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Record W3049346174 · doi:10.1111/jch.14008

Comparison between unattended automated office blood pressure and conventional office blood pressure under the environment of health checkup among Japanese general population

2020· article· en· W3049346174 on OpenAlexaboutno aff
Hirofumi Sakuma, Naoki Nakagawa, Kiwamu Horiuchi, Taiki Hayasaka, Keisuke Maruyama, Jun Sawada, Akiho Minoshima, Takayuki Fujino, Toshiharu Takeuchi, Nobuyuki Sato, Shinobu Osanai, Naoyuki Hasebe

Bibliographic record

VenueJournal of Clinical Hypertension · 2020
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBlood pressureInternal medicinePopulationClinical PracticeSignificant differenceCardiovascular healthMean differenceCardiologyPhysical therapyConfidence interval

Abstract

fetched live from OpenAlex

Unattended automated office blood pressure (AOBP) measurement has been endorsed as the preferred in-office measurement modality in recent Canadian and American clinical practice guidelines. However, the difference between AOBP and conventional office blood pressure (CBP) under the environment of a health checkup remains unclear. We aimed to identify the clinical significance of AOBP as compared to CBP under the environment of a health checkup. There were 491 participants (333 females, mean age of 62.5 years) who were at least 20 years old, including 179 participants who were previously diagnosed with hypertension. Mean AOBPs were 131.8 ± 20.9/76.6 ± 11.7 mm Hg, and CBPs were 135.6 ± 21.6/77.3 ± 11.5 mm Hg. There was a difference of 3.9 mm Hg in systolic blood pressure (SBP) and 0.8 mm Hg in diastolic BP between AOBP and CBP. In all participants, SBP and pulse pressure, as well as the white coat effect (WCE), increased with age. The cutoff value used was 140/90 mm Hg for CBP and 135/85 mm Hg for AOBP, and the prevalence of WCE and masked hypertension effect (MHE) was 12.4% and 14.1%, respectively. Even in a health checkup environment of the general population, there was a difference between the AOBP and CBP, and the WCE was observed more strongly in the elderly with a history of hypertension, suggesting that a combination of AOBP with CBP may be useful in detecting WCE and MHE in all clinical scenarios including health checkups, and help solve the "hypertension paradox" not only in Japan but in all over the world.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.043
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.112
GPT teacher head0.369
Teacher spread0.257 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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