Quality of Life following Ear Surgery Measured by the 36-Item Short Form Health Survey and the Glasgow Benefit Inventory
Bibliographic record
Abstract
BACKGROUND: Quality of life (QOL) following ear surgery is an important outcome measure. Most QOL studies are retrospective and therefore biased by uncertainties about preoperative QOL. OBJECTIVES: The primary objective was to prospectively assess change in QOL following ear surgery. The secondary objective was to determine if QOL was associated with audiometric change. METHODS: Twenty-six patients undergoing ear surgery were studied prospectively between 1999 and 2000. Before and after surgery, patients received a detailed audiometric evaluation and completed a generic (36-Item Short Form Health Survey [SF-36]) and a disease-specific (Glasgow Benefit Inventory [GBI]) QOL instrument. RESULTS: Significant audiometric improvement was noted following surgery. For six of the eight subsections of the SF-36, there was significant improvement following surgery. Three subsections correlated with the reduction in air-bone gap. GBI scores indicated that 50% of patients experienced an increase in QOL. The GBI correlated with one subsection of the SF-36. Higher GBI scores were associated with a reduction in the air-bone gap, but there was no significant correlation. CONCLUSIONS: QOL improved following ear surgery. QOL can be effectively assessed using both generic and disease-specific instruments. Improvement in the SF-36 score was correlated with reduction of the air-bone gap, suggesting that improved hearing was a determinant of improved QOL.
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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 | 0.029 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".