Baseline Dependency of Minimal Clinically Important Improvement
Bibliographic record
Abstract
BACKGROUND: Minimal clinically important improvement (MCII) is the smallest outcome measure change important to patients. Research suggests that MCII is dependent on patients' baseline functional status measures. OBJECTIVE: The purposes of this study were: (1) to confirm whether MCII is dependent on patients' admission scores and (2) to test whether MCII is dependent on selected demographic characteristics. STUDY DESIGN AND SETTING: This was a prospective, longitudinal, observational cohort study of 6,651 patients with orthopedic knee impairments treated in 332 outpatient rehabilitation clinics in 27 states in the United States. OUTCOME MEASURES: Patient self-reports of functional status (FS) from the Lower Extremity Functional Scale were assessed using a computerized adaptive testing application (0-100 scale). METHODS: An anchored-based longitudinal method, with a 15-point Likert-type scale (-7 to +7), was used to provide a global rating of change (GROC). The MCII threshold for the GROC was defined at a cut-score of +3 or greater and was determined using nonparametric receiver operating characteristic curve analysis for each of the following variables: sex, symptom acuity, age group, and quartile of baseline FS scores. RESULTS: The results showed that MCII was dependent on patient baseline and demographic characteristics. Patients who were male, were younger, had more-acute symptoms, or had lower FS scores at admission required more FS change to report meaningful change. LIMITATIONS: As this study was a secondary analysis, how the length of treatment mediated the relationship between the independent and dependent variables was unclear. CONCLUSIONS: Although a single MCII index may provide a standard cut-score defining the smallest FS change that is meaningful to patients, researchers and clinicians should be aware that MCII is context specific and not a fixed attribute. Current results may help researchers, clinicians, and policy makers to interpret FS change related to the importance of the change to the patient.
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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 | 0.009 | 0.046 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".