ArticleFrontiers in neuroscience2022
A prediction model of clinical outcomes in prolonged disorders of consciousness: A prospective cohort study.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Decoding Upper-Limb Motor Imagery from EEG Signals: A Systematic Review of Methods and Applications.Annals of biomedical engineering · 2026Pooled 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
- Exosomes as Emerging Therapeutic Platforms in Neurological and Psychiatric Disorders.Pharmaceutical medicine · 2025Review
- Blink reflex as a prognostic indicator for patients with prolonged disorders of consciousness: a prospective case-control study.BMJ open · 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
- Eye tracking to support assessment of patients with prolonged disorder of consciousness - a case series.Journal of rehabilitation medicine · 2025Observational
- 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
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to establish and validate a prediction model for clinical outcomes in patients with prolonged disorders of consciousness (pDOC). Methods: A total of 170 patients with pDOC enrolled in our rehabilitation unit were included and divided into training ( Results: Univariate and multivariate logistic regression analyses indicated that age, diagnosis at entry, serum albumin (g/L), and pupillary reflex were the independent prognostic factors that were used to construct the nomogram. The area under the curve in the training and validation sets was 0.845 and 0.801, respectively. This nomogram model showed good calibration with good consistency between the actual and predicted probabilities of improved outcomes. The DCA demonstrated a higher net benefit in clinical decision-making compared to treating all or none. Conclusion: Several feasible, cost-effective prognostic variables that are widely available in hospitals can provide an efficient and accurate prediction model for improved clinical outcomes and support clinicians to offer suitable clinical care and decision-making to patients with pDOC and their family members.
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