A Comparison of Satisfaction With Life and the Glasgow Outcome Scale–Extended After Traumatic Brain Injury: An Analysis of the TRACK-TBI Pilot Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relationship between satisfaction with life (SWL) and functional outcome after traumatic brain injury (TBI). SETTING AND PARTICIPANTS: The Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot study (TRACK-TBI Pilot) enrolled patients at 3 US Level I trauma centers within 24 hours of TBI. DESIGN: Patients were grouped by outcome measure concordance (good-recovery/good-satisfaction, impaired-recovery/impaired-satisfaction) and discordance (good-recovery/impaired-satisfaction, impaired-recovery/good-satisfaction). Logistic regression was utilized to determine predictors of discordance. MAIN MEASURES: Functional outcome: Glasgow Outcome Scale-Extended (GOSE); SWL: Satisfaction with Life Scale (SWLS). RESULTS: Of the 586 enrolled subjects, 298 had completed both outcome measures at 6-month follow-up; the correlation between GOSE and SWLS was 0.380. Patients with impaired-recovery (GOSE < 7)/impaired-satisfaction (SWLS < 20) were more likely to have mild TBI (83% vs 62%, P = .012), baseline depression (42% vs 15%, P < .0001), and 6-month depression (59% vs 21%, P < .0001) when compared with patients with impaired-recovery/good-satisfaction. Patients with good-recovery/impaired-satisfaction were more likely to have baseline depression (31% vs 13%, P < .0001) and 6-month depression (33% vs 6%, P < .0001) compared with good-recovery/good-satisfaction. CONCLUSION: Correlation between SWL and functional outcome was not strong, and depression may modulate the association. Future research should account for functional, mental health, and patient-centered outcomes when assessing TBI recovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".