Effectiveness and safety of auricular therapy for post-stroke depression
Bibliographic record
Abstract
BACKGROUND: Post-stroke depression is a common and serious complication after stroke. Its main clinical manifestations are depression or instability, loss of interest, loss of appetite, sleep disorders, pessimism, and unworthiness, and even suicidal tendencies. Auricular therapy (AT), as part of traditional Chinese acupuncture, has achieved good results in the treatment of depression, but different clinical studies have shown mixed results. Therefore, the aim of this systematic review is to assess the effectiveness and safety of AT for post-stroke depression. METHODS: Two reviewers will electronically search the following databases: the Cochrane Central Register of Controlled Trials; Medline (via PubMed); Excerpt Medica Database; China National Knowledge Infrastructure; Chinese Biomedical Literature Database; Chinese Scientific Journal Database; and Wan-Fang Database from the inception to January 1, 2022. Study selection, data extraction, and assessment of study quality will be performed independently by 2 reviewers. If it is appropriate for a meta-analysis, Review Manager Version 5.3 statistical software will be used; otherwise, a descriptive analysis will be conducted. Data will be synthesized by either the fixed-effects or random-effects model according to a heterogeneity test. The results will be presented as risk ratio with 95% confidence intervals for dichotomous data and weight mean difference or standard mean difference 95% confidence intervals for continuous data. RESULT: This study will provide a comprehensive review of the available evidence for the treatment of AT with post-stroke depression. CONCLUSIONS: The conclusions of our study will provide an evidence to judge whether AT is an effective and safe intervention for patients with post-stroke depression. TRIAL REGISTRATION NUMBER: PROSPERO CRD42021289870.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".