Development and Validation of a Risk Score for Predicting ICU Admission in Adults with New-Onset Encephalitis.

Clinical prediction rules Critical care outcomes Encephalitis Prognosis Risk assessment

Journal

Neurocritical care
ISSN: 1556-0961
Titre abrégé: Neurocrit Care
Pays: United States
ID NLM: 101156086

Informations de publication

Date de publication:
31 Jul 2024
Historique:
received: 01 03 2024
accepted: 02 07 2024
medline: 1 8 2024
pubmed: 1 8 2024
entrez: 31 7 2024
Statut: aheadofprint

Résumé

Timely intensive care unit (ICU) admission for patients with encephalitis is associated with better prognosis. Therefore, our aim was to create a risk score predicting ICU admission in adults with encephalitis, which could aid in optimal management and resource allocation. We initially identified variables that would be most predictive of ICU admission among 372 patients with encephalitis from two hospital systems in Houston, Texas (cohort 1), who met the International Encephalitis Consortium (IEC) criteria from 2005 to 2023. Subsequently, we used a binary logistic regression model to create a risk score for ICU admission, which we then validated externally using a separate cohort of patients from two hospitals in Baltimore, Maryland (cohort 2), who met the IEC criteria from 2006 to 2022. Of 634 patients with encephalitis, 255 (40%) were admitted to the ICU, including 45 of 113 (39.8%) patients with an autoimmune cause, 100 of 272 (36.7%) with an infectious cause, and 110 of 249 (44.1%) with an unknown cause (p = 0.225). After conducting a multivariate analysis in cohort 1, we found that the presence of focal neurological signs, new-onset seizure, a Full Outline of Unresponsiveness score ≤ 14, leukocytosis, and a history of chronic kidney disease at admission were associated with an increased risk of ICU admission. The resultant clinical score for predicting ICU admission had an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% confidence interval [CI] 0.72-0.82, p < 0.001). Patients were classified into three risk categories for ICU admission: low risk (score 0, 12.5%), intermediate risk (scores 1-5, 49.5%), and high risk (scores 6-8, 87.5%). External validation in cohort 2 yielded an AUROC of 0.76 (95% CI 0.69-0.83, p < 0.001). ICU admission is common in patients with encephalitis, regardless of etiology. Our risk score, encompassing neurologic and systemic factors, may aid physicians in decisions regarding intensity of care for adult patients with encephalitis upon hospital admission.

Sections du résumé

BACKGROUND BACKGROUND
Timely intensive care unit (ICU) admission for patients with encephalitis is associated with better prognosis. Therefore, our aim was to create a risk score predicting ICU admission in adults with encephalitis, which could aid in optimal management and resource allocation.
METHODS METHODS
We initially identified variables that would be most predictive of ICU admission among 372 patients with encephalitis from two hospital systems in Houston, Texas (cohort 1), who met the International Encephalitis Consortium (IEC) criteria from 2005 to 2023. Subsequently, we used a binary logistic regression model to create a risk score for ICU admission, which we then validated externally using a separate cohort of patients from two hospitals in Baltimore, Maryland (cohort 2), who met the IEC criteria from 2006 to 2022.
RESULTS RESULTS
Of 634 patients with encephalitis, 255 (40%) were admitted to the ICU, including 45 of 113 (39.8%) patients with an autoimmune cause, 100 of 272 (36.7%) with an infectious cause, and 110 of 249 (44.1%) with an unknown cause (p = 0.225). After conducting a multivariate analysis in cohort 1, we found that the presence of focal neurological signs, new-onset seizure, a Full Outline of Unresponsiveness score ≤ 14, leukocytosis, and a history of chronic kidney disease at admission were associated with an increased risk of ICU admission. The resultant clinical score for predicting ICU admission had an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% confidence interval [CI] 0.72-0.82, p < 0.001). Patients were classified into three risk categories for ICU admission: low risk (score 0, 12.5%), intermediate risk (scores 1-5, 49.5%), and high risk (scores 6-8, 87.5%). External validation in cohort 2 yielded an AUROC of 0.76 (95% CI 0.69-0.83, p < 0.001).
CONCLUSIONS CONCLUSIONS
ICU admission is common in patients with encephalitis, regardless of etiology. Our risk score, encompassing neurologic and systemic factors, may aid physicians in decisions regarding intensity of care for adult patients with encephalitis upon hospital admission.

Identifiants

pubmed: 39085505
doi: 10.1007/s12028-024-02063-6
pii: 10.1007/s12028-024-02063-6
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.

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Auteurs

Ralph Habis (R)

Department of Neurology, Johns Hopkins Encephalitis Center, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Meyer 6-160, Baltimore, MD, 21287, USA.

Ashley Heck (A)

Department of Medicine, Section of Infectious Disease, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA.

Paris Bean (P)

Department of Medicine, Section of Infectious Disease, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA.

John Probasco (J)

Department of Neurology, Johns Hopkins Encephalitis Center, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Meyer 6-160, Baltimore, MD, 21287, USA.

Romergryko G Geocadin (RG)

Department of Neurology, Johns Hopkins Encephalitis Center, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Meyer 6-160, Baltimore, MD, 21287, USA.
Departments of Neurosurgery and Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Rodrigo Hasbun (R)

Department of Medicine, Section of Infectious Disease, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA.

Arun Venkatesan (A)

Department of Neurology, Johns Hopkins Encephalitis Center, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Meyer 6-160, Baltimore, MD, 21287, USA. avenkat2@jhmi.edu.

Classifications MeSH