Related Experiment Video
Updated: May 6, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Prognostic Value of the CONUT Score in Predicting All-Cause Mortality in Hospitalized Internal Medicine Patients: A
Betül Çavuşoğlu Türker1, Mehmet Yamak1, Mehmet Çetin1
1Department of İnternal Medicine, University of Health Sciences Turkey, Haseki Health Training and Research Hospital, Aksaray, Dr. Adnan Adıvar Cd. No: 9, 34130 Istanbul, Turkey.
Insights
The CONUT score, a simple nutritional index, strongly predicts mortality in hospitalized patients. Higher CONUT scores indicate increased all-cause mortality risk, aiding early identification of high-risk individuals.
Area of Science:
- Internal Medicine
- Clinical Nutrition
- Prognostic Biomarkers
Background:
- Assessing mortality risk in hospitalized patients is crucial for clinical management.
- The CONUT (Controlling Nutritional Status) score is a readily available nutritional index.
- Limited data exist on the prognostic significance of the CONUT score in internal medicine wards.
Purpose of the Study:
- To evaluate the prognostic significance of the CONUT score.
- To assess the association between the CONUT score and all-cause mortality.
- To identify independent predictors of mortality in hospitalized internal medicine patients.
Main Methods:
- Retrospective cohort study of hospitalized adult internal medicine patients.
- CONUT score calculated using serum albumin, total cholesterol, and lymphocyte count.
- Survival analysis using Cox proportional hazards regression, with multivariate analysis for independent predictors.
Main Results:
- The CONUT score demonstrated a significant association with all-cause mortality.
- CONUT score, age, chronic renal disease, and solid organ malignancy were independent predictors of mortality.
- Each one-point increase in CONUT score nearly doubled the risk of death (HR = 1.219).
Conclusions:
- The CONUT score is a powerful and independent predictor of all-cause mortality in hospitalized internal medicine patients.
- Its simplicity and low cost facilitate integration into routine clinical practice.
- CONUT aids in early risk stratification and identifying patients for closer monitoring and nutritional support.
Abstract:
Aim: This study aimed to evaluate the prognostic significance of the CONUT score and its association with all-cause mortality in hospitalized internal medicine patients. Methods: This retrospective cohort study included hospitalized adult patients followed for long-term all-cause mortality. Demographic data, laboratory parameters, comorbidities, and CONUT scores were recorded at admission. The CONUT score was calculated using serum albumin, total cholesterol, and lymphocyte count. Survival analysis was performed using the Cox proportional hazards regression model. Variables with p < 0.1 in univariate analysis were entered into the multivariate model. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. The primary outcome was all-cause mortality. Results: During the follow-up period, the CONUT score showed a strong and significant association with mortality. In multivariate Cox regression analysis, age, CONUT score, and chronic renal disease were identified as independent predictors of all-cause mortality. Each one-year increase in age was associated with a 5.3% increase in mortality risk (HR = 1.053, 95% CI: 1.048-1.058, p < 0.001). Each one-point increase in CONUT score nearly doubled the risk of death (HR = 1.219, 95% CI: 1.190-1.250, p < 0.001). The presence of chronic renal failure (HR = 2.142, p < 0.001) and solid organ malignancy (HR=1.216 p < 0.001) significantly increased mortality risk. Conclusions: The CONUT score is a powerful and independent predictor of all-cause mortality in hospitalized internal medicine patients. As a simple, inexpensive, and routinely available tool, CONUT can be easily integrated into daily clinical practice for early risk stratification and identification of high-risk patients who may benefit from closer monitoring and nutritional intervention.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
05:16Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
Related Concept Videos
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Life Tables
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups
Cancer Survival Analysis