Bibliographic record
Abstract
CONTEXT: Hearing impairment is prevalent among the elderly population but commonly underdiagnosed. OBJECTIVE: To review the accuracy and precision of bedside clinical maneuvers for diagnosing hearing impairment. DATA SOURCES: MEDLINE and EMBASE databases (1966 to April 2005) were searched for English-language articles related to screening for hearing impairment. STUDY SELECTION: Original studies on the accuracy or precision of screening questions and tests were included. Articles that used unaccepted reference standards or contained insufficient data were excluded. Medical Subject Headings or keywords used in the search included hearing loss, hearing handicap, hearing tests, tuning fork, deafness, physical examination, sensitivity, specificity, audiometry, tuning fork tests, Rinne, Weber, audioscope, Hearing Handicap Inventory for the Elderly-Screening version, whispered voice test, sensorineural, and conductive. DATA EXTRACTION: One author screened all potential articles and 2 authors independently abstracted data. Differences were resolved by consensus. Each included study (n = 24) was assigned a methodological grade. DATA SYNTHESIS: A yes response when asking individuals whether they have hearing impairment has a summary likelihood ratio (LR) of 2.5 (95% confidence interval [CI], 1.7-3.6); a no response has an LR of 0.13 (95% CI, 0.09-0.19). A score of 8 or greater on the screening version of the Hearing Handicap Inventory for the Elderly (HHIE-S) has an LR of 3.8 (95% CI, 3.0-4.8); a score less than 8 has an LR of 0.38 (95% CI, 0.29-0.51). An abnormal Weber tuning fork test response has an LR of 1.6 (95% CI, 1.0-2.3); a normal response has an LR of 0.70 (95% CI, 0.48-1.0). An abnormal Rinne tuning fork test response has LRs ranging from 2.7 to 62; a normal response has LRs from 0.01 to 0.85. Inability to perceive a whispered voice has an LR of 6.1 (95% CI, 4.5-8.4); normal perception has an LR of 0.03 (95% CI, 0-0.24). Not passing the audioscope test has an LR of 2.4 (95% CI, 1.4-4.1); passing has an LR of 0.07 (95% CI, 0.03-0.17). CONCLUSIONS: Elderly individuals who acknowledge they have hearing impairment require audiometry, while those who reply no should be screened with the whispered-voice test. Individuals who perceive the whispered voice require no further testing, while those unable to perceive the voice require audiometry. The Weber and Rinne tests should not be used for general screening.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".