 January 2024, for studies of prediction models for stroke or bleeding, derived or validated in dialysis cohorts. Discrimination measures for models with c-statistic data from three or more cohorts were pooled by random effects meta-analysis and a 95% prediction interval (PI) was calculated. Risk of bias was assessed using PROBAST. The review was conducted according to the PRISMA statement and the CHARMS checklist.

Results: Eight studies were included in this systematic review. All the included studies validated pre-existing models that were derived in cohorts from the general population. None of the identified studies reported the development of a new dialysis specific prediction model for stroke, while dialysis specific risk scores for bleeding were proposed by two studies. In meta-analysis of c-statistics, the CHA2DS2-VASc, CHADS2, ATRIA, HEMORR(2)HAGES and HAS-BLED scores showed very poor discriminative ability in the dialysis population. Six of the eight included studies were at low or unclear risk of bias and certainty of evidence was moderate.

Conclusions: The existing prediction models for stroke and bleeding have very poor performance in the dialysis population. New dialysis-specific risk scores should be developed to guide clinical decision making in these patients.

Keywords: bleeding; dialysis; meta-analysis; prediction models; stroke.

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Conflict of interest statement

T.A.M. has received speaker honoraria from Bayer, BMS Canada, Janssen, AstraZeneca and Pfizer; and has served on advisory boards for Boehringer Ingelheim, Bayer, GSK and Servier outside the submitted work. He has also received research grants from AstraZeneca and Pfizer. He is supported by a Fonds de Recherche Santé Quebec (FRSQ) Junior 1 Clinician Scholar award and a Kidney Research Scientist Core Education and National Training (KRESCENT) program New Investigator Award. E.T. has received speaker honorarium from Baxter Inc., investigator-initiated funding from Otsuka and GSK, and consulting fees from Otsuka. The remaining authors have no relevant disclosures.

Figures

Figure 1:
Figure 1:
The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) flow-chart of studies included in the systematic review.
Figure 2:
Figure 2:
Risk of bias across all included studies.
Figure 3:
Figure 3:
Meta-analysis of c-statistics for: (a) CHA2DS2-VASc score and (b) CHADS2 score.
Figure 4:
Figure 4:
Meta-analysis of c-statistics for: (a) ATRIA score; (b) HEMORR(2)HAGES score and (c) HAS-BLED score.
See this image and copyright information in PMC

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