Physical outcome measures for conductive and mixed hearing loss treatment: A systematic review
Bibliographic record
Abstract
BACKGROUND: The number of potential options for rehabilitation of patients with conductive or mixed hearing loss is continually expanding. To be able to inform patients and other stakeholders, there is a need to identify and develop patient-centred outcomes for treatment of hearing loss. OBJECTIVE OF REVIEW: To identify outcome measures in the physical core area used when reporting the outcome after treatment of conductive and mixed hearing loss in adult patients. TYPE OF REVIEW: Systematic review. SEARCH STRATEGY: Systematic review of the literature related to reported physical outcome measures after treatment of mixed or conductive hearing loss without restrictions regarding type of intervention, treatment or device. EVALUATION METHOD: Any measure reporting the physical outcome after treatment or intervention of mixed or conductive hearing loss was sought and categorised. The physical outcome measures that had been extracted were then grouped into domains. RESULTS: The literature search resulted in the identification of 1434 studies, of which 153 were selected for inclusion in the review. The majority (57%) of papers reported results from middle ear surgery, with the remainder reporting results from either bone conduction hearing devices or middle ear implants. Outcomes related to complications were categorised into 17 domains, whereas outcomes related to treatment success was categorised into 22 domains. CONCLUSIONS: The importance of these domains to patients and other stakeholders needs to be further explored in order to establish which of these domains are most relevant to interventions for conductive or mixed hearing loss. This will allow us to then assess which outcome measures are most suitable for inclusion in the core set.
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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 | 0.013 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".