Sensitivity and responsiveness of the patient-reported TED-QOL to rehabilitative surgery in thyroid eye disease
Bibliographic record
Abstract
We tested the sensitivity and responsiveness of the TED-QOL to rehabilitative surgery in thyroid eye disease (TED). The 3-item TED-QOL and 16-item GO-QOL, which assess quality of life (QoL) in TED, were administered to consecutive patients undergoing rehabilitative surgery. The questionnaires were completed pre-and post-operatively to assess sensitivity (ability to discriminate between different surgical groups) and responsiveness (ability to detect within patient changes over time).56 patients underwent 69 procedures for TED (29 orbital decompressions, 15 strabismus operations, 25 eyelid procedures). The differences in scores between the three types of surgery (a measure of sensitivity) were statistically significant at the 5% level pre-operatively and post-operatively for all 3 TED-QOL scales and for both GO-QOL scales, but much more so for the TED-QOL scales in each case. The within-patient changes between the pre- and post-operative scores for the same subjects (a measure of responsiveness) were statistically very highly significant for the TED-QOL overall and appearance scales for each of the surgeries. The pre- and post-operative difference for the TED-QOL functioning scale was highly statistically significant for strabismus surgery but not for decompression or lid surgery. The change between the pre- and post-operative scores for the GO-QOL was significant for the functioning scale with strabismus and lid surgery, and was highly significant for the appearance scale with lid surgery but not for strabismus surgery or decompression. The 3-item TED-QOL is sensitive and responsive to rehabilitative surgery in TED and compares favorably with the lengthier GO-QOL for these parameters.
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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 | 0.006 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".