Development and Validation Nomogram for Predicting the Survival of Patients with Thrombocytopenia in Intensive Care...

The number of patients with thrombocytopenia (TCP) is relatively high in intensive care units (ICUs). It is therefore necessary to evaluate the prognostic risk of such patients.

This study investigated the risk factors affecting the survival of patients with TCP in the ICU. Using the findings of this investigation, we developed and validated a risk prediction model.

We evaluated patients admitted to the ICU who presented with TCP. We used LASSO regression to identify important clinical indicators. Based on these indicators, we developed a prediction model complete with a nomogram for the development cohort set. We then evaluated the mode's accuracy using a receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA) in a validation cohort.

A total of 141 cases of ICU TCP were included in the sample, of which 47 involved death of the patient. Clinical results were as follows: N (HR 0.91, 95% CI 0.86-0.97, P=0.003); TBIL (HR 1.98, 95% CI 1.02-1.99, P=0.048); APACHE II (HR 1.94, 95% CI 1.39, 2.48, P=0.045); WPRN (HR 6.22, 95% CI 2.86-13.53, P<0.001); WTOST (HR 0.56, 95% CI 0.21-1.46, P<0.001); and DMV [HR1.87, 95% CI 1.12-2.33]. The prediction model yielded an area under the curve (AUC) of 0.918 (95% CI 0.863-0.974) in the development cohort and 0.926 (95% CI 0.849-0.994) in the validation cohort. Application of the nomogram in the validation cohort gave good discrimination (C-index 0.853, 95% CI 0.810-0.922) and good calibration. DCA indicated that the nomogram was clinically useful.

The individualized nomogram developed through our analysis demonstrated effective prognostic prediction for patients with TCP in ICUs. Use of this prediction metric may reduce TCP-related morbidity and mortality in ICUs.