Evidence map›Paper›PMID 39085505›Full record

ArticleNeurocritical care2025

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

Ralph Habis, Ashley Heck, Paris Bean, John Probasco, Romergryko G Geocadin, Rodrigo Hasbun, Arun Venkatesan

Abstract readValidation Study
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In one paragraph

Article in Neurocritical care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ralph HabisDepartment of Neurology, Johns Hopkins Encephalitis Center, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Meyer 6-160, Baltimore, MD, 21287, USA.
Ashley HeckDepartment of Medicine, Section of Infectious Disease, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA.
Paris BeanDepartment of Medicine, Section of Infectious Disease, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA.
John ProbascoDepartment 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 GeocadinDepartment of Neurology, Johns Hopkins Encephalitis Center, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Meyer 6-160, Baltimore, MD, 21287, USA.
Rodrigo HasbunDepartment of Medicine, Section of Infectious Disease, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA.
Arun VenkatesanDepartment 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.ORCID 0000-0002-9335-7361

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTimely 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.

methodsWe 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.

resultsOf 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).

conclusionsICU 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.

Indexed as

EncephalitisIntensive Care UnitsPatient AdmissionAdultAgedFemaleHumansMaleMiddle AgedRisk AssessmentYoung AdultClinical prediction rulesCritical care outcomesEncephalitisPrognosisRisk assessment

Identifiers

PMID39085505

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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.