Development and external validation of a nomogram for predicting in‐hospital mortality in status epilepticus patients in the intensive care unit: A MIMIC ‐ IV and eICU ‐ CRD study

Objective To develop and externally validate a nomogram for predicting in‐hospital mortality in ICU patients with SE, using readily available clinical data collected within the first 24 h of ICU admission. Methods We identified adult SE patients from MIMIC‐IV (training cohort, 2008–2019) using ICD‐9/ICD‐10 codes. Twenty‐seven candidate predictors were screened by LASSO logistic regression with 10‐fold cross‐validation. The final model was constructed with multivariable logistic regression and presented as a nomogram. Internal validation used 1000 bootstrap resamples with optimism correction. External validation was performed in an independent SE cohort from the eICU‐CRD database (2014–2015). Results The training cohort comprised 299 patients (69 deaths, 23.1% mortality). LASSO selected nine predictors: age, first ICU care unit, Glasgow Coma Scale, temperature, SpO 2 , white blood cell count, glucose, bicarbonate, and the Elixhauser comorbidity index. The optimism‐corrected AUC was .807 (95% CI, .754–.860) with a Brier score of .124. External validation in 597 eICU patients yielded an AUC of .750 (95% CI, .685–.815). In sensitivity analyses, a reduced model without the comorbidity score achieved an optimism‐corrected AUC of .786 and an external AUC of .730, and a model without the ICU care‐unit type achieved .817 and .764, respectively. Significance This nine‐variable nomogram provides a validated, bedside‐applicable tool for mortality risk stratification in ICU SE patients, enabling manual risk calculation without electronic computation.