A Dynamic Nomogram to Identify Patients at High Risk of Poor Outcome in Stroke Patients with Chronic Kidney Disease

Abstract

Background and Purpose

Predicting poor outcome for stroke patients with chronic kidney disease (CKD) in clinical practice is difficult. There are no tools available to use for predicting poor outcome in these patients. We aimed to construct and validate a dynamic nomogram to identify CKD–stroke patients at high risk of a 3-month poor outcome.

Patients and Methods

We used data for 502 CKD patients who had an acute ischemic stroke, from Nanjing First Hospital, between September 2014 and September 2020, to train the nomogram. An additional 108 patients enrolled from October 2020 to May 2021 were used for temporal external validation. The performance of the nomogram was evaluated by the area under the receiver operating characteristics curve (AUC) and a calibration plot. The clinical utility of the nomogram was measured by decision curve analysis (DCA) and the clinical impact curve (CIC).

Results

The median age of the cohort was 79 (70–84) years. Age, urea, premorbid modified Rankin Scale (mRS), National Institutes of Health Stroke Scale (NIHSS) on admission, hemiplegia, mechanical thrombectomy, early neurological deterioration, and respiratory infection were used as predictors of 3-month poor outcome to develop the nomogram. In the training set, the AUC of the dynamic nomogram was 0.873 and the calibration plot showed good predictive ability, and both DCA and CIC indicated the excellent clinical usefulness and applicability of the nomogram. In the external validation set, the AUC was 0.875 and the calibration plot also showed good agreement.

Conclusion

This is the first dynamic nomogram constructed for CKD–stroke patients to precisely and expediently identify patients with a high risk of 3-month poor outcome. The outstanding performance and great clinical predictive utility demonstrated the ability of the dynamic nomogram to help clinicians to deploy preventive interventions.

Keywords:

• dynamic nomogram
• stroke
• chronic kidney disease
• poor outcome
• predict

Ethics Approval and Informed Consent

This study followed approval by the ethics committee of Nanjing First Hospital (document number: ChiCTR-OCH-14004382) and complied with the Declaration of Helsinki. Informed consent was waived because of the anonymous data.

Acknowledgments

We thank all authors for their important contributions.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work. Fusang Wang, Xiaohan Zheng, and Juan Zhang share first authorship.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This study was supported by the National Natural Science Foundation of China [grant 81673511], Jiangsu Key Research and Development Plan [grant BE2017613], and Jiangsu Six Talent Peaks Project [grant WSN-151].