ArticleAging2022
A dynamic model to predict long-term outcomes in patients with prolonged disorders of consciousness.
Article in Aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prediction models for functional outcomes in prolonged disorders of consciousness: a systematic review and meta-analysis.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Predicting outcome in disorders of consciousness: A mega-analysis.Annals of clinical and translational neurology · 2024Pooled it
- The autonomic response following taVNS predicts changes in level of consciousness in DoC patients.Scientific reports · 2025Trial
- Influence of High-Frequency Repetitive Transcranial Magnetic Stimulation on Neurobehavioral and Electrophysiology in Patients with Disorders of Consciousness.Neural plasticity · 2022Trial
- Extracerebral Normalization ofNeurocritical care · 2025Article
- Development of a nomogram for predicting the outcome in patients with prolonged disorders of consciousness based on the multimodal evaluative information.BMC neurology · 2025Article
- Electroencephalographic differences between waking and sleeping periods in patients with prolonged disorders of consciousness at different levels of consciousness.Frontiers in human neuroscience · 2025Article
- Natural course and predictors of consciousness recovery in children with prolonged disorder of consciousness.Scientific reports · 2024Article
- Prognosis of patients with prolonged disorders of consciousness after brain injury: a longitudinal cohort study.Frontiers in public health · 2024Article
- Establishment and validation of a bad outcomes prediction model based on EEG and clinical parameters in prolonged disorder of consciousness.Frontiers in human neuroscience · 2024Article
- Long-Term Outcomes among Patients with Prolonged Disorders of Consciousness.Brain sciences · 2023Article
- Transcutaneous auricular vagus nerve stimulation in the treatment of disorders of consciousness: mechanisms and applications.Frontiers in neuroscience · 2023Review
- A prediction model of clinical outcomes in prolonged disorders of consciousness: A prospective cohort study.Frontiers in neuroscience · 2022Article
- Pain perception and attitudes toward life-sustaining treatment in pediatric patients with disorders of consciousness: a survey of Chinese healthcare professionals.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeIt is important to predict the prognosis of patients with prolonged disorders of consciousness (DOC). This study established and validated a nomogram and corresponding web-based calculator to predict outcomes for patients with prolonged DOC.
methodsAll data were obtained from the First Affiliated Hospital of Nanchang University and the Shangrao Hospital of Traditional Chinese Medicine. Predictive variables were identified by univariate and multiple logistic regression analyses. Receiver operating characteristic curves, calibration curves, and a decision curve analysis (DCA) were utilized to assess the predictive accuracy, discriminative ability, and clinical utility of the model, respectively.
resultsIndependent prognostic factors, such as age, Glasgow coma scale score, state of consciousness, and brainstem auditory-evoked potential grade were integrated into a nomogram. The model demonstrated good discrimination in the training and validation cohorts, with area-under-the-curve values of 0.815 (95% confidence interval [CI]: 0.748-0.882) and 0.805 (95% CI: 0.727-0.883), respectively. The calibration plots and DCA demonstrated good model performance and clear clinical benefits in both cohorts.
conclusionsBased on our nomogram, we developed an effective, simple, and accurate model of a web-based calculator that may help individualize healthcare decision-making. Further research is warranted to optimize the system and update the predictors.
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