The improvement of cognitive deficits after whole-body cryotherapy – A randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Whole-body cryotherapy (WBC) - a repetitive, short-term exposure to extremely low temperatures - may become an effective early intervention for mild cognitive impairment (MCI). It is a heterogeneous group of symptoms associated with cognitive dysfunction which is estimated to transform into dementia in 50% cases. STUDY DESIGN: The prospective randomised double-blind sham-controlled study aimed to determine the efficacy of WBC on cognitive functioning and biological mechanisms. The study was registered with Australian New Zealand Clinical Trials Registry (ACTRN12619001627145). METHODS: Participants with MCI (n = 62; (20<MoCA>26) were randomly allocated to cryogenic temperatures (-110 °C till -160 °C) (EG, n = 33) or placebo-controlled group (CG, n = 29). Cognitive functions were measured at baseline (T1), after the 10th WBC session (T2) and after 2 week-break (T3) with DemTect, SLUMS and Test Your Memory (TYM). Secondary outcome measures included quality of life (WHOQoL-BREF), self-reported well-being (VAS) and depressive symptoms (GDS). Whole blood samples (10 ml) were collected at T1 and T2 to evaluate levels of cytokines, neurotrophins, NO and biochemical parameters CRP total cholesterol, prolactin). RESULTS: There were significant differences between groups measured at T2 in immediate recall (DemTect) and in orientation (TYM) in favour of WBC group. Improvement in mood was detected in self-reported depressive symptoms level (WHOQoL-26; T2 p = 0.04; VAS mood T2 p = 0.02; T3 p = 0.07). The significant reduction of BDNF level was observed (p < 0.05). CONCLUSIONS: WBC may increase the performance of cognitive functions. It seems promising to combine WBC with existing behavioural and cognitive trainings in the future studies investigating early interventions methods in MCI.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".