Evidence map›Paper›PMID 34132473›Full record

Observational studyCNS neuroscience & therapeutics2021

Encephalopathy at admission predicts adverse outcomes in patients with SARS-CoV-2 infection.

Lei Tang, Shixin Liu, Yanhe Xiao, Thi My Linh Tran, Ji Whae Choi, Jing Wu, Kasey Halsey, Raymond Y Huang, Jerrold Boxerman, Sohil H Patel and 12 more

Open access · goldAbstract readMulticenter StudyObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in CNS neuroscience & therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 35% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Observational
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

22 authors at 7 institutions in 2 countries.

Lei TangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Shixin LiuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Yanhe XiaoXiangya School of Medicine, Central South University, Changsha, China.
Thi My Linh TranDepartment of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Ji Whae ChoiDepartment of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Jing WuDepartment of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China.
Kasey HalseyDepartment of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Raymond Y HuangDepartment of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Jerrold BoxermanDepartment of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Sohil H PatelDepartment of Radiology, University of Virginia, Charlottesville, VA, USA.
David KungDepartment of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Renyu LiuDepartment of Anaesthesiology and critical care medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Michael D FeldmanDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Daniel D DanoskiDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Wei-Hua LiaoDepartment of Radiology, Xiangya Hospital, Central South University, Changsha, China.
Scott E KasnerDepartment of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Tao LiuDepartment of Biostatistics and Public Health, Brown University, Providence, RI, USA.
Bo XiaoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Paul J ZhangDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Michael ReznikDepartment of Neurology, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Harrison X BaiDepartment of Diagnostic Imaging, Warren Alpert Medical School of Brown University, Providence, RI, USA.
Li YangDepartment of Neurology, The Second Xiangya Hospital, Central South University, Changsha, China.
Brown University · USHospital of the University of Pennsylvania · USCentral South University · CNBrigham and Women's Hospital · USSecond Xiangya Hospital of Central South University · CNUniversity of Virginia · USXiangya Hospital Central South University · CN

Funding

Deep learning for renal tumor characterizationR03CA249554 · NCI · RHODE ISLAND HOSPITAL · PI BAI, HARRISON · 2020 to 2021
$162k
Amazon Web Service for the COVID-19 Diagnostic Development InitiativeBrown University COVID-19 seed grant GR399196Hunan Natural Science Foundation under Award 2018JJ3709Hunan Natural Science Foundation under Award GR399196National Cancer Institute (NCI) of the National Institutes of Health under Award R03CA249554National Natural Science Foundation of China grant under Award 8181101287National Natural Science Foundation of China grant under Award 81971696Research Scholar Grant by RSNA Research & Education Foundation
6 · The paper itself

Abstract

aimsTo determine if neurologic symptoms at admission can predict adverse outcomes in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

methodsElectronic medical records of 1053 consecutively hospitalized patients with laboratory-confirmed infection of SARS-CoV-2 from one large medical center in the USA were retrospectively analyzed. Univariable and multivariable Cox regression analyses were performed with the calculation of areas under the curve (AUC) and concordance index (C-index). Patients were stratified into subgroups based on the presence of encephalopathy and its severity using survival statistics. In sensitivity analyses, patients with mild/moderate and severe encephalopathy (defined as coma) were separately considered.

resultsOf 1053 patients (mean age 52.4 years, 48.0% men [n = 505]), 35.1% (n = 370) had neurologic manifestations at admission, including 10.3% (n = 108) with encephalopathy. Encephalopathy was an independent predictor for death (hazard ratio [HR] 2.617, 95% confidence interval [CI] 1.481-4.625) in multivariable Cox regression. The addition of encephalopathy to multivariable models comprising other predictors for adverse outcomes increased AUCs (mortality: 0.84-0.86, ventilation/ intensive care unit [ICU]: 0.76-0.78) and C-index (mortality: 0.78 to 0.81, ventilation/ICU: 0.85-0.86). In sensitivity analyses, risk stratification survival curves for mortality and ventilation/ICU based on severe encephalopathy (n = 15) versus mild/moderate encephalopathy (n = 93) versus no encephalopathy (n = 945) at admission were discriminative (p < 0.001).

conclusionsEncephalopathy at admission predicts later progression to death in SARS-CoV-2 infection, which may have important implications for risk stratification in clinical practice.

Indexed as

AdultAgedBrain DiseasesCohort StudiesCOVID-19FemaleHumansMaleMiddle AgedPatient AdmissionPredictive Value of TestsRetrospective StudiesCOVID-19encephalopathyneurologic symptomsSARS-CoV-2

Identifiers

PMID34132473
PMCPMC8444722
OpenAlexW3167074647

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.