Analysis Identifies 7 Factors Associated With Mortality in CKD

This new analysis aimed to pinpoint more rigorous predictors of mortality, and it was able to identify “excellent” but not “outstanding” ones, according to the investigators.

A new systematic review has identified 7 clinical characteristics that appear to be predictive of mortality among patients with chronic kidney disease (CKD).

The report, published in World Journal of Nephrology, offers new insights into the types of patients who are at highest risk of death and gives physicians a better understanding of how to analyze individual patient risk factors.

Between 8% and 16% of the world’s population is believed to suffer from CKD, and this incidence is expected to rise in the coming years, noted the authors. These patients face a higher risk of end-stage kidney disease, dialysis, cardiovascular disease, and all-cause mortality, meaning it is important to understand the particular risks for particular patients, the investigators said.

Several factors, such as age, diabetes, and C-reactive protein (CRP), have been identified as risk factors for mortality among patients on dialysis, but the authors said most available studies have not sufficiently demonstrated potential connections.

“Nearly all of the available evidence has reported their findings using regression analysis,” they wrote. “Thus, the accuracy of mortality prediction has not been clearly demonstrated.”

The investigators conducted a systematic review of studies that used associated area under the receiver operating characteristic curve and analysis to identify predictive factors of mortality in patients with CKD. They looked for studies that were observational or conference abstracts, involved nontransplant patients with CKD at any stage, and which used area under the curve (AUC) analysis with a 95% CI.

Eighteen studies met the inclusion criteria, and they covered 832 patients who had CKD without the need for dialysis, and 13,747 patients who were on dialysis because of CKD. Of this latter group, 2160 patients were on hemodialysis, 370 were on peritoneal dialysis, and the rest were on nondifferentiated dialysis.

After analysis of the literature, 24 mortality predictors were identified, but none met the standard of “outstanding” predictors. The following 7, however, met the standard for “excellent” predictors:

  • N-terminal pro-brain natriuretic peptide
  • Brain natriuretic peptide
  • Soluble urokinase plasminogen activator receptor
  • Augmentation index
  • Left atrial reservoir strain
  • CRP
  • Systolic pulmonary artery pressure

One takeaway from the analysis is the importance of monitoring patients’ cardiovascular health, the authors said.

“Echocardiography is an important tool for mortality prognostication in CKD patients by evaluating left atrial reservoir strain, systolic pulmonary artery pressure, diastolic function, and left ventricular mass index,” they wrote.

The authors said their analysis was limited by a lack of uniformity among the predictive factors analyzed in each study. “Because of this limitation, a meta-analysis, subgroup analysis, and test of homogeneity could not be performed,” they said.

Additionally, most studies were observational in nature, meaning there is a possibility of selection bias. Finally, the investigators said there was a relatively low number of patients on peritoneal dialysis, compared with other types, which could have affected the results.

“Nonetheless, the findings from our research could be applied towards the design of future prospective studies, with the goal of developing a prognostication scoring system for mortality in CKD patients,” they said. “To date, the outstanding factors (defined by AUC ≥ 0.90) for mortality prediction in CKD patients have yet to be discovered.”


Hansrivijit P, Chen YJ, Lnu K, et al. Prediction of mortality among patients with chronic kidney disease: a systematic review. World J Nephrol. 2021;10(4):59-75. doi:10.5527/wjn.v10.i4.59

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