Improvement of Hyperbaric Oxygen Therapy on Cognitive Functions in Patients and animals : A systematic review and meta-analysis
Bibliographic record
Abstract
Review question / Objective: Review question / Objective: Population: Participants and animals who were definitively diagnosed with cognitive functions were included.No limitations of location, educational background, and gender were imposed.This study will only consider randomized controlled trials (RCTs) of hyperbaric oxygen therapy for the treatment of patients and animals with cognitive functions.However, other studies, such as reviews, case studies, non-controlled studies, and quasi-RCTs, were excluded.Intervention: hyperbaric oxygen therapy Comparison: The control intervention based on the treatment guidelines of cognitive functions, or did not receive any treatment as a blank control.Outcome: Primary outcomes: Results of the cognitive function evaluations.Secondary outcomes: NeuroTrax computerized cognitive testing battery (NeuroTrax Corporation, Bellaire, TX)., computerized cognitive tests (Cambridge cognition, England) , neuropsychological tests included: the Rey-Osterrieth complex figure test (ROCFT), CVLT(California Verbal Learning Test), Wechsler Adult Intelligence Scale-Revised, Montreal cognitive assessment (MoCA) scale, and mini mental state examination (MMSE), eight-arm radial maze ，Passive Avoidance Learning Test , Y-Maze Test, Morris water maze, adverse reactions and other outcomes recorded in the article.Study design: This meta-analysis is secondary study and the data were extracted from other people's work.INPLASY registration number: This protocol was registered with the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) on 01 June 2022 and was last u p d a t e d o n 0 1 J u n e 2 0 2 2 ( r e g i s t r a t i o n n u m b e r INPLASY202260005).
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.019 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".