Development of long-term cardiovascular disease risk prediction model for hemodialysis patients with end-stage renal disease based on nomogram

Abstract

Background: Chronic kidney disease (CKD) is a leading public health problem worldwide. Cardiovascular diseases are the primary cause of death in hemodialysis patients with CKD. Therefore, it is necessary to develop a simple risk assessment tool for cardiovascular events in hemodialysis patients with CKD.Methods: A cohort of 370 hemodialysis patients, who were recruited between January 2015 to September 2019 in south China, were involved in the present study. On the basis of routine blood test indicators and ultrasonic cardiogram parameters, the optimal parameter set was determined and a Cox proportional hazards model coupled with a nomogram was used to predict cardiovascular risk over 3, 5, and 10 years. Predictive performance was evaluated using Harrell's concordance index (C-index) and the area under the receiveroperating characteristic curve (AUROC). The results were validated using both 10-fold cross-validation and hold-out validation (70% training and 30% validation, repeated 100 times). Results:The optimal parameter set consisted of hypertension, diabetes mellitus, age, phosphate, triglyceride, C-reactive protein, white blood cells, and interventricular septum thickness. The timedependent AUROCs for predicting 3-, 5-, and 10-year cardiovascular event occurrence risk were 0.836, 0.845, and 0.869, respectively. The nomogram showed satisfactory prediction performance (C-index: 0.808, 95% confidence interval: 0.773-0.844) and was well-calibrated. The results were further confirmed by 10-fold cross-validation and hold-out validation (C-index: 0.794 and 0.798, respectively).Conclusions: On the basis of several easy-to-detect clinical parameters, we developed a simple and useful nomogram for predicting cardiovascular risk in long-term hemodialysis patients that is of potential value for clinical application.

Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis

“…Li et al [ 8 ] showed that the nomogram model predicted the probability of withdrawal in peritoneal dialysis patients. In addition, You et al [ 9 ] developed a simple and practical nomogram prediction model that could assess the risk of cardiovascular events in long-term hemodialysis patients with chronic kidney disease. However, there is no accurate nomogram model to assess the risk factors for cardiovascular events in DN patients receiving maintenance hemodialysis.…”

Risk prediction models for cardiovascular events in hemodialysis patients: A systematic review

“…After reviewing the titles and abstracts, 3224 articles were excluded, leaving 86 articles to be read in full text. Ultimately, nine articles [14][15][16][17][18][19][20][21][22] containing 12 models were included (Figure 1). indicates not mentioned.…”

“…Three prospective cohort studies 14,17,19 and six retrospective cohort studies 15,16,18,[20][21][22] were included in the nine articles. The total sample size comprised 16,529 patients, with 3651 patients experiencing an outcome event.…”

A Retrospective Study from a Single Center in China to Develop a Nomogram to Predict One-Year Mortality in Patients with End-Stage Renal Disease Who Are Receiving Hemodialysis

“…However, the establishment of an effective prediction model by combing multiple prognostic factors could play an important role in clinical risk assessment and individual patient’s treatment [ 11 ]. There have been few studies based on the biochemical indicators of liver and kidney function needed to construct a prediction model associated with the risk of ESRD patients receiving HD [ 11 – 14 ].…”