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Record W4410159610 · doi:10.14740/cr1748

Complex Interactions of Social Determinants of Health on Survival Outcomes in Hispanic Patients With Pulmonary Arterial Hypertension in a US-Mexican Border City

2025· article· en· W4410159610 on OpenAlexvenueno aff
Hedaia Algheriani, Marco Cazares-Parson, Michael Brockman, Bobak Zakhireh, Sunil Kumar Srinivas, Debabrata Mukherjee, Alok Dwivedi, Nils Nickel

Bibliographic record

VenueCardiology Research · 2025
Typearticle
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsnot available
FundersTexas Tech University
KeywordsMedicineInternal medicineCardiologyPulmonary hypertensionDemography

Abstract

fetched live from OpenAlex

Background: Pulmonary arterial hypertension (PAH) is a chronic disease of the pulmonary blood vessels that can lead to right heart failure, resulting in increased morbidity and mortality if left untreated. While right heart hemodynamics and functional capacity are a well-established predictors of outcome in PAH, emerging evidence suggests that social determinants of health (SDOH) may have a significant impact on patients with PAH, influencing outcomes and survival rates. This study explores the impact of SDOH and their intricate interactions on survival among a Hispanic patient cohort along the US-Mexico border. Methods: A retrospective analysis was conducted on a single-center cohort of 158 PAH patients (72% female, mean age 58 years) using Cox proportional hazards models and latent class analyses. The primary outcome was mortality during the follow-up period, with secondary analyses examining the impact of individual and combined SDOH on survival. Results: During a mean follow-up period of 3.8 years (range: 0.2 to 6 years), 37 patients (23.4%) died. Lack of health insurance (hazard ratio (HR) 2.17; 95% confidence interval (CI): 1.05 - 4.49, P = 0.037) and unemployment (HR 2.99; 95% CI: 1.42 - 6.30, P = 0.004) were significantly associated with a higher risk of death within 5 years of follow-up. Latent variable modeling revealed that patients aged ≥ 60 years, who were uninsured, unmarried, and unemployed along with greater PAH severity (measured with cardiac output, mean pulmonary arterial pressure, six-minute walk distance, and World Health Organization Functional Class > 2) had the highest risk of poor outcomes (HR 3.6, 95% CI: 1.9 - 6.8, P < 0.001). Interestingly, the type of insurance did not have a significant impact on survival. Conclusion: The findings underscore the critical need for improved access to insurance coverage and enhanced social support to promote better health outcomes among this vulnerable Hispanic population. Addressing these SDOH is essential in closing the health disparity gap and improving survival rates in PAH patients.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.113
GPT teacher head0.440
Teacher spread0.327 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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