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Charlson comorbidity index and all-cause mortality in patients with delayed hemodialysis initiation: a prospective
Allina P Flores-Mendoza1,2, Mariano García-Campa3,4, Concepción Sánchez-Martínez5
1Transplant Service, School of Medicine and University Hospital "Dr. José E González;" Autonomous University of Nuevo León, Av. Francisco Madero, Monterrey, 6664, México. allina.floresmnd@uanl.edu.mx.
Insights
Prognostic factors like the Charlson Comorbidity Index (CCI) and surprise questions help predict mortality risk in chronic kidney disease (CKD) patients starting hemodialysis (HD). Integrating these tools aids patient-centered care, especially in resource-limited settings.
Area of Science:
- Nephrology
- Public Health
- Geriatrics
Background:
- Chronic kidney disease (CKD) is a growing public health concern.
- Effective risk stratification is crucial for patient-centered care in CKD.
- Existing prognostic scales for CKD patients initiating dialysis include the Charlson Comorbidity Index (CCI), surprise questions, and functional/biochemical parameters.
Purpose of the Study:
- To identify prognostic factors for all-cause mortality in patients with CKD undergoing delayed initiation of hemodialysis (HD).
Main Methods:
- A prospective cohort study was conducted in a Mexican dialysis center.
- 218 patients with CKD and delayed HD initiation were included.
- Patients were stratified by CCI, and sociodemographic, functional, and biochemical data were collected to assess mortality.
Main Results:
- Overall all-cause mortality was 40% during a median follow-up of 45.5 weeks.
- Higher CCI scores correlated with lower survival rates (e.g., very high CCI: 41% survival).
- Patients answering "no" to the surprise question and those with high/very high CCI demonstrated significantly increased mortality risk.
Conclusions:
- Individualized, patient-centered care is essential for CKD management.
- Combining the CCI and the "surprise question" can guide therapeutic strategies.
- These integrated tools are particularly valuable for decision-making in resource-limited settings.
Background:
Chronic kidney disease (CKD) has recently been recognized as a public health issue. Prognosis and risk stratification are fundamental for decision-making to implement patient-centered strategies in clinical practice. Different prognosis scales have been evaluated, such as the Charlson Comorbidity Index (CCI), surprise questions, functional and biochemical parameters, to stratify patients with CKD initiating dialysis. The aim of this study was to determine prognostic factors for mortality in patients with CKD and delayed initiation of hemodialysis (HD).
Methods:
We performed a prospective cohort study based on data from a reference dialysis center in the northeastern region of Mexico. Individuals with CKD and delayed initiation of hemodialysis were stratified according to the CCI at admission. Additionally, sociodemographic, functional, and biochemical parameters were compared to assess all-cause mortality.
Results:
A total of 218 patients were included, with a median follow-up of 45.5 weeks. An important proportion of all-cause mortality was associated with infections among all groups. At the end of follow-up, overall all-cause mortality was 40%. Patients stratified with a low CCI had a survival rate of 79.2%, whereas those with moderate, high and very high CCIs had survival rates of 66.7%, 56.6%, and 41%, respectively. After adjusting for clinical and biochemical characteristics, patients who answered that they would not be surprised if they died in the following 6 months had an increased risk of all-cause mortality regardless of the CCI category. Patients with a high CCI (HR: 2.52; 95% CI: 1.22-5.18) and very high CCI (HR: 3.73; 95% CI: 1.89-7.36) clearly had increased risk for all-cause mortality.
Conclusion:
Individualized patient-centered care should be the goal of standard care. By integrating the CCI and the surprise question (would you be surprised if the patient died in the following 6 months), it is possible to guide decisions further therapeutic strategies in patients in resource-limited settings.
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