0341 SEQUENTIAL THERAPIES FOR COMORBID AND PRIMARY INSOMNIA: A RANDOMIZED CONTROLLED TRIAL
Bibliographic record
Abstract
Despite evidence supporting pharmacological and cognitive/behavioral insomnia therapies, it remains unclear how best to combined these therapies to optimize outcomes. This paper reports findings from a two-site randomized clinical trial examining the efficacy of these therapies, employed individually and in various sequences. Patients were 211 adults (132 women; M age = 45.6 ± 14.9 years old) with insomnia disorder, including 72 who also presented a comorbid psychiatric disorder. They were randomly assigned to first-stage 6-week therapy involving either behavioral therapy (BT) or zolpidem. Patients in remission continued on maintenance therapy for 12 months. Those not achieving remission were randomized to a second, 6-week treatment involving either pharmacotherapy (zolpidem or trazodone) or psychological therapy (BT or cognitive therapy-CT). The primary end points reported here include Insomnia Severity Index - defined treatment response (≥ 8 point decline) and remission (total score < 8). Intent-to-treat analyses showed that there were similar proportions of treatment responders (45% vs. 41%) after initial treatment with BT or zolpidem, but a larger proportion of remitters in BT (33% vs. 25%). For those who did not remit with BT, the addition of zolpidem or cognitive therapy as a second treatment yielded equivalent response rates (54% and 56%, respectively), but larger remission rates when there was a switch of treatment modality (BT to zolpidem; 35%) than when patients remained within the same treatment modality (BT to CT; 22%). For those who did not remit with zolpidem, the addition of BT or trazodone yielded identical response rates (44%) and remission rates (22%). Although response/remission rates were generally lower among patients with psychiatric comorbidity, treatment sequences that involved BT followed by CT or zolpidem followed by trazodone led to better outcomes for comorbid insomnia than for insomnia without comorbidity. These preliminary, descriptive, findings suggest that sequential therapy is an effective strategy to optimize insomnia management. Adding a second treatment produces an added value for those who fail to respond to initial therapies. Patients with comorbid insomnia may benefit from therapies (cognitive therapy, antidepressant) that target mood in addition to sleep. National Institutes of Health (MH091053).
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".