Therapeutic Effects of Tamsulosin in Nightmare Disorder: A Randomized, Double Blind, Placebo-Controlled, Cross-Over, Pilot Study
Bibliographic record
Abstract
Abstract Nightmare disorder is associated with functional impairment, distress, and low quality of life; however, studies on pharmacotherapy of this debilitating disorder yielded mixed results. Prazosin, a non-selective α1 blocker is reported to be effective in treatment of post-traumatic stress disorder-related nightmares. We aimed at investigating therapeutic effects of tamsulosin which has higher affinity for blocking α1A and α1D adrenoceptors in treatment of nightmare disorder. A randomized, double blind, cross-over, placebo-controlled pilot study was conducted. Patients were randomly assigned to receive Tamsulosin 0.4 mg once daily or placebo for period of four weeks. Following a 2-week wash-out period, they were crossed over to the other group and received drug or placebo for duration of 4 additional weeks. Nightmare frequency and intensity measurements were carried out using Disturbing Dreams and Nightmares Severity Index (DDNSI). Blood pressure measurements were also performed. According to per protocol analysis, mean DDNSI scores decreased following administration of tamsulosin and a statistical trend towards significance was reported (p=0.065, d=0.236). Results of intention to treat analysis showed significant difference in DDNSI scores after drug use (p=0.030, d=0.651). Additionally, DDNSI scores dropped significantly following placebo use. However, intention to treat analysis showed no statistically significant difference pre and post placebo period (0.064, d=0.040). Tamsulosin may be effective in treatment of nightmare disorder. However, further larger clinical trials are recommended to clarify the effectiveness of tamsulosin and α1 subtypes in pharmacotherapy of nightmares.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".