Effect of prolonged standardized bed rest on cystatin C and other markers of cardiovascular risk
Bibliographic record
Abstract
BACKGROUND: Sedentary lifestyle is associated with coronary artery disease but even shorter periods of physical inactivity may increase cardiovascular risk. Cystatin C is independently associated with cardiovascular disease and our objective was to investigate the relation between this novel biomarker and standardized bed rest. Research of immobilization physiology in humans is challenging because good biological models are in short supply. From the Women International Space simulation for Exploration study (WISE) we studied markers of atherosclerosis and kidney function, including cystatin C, in a standardized bed rest study on healthy volunteers. Fifteen healthy female volunteers participated in a 20-day ambulatory control period followed by 60 days of bed rest in head-down tilt position (-6°) 24 h a day, finalized by 20 days of recovery. The subjects were randomized into two groups during bed rest: a control group (n = 8) that remained physically inactive and an exercise group (n = 7) that participated in both supine resistance and aerobic exercise training. RESULTS: Compared to baseline values there was a statistically significant increase in cystatin C in both groups after bed rest (P < 0.001). Glomerular filtration rate (GFR), calculated by both cystatin C and Cockcroft-Gault equation, decreased after bed rest while there were no differences in creatinine or creatine kinase levels. CRP did not change during bed rest in the exercise group, but there was an increase of CRP in the control group during recovery compared to both the baseline and the bed rest periods. The apo-B/apo-Ai ratio increased during bed rest and decreased again in the recovery period. Subjects experienced a small but statistically significant reduction in weight during bed rest and compared to baseline weights remained lower at day 8 of recovery. CONCLUSION: During and following prolonged standardized bed rest the concentrations of several clinically relevant cardiovascular risk markers change.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".