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P035 SOCIAL DETERMINANTS OF HEALTH AND CONTROL OF HYPERTENSION

2024· article· en· W4402610335 on OpenAlexaffabout
Alexander G. Logan, Inna Lokteva, Yuhua Zhang, ZhihuiAmy Liu

Bibliographic record

VenueJournal of Hypertension · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsUniversity Health NetworkLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsMedicineSocial determinants of healthControl (management)Environmental healthPublic healthNursingArtificial intelligence

Abstract

fetched live from OpenAlex

Background and Objectives: Recent national blood pressure (BP) survey data of adults in Canada and United States show a troubling decline in the control of hypertension, particularly in women, the elderly and those with low income, less education and under-using health services. Social determinants of health (SDH) can be important barriers to controlling hypertension. Studies assessing associations of BP control and SDH have focused on one or a few domains. Objectives of this study are to screen treated hypertensive patients for a wide range of SDH, test for correlations and assess the effects of high-quality treatment on SDH and BP control relationship. Method: We created and applied a screening tool to gather personal information on 14 SDH from consecutive consenting eligible patients attending a complex hypertension care clinic. Logistic regression was used to assess association of each SDH domain with BP control. Results: Of 90 patients enrolled, 88 completed the 6-month study. At baseline, mean age (standard deviation) was 64 (14) years, 64% male, 69% white, 25% experiencing financial hardship, mean BMI 30.4 kg/m2 (5.9), mean automated office BP 138/78 (23/14), mean number of co-morbid conditions 4.2 (2.0) and 55% had treatment-resistant hypertension. From baseline to exit, BP fell to 127/73 (17/12), p<0.001, mean number of antihypertensive drug classes increased from 3.06 (1.43) to 3.23 (1.30), p=0.049 but BMI remained unchanged. There were no associations between uncontrolled hypertension and any of the 14 SDOH domains at baseline. However, at exit financial status was associated with uncontrolled hypertension on univariate analysis (p=0.022) and on multivariate analysis. Stress (p=0.063) and optimism status (p=0.085] showed a similar trend. These analyzes indicated better BP control among those with poorer financial status, higher stress levels or more pessimistic outlook. Conclusion: None of the SDOH were associated with uncontrolled hypertension at baseline. However good medical care and follow-up appeared to have improved BP control, noticeably in those experiencing financial hardship. Explanation of findings requires further study.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.151
GPT teacher head0.424
Teacher spread0.273 · 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 designObservational
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

Citations0
Published2024
Admission routes2
Has abstractyes

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