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Record W4235424417 · doi:10.1016/j.ekir.2017.02.009

Recommended Standards for Assessing Blood Pressure in Human Research Where Blood Pressure or Hypertension Is a Major Focus

2017· article· en· W4235424417 on OpenAlexaff
True Consortium

Bibliographic record

VenueKidney International Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsHypertension Canada
Fundersnot available
KeywordsMedicineBlood pressureIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Although inaccurate, nonreproducible blood pressure values can result from nonstandardized assessments, recommended approaches to standardize blood pressure measurement are often not followed in research studies. METHODS: An expert consensus of national and international health and scientific organizations developed recommended minimum standards for assessing blood pressure in research subjects where: (i) blood pressure or hypertension is a major endpoint, or (ii) blood pressure is likely a major mediator of the research outcome. RESULTS: Minimum research standards are presented for training of observers, technical aspects of assessing blood pressure, and equipment for both adults and children. DISCUSSION: The standards are based on prior recommendations, some of which did not conform to current evidence-based methods. All new research should require adherence to these minimum standards on the patient populations described above. Readers need to use caution in interpreting studies if the standards are not met in the defined populations.

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)0.264
metaresearch head score (Gemma)0.552
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.736
Threshold uncertainty score0.907

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2640.552
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.007
Bibliometrics0.0130.008
Science and technology studies0.0040.008
Scholarly communication0.0070.005
Open science0.0180.006
Research integrity0.0190.025
Insufficient payload (model declined to judge)0.0070.007

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 head0.101
GPT teacher head0.419
Teacher spread0.318 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations22
Published2017
Admission routes1
Has abstractyes

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