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Hypertension in China

2018· letter· en· W2805890292 on OpenAlexaff
Norman R.C. Campbell, Xinhua Zhang

Bibliographic record

VenueCirculation · 2018
Typeletter
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsLibin Cardiovascular Institute of Alberta
Fundersnot available
KeywordsMedicineChinaCardiologyIntensive care medicine

Abstract

fetched live from OpenAlex

Hypertension in China Time to Transition From Knowing the Problem to Implementing the SolutionArticle, see p 2344 T he Global Burden of Disease Study estimated that increased blood pressure was the world's leading risk for death, contributing to >10 million deaths in 2016. 1 Hypertension is very common, with 40% of those >25 years of age having high blood pressure, representing ≈1.4 billion people worldwide.2 Almost half of those with hypertension are unaware, and although many of those who are aware are treated with antihypertensive drugs, most do not have their blood pressure lowered to recommended targets.3 How does China, the most populous nation in the world, fare?Wang et al 4 report in this issue of Circulation results from a large population blood pressure survey providing up-to-date data for China.The survey methods included stratified multistage random sampling to provide data representative of the Chinese population >15 years of age and the assessment of blood pressure using a standardized technique with a validated electronic manometer.Specifically, the survey was designed to examine blood pressure in 14 age-sex groups, in rural and urban settings, and in all 31 provinces of China.The survey methodology and the overall response rate of 66.4% are similar to those of other high-quality population blood pressure surveys.The survey data largely reflect global data in many regards, but in such a large population, the numbers are staggering 4 : Almost 250 million people have hypertension, >125 million are unaware, close to 150 million are not on antihypertensive drug therapy (59.3%), and "only" 37 million (15.3%) are controlled.4 Just over 435 million (40%) adult Chinese had prehypertension.Minority ethnic populations had lower rates of awareness (36.9% versus 48.0%), treatment (29.5% versus 42.0%), and control (8.4% versus 16.1%) compared with urban populations of Han ethnicity.4 Recently, the American College of Cardiology/American Heart Association hypertension guidelines were released, with 2 major features being a change in the definition of hypertension from 140/90 to 130/80 mm Hg and a recommendation to treat those at high cardiovascular risk who meet or exceed 130/80 mm Hg. 5 Almost 50% of adults in China meet the new definition for hypertension, but a relatively small increment (≈2%) meet the new criteria to be prescribed hypertension pharmacotherapy.6 Nevertheless, the current task of identifying those who have hypertension by the 140/90 mm Hg criterion is enormous and likely to exceed primary care capacity for many years to come.Adoption of the 130/80 mm Hg criterion is likely to occur over time with a focus on identification of those at high cardiovascular risk.6 The needless human morbidity and suffering from chronic disease led by hypertension-related diseases have been viewed as a major threat to global economic development.7 As a result, the World Health Assembly agreed to 9 targets to reduce

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.041
GPT teacher head0.261
Teacher spread0.220 · 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 designObservational
Domainnot available
GenreEditorial

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".

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Citations35
Published2018
Admission routes1
Has abstractno

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