Preliminary safety analysis of high-intensity interval training (HIIT) in persons with chronic stroke
Bibliographic record
Abstract
The purpose of this study was to assess safety via electrocardiographic (ECG), blood pressure (BP), heart rate (HR), and orthopedic responses to 3 different high-intensity interval training (HIIT) protocols in persons with stroke. Eighteen participants (10 male; 61.9 + 8.3 years of age; 5.8 + 4.2 years poststroke) completed a symptom-limited graded exercise test (GXT) with ECG monitoring to screen for eligibility and determine HR peak. The 3 HIIT protocols involved repeated 30 s bursts of treadmill walking at maximum speed alternated with rest periods of 30 s (P30), 1 min (P60), or 2 min (P120). Sessions were performed in random order and included 5 min warm up, 20 min HIIT, and 5 min cool down. Variables measured included ECG activity, BP, HR, signs and symptoms of cardiovascular intolerance, and orthopedic concerns. Generalized linear mixed models and Tukey–Kramer adjustment were used to compare protocols using p < 0.05. No signs or symptoms of cardiovascular intolerance, significant arrhythmias, ST segment changes, or orthopedic responses resulted in early termination of any HIIT session. HIIT elicited HRs in excess of 88% of measured HRpeak including 6 (P30), 8 (P60), and 2 (P120) participants eliciting a HR response above their GXT HRpeak. Both maximum BP and HR were significantly higher in P30 and P60 relative to P120. Preliminary data indicate that persons with chronic stroke who have been prescreened with an ECG stress test, a symptom-limited GXT, and a harness for fall protection may safely participate in HIIT, generating substantially higher HRs than what is seen in traditional moderate intensity training.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".