Effect of Elevated Ambient Temperature on Simulator-Derived Oscillometric Blood Pressure Measurement
Bibliographic record
Abstract
BACKGROUND: Oscillometric blood pressure (BP) devices are typically labeled for use up to 40 °C. Many geographic regions have ambient temperatures exceeding 40 °C. We assessed the effect of increased ambient temperature (40-55 °C) on simulator-derived oscillometric BP measurement. METHODS: Three Omron BP769CAN devices, 3 A&D Medical UA-651BLE devices, and accompanying cuffs were used. A custom heat chamber heated each device to the specified temperature. A noninvasive BP simulator was used to take 3 measurements with each device at differing temperatures (22, 40, 45, 50, and 55 °C) and BP thresholds: 80/50, 100/60, 120/80, 140/90, 160/110, and 180/130 mm Hg. Using each device as its own control (22 °C), we determined the relative differences in mean BP for each device at each temperature and BP setting, assessed graphical trends with increasing temperature, and examined variability. RESULTS: Graphical trends of mean simulator-subtracted BP differences from room temperature showed no discernable pattern, with differences clustered around zero. Overall mean difference in BP (combined elevated temperatures minus room temperature) was -0.8 ± 2.1 (systolic ± SD)/1.2 ± 3.5 (diastolic ± SD) mm Hg for the A&D device and 0.2 ± 0.4 (systolic ± SD)/-0.1 ± 0.1 (diastolic ± SD) mm Hg for the Omron. All individual elevated temperature differences (elevated temperature minus room temperature) except A&D diastolic BP at 50 °C were within 5 mm Hg. CONCLUSIONS: In this simulator-based study assessing within-device differences, higher ambient temperatures resulted in oscillometric BP measurements that were comparable to those performed at room temperature.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".