ArticleCardiology research and practice2021
Racial and Socioeconomic Disparities in Out-Of-Hospital Cardiac Arrest Outcomes: Artificial Intelligence-Augmented Propensity Score and Geospatial Cohort Analysis of 3,952 Patients.
Article in Cardiology research and practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 27 citations in OpenAlex.
- Disparities in Emergency Medical Services Intra-Arrest Transport by Neighborhood Socioeconomic Vulnerability.JAMA network open · 2026Article
- An open-source application for self-service, Health Insurance and Portability Accountability Act-compliant geocoding.Journal of clinical and translational science · 2026Article
- Use of artificial intelligence in the out-of-hospital care settings: a scoping review.BMJ digital health & AI · 2026Article
- Does Single Dose Epinephrine Improve Outcomes for Patients with Out-of-Hospital Cardiac Arrest by Sex or Race?The western journal of emergency medicine · 2025Article
- Reshaping transplantation with AI, emerging technologies and xenotransplantation.Nature medicine · 2025Review
- 2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.Circulation · 2025Review
- Artificial Intelligence to Promote Racial and Ethnic Cardiovascular Health Equity.Current cardiovascular risk reports · 2024Article
- 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.Circulation · 2024Review
- Sociodemographic Factors and the Risk of Pediatric Out-of-Hospital Cardiac Arrest in Ontario, Canada: A Province-Wide Case-Control Study.Journal of the American Heart Association · 2024Article
- New Innovations to Address Sudden Cardiac Arrest.US cardiology · 2024Review
- Big Data, Big Insights: Leveraging Data Analytics to Unravel Cardiovascular Exposome Complexities.Methodist DeBakey cardiovascular journal · 2024Review
- Artificial intelligence to support out-of-hospital cardiac arrest care: A scoping review.Resuscitation plus · 2023Article
- Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association.Circulation · 2023Review
- Using Pointwise Mutual Information for Breast Cancer Health Disparities Research With SEER-Medicare Claims.Methodology : European journal of research methods for the behavioral & social sciences · 2023Article
- Racial/ethnic and gender disparities of the impact of the COVID-19 pandemic in out-of-hospital cardiac arrest (OHCA) in Texas.Resuscitation · 2022Article
- Artificial Intelligence-Augmented Propensity Score, Cost Effectiveness and Computational Ethical Analysis of Cardiac Arrest and Active Cancer with Novel Mortality Predictive Score.Medicina (Kaunas, Lithuania) · 2022Article
- Fractional Flow Reserve Cardio-Oncology Effects on Inpatient Mortality, Length of Stay, and Cost Based on Malignancy Type: Machine Learning Supported Nationally Representative Case-Control Study of 30 Million Hospitalizations.Medicina (Kaunas, Lithuania) · 2022Article
- Consequences of inequity in the neurosurgical workforce: Lessons from traumatic brain injury.Frontiers in surgery · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSocial disparities in out-of-hospital cardiac arrest (OHCA) outcomes are preventable, costly, and unjust. We sought to perform the first large artificial intelligence- (AI-) guided statistical and geographic information system (GIS) analysis of a multiyear and multisite cohort for OHCA outcomes (incidence and poor neurological disposition).
methodWe conducted a retrospective cohort analysis of a prospectively collected multicenter dataset of adult patients who sequentially presented to Houston metro area hospitals from 01/01/07-01/01/16. Then AI-based machine learning (backward propagation neural network) augmented multivariable regression and GIS heat mapping were performed.
resultsOf 3,952 OHCA patients across 38 hospitals, African Americans were the most likely to suffer OHCA despite representing a significantly lower percentage of the population (42.6 versus 22.8%;
conclusionThis large, longitudinal AI-guided analysis statistically and geographically identifies racial and socioeconomic disparities in OHCA outcomes in a way that may allow targeted medical and public health coordinated efforts to improve clinical, cost, and social equity outcomes.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.