Evidence map›Paper›PMID 37704934›Full record

ArticleNeurocritical care2023

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Physiology and Big Data.

Erta Beqiri, Neeraj Badjatia, Ari Ercole, Brandon Foreman, Peter Hu, Xiao Hu, Kerri LaRovere, Geert Meyfroidt, Dick Moberg, Chiara Robba and 5 more

Erratum issuedAbstract read
In one paragraph

Article in Neurocritical care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Erta BeqiriBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Neeraj BadjatiaProgram in Trauma, Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA.
Ari ErcoleDivision of Anaesthesia, University of Cambridge, Cambridge, UK.
Brandon ForemanUniversity of Cincinnati, Cincinnati, OH, USA.
Peter HuProgram in Trauma, Departments of Anesthesiology and Surgery, University of Maryland School of Medicine, Baltimore, MD, USA.
Xiao HuSchool of Nursing, Emory University, Atlanta, GA, USA.
Kerri LaRovereDepartment of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
Geert MeyfroidtDepartment and Laboratory of Intensive Care Medicine, University Hospitals Leuven and KU Leuven, Louvain, Belgium.
Dick MobergMoberg Analytics, Inc, Philadelphia, PA, USA.
Chiara RobbaIstituto di Ricovero e Cura a Carattere Scientifico Policlinico San Martino, Genoa, Italy.
Eric S RosenthalDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Peter SmielewskiBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Mark S WainwrightDivision of Pediatric Neurology, Seattle Children's Hospital, University of Washington, Seattle, WA, USA.
Soojin ParkDepartments of Neurology and Biomedical Informatics, Columbia University Vagelos College of Physicians and Surgeons, NewYork-Presbyterian Hospital, New York, NY, USA. Sp3291@cumc.columbia.edu.ORCID 0000-0002-3688-7307
Curing Coma Campaign and its Contributing Members

Funding

Bridge2AI: Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AIOT2OD032701 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI BIHORAC, AZRA, CLERMONT, GILLES · 2022 to 2025
$24.6M
Machine Learning to Optimize Management of Acute HydrocephalusR01NS131606 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Soojin Park · 2023 to 2026
$2.6M
ContinuOuS Monitoring Tool for Delayed Cerebral IsChemia (COSMIC)R01NS129760 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Soojin Park · 2023 to 2026
$2.5M
Real-Time Prediction of Delayed Cerebral Ischemia after Subarachnoid HemorrhageK23NS105950 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI ROSENTHAL, ERIC S. · 2018 to 2022
$1.0M
Medical Research Council MR N013433-1NIH HHS OT2 OD032701NIH HHS OT2 OD032701-01NIH HHS R01NS129760NIH HHS R01NS131606NINDS NIH HHS K23 NS105950NINDS NIH HHS R01 NS129760NINDS NIH HHS R01 NS131606
6 · The paper itself

Abstract

backgroundThe implementation of multimodality monitoring in the clinical management of patients with disorders of consciousness (DoC) results in physiological measurements that can be collected in a continuous and regular fashion or even at waveform resolution. Such data are considered part of the "Big Data" available in intensive care units and are potentially suitable for health care-focused artificial intelligence research. Despite the richness in content of the physiological measurements, and the clinical implications shown by derived metrics based on those measurements, they have been largely neglected from previous attempts in harmonizing data collection and standardizing reporting of results as part of common data elements (CDEs) efforts. CDEs aim to provide a framework for unifying data in clinical research and help in implementing a systematic approach that can facilitate reliable comparison of results from clinical studies in DoC as well in international research collaborations.

methodsTo address this need, the Neurocritical Care Society's Curing Coma Campaign convened a multidisciplinary panel of DoC "Physiology and Big Data" experts to propose CDEs for data collection and reporting in this field.

resultsWe report the recommendations of this CDE development panel and disseminate CDEs to be used in physiologic and big data studies of patients with DoC.

conclusionsThese CDEs will support progress in the field of DoC physiologic and big data and facilitate international collaboration.

Indexed as

Biomedical ResearchCommon Data ElementsArtificial IntelligenceBig DataConsciousness DisordersHumansBig DataComaCommon data elementsConsciousnessHigh-resolution dataIntensive carePhysiologic data

Identifiers

PMID37704934
PMCPMC10782548

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.