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Record W1866764238 · doi:10.1155/2015/801709

A Comparison of Casual In-Clinic Blood Pressure Measurements to Standardized Guideline-Concordant Measurements in Severely Obese Individuals

2015· article· en· W1866764238 on OpenAlexafffundabout
Sana Vahidy, Sumit R. Majumdar, Raj Padwal

Bibliographic record

VenueInternational Journal of Hypertension · 2015
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsDiabetes CanadaUniversity of Alberta
FundersCanadian Institutes of Health ResearchUniversity of AlbertaGovernment of Alberta
KeywordsMedicineCasualAlgorithmGuidelineMathematicsMaterials sciencePathology

Abstract

fetched live from OpenAlex

Background/Objectives. The objective of this study was to compare casual BP taken in a bariatric clinic to standardized guideline-concordant BP. Subjects/Methods. A cross sectional analysis was performed using baseline data from a weight management trial. Patients were recruited from a Canadian bariatric care program. Standardized BP was performed using a Watch BP oscillometric device. Casual in-clinic BP single readings, taken using a Welch Allyn oscillometric device, were chart-abstracted. Paired t-tests, Bland-Altman plots, and Pearson's correlations were used for analysis. Results. Data from 134 patients were analyzed. Mean age was 41.5 ± 8.9 y, mean BMI was 46.8 ± 6.5 kg/m(2), and 40 (30%) had prior hypertension. Mean casual in-clinic BP was 128.8 ± 14.1/81.6 ± 9.9 mmHg and mean standardized BP was 133.2 ± 15.0/82.0 ± 10.3 mmHg (difference of -4.3 ± 12.0 for systolic (p < 0.0001) and -0.4 ± 10.0 mmHg for diastolic BP (p = 0.6)). Pearson's coefficients were 0.66 (p < 0.0001) for SBP and 0.50 (p < 0.0001) for DBP. 28.4% of casual versus 26.9% of standardized measurements were ≥140/90 mmHg (p < 0.0001). Conclusion. In this bariatric clinic, casual BP was unexpectedly lower than standardized BP. This could potentially lead to the underdiagnosis of hypertension.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.258
GPT teacher head0.417
Teacher spread0.159 · 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 designObservational
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

Citations2
Published2015
Admission routes3
Has abstractyes

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