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Record W1973832787 · doi:10.1111/jch.12061

Public‐Use Blood Pressure Machines in Pharmacies for Identification of Undetected Hypertension in the Community

2013· letter· en· W1973832787 on OpenAlexafffundabout
Sherilyn K. D. Houle, Ross T. Tsuyuki

Bibliographic record

VenueJournal of Clinical Hypertension · 2013
Typeletter
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates - Health Solutions
KeywordsMedicineBlood pressureInteractive kioskCommunity pharmacyPharmacyInternal medicineFamily medicineWorld Wide Web

Abstract

fetched live from OpenAlex

Detection and monitoring of hypertension is largely dependent on screening at medical visits, which may explain why one third to one half of patients have poorly controlled blood pressure (BP) and many patients are unaware that they have hypertension.1, 2 Community pharmacies offer a highly accessible and frequently used platform for patients to self-measure their BP free of charge at automated kiosks. PharmaSmart PS-2000 (PharmaSmart Canada Corporation, Vancouver, BC) BP kiosks are validated devices3 measuring seated BP at the brachial artery. These kiosks also have Internet connectivity, allowing collection of anonymized results obtained at these kiosks. However, until now there were no data on the range of readings acquired at these kiosks and their potential role in identifying undetected hypertension in the community. We obtained data from PharmaSmart on readings obtained from 341 locations of a Canadian chain pharmacy between January 2010 and November 2011. Because these results are collected anonymously with no ability to trace results to individual users, we assumed that each result corresponded to a unique individual. We classified readings consistent with North American hypertension guidelines4, 5 as optimal (<130/80 mm Hg), prehypertensive (130–139/80–89 mm Hg), uncontrolled (140–159/90–109 mm Hg), or very high (≥160/110 mm Hg). Age, sex, and comorbidity status of users was unknown, so classifications for patients without complicating factors were applied. When systolic and diastolic values from the same reading fell into 2 different categories, the higher category was utilized. A total of 8,457,552 readings were taken in the observation period, with an average usage across all pharmacies of 964±26.8 measurements monthly. Mean BP was 131/78 mm Hg (standard deviation, 13.7/13.4) with mean pulse of 76 beats per minute (standard deviation 5.6). Since BP kiosks are freely available for public use, the potential for improper technique must be considered. To estimate the potential impact of improper technique such as lack of rest or consumption of cigarettes or caffeine, coefficients of determination (R2) were calculated to assess the potential association between heart rate and BP. These showed that any association between BP result and heart rate were very weak (R2=0.17 for systolic BP, R2=0.04 for diastolic BP). Because these kiosks are frequently used and approximately two thirds of results obtained are elevated, this may present a unique and important opportunity for the early detection of hypertension (or poorly controlled hypertension) in the community, particularly among individuals who do not regularly present to a physician. To ensure accurate results, patient education on proper measurement is critical. While the PS-2000 has been well-validated, the freely accessible nature of these machines requires health professionals to be vigilant in ensuring users receive training in self-monitoring technique. This research identifies public-use BP kiosks as a potentially valuable tool in the early detection of undetected or uncontrolled BP. Given the accessibility and frequent use of kiosks by the public, future research on individuals' motivation to measure their BP at these kiosks and how we can utilize the results is warranted. The authors wish to thank Josh Sarkis and Lisa Goodwin at PharmaSmart for providing data access on BP readings obtained at their PS-2000 kiosks. Ms Houle receives funding for her PhD studies from the Canadian Institutes of Health Research, Hypertension Canada and the Interdisciplinary Chronic Disease Collaboration (funded by Alberta Innovates – Health Solutions). Dr Tsuyuki was previously a consultant for PharmaSmart Inc; however, no funding was received by PharmaSmart for this study, nor did they play any role in data analysis or interpretation.

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)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
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 score0.258
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.006
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 head0.312
GPT teacher head0.396
Teacher spread0.084 · 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.

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".

Quick stats

Citations10
Published2013
Admission routes3
Has abstractyes

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