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Record W4412753016 · doi:10.15420/japsc.2024.57

Community Hypertension Care in Sri Lanka: Current Approaches and Opportunities

2025· article· en· W4412753016 on OpenAlexaff
Nazneem Wahab, Neranga Samaratunge, Dulaanga Rathnayake

Bibliographic record

VenueJournal of Asian Pacific Society of Cardiology · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsRoyal Alexandra Hospital
Fundersnot available
KeywordsSri lankaCurrent (fluid)MedicineBusinessIntensive care medicineEnvironmental planningGeographyEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Non-communicable disease-related deaths account for 69% of deaths in Southeast Asia. Hypertension (HTN) is the leading risk factor for non-communicable diseases globally. Sri Lanka, a low–middle-income South Asian country, has a population prevalence of HTN of 35%. A narrative synthesis combining results from academic medical databases and relevant grey literature was performed to review Sri Lanka’s national healthcare strategy for HTN management in outpatient clinical settings. Despite significant investments in primary healthcare infrastructure, only approximately 2% of the target adult population is screened annually and only approximately 40% of patients with documented HTN have achieved treatment goals. HTN management remains difficult due to broader health system challenges and sociodemographic factors. Preventative medicine is still conceptually quite unfamiliar to the population. Additional strategies to improve community HTN care should include a team-based systematic approach, patient-centric community-based education and corporate and civic partnerships to improve healthcare delivery and promote public awareness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.119
GPT teacher head0.298
Teacher spread0.179 · 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 designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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