AUTHOR=Jin Guangyong , Hu Wei , Zeng Longhuan , Ma Buqing , Zhou Menglu 

TITLE=Prediction of long-term mortality in patients with ischemic stroke based on clinical characteristics on the first day of ICU admission: An easy-to-use nomogram

JOURNAL=Frontiers in Neurology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2023.1148185

DOI=10.3389/fneur.2023.1148185

ISSN=1664-2295

ABSTRACT=Background: This study was aimed to establish and validate an ease-to-use nomogram for predicting long-term mortality among ischemic stroke.
Methods: All raw data were from the Medical Information Mart for Intensive Care IV database. Clinical features associated with long-term mortality (1-year mortality)  among ischemic stroke were identified using least absolute shrinkage and selection operator regression. Then, binary logistic regression was used to construct a nomogram, discrimination of which was evaluated by the concordance index (C-index), integrated discrimination improvement (IDI) and net reclassification index (NRI). Finally, a calibration curve and decision curve analysis (DCA) were employed to calibration and net clinical benefit, compared with Glasgow Coma Scale (GCS) and the commonly used disease severity scoring system.
Results: Identified patients with ischemic stroke were randomly assigned into developing (n=1443) and verification (n=646) cohorts. The following factors were associated with 1-year mortality among ischemic stroke, namely age on ICU admission, marital status, underlying dementia, underlying malignant cancer, underlying metastatic solid tumor, heart rate, respiratory rate, oxygen saturation, white blood cells, anion gap, mannitol injection, invasive mechanical ventilation and GCS. The construction of nomogram was based on features above. The C-index of the nomogram in the developing and verification cohorts were 0.820 and 0.816, respectively. Compared with GCS and the commonly used disease severity scoring system, the IDI and NRI of the constructed nomogram had a statistically positive improvement in predicting long-term mortality in both developing and verification cohorts (All P < 0.001). The actual mortality was consistent with the predicted mortality in the developing (P = 0.862) and verification (P = 0.568) cohorts. Our nomogram exhibited greater net clinical benefit than GCS and the commonly used disease severity scoring system.
Conclusion: This proposed nomogram has good performance for predicting long-term mortality among ischemic stroke patients.