Common Data Elements for Disorders of Consciousness : Recommendations from the Working Group on Physiology and Big Data
© 2023. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society..
BACKGROUND: The 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.
METHODS: To 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.
RESULTS: We report the recommendations of this CDE development panel and disseminate CDEs to be used in physiologic and big data studies of patients with DoC.
CONCLUSIONS: These CDEs will support progress in the field of DoC physiologic and big data and facilitate international collaboration.
| Errataetall: |
ErratumIn: Neurocrit Care. 2024 Feb;40(1):382-383. - PMID 38057543 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:39 |
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| Enthalten in: |
Neurocritical care - 39(2023), 3 vom: 01. Dez., Seite 593-599 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Beqiri, Erta [VerfasserIn] |
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| Links: |
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| Themen: |
Big Data |
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| Anmerkungen: |
Date Completed 04.12.2023 Date Revised 29.02.2024 published: Print-Electronic ErratumIn: Neurocrit Care. 2024 Feb;40(1):382-383. - PMID 38057543 Citation Status MEDLINE |
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| doi: |
10.1007/s12028-023-01846-7 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2023. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society. | ||
| 520 | |a BACKGROUND: The 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 | ||
| 520 | |a METHODS: To 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 | ||
| 520 | |a RESULTS: We report the recommendations of this CDE development panel and disseminate CDEs to be used in physiologic and big data studies of patients with DoC | ||
| 520 | |a CONCLUSIONS: These CDEs will support progress in the field of DoC physiologic and big data and facilitate international collaboration | ||
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| 650 | 4 | |a Consciousness | |
| 650 | 4 | |a High-resolution data | |
| 650 | 4 | |a Intensive care | |
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