Adverse Events During Submaximal Aerobic Exercise Testing in People With Subacute Stroke: A Scoping Review
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Concern for adverse cardiovascular events and limited guidance regarding how to conduct aerobic exercise (AEx) testing for individuals poststroke are key barriers to implementation by physical therapists in stroke rehabilitation. This study aimed to describe the nature and safety of submaximal AEx testing protocols for people with subacute stroke (PwSS) and the nature of comorbidity of PwSS who underwent submaximal AEx testing. METHODS: We conducted a scoping review and searched MEDLINE, EMBASE, PsycINFO, CINAHL, and SPORTDiscus from inception to October 29, 2020. Studies involving submaximal AEx testing with PwSS, reporting on participant comorbidity and on adverse events during testing, were eligible. Two reviewers independently conducted title and abstract and full-text screening. One reviewer extracted data; a second reviewer verified data. RESULTS: Thirteen studies involving 452 participants and 19 submaximal AEx testing protocols (10 field test, 7 incremental, and 2 constant load) were included. Hypertension (41%), diabetes (31%), and dyslipidemia (27%) were the most common comorbidities reported. No protocols resulted in a serious adverse event. The most common test termination criterion was a heart rate (HR) limit (9 protocols); a limit of 85% age-predicted maximal HR (APM-HR) most frequently reported. Average APM-HR achieved, computed using mean age and mean peak HR, ranged from 59% to 88% across 13 protocols. DISCUSSION AND CONCLUSION: Diverse submaximal AEx testing protocols with conservative test termination criteria can be safely implemented with PwSS. Results can inform clinical practice guidelines and address physical therapists' concerns with the occurrence of serious adverse events during submaximal AEx testing.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A430 ).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".