Development and Validation of Prediction Models for Hypertensive Nephropathy, the PANDORA Study

Authors

• Xiaoli Yang, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Bingqing Zhou, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Li Zhou, Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China.
• Liufu Cui, Department of Cardiology, Kailuan General Hospital, Tangshan, China.
• Jing Zeng, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Shuo Wang, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Weibin Shi, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Ye Zhang, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Xiaoli Luo, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Chunmei Xu, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Yuanzheng Xue, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Hao Chen, Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China.
• Shuohua Chen, Department of Cardiology, Kailuan General Hospital, Tangshan, China.
• Guodong Wang, Department of Cardiology, Kailuan General Hospital, Tangshan, China.
• Li Guo, Department of Endocrinology, Southwest Hospital, Third Military Medical University, Chongqing, China.
• Pedro A. Jose, Division of Renal Disease & Hypertension, The George Washington University School of Medicine & Health Sciences, Washington, DC, United States.
• Christopher S. Wilcox, Division of Nephrology and Hypertension, Department of Medicine and Center for Hypertension, Kidney and Vascular Health, Georgetown University, Washington, DC, United States.
• Shouling Wu, Department of Cardiology, Kailuan General Hospital, Tangshan, China.
• Gengze Wu, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.
• Chunyu Zeng, Department of Cardiology, Daping Hospital, Third Military Medical University, Chongqing, China.

Document Type

Journal Article

Publication Date

1-1-2022

Journal

Frontiers in cardiovascular medicine

Volume

9

DOI

10.3389/fcvm.2022.794768

Keywords

chronic kidney disease; hypertension; hypertensive nephropathy; pulse pressure; risk model

Abstract

Importance: Hypertension is a leading cause of end-stage renal disease (ESRD), but currently, those at risk are poorly identified. Objective: To develop and validate a prediction model for the development of hypertensive nephropathy (HN). Design Setting and Participants: Individual data of cohorts of hypertensive patients from Kailuan, China served to derive and validate a multivariable prediction model of HN from 12, 656 individuals enrolled from January 2006 to August 2007, with a median follow-up of 6.5 years. The developed model was subsequently tested in both derivation and external validation cohorts. Variables: Demographics, physical examination, laboratory, and comorbidity variables. Main Outcomes and Measures: Hypertensive nephropathy was defined as hypertension with an estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m and/or proteinuria. Results: About 8.5% of patients in the derivation cohort developed HN after a median follow-up of 6.5 years that was similar in the validation cohort. Eight variables in the derivation cohort were found to contribute to the risk of HN: salt intake, diabetes mellitus, stroke, serum low-density lipoprotein, pulse pressure, age, hypertension duration, and serum uric acid. The discrimination by concordance statistics (C-statistics) was 0.785 (IQR, 0.770-0.800); the calibration slope was 1.129, the intercept was -0.117; and the overall accuracy by adjusted was 0.998 with similar results in the validation cohort. A simple points scale developed from these data (0, low to 40, high) detected a low morbidity of 7% in the low-risk group (0-10 points) compared with >40% in the high-risk group (>20 points). Conclusions and Relevance: A prediction model of HN over 8 years had high discrimination and calibration, but this model requires prospective evaluation in other cohorts, to confirm its potential to improve patient care.

APA Citation

Yang, Xiaoli; Zhou, Bingqing; Zhou, Li; Cui, Liufu; Zeng, Jing; Wang, Shuo; Shi, Weibin; Zhang, Ye; Luo, Xiaoli; Xu, Chunmei; Xue, Yuanzheng; Chen, Hao; Chen, Shuohua; Wang, Guodong; Guo, Li; Jose, Pedro A.; Wilcox, Christopher S.; Wu, Shouling; Wu, Gengze; and Zeng, Chunyu, "Development and Validation of Prediction Models for Hypertensive Nephropathy, the PANDORA Study" (2022). GW Authored Works. Paper 608.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/608

Department

Medicine