Inclusion of Under-Represented Racial and Ethnic Groups in Cardiovascular Clinical Trials.

INTRODUCTION: Non-White racial and ethnic groups have been traditionally under-represented for decades in the field of cardiology, specifically in cardiovascular research studies. This underrepresentation has occurred despite the fact that these racial and ethnic groups have been shown to be at increased risk of cardiovascular disease (CVD). METHODS: To assess the trend of representation in mainstream landmark cardiovascular trials, we performed a review of major cardiovascular trials published between 1986 and 2019. Mainstream landmark trials were selected as classified by established cardiology standards. The reported numbers of racial and ethnic participants were assessed within these categorised cardiovascular trials over a continuous time period. RESULTS: A total of 1,138,683 patients were assessed from 153 randomised clinical trials. Of these trials, only 56% (n=86) reported information about race. Of note, 99% (n=152) of these trials reported gender. About three-quarters of the trials (77%) were undertaken at least partly in the United States (US). Our results show that the percentage of non-White participants in clinical trials was not significantly different over time (p=0.85), suggesting no significant improvement in non-White racial/ethnic representation. Further analysis of only the US inclusive trials (n=20) also showed no significant improvement in representation (p=0.38). CONCLUSION: Only about half of all major cardiovascular landmark trials reported any racial or ethnic information, despite more recent calls over the last 5-10 years for diversity and representation in cardiovascular research studies. Additionally, no significant improvement in inclusion of traditionally under-represented racial and ethnic groups (UREGs) in these trials has occurred over time. Our analysis shows that there is still major work to be done to foster better representation and evaluation of the UREG population in cardiovascular trials.

Kidney Injury and Repair Biomarkers in Marathon Runners.

BACKGROUND: Investigation into strenuous activity and kidney function has gained interest given increasing marathon participation. STUDY DESIGN: Prospective observational study. SETTING & PARTICIPANTS: Runners participating in the 2015 Hartford Marathon. PREDICTOR: Completing a marathon. OUTCOMES: Acute kidney injury (AKI) as defined by AKI Network (AKIN) criteria. Stage 1 AKI was defined as 1.5- to 2-fold or 0.3-mg/dL increase in serum creatinine level within 48 hours of day 0 and stage 2 was defined as a more than 2- to 3-fold increase in creatinine level. Microscopy score was defined by the number of granular casts and renal tubular epithelial cells. MEASUREMENTS: Samples were collected 24 hours premarathon (day 0), immediately postmarathon (day 1), and 24 hours postmarathon (day 2). Measurements of serum creatinine, creatine kinase, and urine albumin were completed, as well as urine microscopy analysis. 6 injury urine biomarkers (IL-6, IL-8, IL-18, kidney injury molecule 1, neutrophil gelatinase-associated lipocalin, and tumor necrosis factor α) and 2 repair urine biomarkers (YKL-40 and monocyte chemoattractant protein 1) were measured. RESULTS: 22 marathon runners were included. Mean age was 44 years and 41% were men. 82% of runners developed an increase in creatinine level equivalent to AKIN-defined AKI stages 1 and 2. 73% had microscopy diagnoses of tubular injury. Serum creatinine, urine albumin, and injury and repair biomarker levels peaked on day 1 and were significantly elevated compared to day 0 and day 2. Serum creatine kinase levels continued to significantly increase from day 0 to day 2. LIMITATIONS: Small sample size and limited clinical data available at all time points. CONCLUSIONS: Marathon runners developed AKI and urine sediment diagnostic of tubular injury. An increase in injury and repair biomarker levels suggests structural damage to renal tubules occurring after marathon. The results of our study should be validated in larger cohorts with longer follow-up of kidney function.

Determining the clinical significance of computer interpreted electrocardiography conclusions.

BACKGROUND: Computerized electrocardiogram (EKG) interpretation technology was developed in the mid-20th century, but its use continues to be controversial. This study aims to determine clinical factors which indicate greater odds of clinical significance of an abnormal computerized EKG interpretation. METHODS: The inclusion criteria for this retrospective study were patients who underwent outpatient echocardiography for the indication of an abnormal EKG and had an EKG abnormality diagnosed by the computerized EKG system. Qualifying patients had the results of their computerized EKG, echocardiogram, and charted patient characteristics collected. Computerized diagnoses and patient characteristics were assessed to determine if they were associated with increasing or decreasing the odds of an echocardiographic abnormality via logistic regression. Chi-square and t-test analyses were used for categorical and continuous variables, respectively. Odds ratios are presented as odds ratio [95% confidence interval]. A P-value of ≤ 0.05 was considered statistically significant. RESULTS: A total of 515 patients were included in this study. The population was 59% women with an average age of 57 ± 16 years, and a mean BMI of 30.1 ± 7.3 kg/m2. Patients with echocardiographic abnormalities tended to have more cardiac risk factors than patients without abnormalities. In our final odds ratio model consisting of both patient characteristics and EKG diagnoses, age, coronary disease (CAD), and diabetes mellitus (DM) increased the odds of an echocardiographic abnormality (1.04 [1.02-1.06], 2.68 [1.41-5.09], and 1.75 [1.01-3.04], respectively). That model noted low QRS voltage decreased the odds of an abnormal echocardiogram (0.31 [0.10-0.91]). CONCLUSION: Our findings suggest that in patients with an abnormal computerized EKG reading, the specific factors of older age, CAD, and DM are associated with higher odds of abnormalities on follow-up echocardiography. These results, plus practitioner overreading, can be used to determine more appropriate management when faced with an abnormal computerized EKG diagnosis.