Francesco Brigo1, Gianni Turcato2, Giada Giovannini3,4, Stefano Meletti5,6, Simona Lattanzi7, Niccolò Orlandi3,8, Giulia Turchi3, Arian Zaboli9. 1. Department of Neurology, Hospital of Merano-Meran (SABES-ASDAA), Merano-Meran, Italy. 2. Department of Internal Medicine, Hospital of Santorso, AULSS-7), Santorso, Italy. 3. Neurology Department, Azienda Ospedaliera-Universitaria di Modena, Modena, Italy. 4. Clinical and Experimental Medicine, University of Modena and Reggio-Emilia, Modena, Italy. 5. Neurology Department, Azienda Ospedaliera-Universitaria di Modena, Modena, Italy. stefano.meletti@unimore.it. 6. Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio-Emilia, Modena and Reggio-Emilia, Italy. stefano.meletti@unimore.it. 7. Neurological Clinic, Department of Experimental and Clinical Medicine, Marche Polytechnic University, Ancona, Italy. 8. Department of Biomedical, Metabolic, and Neural Sciences, University of Modena and Reggio-Emilia, Modena and Reggio-Emilia, Italy. 9. Department of Emergency Medicine, Hospital of Merano-Meran (SABES-ASDAA), Merano-Meran, Italy.
Abstract
BACKGROUND: To develop a nomogram using the parameters of the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) and to evaluate its accuracy compared with the EMSE alone in the prediction of 30-day mortality in patients with status epilepticus (SE). METHODS: We included a cohort of patients with SE aged ≥ 21 years admitted from 2013 to 2021. Regression coefficients from the multivariable logistic regression model were used to generate a nomogram predicting the risk of 30-day mortality. Discrimination of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUCROC) with 95% confidence interval. Internal validation was performed by bootstrap resampling. RESULTS: Among 698 patients with SE, the 30-day mortality rate was 28.9% (202 of 698). On the multivariable analysis, all EMSE parameters (except for the comorbidity group including metastatic solid tumor or AIDS) were associated with a significantly higher risk of 30-day mortality and were included in the nomogram. The discriminatory capability of the nomogram with bootstrap resampling (5000 resamples) had an AUCROC of 0.830 (95% confidence interval 0.798-0.862). Conversely, the AUCROC of the EMSE was 0.777 (95% confidence interval 0.742-0.813). Thus, the probability that a patient who died within 30 days from SE had a higher score than a patient who survived was 83%, indicating good discriminatory power of the nomogram. Conversely, the risk predicted using the EMSE alone was 77%. The nomogram was well calibrated. CONCLUSIONS: A nomogram based on EMSE parameters appears superior to the EMSE in predicting the risk of 30-day mortality after SE. The discrimination and calibration of the nomogram shows a better predictive accuracy than the EMSE alone.
BACKGROUND: To develop a nomogram using the parameters of the Epidemiology-Based Mortality Score in Status Epilepticus (EMSE) and to evaluate its accuracy compared with the EMSE alone in the prediction of 30-day mortality in patients with status epilepticus (SE). METHODS: We included a cohort of patients with SE aged ≥ 21 years admitted from 2013 to 2021. Regression coefficients from the multivariable logistic regression model were used to generate a nomogram predicting the risk of 30-day mortality. Discrimination of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUCROC) with 95% confidence interval. Internal validation was performed by bootstrap resampling. RESULTS: Among 698 patients with SE, the 30-day mortality rate was 28.9% (202 of 698). On the multivariable analysis, all EMSE parameters (except for the comorbidity group including metastatic solid tumor or AIDS) were associated with a significantly higher risk of 30-day mortality and were included in the nomogram. The discriminatory capability of the nomogram with bootstrap resampling (5000 resamples) had an AUCROC of 0.830 (95% confidence interval 0.798-0.862). Conversely, the AUCROC of the EMSE was 0.777 (95% confidence interval 0.742-0.813). Thus, the probability that a patient who died within 30 days from SE had a higher score than a patient who survived was 83%, indicating good discriminatory power of the nomogram. Conversely, the risk predicted using the EMSE alone was 77%. The nomogram was well calibrated. CONCLUSIONS: A nomogram based on EMSE parameters appears superior to the EMSE in predicting the risk of 30-day mortality after SE. The discrimination and calibration of the nomogram shows a better predictive accuracy than the EMSE alone.