Reliability of Postsurgical Soft Tissue Reaction Grading Scales for Bone-anchored Hearing Implants
Bibliographic record
Abstract
OBJECTIVE: This study aims to assess and compare the reliability of the Holgers, the IPS, and the Tullamore scales for skin tolerability assessment of postoperative bone-anchored hearing implant images. STUDY DESIGN: A survey study and retrospective review of percutaneous osseointegrated auditory implant images for scoring using three skin classification scales. SETTING: McGill University Health Center, Montreal, Quebec, Canada. PARTICIPANTS: Healthcare workers experienced and inexperienced with osseointegrated auditory implant skin classification scales. MAIN OUTCOME MEASURES: Participation involved completing: 1) survey questionnaires assessing experience with osseointegrated auditory implants and related skin reactions and 2) scoring postoperative osseointegrated auditory implant with surrounding skin images using the Holgers Classification, the IS (of the IPS) scale, and the Tullamore Classification. Participants were asked to rate 12 images of postoperative osseointegrated auditory implant and surrounding soft tissue. This process was repeated until participants scored all images using the three scales; each rater graded 36 images in total. The order in which scales were presented occurred at random. Intraclass correlation coefficients were calculated to assess reliability. RESULTS: Thirty-one participants were recruited to the study. Fourteen (45.2%) had experience with at least 1 osseointegrated auditory implant skin classification scale, while 17 (54.8%) did not have experience. The wide and overlapping 95% confidence intervals of the intraclass correlation coefficients results do not provide us with enough evidence to define a well-established degree and hierarchy of reliability when comparing the scales. Among experienced raters, all scales presented moderate to good reliability. CONCLUSIONS: The Holgers Classification, the IPS scale, and the Tullamore Classification all present moderate to good reliability when used by experienced raters to assess skin reactions following surgical implantation of an osseointegrated hearing device. As a result, clinicians should use these scales with a degree of caution. The findings of this study do not provide us with enough evidence to single out one of the scales as a standard to follow, but more extensive studies are required to assess the reliability of the scales.
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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 | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".