Systematic Review of Quality of Life in Bone Anchored Hearing: Conductive vs. Unilateral Sensorineural Hearing Loss
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to systematically review the differences in disease-specific quality of life (QoL) benefits experienced by bone-anchored hearing implant (BAHI) users between those diagnosed with unilateral sensorineural hearing loss (U-SNHL) and those with conductive/mixed hearing loss (CHL). DATA SOURCES: Eligible studies were searched for in Medline (Ovid), Embase (Ovid), CINAHL (Ebsco), Cochrane (Wiley), Global Health (Ovid), Web of Science (Clarivate Analytics), Africa Wide Information (Ebsco) and Global Index Medicus (WHO) from inception to October 23, 2022. Updated searches were performed on November 9, 2023, and July 11, 2024. REVIEW METHODS: There were no restrictions on language. PRISMA standards were followed, and screening was conducted by two independent reviewers in Rayyan, with a third reviewer resolving conflicts. Risk of bias was assessed using RoBANS. Articles were included if patients were implanted with a BAHI and administered a validated, disease-specific QoL measure. RESULTS: One thousand, three hundred twelve articles were identified after duplicate removal, with 56 articles meeting the inclusion criteria. Eight different disease-specific QoL measures were administered. In all, the APHAB's "Global" (p = 0.0002), EC (p < 0.00001), and BN (p = 0.02) scores, as well as the GBI's "Global" (p = 0.0001), "General" (p = 0.002), and "Physical" (p = 0.02) scores were significantly different between U-SNHL and CHL populations. CONCLUSION: These results demonstrated disease-specific QoL differences between BAHI users with U-SNHL and CHL. Specifically, patients with CHL reported greater benefits in domains pertaining to communication ease, the clarity of sound, and their overall health and psychosocial status.
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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 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.008 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".