Bibliographic record
Abstract
The history of blood pressure (BP) measurement is relatively brief. The BP cuff invented by Scipione Riva-Rocci in Italy1 and the auscultation of sounds first described by Nikolai Korotkov2 in Russia in the early 1900s have served as the basis for the measurement of BP for more than a century. In research, a modification of the mercury sphygmomanometer utilized the random-zero Hawksley BP technique but was not found to be accurate.3 Oscillometric devices have all but replaced the older methods in the Western world and have been rapidly adopted for the measurement of BP both in the clinic and in research.4 A problem that has long been recognized with the accuracy of BP measurement when an observer is present in the room is the white-coat effect.5 Some creative solutions have emerged. For instance, oscillometric devices can now be programmed to measure BP at periodic intervals including the BpTRU device, which is commonly used in Canadian practices.6 However, a newer development in which a mandatory 5-minute rest is required before the cuff inflates three times at periodic intervals to measure an oscillometric pressure has been used in the Systolic Blood Pressure Intervention Trial (SPRINT).7 This 5-minute unobserved oscillometric BP is less likely to have a “white-coat” effect. However, such a technique is not commonly used in most practices, yet we strive to translate the findings of SPRINT in the mistaken belief that BP is BP is BP. In this issue of the Journal of Clinical Hypertension, Cohen and colleagues assess the accuracy of the Omron HEM-907XL oscillometric BP measurement device (Lake Forest, IL, USA)—the device used in the SPRINT study—among nondialytic patients with chronic kidney disease8. Of note, such patients were participants in the SPRINT study, which was the motivation for validating this device. The researchers found that using the rigorous protocol of the Association for the Advancement of Medical Instrumentation, the systolic BP using an aneroid device was 2.5 mm Hg lower using one method and 5.1 mm Hg lower using the second method. The diastolic BPs were similar. Thus, the authors conclude that such a device may not be as accurate for the estimation of systolic BP. One has to recognize that 2 or 3 consecutive Korotkoff sounds are needed before a systolic BP is identified. The question remains: can the human brain really play back the sounds and recognize what the systolic BP might have been at the onset of the Korotkoff sounds? In fact, one may argue that using a sphygmocorder, which records both the BP and Korotkoff sounds simultaneously, would be ideal to validate such a device9; however, few investigations have used such methodology. The next question that emerges is whether the human ears are good enough to detect the systolic and diastolic sounds. Using a very sensitive microphone, Pickering and colleagues10 have discovered that such a microphone agrees more closely with the intra-arterial recordings compared with the human ear. On the other hand, it is possible that the device tested in the study was indeed miscalibrated. The oscillometric device is based on the detection of maximal oscillation, which occurs when the arterial wall is completely unloaded. This occurs when the cuff pressure equals the mean arterial pressure. At such a pressure, the oscillations of the air column within the BP cuff and its connecting tube are maximal. Proprietary algorithms then impute the systolic and diastolic BP. It is clear that arterial wall stiffness can influence such oscillations of the air column.11 This is particularly likely to happen in patients with chronic kidney disease, in whom such a device may not provide accurate readings.11 This study did not measure the arterial wall stiffness; therefore, we are unable to make direct cause and effect conclusions. A long-held belief has been that the human ear is the gold standard for BP measurement because such measurements have formed the basis of the practice of hypertension through the conduct of randomized controlled trials. Most of the older trials used mercury sphygmomanometers and auscultated BPs to form the basis of BP measurements. However, the validation of oscillometric devices has now occurred with the large randomized controlled trials such as the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT)12 and SPRINT.7 Both of these large trials used oscillometric devices. In SPRINT, it is quite clear that the oscillometric systolic BP differences were associated with reductions in clinically meaningful cardiovascular outcomes, thus implicitly validating the oscillometric device.7 In conclusion, it is not only important to use a validated device when measuring BP in our patients, it is also important that we pay attention to how BP is measured. For example, it is important that the patient is seated and rested alone in a quiet room for 5 minutes. Furthermore, it is important to recognize any person present in the room or other distractions that may unintentionally influence BP. Unless we pay attention to both the devices and the way we measure BP, we will continue to believe that the method of measurement of BP is unimportant. In other words, we may continue to believe that BP is BP is BP. Clearly, it is not. A well-measured BP is like a well-measured test, which is valuable and valid. Without such a measurement, we risk undertreating or overtreating patients with hypertension. The author is supported by the National Institutes of Health (R01-HL126903) and a grant for the VA Merit Review (5-I01-CX000829-04).
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".