Accuracy in blood pressure monitoring: The effect of noninvasive blood pressure cuff inflation on intra-arterial blood pressure values
Bibliographic record
Abstract
CONTEXT: Both invasive and noninvasive blood pressure (invasive arterial blood pressure [IABP] and noninvasive BP [NIBP]) monitors are used perioperatively; however, they often produce different values. The reason for this discrepancy is not clear, and it is possible that the act of cuff inflation itself might affect the IABP values, especially with the recurrent cycling of NIBP cuff. AIM: The aim of this study was to determine the effect of ipsilateral NIBP cuff inflation on the contralateral IABP values. SETTINGS AND DESIGNS: Prospective, observational study. MATERIALS AND METHODS: One hundred consecutive patients were studied. The NIBP device was set to cycle every 5 min for a total of 6 times. During each cuff inflation cycle, changes in IABP values from the arterial line in the contralateral arm were recorded. A total of 582 measurements were included for data analysis. STATISTICAL ANALYSIS: -test, analysis of variance. RESULTS: Mean (± standard deviation) changes in systolic BP (SBP), diastolic BP, and mean BP with cuff inflation were 6.7 ± 5.9, 2.6 ± 4.0, and 4.0 ± 3.9 mmHg, respectively. We observed an increase of 0-10 mmHg in SBP in majority (73.4%) of cuff inflations. The changes in IABP did not differ between the patients with or without hypertension or with the baseline SBP. CONCLUSIONS: This study showed that there is a transient reactive rise in IABP values with NIBP cuff inflation. This is important information in the perioperative and intensive care settings, where both these measurement techniques are routinely used. The exact mechanism for this effect is not known but may be attributed to the pain and discomfort from cuff inflation.
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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 | 0.014 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".