Evidence map›Paper›PMID 32919461›Full record

ArticleBMC neurology2020

The misdiagnosis of prolonged disorders of consciousness by a clinical consensus compared with repeated coma-recovery scale-revised assessment.

Jing Wang, Xiaohua Hu, Zhouyao Hu, Ziwei Sun, Steven Laureys, Haibo Di

Registry-linked trialOpen access · goldAbstract readComparative Study
In one paragraph

Article in BMC neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04139239 (Diagnostic Accuracy of the Vegetative and Minimally Conscious State), which is not on this map. Cited by 64 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 4 pooled it
7.6field-weighted citation impact, top 2% 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.

NCT04139239 completednot on this map

Diagnostic Accuracy of the Vegetative and Minimally Conscious State: Clinical Consensus Versus Standardized Neurobehavioral Assessment

TypeobservationalSponsorHangzhou Normal UniversityRan2017 to 2019Enrolled150ConditionsDisorder of Consciousness, Minimally Conscious StateArmsComa Recovery Scale-revision
3 · Its place in the literature

Who cites it

64 citing papers in PubMed, 4 syntheses or guidelines pooled it, 135 citations in OpenAlex.

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4 more citing papers are in PubMed but not listed here.

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

6 authors at 2 institutions in 1 country.

Jing WangInternational Unresponsive Wakefulness Syndrome and Consciousness Science Institute, Hangzhou Normal University, Hangzhou, 310036, China. wangjingwyl@aliyun.com.ORCID http://orcid.org/0000-0003-2445-4966
Xiaohua HuRehabilitation Center for Brain Damage, Wujing Hospital of Hangzhou City, Hangzhou, China.
Zhouyao HuInternational Unresponsive Wakefulness Syndrome and Consciousness Science Institute, Hangzhou Normal University, Hangzhou, 310036, China.
Ziwei SunInternational Unresponsive Wakefulness Syndrome and Consciousness Science Institute, Hangzhou Normal University, Hangzhou, 310036, China.
Steven LaureysComa Science Group, GIGA Consciousness, University and University Hospital of Liège, Liège, Belgium.
Haibo DiInternational Unresponsive Wakefulness Syndrome and Consciousness Science Institute, Hangzhou Normal University, Hangzhou, 310036, China. dihaibo19@aliyun.com.
Hangzhou Normal University · CNHangzhou Red Cross Hospital · CN

Funding

Regulation of hepatic stellate cells in development and alcoholic liver injuryR00AA020514 · NIAAA · CINCINNATI CHILDRENS HOSP MED CTR · PI YIN, CHUNYUE · 2014 to 2016
$722k
Regulation of hepatic stellate cells in development and alcoholic liver injuryK99AA020514 · NIAAA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI YIN, CHUNYUE · 2011 to 2012
$179k
NIAAA NIH HHS K99 AA020514NIAAA NIH HHS R00 AA020514
6 · The paper itself

Abstract

backgroundPrevious studies have shown that a single Coma-Recovery Scale-Revision (CRS-R) assessment can identify high rates of misdiagnosis by clinical consensus. The aim of this study was to investigate the proportion of misdiagnosis by clinical consensus compared to repeated behavior-scale assessments in patients with prolonged disorders of consciousness (DOC).

methodsPatients with prolonged DOC during hospitalization were screened by clinicians, and the clinicians formed a clinical-consensus diagnosis. Trained professionals used the CRS-R to evaluate the consciousness levels of the enrolled patients repeatedly (≥5 times) within a week. Based on the repeated evaluation results, the enrolled patients with prolonged DOC were divided into unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and emergence from MCS (EMCS). Finally, the relationship between the results of the CRS-R and the clinical consensus were analyzed.

resultsIn this study, 137 patients with a clinical-consensus diagnosis of prolonged DOC were enrolled. It was found that 24.7% of patients with clinical UWS were actually in MCS after a single CRS-R behavior evaluation, while the repeated CRS-R evaluation results showed that the proportion of misdiagnosis of MCS was 38.2%. A total of 16.7% of EMCS patients were misdiagnosed with clinical MCS, and 1.1% of EMCS patients were misdiagnosed with clinical UWS.

conclusionsThe rate of the misdiagnosis by clinical consensus is still relatively high. Therefore, clinicians should be aware of the importance of the bedside CRS-R behavior assessment and should apply the CRS-R tool in daily procedures.

trial registrationClinicalTrials.gov ID: NCT04139239 ; Registered 24 October 2019 - Retrospectively registered.

Indexed as

Clinical Decision-MakingConsciousnessConsciousness DisordersPersistent Vegetative StateAdultAgedAged, 80 and overConsensusDiagnostic ErrorsFemaleHumansMaleMiddle AgedWakefulnessYoung AdultComa-recovery scale-revisedDisorders of consciousnessMinimally conscious stateMisdiagnosisUnresponsive wakefulness syndrome

Identifiers

PMID32919461
PMCPMC7488705
OpenAlexW3085586288

What OpenQuestion holds

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Registered trials

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.