Racial and Gender Differences in Patient Satisfaction Scores Among Oncologists.

BACKGROUND: Patient satisfaction scores (PSS) have been adopted in health care reimbursement and faculty promotion metrics. Oncology patients face a challenging prognosis, where PSS may be perceived differently. We hypothesized that PSS differed based on gender and racial demographics of oncologists. MATERIALS AND METHODS: This was an institutional review board exempt cross-sectional study utilizing PSS data for outpatient oncologists within a large comprehensive cancer center. Patient demographics included age, gender, race/ethnicity, geographical residence, and disease site. Characteristics of oncologists included gender and race/ethnicity. We used PSS ≥95 to make comparisons. The association between patient and physician characteristics were evaluated using the t test and χ2 test. RESULTS: A total of 15,849 oncology patients were identified between 2011 and 2020. Survey respondents were predominantly female (53.2%), white (93.4%), between 50 and 70 years of age (55.3%), and living in an urban setting (63.6%). There were 303 oncologists with the majority being male (64.4%) and white (58.1%). Compared with white oncologists, Asian and Hispanic oncologists received lower PSS (P=0.001 and 0.0085, respectively). On subset analysis, these differences were significant among patients older than 50 years, living in rural counties, and reporting white or non-Hispanic race/ethnicity, or among patients of either gender (all P<0.05). Patients with genitourinary malignancies provided lower PSS for female oncologists (P=0.005). CONCLUSIONS: Asian and Hispanic oncologists were more likely to receive lower PSS. In addition, female oncologists treating genitourinary malignancies received lower PSS. Appropriate statistical adjustments are needed for PSS among oncologists to account for race, gender, and physician subspecialization to allow for equitable professional opportunities across demographics.

Validating an Idiopathic Dilated Cardiomyopathy Diagnosis Using Cardiovascular Magnetic Resonance: The Dilated Cardiomyopathy Precision Medicine Study.

BACKGROUND: Coronary angiography to identify coronary artery disease has been foundational to distinguish the cause of dilated cardiomyopathy (DCM), including the assignment of idiopathic or ischemic cardiomyopathy. Late gadolinium enhancement (LGE) with cardiovascular magnetic resonance (CMR) has emerged as an approach to identify myocardial scar and identify etiology. METHODS: The DCM Precision Medicine Study included patients with left ventricular dilation and dysfunction attributed to idiopathic DCM, after expert clinical review excluded ischemic or other cardiomyopathies. Ischemic cardiomyopathy was defined as coronary artery disease with >50% narrowing at angiography of ≥1 epicardial coronary artery. CMR was not required for study inclusion, but in a post hoc analysis of available CMR reports, patterns of LGE were classified as (1) no LGE, (2) ischemic-pattern LGE: subendocardial/transmural, (3) nonischemic LGE: midmyocardial/epicardial. RESULTS: Of 1204 idiopathic DCM patients evaluated, 396 (32.9%) had a prior CMR study; of these, 327 (82.6% of 396) had LGE imaging (mean age 46 years; 53.2% male; 55.4% White); 178 of the 327 (54.4%) exhibited LGE, and 156 of the 178 had LGE consistent with idiopathic DCM. The remaining 22 had transmural or subendocardial LGE. Of these 22, coronary angiography was normal (13), showed luminal irregularities (3), a distant thrombus (1), coronary artery disease with <50% coronary artery narrowing (1), or was not available (4). CONCLUSIONS: Of 327 probands enrolled in the DCM Precision Medicine Study cohort who had LGE-CMR data available, an ischemic-pattern of LGE was identified in 22 (6.7%), all of whom had idiopathic DCM as adjudicated by expert clinical review. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03037632.

Abnormal Cardiac Repolarization After Seizure Episodes in Structural Brain Diseases: Cardiac Manifestation of Electrical Remodeling in the Brain?

Background Abnormal cardiac repolarization is observed in patients with epilepsy and can be associated with sudden death. We investigated whether structural brain abnormalities are correlated with abnormal cardiac repolarizations in patients with seizure or epilepsy. Methods and Results We retrospectively analyzed and compared 12-lead ECG parameters following seizures between patients with and without structural brain abnormalities. A total of 96 patients were included: 33 women (17 with and 16 without brain abnormality) and 63 men (44 with and 19 without brain abnormality). Brain abnormalities included past stroke, chronic hematoma, remote bleeding, tumor, trauma, and postsurgical state. ECG parameters were comparable for heart rate, PR interval, and QRS duration between groups. In contrast, corrected QT intervals evaluated by Fridericia, Framingham, and Bazett formulas were prolonged in patients with brain abnormality compared with those without (women: Fridericia [normal versus abnormal], 397.4±32.7 versus 470.9±48.9; P=0.002; Framingham, 351.0±40.1 versus 406.2±46.1; P=0.002; Bazett, 423.8±38.3 versus 507.7±56.6; P<0.0001; men: Fridericia, 403.8±30.4 versus 471.0±47.1; P<0.0001; Framingham, 342.7±36.4 versus 409.4±45.8; P<0.0001; Bazett, 439.3±38.6 versus 506.2±56.8; P<0.0001). QT dispersion and Tpeak-Tend intervals were comparable between groups. We also observed abnormal ST-segment elevation in 5 patients. Importantly, no patients showed fatal arrhythmias during or after seizures. Conclusions Our study demonstrated that brain abnormalities can be associated with abnormal cardiac repolarization after seizures, which might be a manifestation of electrophysiological remodeling in the brain.

Where Are the Women in Radiation Oncology? A Cross-Sectional Multi-Specialty Comparative Analysis.

PURPOSE: We aimed to evaluate the growth of women within the general radiation oncology (RO) workforce in comparison to the growth among other medical specialties. We also sought to create a predictive model for gender diversity to guide future recruitment efforts. METHODS AND MATERIALS: We identified 16 medical specialties, including RO, for analyses. We used data from the Association of American Colleges and assessed female representation at 4 time points (2006, 2011, 2016, and 2020). Additionally, we determined characteristics of medical specialties that were predictive of increased gender diversity. We performed univariate statistical analysis with linear regression to evaluate factors predictive of greater gender diversity among the medical specialties in our cohort. RESULTS: The proportion of women within the represented specialties increased over time. Obstetrics/gynecology (14,750 [2006], 23,921 [2020]; 18.7% absolute growth) and dermatology (3568 [2006], 6329 [2020]; 15.1% absolute growth) experienced the highest absolute growth in female representation between 2006 and 2020. When assessing changes between various time points in RO, the absolute change in female physicians increased by 1.5% between 2006 and 2011, by 2.2% between 2011 and 2016, and by only 0.4% between 2016 and 2020, which was the lowest growth pattern relative to the other 15 specialties. Factors predictive of gender diversity among specialties were lower average step 1 scores (P = .0056), fewer years of training (P = .0078), fewer work hours (P = .046), the availability of a standard third year clerkship for a given specialty (P = .0061), and a high baseline number of female physicians within a specialty (P = .0078). Research activities (P = .099) and interest among matriculating medical students (P = .28) were not statistically significant. CONCLUSIONS: The percentage of women in RO lags behind other medical specialties and has been notably low in the last few years. Interventions that incorporate novel initiatives proposed within this study may accelerate current recruitment milestones.