Hearing Impairment and Type 1 Diabetes in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Cohort
Bibliographic record
Abstract
OBJECTIVE To evaluate the prevalence of hearing impairment in participants with type 1 diabetes enrolled in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study and compare with that of a spousal control group without diabetes. Among participants with type 1 diabetes, to evaluate the association of hearing impairment with prior DCCT therapy and overall glycemia. RESEARCH DESIGN AND METHODS DCCT/EDIC participants (n = 1,150) and 288 spouses without diabetes were recruited for the DCCT/EDIC Hearing Study. All subjects completed a self-administered questionnaire, medical history, and physical measurements. Audiometry was performed by study-certified personnel; audiograms were assessed centrally. Speech-frequency (pure-tone average [PTA] thresholds at 500, 1,000, 2,000, and 4,000 Hz) and high-frequency impairment (PTA thresholds at 3,000, 4,000, 6,000, and 8,000 Hz) were defined as PTA >25 dB hearing loss. Logistic regression models were adjusted for age and sex. RESULTS DCCT/EDIC participants and spousal control subjects were similar in age, race, education, smoking, and systolic blood pressure. There were no statistically significant differences between groups in the prevalence or adjusted odds of speech- or high-frequency impairment in either ear. Among participants with type 1 diabetes, for every 10% increase in the time-weighted mean HbA1c, there was a 32% (95% CI 1.15–1.50) and 19% (95% CI 1.07–1.33) increase in speech- and high-frequency hearing impairment, respectively. CONCLUSIONS We found no significant difference in the prevalence of hearing impairment between the group with type 1 diabetes and the spousal control group. Among those with type 1 diabetes, higher mean HbA1c over time was associated with hearing impairment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".