Loudness dependence of the auditory evoked potential and response to antidepressants in Chinese patients with major depression
Bibliographic record
Abstract
OBJECTIVE: To investigate the loudness dependence of the auditory evoked potential (LDAEP) in predicting response to treatment for major depression. METHODS: One hundred patients of Chinese ethnicity with major depression were divided into 2 groups, having strong or weak pretreatment LDAEP; the cutoff was the median of the LDAEP slope (for amplitude as a function of intensity). There were no between-group differences before treatment in terms of score on the Hamilton Depression Rating Scale (HDRS), age or sex distribution. The LDAEP for 4 intensity levels (60, 70, 80 and 90 dB) was recorded before treatment. Each patient then received fluoxetine 20 mg per day for 4 weeks. The response to treatment was evaluated by means of the HDRS. RESULTS: At week 4, the HDRS score had declined by 44.3; for the group with strong LDAEP and by 34.4% for the group with weak LDAEP (t for mean difference = 2.584, p = 0.011). CONCLUSION: Strong pretreatment LDAEP predicted a favourable response to treatment with a selective serotonin reuptake inhibitor in patients with major depression.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".