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Automated Blood Pressure Measurement in Public Places

2005· article· en· W2071722742 on OpenAlexaboutno aff
Ari Mosenkis, Raymond R. Townsend

Bibliographic record

VenueJournal of Clinical Hypertension · 2005
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBlood pressureMedical instrumentationPublic healthProtocol (science)PharmacyMedical emergencyFamily medicineInternal medicineAlternative medicineCardiologyNursingPathology

Abstract

fetched live from OpenAlex

Within the past few decades, automated blood pressure (BP) devices began appearing in public places, such as pharmacies and supermarkets, with the goal of detecting undiagnosed, untreated, or inadequately treated hypertension (HTN). The widespread use of such devices in public places raises two important questions: 1) how accurate is this technique in diagnosing HTN? and 2) how effective is this public health strategy in accomplishing its objectives? There are two published guidelines for the validation of automated BP measurement devices, one by the British Hypertension Society1 and one by the American Association for the Advancement of Medical Instrumentation, which has been adopted by the FDA.2 Many automated BP measurement devices are commercially available, yet only a fraction of them have been independently validated.3, 4 Furthermore, even among those devices that have been validated in controlled settings, few have been formally tested in the environments in which they are now commonly being used. In one study that used two automated devices in pharmacies in Toronto, Canada, investigators measured the BP of volunteers according to a strict protocol (i.e., seated, after resting for 2 minutes and excluding subjects with large arm circumferences) and found that neither device met criteria for precision according to either the British or American standards.5, 6 A similar study, performed in grocery stores in Denver, CO, found the device in question to be inconsistent and inaccurate, with a sensitivity of 26% and a negative predictive value of 45% for diagnosing HTN.7 The accuracy of such devices is even more uncertain when utilized in an uncontrolled fashion where there is no standardization for subject position (i.e., sitting vs. standing), arm position (i.e., at the level of the heart), activity level (i.e., at rest), noise level, and arm circumference. Indeed, based on data from the Third National Health and Nutrition Examination Survey (NAHNES III), it is estimated that nearly half of all Americans with HTN have arm circumferences above the limits of one commonly used device.8 Only one study we could find has attempted to measure the efficacy of this public health strategy as a screening tool.9 In this study, automated devices were placed in 13 public places in Exeter, England (including post offices, supermarkets, and homeless shelters) for up to 18 weeks. Of the 769 people who used the devices, 221 recorded elevated BPs (defined as >135/85 mm Hg or systolic BP >160 mm Hg), among whom only 58 were available for follow-up and only 36 subsequently had formal BP measurements by a health care provider. Of this group, 11 subjects (1.4% of all users) were diagnosed with HTN, five of whom started antihypertensive therapy. Another 11 subjects were identified with inadequately treated HTN and five had adjustments made to their antihypertensive regimen, although it is unclear as to whether these changes were prompted by the study measurements. The authors contend that more diagnoses of HTN were likely made among the three quarters of subjects who did not live in Exeter and whose outcomes could not be determined in the study. Conversely, the investigators could not record the incidence of undiagnosed hypertension in patients whose BP readings may have been erroneously normal in the study. Thus, the results of this approach to screening are unclear, since neither its sensitivity nor its specificity is known. Another criticism of this strategy is that no effective protocol exists in most settings for the referral of patients with elevated BP readings to health care providers. In conclusion, automated BP measurement in public places is of questionable accuracy and is of uncertain efficacy as a screening tool. Using such a strategy, some people might be incorrectly labeled as hypertensive and, of greater concern, some people who truly have HTN might be labeled as normal and might then be left with a false sense of security. Even if this strategy is effective in identifying some people with previously undiagnosed HTN, referral systems of such patients to health care providers are not usually in place. There may, however, be a silver lining surrounding this issue. Even if only 1 % of users are newly diagnosed with HTN, this may, potentially, represent thousands of new diagnoses and could result in prevention of large numbers of cardiovascular events, if patients can be referred for follow-up care. At the very least, despite its problems, the measurement of BP in public places serves to promote awareness of HTN as a public health problem.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.180
GPT teacher head0.374
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations0
Published2005
Admission routes1
Has abstractyes

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