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Record W1969506301 · doi:10.1136/bmj.d4891

Management of hypertension: summary of NICE guidance

2011· article· en· W1969506301 on OpenAlexaboutno aff
T. Krause, Kate Lovibond, Mark J. Caulfield, Terry McCormack, Bryan Williams

Bibliographic record

VenueBMJ · 2011
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
FundersNational Institute for Health and Care Research
KeywordsNiceExcellenceGuidelineMedicineBest practiceSystematic reviewPrimary careExpert opinionQuarter (Canadian coin)Family medicineAlternative medicineEvidence-based practiceClinical PracticeMEDLINEPediatricsIntensive care medicinePathologyComputer scienceManagement

Abstract

fetched live from OpenAlex

Hypertension is one of the most important preventable causes of death worldwide and one of the commonest conditions treated in primary care in the United Kingdom, where it affects more than a quarter of all adults and over half of those over the age of 65 years.1 This article summarises the most recent recommendations from the National Institute for Health and Clinical Excellence (NICE) on the management of hypertension,2 which updates the 2004 and 2006 clinical guidelines.3 4 5 NICE recommendations are based on systematic reviews of best available evidence and explicit consideration of cost effectiveness. When minimal evidence is available, recommendations are based on the Guideline Development Group’s experience and opinion of what constitutes good practice. Evidence levels for the recommendations are given in italic in square brackets. ### Diagnosing hypertension (Updated recommendation) [ Based on the experience and opinion of the Guideline Development Group (GDG) ]

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)0.043
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.043
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0060.002
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0160.010

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 head0.099
GPT teacher head0.293
Teacher spread0.194 · 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

Citations485
Published2011
Admission routes1
Has abstractyes

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