Comparative Efficacy of 5 non-pharmaceutical Therapies For Adults With Post-stroke Cognitive Impairment: Protocol For A Bayesian Network Analysis Based on 55 Randomized Controlled Trials
Bibliographic record
Abstract
Review question / Objective: This study will provide evidence-based references for the efficacy of 5 different non-pharmaceutical therapies in the treatment of post-stroke cognitive impairment(PSCI). 1. Types of studies. Only randomized controlled trials (RCTs) of Transcranial Magnetic Stimulation(TMS), Transcranial Direct Current Stimulation(tDCS), Acupuncture, Virtual Reality Exposure Therapy(VR) and Computer-assisted cognitive rehabilitation(CA) for PSCI will be recruited. Additionally, Studies should be available in full papers as well as peer reviewed and the original data should be clear and adequate. 2. Types of participants. All adults with a recent or previous history of ischaemic or hemorrhagic stroke and diagnosed according to clearly defined or internationally recognized diagnostic criteria, regardless of nationality, race, sex, age, or educational background. 3.Types of interventions and controls. The control group takes non-acupuncture treatment, including conventional rehabilitation or in combination with symptomatic support therapy. The experimental group should be treated with acupuncture on basis of the control group. 4.The interventions of the experimental groups were Transcranial Magnetic Stimulation(TMS), Transcranial Direct Current Stimulation(tDCS), Acupuncture, Virtual Reality Exposure Therapy(VR) or Computer-assisted cognitive rehabilitation(CA), and the interventions of the control group takes routine rehabilitation and cognition training or other therapies mentioned above that were different from the intervention group. 5.Types of outcomes. The primary outcomes are measured with The Mini-Mental State Examination (MMSE) and/or The Montreal Cognitive Assessment Scale (MoCA), which have been widely used to evaluate the cognitive abilities. The secondary outcome indicator was the Barthel Index (BI) to assess independence in activities of daily living (ADLs).
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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 | 0.074 | 0.117 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.019 | 0.027 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.056 | 0.005 |
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".