Deteriorated Cardiometabolic Risk Profile in Individuals With Excessive Blood Pressure Response to Submaximal Exercise
Bibliographic record
Abstract
BACKGROUND: Early identification of individuals at increased cardiometabolic risk is an essential step to improve primary preventive interventions. Excessive maximal exercise blood pressure (EBP) has been associated with several adverse outcomes. We examined how submaximal EBP could help us to identify individuals with a deteriorated cardiometabolic risk profile. METHODS: Data from an observational study of 3,913 participants from a convenience sample were used. Subjects included in the analyses completed a comprehensive cardiometabolic health assessment (resting blood pressure [BP]; waist circumference; lipid profile; HbA1c; submaximal treadmill exercise test including a standardized stage [3.5 mph and 2% slope] with BP and heart rate measurements). Participants were classified on BP response at the standardized stage (Normal or Excessive Response). Excessive response was defined as systolic BP ≥ 80th percentile or diastolic BP ≥ 90 mmHg. Subjects were also classified into five resting BP subgroups according to current guidelines. RESULTS: The Excessive Response group had more deteriorated cardiometabolic and cardiorespiratory profiles than the Normal Response group (P ≤ 0.01). The Excessive Response group also showed a greater proportion of carriers of the hypertriglyceridemic waist phenotype in most resting BP subgroups (P ≤ 0.05). Finally, excessive BP response to submaximal exercise showed an independent contribution on cardiometabolic and cardiorespiratory factors beyond age, sex, and resting BP. CONCLUSIONS: This study demonstrates that an excessive BP response to a submaximal exercise is associated with a deteriorated cardiometabolic risk profile beyond resting BP profile. Therefore, submaximal EBP represents a simple screening tool to better identify at-risk individuals requiring aggressive preventive lifestyle interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".