학술논문
Prognostication in Acute Neurological Emergencies.
Document Type
Academic Journal
Author
Sloane KL; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania 19104, USA. Electronic address: Kelly.sloane@pennmedicine.upenn.edu.; Miller JJ; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA. Electronic address: Jmiller30@mgh.harvard.edu.; Piquet A; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, University of Colorado, Aurora, CO, USA. Electronic address: amanda.piquet@CUAnschutz.edu.; Edlow BL; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA. Electronic address: bedlow@mgh.harvard.edu.; Rosenthal ES; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA. Electronic address: erosenthal@mgh.harvard.edu.; Singhal AB; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA. Electronic address: asinghal@partners.org.
Source
Publisher: Saunders Country of Publication: United States NLM ID: 9111633 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-8511 (Electronic) Linking ISSN: 10523057 NLM ISO Abbreviation: J Stroke Cerebrovasc Dis Subsets: MEDLINE
Subject
Language
English
Abstract
Background: For patients with acute, serious neurological conditions presenting to the emergency department (ED), prognostication is typically based on clinical experience, scoring systems and patient co-morbidities. Because estimating a poor prognosis influences caregiver decisions to withdraw life-sustaining therapy, we investigated the consistency of prognostication across a spectrum of neurology physicians.
Methods: Five acute neurological presentations (2 with large hemispheric infarction; 1 with brainstem infarction, 1 with lobar hemorrhage, and 1 with hypoxic-ischemic encephalopathy) were selected for a department-wide prognostication simulation exercise. All had presented to our tertiary care hospital's ED, where a poor outcome was predicted by the ED neurology team within 24 hours of onset. Relevant clinical, laboratory and imaging data available before ED prognostication were presented on a web-based platform to 120 providers blinded to the actual outcome. The provider was requested to rank-order, from most to least likely, the predicted 90-day modified Rankin Scale (mRS) score. To determine the accuracy of individual outcome predictions we compared the patient's the actual 90-day mRS score to highest ranked predicted mRS score. Additionally, the group's "weighted" outcomes, accounting for the entire spectrum of mRS scores ranked by all respondents, were compared to the actual outcome for each case. Consistency was compared between pre-specified provider roles: neurology trainees versus faculty; non-vascular versus vascular faculty.
Results: Responses ranged from 106-110 per case. Individual predictions were highly variable, with predictions matching the actual mRS scores in as low as 2% of respondents in one case and 95% in another case. However, as a group, the weighted outcome matched the actual mRS score in 3 of 5 cases (60%). There was no significant difference between subgroups based on expertise (stroke/neurocritical care versus other) or experience (faculty versus trainee) in 4 of 5 cases.
Conclusion: Acute neuro-prognostication is highly variable and often inaccurate among neurology providers. Significant differences are not attributable to experience or subspecialty expertise. The mean outcome prediction from group of providers ("the wisdom of the crowd") may be superior to that of individual providers.
(Copyright © 2021 Elsevier Inc. All rights reserved.)
Methods: Five acute neurological presentations (2 with large hemispheric infarction; 1 with brainstem infarction, 1 with lobar hemorrhage, and 1 with hypoxic-ischemic encephalopathy) were selected for a department-wide prognostication simulation exercise. All had presented to our tertiary care hospital's ED, where a poor outcome was predicted by the ED neurology team within 24 hours of onset. Relevant clinical, laboratory and imaging data available before ED prognostication were presented on a web-based platform to 120 providers blinded to the actual outcome. The provider was requested to rank-order, from most to least likely, the predicted 90-day modified Rankin Scale (mRS) score. To determine the accuracy of individual outcome predictions we compared the patient's the actual 90-day mRS score to highest ranked predicted mRS score. Additionally, the group's "weighted" outcomes, accounting for the entire spectrum of mRS scores ranked by all respondents, were compared to the actual outcome for each case. Consistency was compared between pre-specified provider roles: neurology trainees versus faculty; non-vascular versus vascular faculty.
Results: Responses ranged from 106-110 per case. Individual predictions were highly variable, with predictions matching the actual mRS scores in as low as 2% of respondents in one case and 95% in another case. However, as a group, the weighted outcome matched the actual mRS score in 3 of 5 cases (60%). There was no significant difference between subgroups based on expertise (stroke/neurocritical care versus other) or experience (faculty versus trainee) in 4 of 5 cases.
Conclusion: Acute neuro-prognostication is highly variable and often inaccurate among neurology providers. Significant differences are not attributable to experience or subspecialty expertise. The mean outcome prediction from group of providers ("the wisdom of the crowd") may be superior to that of individual providers.
(Copyright © 2021 Elsevier Inc. All rights reserved.)