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PurposeA relationship between mean heart dose (MHD) and acute coronary event (ACE) rate was reported in a study of patients with breast cancer (BC). The main objective of our cohort study was to validate this relationship and investigate if other dose-distribution parameters are better predictors for ACEs than MHD.Patients and MethodsThe cohort consisted of 910 consecutive female patients with BC treated with radiotherapy (RT) after breast-conserving surgery. The primary end point was cumulative incidence of ACEs within 9 years of follow-up. Both MHD and various dose-distribution parameters of the cardiac substructures were collected from three-dimensional computed tomography planning data.ResultsThe median MHD was 2.37 Gy (range, 0.51 to 15.25 Gy). The median follow-up time was 7.6 years (range, 0.1 to 10.1 years), during which 30 patients experienced an ACE. The cumulative incidence of ACE increased by 16.5% per Gy (95% CI, 0.6 to 35.0; P = .042). Analysis showed that the volume of the left ventricle receiving 5 Gy (LV-V5) was the most important prognostic dose-volume parameter. The most optimal multivariable normal tissue complication probability model for ACEs consisted of LV-V5, age, and weighted ACE risk score per patient (c-statistic, 0.83; 95% CI, 0.75 to 0.91).ConclusionA significant dose-effect relationship was found for ACEs within 9 years after RT. Using MHD, the relative increase per Gy was similar to that reported in the previous study. In addition, LV-V5 seemed to be a better predictor for ACEs than MHD. This study confirms the importance of reducing exposure of the heart to radiation to avoid excess risk of ACEs after radiotherapy for BC.

We observed a high incidence of significant AKI in a PICU population at risk, which was associated with high mortality. Pediatric RIFLE criteria may guide in the early identification of patients at risk for AKI and in the initiation of therapy.

Background: Shared decision making (SDM) is an interactive process between clinicians and patients in which both share information, deliberate together, and make clinical decisions. Clinics serving safety net patients face special challenges, including fewer resources and more challenging work environments. The use of SDM within safety net institutions has not been well studied.Methods: We recruited a convenience sample of 15 safety net primary care clinicians (13 physicians, 2 nurse practitioners). Each answered a 9-item SDM questionnaire and participated in a semistructured interview. From the transcribed interviews and questionnaire data, we identified themes and suggestions for introducing SDM into a safety net environment.Results

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