Analysis of In-Hospital Mortality Risk Factors and Establishment of a Nomogram Prediction Model for Patients with Stage 5 CKD in the Intensive Care Unit (ICU)

Background: Patients with stage 5 chronic kidney disease (CKD5) have a high risk of mortality. ICU patients have lots of abnormal results. Defining the risk factors for in-hospital mortality in ICU CKD5 patients will help doctors pay more attention to the most important factors and intervene in a timely manner. In this study, we analyzed the risk factors related to in-hospital mortality and drew the nomogram to predict in-hospital mortality in CKD5 non-dialysis (CKD 5ND) patients. Methods: According to the diagnosis code, 495 CKD 5ND patients were selected from the MIMIC-IV database. The differences between the survival group and the death group were analyzed by two independent samples t-test, rank-sum test, or chi-square test. The nomograms to predict the risk of in-hospital mortality in CKD 5ND patients were established respectively. In order to evaluate the nomogram, ROC curve, calibration curve, and DCA curve were used. Boostrap-resampling was used for internal verification. eICU patients were used for external verification. And the predictive performance of the nomogram was compared with commonly scores. Results: There were 1439 CKD5 patients in the MIMIC-IV database, including 495 non-dialysis patients. There were 425 CKD5 ND patients in the survival group and 70 patients in the death group. Age, SBP, WBC, RDW, and BUN/Scr were the correlation factors for in-hospital mortality in CKD5 ND patients. Internal and external validation showed that the CKD5 ND patients nomogram prediction model had good calibration, clinical benefit, and discrimination (training set AUC=0.832, validation set AUC=0.770). The predictive ability of nomogram was better than the three commonly used scores. Conclusion: The nomogram prediction model predicting in-hospital mortality of CKD5 ND patients has good discrimination, calibration, and clinical value, which are established by Age, SBP, WBC, RDW, and BUN/Scr.

Authors

Institutions

Publication Details

Journal
Journal of the American Society of Nephrology
Published
2024-10-01
DOI
https://doi.org/10.1681/asn.202456q8470x
Primary Topic
Pharmacy and Medical Practices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of In-Hospital Mortality Risk Factors and Establishment of a Nomogram Prediction Model for Patients with Stage 5 CKD in the Intensive Care Unit (ICU)

Fanna Liu
Journal of the American Society of Nephrology
Pharmacy and Medical Practices
article

Analysis of In-Hospital Mortality Risk Factors and Establishment of a Nomogram Prediction Model for Patients with Stage 5 CKD in the Intensive Care Unit (ICU)

Fanna Liu
article en

Abstract

Background: Patients with stage 5 chronic kidney disease (CKD5) have a high risk of mortality. ICU patients have lots of abnormal results. Defining the risk factors for in-hospital mortality in ICU CKD5 patients will help doctors pay more attention to the most important factors and intervene in a timely manner. In this study, we analyzed the risk factors related to in-hospital mortality and drew the nomogram to predict in-hospital mortality in CKD5 non-dialysis (CKD 5ND) patients. Methods: According to the diagnosis code, 495 CKD 5ND patients were selected from the MIMIC-IV database. The differences between the survival group and the death group were analyzed by two independent samples t-test, rank-sum test, or chi-square test. The nomograms to predict the risk of in-hospital mortality in CKD 5ND patients were established respectively. In order to evaluate the nomogram, ROC curve, calibration curve, and DCA curve were used. Boostrap-resampling was used for internal verification. eICU patients were used for external verification. And the predictive performance of the nomogram was compared with commonly scores. Results: There were 1439 CKD5 patients in the MIMIC-IV database, including 495 non-dialysis patients. There were 425 CKD5 ND patients in the survival group and 70 patients in the death group. Age, SBP, WBC, RDW, and BUN/Scr were the correlation factors for in-hospital mortality in CKD5 ND patients. Internal and external validation showed that the CKD5 ND patients nomogram prediction model had good calibration, clinical benefit, and discrimination (training set AUC=0.832, validation set AUC=0.770). The predictive ability of nomogram was better than the three commonly used scores. Conclusion: The nomogram prediction model predicting in-hospital mortality of CKD5 ND patients has good discrimination, calibration, and clinical value, which are established by Age, SBP, WBC, RDW, and BUN/Scr.

Journal of the American Society of NephrologyVol. 35(10S)
Guangzhou Chemistry (China) (CN)
Good health and well-being
Openalex Percentile: Top 76%
Pharmacy and Medical Practices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Analysis of In-Hospital Mortality Risk Factors and Establishment of a Nomogram Prediction Model for Patients with Stage 5 CKD in the Intensive Care Unit (ICU) — Fanna Liu · Journal of the American Society of Nephrology (2024) | TGRS Research Map | TGRS