Al-Kindi, Sadeer

Abstract Introduction Cardiovascular disease (CVD) is the leading cause of death among patients with kidney failure on dialysis. Social determinants of health may worsen this risk but are seldom incorporated into prognostic models. ICD-10 Z-codes provide standardized documentation of social determinants of health, yet their prognostic value in dialysis populations remains uncertain. This study examined whether Z-coded social determinants of health are associated with adverse cardiovascular outcomes and mortality among patients receiving dialysis for kidney failure. Methods A retrospective cohort study was conducted using the TriNetX Research Network (2010–2024), encompassing de-identified data from 103 institutions. Adults with kidney failure on chronic dialysis were stratified by the presence of ICD-10 Z-codes (Z55–Z65). Propensity score matching (1:1) balanced demographics, comorbidities, medications, and laboratory values. Primary outcomes were all-cause mortality and hospitalization; secondary outcomes included acute heart failure, myocardial infarction, stroke, cardiac arrest, bradyarrhythmias, and ventricular tachycardia. Results After matching, mean age was 62 years, and 42.4% were female in the Z-code cohort versus 41.2% in controls. Over one year, mortality occurred in 12.5% versus 10.9% (hazard ratio [HR], 1.22; 95% confidence interval [CI], 1.15–1.29) and all-cause hospitalizations in 57.3% versus 53.1% (HR, 1.22; 95% CI, 1.19–1.26). Cardiovascular complications were consistently higher in Z-coded patients, including heart failure (24.3% vs 20.5%; HR, 1.29), myocardial infarction (8.0% vs 7.1%; HR, 1.19), stroke (6.6% vs 6.2%; HR, 1.13), cardiac arrest (3.8% vs 3.1%; HR, 1.29), and bradyarrhythmias (6.9% vs 5.5%; HR, 1.33). Discussion Among patients with kidney failure, documented Z-coded social risk factors were associated with greater mortality and cardiovascular morbidity. Incorporating social determinants of health documentation into nephrology care may improve risk stratification and inform targeted interventions.

Background Although micro‐ and nanoplastics are an emerging risk factor for the development of cardiovascular diseases, the association of marine microplastic levels (MMLs) with the burden of cardiometabolic diseases at a population level remains unexplored. We investigated the relationship between the mean microplastic concentration in ocean water within 200 nautical miles of the US coastline and the prevalence of type 2 diabetes, coronary artery disease, and stroke in nearby counties. Methods Microplastic concentration data within 200 nautical miles of the US coastline were geospatially analyzed to calculate mean MMLs. The coastal counties were stratified into 4 categories based on MMLs in the adjacent ocean water body: low, medium, high, or very high. The Behavioral Risk Factor Surveillance System 2019 to 2020 survey data were used to identify the prevalence of type 2 diabetes, coronary artery disease, and stroke in these counties. Univariate and population‐weighted multivariate quasi‐Poisson regression, adjusted for county‐level confounding variables, was used to evaluate the unadjusted and adjusted associations between disease prevalence and MMLs. Results The mean age of the population was 43±6 years. After adjusting for age, sex, physician access, and socioenvironmental vulnerabilities at the county level, counties with very high MMLs exhibited an 18%, 7%, and 9% higher adjusted prevalence of type 2 diabetes, coronary artery disease, and stroke, respectively, compared with those with low levels. Conclusion Marine microplastic levels were significantly associated with the prevalence of cardiometabolic diseases in coastal counties. Comprehensive studies at an individual level are needed to further investigate the health impacts of microplastic pollution.

Background Although cardiovascular mortality (CVM) rates in the United States have been declining overall, our study evaluated whether this holds true for areas with increased social deprivation. Methods and Results We used county‐level cross‐sectional age‐adjusted CVM rates (aa‐CVM) (2000–2019) linked to the Centers for Disease Control and Prevention Social Vulnerability Index (SVI–2010). We grouped counties as per SVI (Groups I 0–0.2, II 0.21–0.4, III 0.41–0.6, IV 0.61–0.8, and V 0.81–1) and calculated the relative change in the aa‐CVM between 2000 to 2003 and 2016 to 2019. We used adjusted linear regression analyses to explore the association between a higher SVI and temporal aa‐CVM improvement; we studied this temporal change in aa‐CVM across subgroups of race, sex, and location. The median aa‐CVM rate (per 100 000) was 272.6 (interquartile range [IQR]: 237.5–311.7). The aa‐CVM was higher in men (315.6 [IQR: 273.4–363.9]) than women (221.3 [IQR: 189.6–256.7]), and in Black residents (347.2 [IQR: 301.1–391.1]; P <0.001) than White residents (258.9 [IQR: 226–299.1]; P <0.001). The aa‐CVM for SVI I (233.6 [IQR: 214.8–257.0]) was significantly lower than that of group V (323.6 [IQR: 277.2–359.2]; P <0.001). The relative reduction in CVM was significantly higher for SVI group I (32.2% [IQR: 24.2–38.4]) than group V (27.2% [IQR: 19–34.1]) counties. After multivariable adjustment, a higher SVI index was associated with lower relative improvement in the age‐adjusted CVM (model coefficient −3.11 [95% CI, −5.66 to −1.22]; P <0.001). Conclusions Socially deprived counties in the United States had higher aa‐CVM rates, and the improvement in aa‐CVM over the past 20 years was lower in these counties.