Prediction model for quality of life in sepsis survivors one year after discharge

BACKGROUND: Sepsis survivors experience poor long-term quality of life post-discharge. The aim of this study was to analyze the factors that impact the long-term quality of life of sepsis survivors and develop a clinical prediction model. METHODS: A total of 442 sepsis patients from the Emergency Intensive Care Unit of a tertiary hospital in Wenzhou were included. These patients were assigned to the training set or the validation set at a ratio of 7:3. The European Quality of Life 5 Dimensions 5 Level Version (EQ-5D-5L) questionnaire was used to evaluate the quality of life in sepsis survivors one year after discharge. Multivariate logistic regression analysis was used to identify predictors, which were then used to develop the prediction model and subsequently derive a scoring system. The model's effectiveness was assessed using an area under the receiver operating characteristic curve, calibration curves, and clinical decision analysis. RESULTS: Of the 442 patients included, 70 died one year after discharge, and 372 completed the questionnaire. A total of 46.6% of sepsis survivors have poor quality of life one year after discharge in the training set. Multivariate logistic regression revealed that age, platelet, serum albumin, serum urea, and C-reactive protein were independent risk factors for poor quality of life in sepsis survivors. The area under the curve of the scoring system was 0.777 (95% CI: 0.726-0.828). The calibration curves showed that it was well calibrated. Decision curve analysis indicated that the scoring system provided good clinical usefulness. The internal validation also demonstrated its effectiveness. CONCLUSION: The prediction model incorporating five risk factors may predict quality of life one year after discharge in sepsis survivors, which provides a measure to develop post-discharge rehabilitation and follow-up plans for this patient population.