Predicting Functional Dependency in Patients with Disorders of Consciousness : A TBI-Model Systems and TRACK-TBI Study
© 2023 American Neurological Association..
OBJECTIVE: It is not currently possible to predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Our objective was to fit and externally validate a prediction model for 1-year dependency in patients with DoC ≥ 2 weeks after TBI.
METHODS: We included adults with TBI enrolled in TBI Model Systems (TBI-MS) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) studies who were not following commands at rehabilitation admission or 2 weeks post-injury, respectively. We fit a logistic regression model in TBI-MS and validated it in TRACK-TBI. The primary outcome was death or dependency at 1 year post-injury, defined using the Disability Rating Scale.
RESULTS: In the TBI-MS Discovery Sample, 1,960 participants (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria, and 406 (27%) were dependent 1 year post-injury. In a TBI-MS held out cohort, the dependency prediction model's area under the receiver operating characteristic curve was 0.79 (95% CI 0.74-0.85), positive predictive value was 53% and negative predictive value was 86%. In the TRACK-TBI external validation (n = 124, age 40 [16] years, 77% male, 81% white), the area under the receiver operating characteristic curve was 0.66 (0.53, 0.79), equivalent to the standard IMPACTcore + CT score (p = 0.8).
INTERPRETATION: We developed a 1-year dependency prediction model using the largest existing cohort of patients with DoC after TBI. The sensitivity and negative predictive values were greater than specificity and positive predictive values. Accuracy was diminished in an external sample, but equivalent to the IMPACT model. Further research is needed to improve dependency prediction in patients with DoC after TBI. ANN NEUROL 2023;94:1008-1023.
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:94 |
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| Enthalten in: |
Annals of neurology - 94(2023), 6 vom: 01. Dez., Seite 1008-1023 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Snider, Samuel B [VerfasserIn] |
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Date Completed 16.11.2023 Date Revised 18.02.2024 published: Print-Electronic UpdateOf: medRxiv. 2023 Mar 15;:. - PMID 36993195 Citation Status MEDLINE |
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| doi: |
10.1002/ana.26741 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM359707467 |
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| 100 | 1 | |a Snider, Samuel B |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Predicting Functional Dependency in Patients with Disorders of Consciousness |b A TBI-Model Systems and TRACK-TBI Study |
| 264 | 1 | |c 2023 | |
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| 500 | |a Date Completed 16.11.2023 | ||
| 500 | |a Date Revised 18.02.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a UpdateOf: medRxiv. 2023 Mar 15;:. - PMID 36993195 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2023 American Neurological Association. | ||
| 520 | |a OBJECTIVE: It is not currently possible to predict long-term functional dependency in patients with disorders of consciousness (DoC) after traumatic brain injury (TBI). Our objective was to fit and externally validate a prediction model for 1-year dependency in patients with DoC ≥ 2 weeks after TBI | ||
| 520 | |a METHODS: We included adults with TBI enrolled in TBI Model Systems (TBI-MS) or Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) studies who were not following commands at rehabilitation admission or 2 weeks post-injury, respectively. We fit a logistic regression model in TBI-MS and validated it in TRACK-TBI. The primary outcome was death or dependency at 1 year post-injury, defined using the Disability Rating Scale | ||
| 520 | |a RESULTS: In the TBI-MS Discovery Sample, 1,960 participants (mean age 40 [18] years, 76% male, 68% white) met inclusion criteria, and 406 (27%) were dependent 1 year post-injury. In a TBI-MS held out cohort, the dependency prediction model's area under the receiver operating characteristic curve was 0.79 (95% CI 0.74-0.85), positive predictive value was 53% and negative predictive value was 86%. In the TRACK-TBI external validation (n = 124, age 40 [16] years, 77% male, 81% white), the area under the receiver operating characteristic curve was 0.66 (0.53, 0.79), equivalent to the standard IMPACTcore + CT score (p = 0.8) | ||
| 520 | |a INTERPRETATION: We developed a 1-year dependency prediction model using the largest existing cohort of patients with DoC after TBI. The sensitivity and negative predictive values were greater than specificity and positive predictive values. Accuracy was diminished in an external sample, but equivalent to the IMPACT model. Further research is needed to improve dependency prediction in patients with DoC after TBI. ANN NEUROL 2023;94:1008-1023 | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Temkin, Nancy R |e verfasserin |4 aut | |
| 700 | 1 | |a Barber, Jason |e verfasserin |4 aut | |
| 700 | 1 | |a Edlow, Brian L |e verfasserin |4 aut | |
| 700 | 1 | |a Giacino, Joseph T |e verfasserin |4 aut | |
| 700 | 1 | |a Hammond, Flora M |e verfasserin |4 aut | |
| 700 | 1 | |a Izzy, Saef |e verfasserin |4 aut | |
| 700 | 1 | |a Kowalski, Robert G |e verfasserin |4 aut | |
| 700 | 1 | |a Markowitz, Amy J |e verfasserin |4 aut | |
| 700 | 1 | |a Rovito, Craig A |e verfasserin |4 aut | |
| 700 | 1 | |a Shih, Shirley L |e verfasserin |4 aut | |
| 700 | 1 | |a Zafonte, Ross D |e verfasserin |4 aut | |
| 700 | 1 | |a Manley, Geoffrey T |e verfasserin |4 aut | |
| 700 | 1 | |a Bodien, Yelena G |e verfasserin |4 aut | |
| 700 | 0 | |a TRACK-TBI investigators |e verfasserin |4 aut | |
| 700 | 1 | |a Badjatia, Neeraj |e investigator |4 oth | |
| 700 | 1 | |a Duhaime, Ann-Christine |e investigator |4 oth | |
| 700 | 1 | |a Foreman, Brandon |e investigator |4 oth | |
| 700 | 1 | |a Gopinath, Shankar |e investigator |4 oth | |
| 700 | 1 | |a Grandhi, Ramesh |e investigator |4 oth | |
| 700 | 1 | |a Keene, C Dirk |e investigator |4 oth | |
| 700 | 1 | |a McCrea, Michael |e investigator |4 oth | |
| 700 | 1 | |a Merchant, Randall |e investigator |4 oth | |
| 700 | 1 | |a Mukherjee, Pratik |e investigator |4 oth | |
| 700 | 1 | |a Ngwenya, Laura B |e investigator |4 oth | |
| 700 | 1 | |a Okonkwo, David |e investigator |4 oth | |
| 700 | 1 | |a Schnyer, David |e investigator |4 oth | |
| 700 | 1 | |a Taylor, Sabrina R |e investigator |4 oth | |
| 700 | 1 | |a Yue, John |e investigator |4 oth | |
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