Most Efficient and Meaningful Patient-Reported Appearance Assessment in Different Cleft Types and Age Groups with CLEFT-Q
Bibliographic record
Abstract
BACKGROUND: The CLEFT-Q, a questionnaire developed and validated specifically for cleft patients, contains seven appearance scales. The International Consortium of Health Outcomes Measurement (ICHOM) has incorporated only some CLEFT-Q appearance scales in the Standard Set to minimize burden. This study evaluates which appearance scales provide the most meaningful information in the different cleft types at specific ages, for the most efficient cleft appearance outcome assessment. METHODS: Within this international multicenter study, outcomes of the seven appearance scales were collected, either as part of the ICHOM Standard Set, or as part of the field test study performed to validate the CLEFT-Q. Analyses were performed in separate age groups and cleft types, and involved univariate regression analyses, trend analyses, t tests, correlations, and floor and ceiling effects. RESULTS: A total of 3116 patients were included. Scores for most appearance scales showed a downward trend by age group, with the exception of the Teeth and Jaw scales. In all cleft types, several scales correlated strongly with each other. No floor effects were observed, but ceiling effects were found in several scales in different age groups, most often in the CLEFT-Q Jaw scale. CONCLUSIONS: A proposition for the most meaningful and efficient appearance outcome assessment in cleft patients is made. It was composed so that recommendations are of value for different cleft protocols and initiatives. Suggestions for the use of scales in the ICHOM Standard Set at different ages are given, and also from a clinical perspective. Use of the CLEFT-Q Scar, Lips, and Nose scales will provide additional relevant information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".