Developing and validating a prognostic model to predict ICU mortality in patients with sepsis-associated thrombocytopenia: a retrospective cohort study based on MIMIC-IV.

Abstract

Given the high morbidity and mortality of patients with sepsis-associated thrombocytopenia (SATP) in the intensive care unit, this study retrospectively analysed the influencing factors for poor prognosis in patients with SATP using the MIMIC database, constructed a nomogram model and verified the predictive performance of the model. A retrospective cohort study. The data from MIMIC-IV, V.2.2. The clinical features of SATP, including demographics, comorbidities, vital signs, laboratory parameters, treatments and clinical management, were extracted from the MIMIC-IV database. 1409 patients with SATP were included in this study and randomly divided into a training set and a validation set in a ratio of 7:3. The least absolute shrinkage and selection operator and multivariable Cox regression analysis were used to determine the optimal predictors and establish a prediction model. The receiver operating characteristic curve, calibration curve and decision curve analysis (DCA) were used to verify the accuracy and application value of the model. The nomogram model incorporates nine factors, including clinical characteristics, laboratory test indicators, comorbidities and treatment methods, which were identified as predictors of SATP and used to construct the model. The area under the curve of the model was 0.868 (95% CI: 0.794 to 0.942) in the training set and 0.836 (95% CI: 0.681 to 0.991) in the validation set. The calibration curve and DCA confirmed the clinical application value of the nomogram. The constructed nomogram for predicting patients with SATP has favourable predictive ability and is helpful to further optimise clinical management strategies.