Psychometric evaluation of EQ-5D-5L in OHCA survivors from the TTM2 trial: a post hoc analysis
Bibliographic record
Abstract
Aims Our aim was to investigate the psychometric properties of the health assessment instrument EQ-5D-5L in OHCA survivors. Methods We included survivors from the Targeted Hypothermia versus Targeted Normothermia after OHCA (TTM2) trial, who completed EQ-5D-5L at 6 months. Confirmatory factor analysis was used to evaluate the hypothesised unidimensional latent structure of EQ level sum score (EQ LSS), summarizing scores across Mobility , Self-care , Usual activities , Pain/discomfort , and Anxiety/depression . Differential item functioning was evaluated for age. We examined internal consistency and precision for the EQ LSS. We evaluated construct validity of EQ LSS, EQ value and EQ VAS, using the modified Rankin Scale and Montreal Cognitive Assessment, representing functional outcome and cognitive function—two common health challenges experienced by OHCA survivors. Results 783 of 939 (84%) eligible survivors were included. Confirmatory factor analysis showed good model fit and strong factor loadings for all dimensions (0.61–0.90). We observed a significant but negligible effect of age on Mobility (β = 0.29, p < 0.001, ΔR 2 = 0.019). Internal consistency was 0.88. The floor effect was 35%. Survivors with more functional dependency and/or cognitive problems reported significantly worse health by EQ LSS, EQ value, and EQ VAS (all, p < 0.001). Conclusion The psychometric properties of EQ LSS support its use to measure health status in OHCA research. The strong association between health and functional dependency indicate robust and comparable construct validity for EQ LSS, EQ value, and EQ VAS in this sample.
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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 | 0.023 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".