Functional Status Score for the ICU: An International Clinimetric Analysis of Validity, Responsiveness, and Minimal Important Difference
Bibliographic record
Abstract
OBJECTIVES: To evaluate the internal consistency, validity, responsiveness, and minimal important difference of the Functional Status Score for the ICU, a physical function measure designed for the ICU. DESIGN: Clinimetric analysis. SETTINGS: Five international datasets from the United States, Australia, and Brazil. PATIENTS: Eight hundred nineteen ICU patients. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Clinimetric analyses were initially conducted separately for each data source and time point to examine generalizability of findings, with pooled analyses performed thereafter to increase power of analyses. The Functional Status Score for the ICU demonstrated good to excellent internal consistency. There was good convergent and discriminant validity, with significant and positive correlations (r = 0.30-0.95) between Functional Status Score for the ICU and other physical function measures, and generally weaker correlations with nonphysical measures (|r| = 0.01-0.70). Known group validity was demonstrated by significantly higher Functional Status Score for the ICU scores among patients without ICU-acquired weakness (Medical Research Council sum score, ≥ 48 vs < 48) and with hospital discharge to home (vs healthcare facility). Functional Status Score for the ICU at ICU discharge predicted post-ICU hospital length of stay and discharge location. Responsiveness was supported via increased Functional Status Score for the ICU scores with improvements in muscle strength. Distribution-based methods indicated a minimal important difference of 2.0-5.0. CONCLUSIONS: The Functional Status Score for the ICU has good internal consistency and is a valid and responsive measure of physical function for ICU patients. The estimated minimal important difference can be used in sample size calculations and in interpreting studies comparing the physical function of groups of ICU patients.
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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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".