Background We aimed to develop and feasibility test an educational video culturally targeted to African American (AA) patients regarding kidney allocation. Methods We iteratively refined an animated video for AAs with multiple stakeholder input and conducted a one‐group, pre–post study with 50 kidney transplant candidates to assess video feasibility and acceptability. A mixed population was chosen to obtain race‐specific acceptability data and efficacy estimates for a larger study. Results Median participant age was 56 years, and 50% were AA. Comparing pre–post video scores, large knowledge effect sizes were found for the cohort (r = 0.7) and in the context of AA race (r = 0.8), low health literacy (r = 0.6), low educational achievement (r = 0.7), age >55 years (r = 0.6), dialysis vintage ≥1 year (r = 0.8), low income (r = 0.7) and low technology access (r = 0.8). Over 87% of participants provided positive ratings on each of the seven acceptability items. The frequency of positive responses increased pre–post video for kidney allocation understanding (78% vs 94%, P = 0.008), decisional self‐efficacy (64% vs 88%, P < 0.001) and belief in fairness (76% vs 90%, P = 0.02). Conclusions In collaboration with key stakeholders, a culturally targeted educational video was developed that was well received. Results are promising to impact kidney allocation knowledge among AA and non‐AA kidney transplant candidates.

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Introduction Multiple risk models are used to predict the presence of obstructive coronary artery disease (CAD) in patients with chest pain. We aimed to compare the performance of these models to an experienced cardiologist's assessment utilizing coronary angiography (CA) as a reference. Materials and methodsWe prospectively enrolled patients without known CAD referred for elective CA. We assessed pretest probability of CAD using the following risk models: Diamond-Forrester (original and updated), Duke Clinical score, ACC/AHA, CAD consortium (basic and clinical) and PROMISE minimal risk tool. All patients completed self-administrative Rose angina questionnaire. Independently, an experienced cardiologist assessed the patients to provide a binary prediction of obstructive CAD prior to CA. Obstructive CAD was defined as >80% stenosis in epicardial coronary arteries by visual assessment, or fractional flow reserve <0.80 in intermediate lesions (30-80%).Results A total of 150 patients were recruited (100 women, 50 men). Mean age was 58 (32-78) years. Obstructive CAD was found in 31 patients (21%). The area under the curve (AUC) for all the clinical risk prediction models (except the Duke Clinical Score, AUC 0.73, P = 0.07) was significantly lower compared with the clinician's assessment (AUC 0.51-0.65 vs. 0.81, respectively, P < 0.01). The clinician's assessment had sensitivity comparable to the Duke Clinical score, which was higher than all other clinical models. There was no difference in prediction performance on the basis of sex in this predominantly female population. Discussion/ConclusionIn stable patients with chest pain and suspected CAD, current clinical risk models which are universally based upon the characteristics of the chest pain, show suboptimal performance in predicting obstructive CAD. These findings have important clinical implications, as current appropriateness criteria for recommending CA are on the basis of these risk models.

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