Hurt, Ryan

Introduction/Objective Opportunistic salpingectomy (OS) has been shown to reduce high-grade serous ovarian cancer (HGSOC) by 42-80%, yet awareness of this strategy outside of obstetrics and gynecology remains limited. The objective of this study was to assess awareness and counseling practices regarding OS for HGSOC prevention among primary care providers (PCPs). Methods We conducted a cross-sectional survey study using a 6-item electronic survey evaluating PCP knowledge and counseling practices related to HGSOC prevention through OS. The study was conducted at a single tertiary care center with gynecologic oncology services. Survey items assessed awareness of HGSOC origin, awareness of OS as a preventative strategy, counseling frequency in the setting of abdominal or pelvic surgery, counseling comfort, and resources needed to increase confidence in recommending OS. Response formats included Likert scales and Yes/No/Unsure options. The survey was distributed by email to attending physicians and advanced practice providers (APPs) in the Department of Family Medicine (FM) and Internal Medicine (IM). Results Of 398 providers surveyed, 136 responded (34% overall response rate; FM 44%, IM 28%), including 96 attending physicians and 40 APPs. Most PCPs were unaware that HGSOC originates in the fallopian tubes (60%) and were unaware of OS as a preventive strategy (71%). Counseling was uncommon: 11% had ever counseled on OS, while 74% had not and 15% reported it was outside their scope. Most respondents (63%) reported being not at all comfortable counseling patients about OS. Providers identified clinical guidelines (60%), CME or training modules (50%), eligibility criteria (48%), gynecology collaboration pathways (48%), and patient-friendly materials (44%) as key supports to improve counseling confidence. Conclusion PCP awareness and counseling regarding OS are limited. Given that guideline support for OS has solidified only in recent years, these gaps are not surprising—and they represent a clear, actionable opportunity. PCPs are well-positioned to lead the expansion of ovarian cancer prevention beyond specialty care with the right tools and support.

Purpose The purpose of the present study was to investigate body mass index, multi-morbidity, and COVID-19 Risk Score as predictors of severe COVID-19 outcomes. Patients Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between January 1, 2020 and May 23, 2020; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens. Measures Demographic and clinical data were extracted from the electronic medical record. The data included: date of birth, gender, ethnicity, race, marital status, medications (active COVID-19 agents), weight and height (from which the Body Mass Index (BMI) was calculated, history of smoking, and comorbid conditions to calculate the Charlson Comorbidity Index (CCI) and the U.S Department of Health and Human Services (DHHS) multi-morbidity score. An additional COVID-19 Risk Score was also included. Outcomes included hospital admission, ICU admission, and death. Results Cox proportional hazards models were used to determine the impact on mortality or hospital admission. Age, sex, and race (white/Latino, white/non-Latino, other, did not disclose) were adjusted for in the model. Patients with higher COVID-19 Risk Scores had a significantly higher likelihood of being at least admitted to the hospital (HR = 1.80; 95% CI = 1.30, 2.50; P < .001), or experiencing death or inpatient admission (includes ICU admissions) (HR = 1.20; 95% CI = 1.02, 1.42; P = .028). Age was the only statistically significant demographic predictor, but obesity was not a significant predictor of any of the outcomes. Conclusion Age and COVID-19 Risk Scores were significant predictors of severe COVID-19 outcomes. Further work should examine the properties of the COVID-19 Risk Factors Scale.

Objective To describe the process and outcome of creating a patient cohort in the early stages of the COVID-19 pandemic in order to better understand the process of and predict the outcomes of COVID-19. Patients and Methods A total of 1169 adults aged 18 years of age or older who tested positive in Mayo Clinic Rochester or the Mayo Clinic Midwest Health System between January 1 and May 23 of 2020. Results Patients were on average 43.9 years of age and 50.7% were female. Most patients were white (69.0%), and Blacks (23.4%) and Asians (5.8%) were also represented in larger numbers. Hispanics represented 16.3% of the sample. Just under half of patients were married (48.4%). Common comorbid conditions included: cardiovascular diseases (25.1%), dyslipidemia (16.0%), diabetes mellitus (11.2%), chronic obstructive pulmonary disease (6.6%), asthma (7.5%), and cancer (5.1%). All other comorbid conditions were less the 5% in prevalence. Data on 3 comorbidity indices are also available including the: DHHS multi-morbidity score, Charlson Comorbidity Index, and Mayo Clinic COVID-19 Risk Factor Score. Conclusion In addition to managing the ever raging pandemic and growing death rates, it is equally important that we develop adequate resources for the investigation and understanding of COVID-19-related predictors and outcomes.