Detailed assessment of the hemodynamic response to psychosocial stress using real‐time MRI
Bibliographic record
Abstract
PURPOSE: To demonstrate that combining the Montreal Imaging Stress Task (MIST) with real-time cardiac magnetic resonance imaging (MRI) allows detailed assessment of the cardiovascular mental stress response. MATERIALS AND METHODS: 22 healthy volunteers (1:1 M:F, 26-64 years) underwent MRI during rest and the MIST. Real-time spiral phase contrast MR, accelerated with sensitivity encoding (SENSE) was used to assess stroke volume (SV), and radial k-t SENSE was used to assess ventricular volumes. Simultaneous heart rate (HR) and blood pressure (BP) measures allowed calculation of cardiac output (CO), systemic vascular resistance (SVR), and arterial compliance (TAC). Endocrine responses were assessed using salivary cortisol. RESULTS: In response to stress, BP increased due to increased CO and reduced TAC but not increased SVR, which fell. HR, not SV, determined CO increases. Greater BP responses occurred in men due to greater CO increases and relatively higher SVR. Older participants had greater BP responses due to greater falls in TAC. Greater cortisol response was correlated with greater falls in TAC but resting cortisol and TAC were not related. CONCLUSION: This new approach allows detailed, accurate assessment of stress physiology. Preliminary findings suggest stress exposes relationships, not seen at rest, of cardiovascular function with age, sex, and endocrine function.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".