Exercise Does Not Cause an Arm-Leg Pressure Gradient in Healthy Children
Bibliographic record
Abstract
A study was recently published questioning the use of exercise blood pressure gradients to assess post-operative coarctation of the aorta repair. This study also reported a significant arm-leg blood pressure gradient in healthy controls. We believe these results may be due to methodological problems, specifically the use of automated equipment to measure blood pressure which result in delays in obtaining blood pressure readings. PURPOSE: To assess resting arm-leg blood pressures and immediate post-exercise arm-leg blood pressures to determine if an arm-leg blood pressure gradient is developed in healthy children. METHODS: We recruited 12 healthy children between the ages of 10–17 years old. Blood pressure measurements on the right arm (RA) and right leg (RL) were done with a mercury sphygmomanometer and auscultation; blood pressures on the left arm (LA) and left leg (LL) were done with the automated Dinamap Vital Signs Monitor. Subjects exercised to volitional fatigue on a recumbent cycle ergometer. All four limb blood pressures were taken at rest, immediately on cessation of exercise, and four minutes post-exercise. The right arm blood pressure was also taken at peak exercise. The time taken to obtain each limb's blood pressure was recorded. RESULTS: The median resting RA and LA (114.5 vs 110.0 mmHg; p>0.05) and RL and LL (120.0 vs 124.5; p>0.05) systolic blood pressures were similar as were the 4 minute post-exercise systolic blood pressures. The immediate post-exercise RA-LA (172.0 vs 173.5 mmHg; p>0.05) systolic blood pressures were similar, however, the RL-LL (168.0 vs 146.0; p<0.0001) systolic blood pressures were markedly different. At rest and at 4 minutes post-exercise, the subjects had a negative arm-leg systolic pressure gradient (ie. leg pressure was greater than arm). However, the immediate postexercise RA-RL gradient was 3.0mmHg and LA-LL gradient was 19.0mmHg. There was a median time delay of 40 seconds in measuring RA blood pressure, 8 seconds between RA and LA, 13 seconds between RA and RL, and 29 seconds between LA and LL immediately post-exercise. The median blood pressure fall from peak-exercise to four minutes post-exercise was 50 mmHg. CONCLUSIONS: Automated blood pressure equipment such as the Dinamap Vital Signs Monitor record spurious blood pressure gradients in a rapidly changing vascular system. Timing of blood pressure measurements is crucial in determining the presence or absence of an arm-leg gradient. We recommend that leg blood pressure be taken before the arm when trying to determine whether an arm-leg pressure gradient is present.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".