Trial reportCNS neuroscience & therapeutics2023
Development and validation of a nomogram to provide individualized predictions of functional outcomes in patients with convulsive status epilepticus at 3 months: The modified END-IT tool.
Trial report in CNS neuroscience & therapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Development and validation of a nomogram to provide individualized predictions of functional outcomes in patients with convulsive status epilepticus at 3 months: The modified END-IT tool.CNS neuroscience & therapeutics · 2023Trial
- Outcomes and risk factors for functional prognosis at 3 months after intravenous thrombolysis with r-tPA in patients with acute ischemic stroke: a retrospective cohort study.Thrombosis journal · 2025Article
- Hypoalbuminemia in status epilepticus is a biomarker of short- and long-term mortality: A 9-year cohort study.European journal of neurology · 2025Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
aimsThe prediction of outcomes in convulsive status epilepticus (CSE) remains a constant challenge. The Encephalitis-Nonconvulsive Status Epilepticus-Diazepam Resistance-Image Abnormalities-Tracheal Intubation (END-IT) score was a useful tool for predicting the functional outcomes of CSE patients, excluding cerebral hypoxia patients. With further understanding of CSE, and in view of the deficiencies of END-IT itself, we consider it necessary to modify the prediction tool.
methodsThe prediction model was designed from a cohort of CSE patients from Xijing Hospital (China), between 2008 and 2020. The enrolled subjects were randomly divided into training cohort and validation cohort as a ratio of 2:1. The logistic regression analysis was performed to identify the predictors and construct the nomogram. The performance of the nomogram was assessed by calculating the concordance index, and creating calibration plots to check the consistency between the predicted probabilities of poor prognosis and the actual outcomes of CSE.
resultsThe training cohort included 131 patients and validation cohort included 66 patients. Variables included in the nomogram were age, etiology of CSE, non-convulsive SE, mechanical ventilation, abnormal albumin level at CSE onset. The concordance index of the nomogram in the training and validation cohorts was 0.853 (95% CI, 0.787-0.920) and 0.806 (95% CI, 0.683-0.923), respectively. The calibration plots showed an adequate consistency between the reported and predicted unfavorable outcomes of patients with CSE at 3 months after discharge.
conclusionsA nomogram for predicting the individualized risks of poor functional outcomes in CSE was constructed and validated, which has been an important modification of END-IT score.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.