Comparisons of Auditory Steady State and Auditory Brainstem Response Thresholds in Infants with Normal Hearing and Conductive Hearing Loss
Bibliographic record
Abstract
ABSTRACT This study investigates how well the air- and bone-conduction auditory steady-state response detects mild conductive hearing loss compared to the auditory brainstem response in young infants. Air-bone gap sizes are compared between infants with normal hearing and conductive loss using a two-group cross-sectional design. Twenty-three (500 Hz) and 22 (2000 Hz) infants (0-6 months of age) with normal hearing and 15 (500 Hz) infants with conductive loss were recruited from newborn hearing screening. Thresholds were obtained to frequency-specific air- and bone-conducted stimuli. There were no instances of conductive loss at 2000 Hz. 500 Hz mean thresholds and air-bone gap sizes were compared. Sensitivity and specificity for identifying conductive loss were measured. Overall, mean bone-conduction thresholds were similar between groups, and mean 500-Hz air conduction thresholds were higher with larger air-bone gap size for infants with conductive loss. Sensitivity and specificity for identifying conductive loss was highest for air-conduction auditory brainstem response threshold measurement compared to screening and auditory steady-state response threshold measurements. Compared to the auditory brainstem response, the variability of auditory steady-state response thresholds and air-bone gap size was too great to reliably separate normal hearing from mild conductive loss. More research is needed using infants with varying degrees of hearing loss at multiple frequencies to fully assess the appropriateness of the auditory steady-state response as a clinical diagnostic tool for an infant population.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".