Vincent, Ann

Objectives: To identify patient characteristics, health concerns, and barriers to care based on overweight or obesity. Methods: A 50-question anonymous survey was administered to patients. Data were compared by body mass index (BMI). Results: Among 3976 distributed surveys, 899 were returned and 682 were analyzed. Most respondents were women (60%), White (94%), and married/partnered (65%) and had some college education (80%). Younger and unmarried persons had higher BMI ( P < .001). Concern for quality of life ( P < .001) and importance of lifestyle changes ( P = .006) increased with BMI, but confidence in making changes decreased as BMI increased ( P < .001). Perceived good health decreased with increasing BMI ( P < .001), whereas depression and other comorbid conditions increased. Self-esteem decreased and stigma increased with higher BMI (both P < .001). Weight discussions with clinicians ( P < .001) and belief that clinicians should be involved in weight management ( P = .002) increased with BMI, yet self-perception of being judged by clinicians also increased ( P < .001). As BMI increased, delays in seeking health care increased ( P < .001). Conclusions: This survey study highlights perceived health concerns and barriers to care among persons with overweight and obesity. With higher BMI, self-esteem decreased, and stigma, self-perception of poor health, perception of being judged by clinicians, and delay in seeking medical care increased.

Abstract Background: Circulating levels of THC and CBD may be altered when administered with medications that strongly or moderately inhibit or induce CYP450 enzymes responsible for metabolizing both substances. THC and CBD levels can also theoretically be altered in individuals who carry germline genetic variants or atypical phenotypes of CYP450 enzymes. In individuals where drug and gene interactions occur together, there could be a heightened impact on the circulating levels of THC and CBD. Materials and Methods: We conducted a retrospective chart review using a database of participants who previously completed pharmacogenomic testing and reported oral cannabis use in a medical encounter. Two pharmacogenomic-trained pharmacists reviewed medications and atypical variants in each participant to characterize the predicted effect of cannabis-drug, cannabis-gene, and cannabis-drug-gene interactions on circulating levels of THC and CBD. Results: Oral cannabis use was confirmed in 71 participants, with an average age of 68.5 years and primarily White women. Regarding THC metabolism, drug-only interactions were noted in 1 participant; both drug and gene interactions were noted in 4 participants; single- or combination-gene-only interactions were noted in 38 participants; and 28 participants had no interactions. Concerning CBD metabolism, drug-only interactions were noted in 4 participants; both drug and gene interactions were noted in 4 participants; single- or combination-gene-only interactions were noted in 36 participants; and 27 participants had no interactions. Conclusion: This study is the first, to our knowledge, to conceptualize the potential impact of drugs and atypical phenotypes on altering circulating levels of THC and CBD in a clinical sample. The absence of published clinical outcomes in this field renders it challenging to estimate clinical significance of these findings. Until such data become available, leveraging the theoretical insights into drug interactions and atypical cannabis metabolism described in our study may serve as a tool to guide clinical care.

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.

Objectives The objective of this study was to evaluate the problem of multiple chronic conditions and polypharmacy in patients with fibromyalgia. Design Retrospective medical record review. Setting Olmsted County, Minnesota. Participants 1111 adults with fibromyalgia. Primary and secondary outcome measures Number and type of chronic medical and psychiatric conditions, medication use. Results Medical record review demonstrated that greater than 50% of the sample had seven or more chronic conditions. Chronic joint pain/degenerative arthritis was the most frequent comorbidity (88.7%), followed by depression (75.1%), migraines/chronic headaches (62.4%) and anxiety (56.5%). Approximately, 40% of patients were taking three or more medications for symptoms of fibromyalgia. Sleep aids were the most commonly prescribed medications in our sample (33.3%) followed by selective serotonin reuptake inhibitors (28.7%), opioids (22.4%) and serotonin norepinephrine reuptake inhibitors (21.0%). Conclusions The results of our study highlight the problem of multiple chronic conditions and high prevalence of polypharmacy in fibromyalgia. Clinicians who care for patients with fibromyalgia should take into consideration the presence of multiple chronic conditions when recommending medications.

AbstractResearch demonstrates that patients with fibromyalgia who have higher positive and lower negative affect have lower symptom burden. Affect has been shown to be associated with resilience. This study examined the relationship between affect, resilience and fibromyalgia symptom burden in a clinical sample of patients with fibromyalgia. We hypothesized that (a) positive and negative affect would be associated with fibromyalgia symptom burden; (b) resilience would be associated with positive and negative affect; (c) resilience would be associated with fibromyalgia symptom burden; and (d) the connection between resilience and fibromyalgia symptom burden would be mediated by both positive and negative affect. A sample of 858 patients with fibromyalgia completed questionnaires. Mediation modelling revealed statistically significant direct effects of resilience on fibromyalgia symptom burden (β = −0.10, P < 0.001) and statistically significant indirect effects of resilience on fibromyalgia symptom burden through affect (β = −0.36, P < 0.001), suggesting that both resilience and affect influence fibromyalgia symptom burden. Our results suggest that improving affect through resiliency training could be studied as a modality for improving fibromyalgia symptom burden. Copyright © 2013 John Wiley & Sons, Ltd.

AbstractUtilizing billing records, we identified patients seen at Mayo Clinic with a diagnosis or history of fibromyalgia who were then contacted for enrollment in a fibromyalgia research registry. Fibromyalgia was confirmed through medical record review. Eligible patients were mailed an invitation that included a demographic questionnaire and the Fibromyalgia Research Survey. The Fibromyalgia Research Survey yields a widespread pain score (scale range 0–19) and a symptom severity score (scale range 0–12). A total of 4,034 patients returned the completed survey; 92.8% were female, their mean age was 57.4 (±13.4), and 83.7% were from the Midwest region of the United States. The mean widespread pain score for all participants was 11.3 (±4.5) and the mean symptom severity score was 8.2 (±2.4), indicating moderate‐to‐severe fibromyalgia symptoms, which is not unusual for patients presenting to a tertiary care center. Using a systematic process, we describe the creation of a fibromyalgia registry for future research.