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Blood pressure measurement and the guidelines: a proposed new algorithm for the diagnosis of hypertension

2004· review· en· W1991932874 on OpenAlexaff
Martin G. Myers

Bibliographic record

VenueBlood Pressure Monitoring · 2004
Typereview
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsUniversity of TorontoWomen's College HospitalHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineSphygmomanometerBlood pressureAmbulatory blood pressureAmbulatoryMercury (programming language)Medical emergencyIntensive care medicineInternal medicineComputer science

Abstract

fetched live from OpenAlex

Current hypertension guidelines continue to base management decisions on the office BP as recorded by mercury sphygmomanometry. The imminent disappearance of mercury from the workplace for environmental and safety reasons provides an opportunity to re-assess how a diagnosis of hypertension is made. There are now several validated, automated BP recording devices available to replace mercury sphygmomanometers in the office setting. Self/home and 24-hour ambulatory BP monitoring should now become an integral part of the diagnostic algorithm for hypertension in view of their superior ability to predict clinical outcomes when compared to traditional office BP measurements.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0120.009
Science and technology studies0.0010.002
Scholarly communication0.0040.007
Open science0.0060.002
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0040.004

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 head0.182
GPT teacher head0.343
Teacher spread0.161 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations17
Published2004
Admission routes1
Has abstractyes

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