Response to "Automated Sphygmomanometers Should Not Replace Manual Ones, Based on Current Evidence"
Bibliographic record
Abstract
To the Editor: The Ontario Survey on the Prevalence of High Blood Pressure (ON-BP) used the automated BpTRU device to measure BP in 2,551 residents in the province of Ontario. ON-BP was a survey and not a study on the white-coat response. A sample of 238 individuals had BP readings taken with both the BpTRU device and a mercury sphygmomanometer with the mean BpTRU values being 3/3 mm Hg lower.1 ON-BP was not designed to look at the factors that contributed to the lower BP readings when taken with the automated device. Validation studies using established protocols have documented the accuracy of the BpTRU in comparison to the mercury sphygmomanometer.2,3 In hypertensive patients, BP does fall when the observer leaves the room.4 There is no reason to believe that the small difference in BP between the devices observed in ON-BP was not at least partly due to the subjects being alone for the BpTRU measurements. A properly serviced mercury sphygmomanometer is the “gold standard” for BP measurement and is used in validation studies. The reports of inaccurate mercury devices cited by Turner and van Schalkwyk in their “Automated Sphygmomanometers Should Not Replace Manual Ones, Based on Current Evidence”5 pertain to their use in routine clinical practice and not to a research study such as ON-BP. To quote the AHA statement on BP devices, “There is less to go wrong with mercury sphygmomanometers than with other devices”.6 The BpTRU has a continuous auto-zero offset calibration which, enables the device to give repeated accurate readings. It is not necessary and also not practical to re-calibrate the device for every patient. The editor also wondered whether the Bland-Altman format should be used in our data analysis. The reason for not doing so was explained in detail by our statistician. The analysis of this sub-set of 238 participants of the ON-BP study was not intended to examine how closely the individual pairs of readings agreed. Indeed, differences between the manual and automated readings were anticipated because of the different conditions of measurement. The comparison of the techniques was done to determine how one would transform the automated BP readings in the ON-BP survey to obtain comparable manual readings for comparison with other BP surveys. It is true that the AHA guidelines6 recommend that (home) BP “devices be checked on each patient before the readings are accepted as being valid”. This statement was made in a discussion about home devices and not sphygmomanometers designed specifically for professional use such as the BpTRU. AHA guidelines do not state exactly how an automated device should be “checked” and what difference between the automated device and the manual recorder is unacceptable. In a survey of 2,551 individuals, it would neither be possible to compare readings in individuals for “systematic errors” nor would there be any point in doing so because the BP measurements were not being used to “diagnose or manage hypertension”. The BpTRU has successfully passed the highest standards for validating automated oscillometric sphygmomanometers. It was chosen for the ON-BP survey in order to avoid the numerous sources of error associated with manual BP measurement with devices such as the mercury sphygmomanometer as outlined in detail in the AHA report on blood pressure measurement.6 There is currently no perfect method for measuring BP and all methods, particularly mercury, have limitations associated with their use. The authors declared no conflict of interest.
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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 | 0.012 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".