Citations

Estimates of fibromyalgia prevalence vary widely worldwide due to differences in diagnostic criteria, study methodology, and population characteristics. Accurate estimates are essential to inform population-level surveillance, guide resource allocation, and highlight disparities in disease recognition and access to care. The objective of this systematic review and meta-analysis was to determine the global prevalence of fibromyalgia in the general population, and secondarily to identify factors moderating prevalence variation and to assess prevalence in defined at-risk subpopulations. Pooled prevalence estimates with 95% confidence intervals (CIs) were calculated using the inverse variance heterogeneity model with Freeman–Tukey transformation. Subgroup analyses were performed by sex, diagnostic criteria, country, and other study characteristics, and meta-regression assessed moderators including publication year and Human Development Index (HDI). Of 21,645 records identified, 1,728 underwent full-text review and 882 studies were included in the final analysis. Across 38 countries and 30,070,032 individuals (188 studies), the pooled fibromyalgia prevalence in the general population was 1.40% (95% CI, 0.49–2.47), with substantial heterogeneity (I 2 = 100%) and very low certainty of evidence. Among at-risk subpopulations (9,771,123 participants; 768 studies), prevalence was markedly higher in autoimmune and inflammatory conditions, such as chronic urticaria (37.1%), interstitial cystitis (30.8%), systemic sclerosis (20.6%), celiac disease (20.5%), and inflammatory bowel disease (19.9%), and elevated in chronic pain, rheumatologic, and post-infection cohorts. Meta-regression identified publication year (β = 0.008, P < .001) and HDI (β = 0.725, P = .002) as significant moderators of prevalence. In conclusion, fibromyalgia affects 1% to 2% of the global population, with substantially higher rates in at-risk subpopulations. Temporal and socioeconomic trends emphasize diagnostic inconsistency and global disparities in care.

Peri- and postmenopausal women often experience unexplained weight gain despite maintaining consistent dietary and lifestyle habits. While the biological mechanisms underlying this phenomenon remain poorly understood, physiological and pathophysiological changes during the menopausal transition are likely contributors. Proteomic profiling holds potential for revealing key molecular pathways involved in the pathogenesis of obesity in this population. This review synthesizes current evidence on proteomic alterations linked to overweight and obesity in peri- and postmenopausal women. A structured literature search was performed across Ovid MEDLINE®, EMBASE, the Cochrane Library, and Scopus for studies published between October 2010 and March 2025. Eligible studies included original research involving overweight or obese peri- or postmenopausal women that reported proteomic data. Extracted information encompassed study design, participant characteristics, sample types, and proteomic findings. Identified proteins were cross-referenced with a prior review of consistently dysregulated proteins in obesity. Five studies met the inclusion criteria, collectively revealing consistent proteomic patterns associated with inflammation, metabolic dysfunction, and endothelial dysregulation. These included C-reactive protein, Tissue necrotic factor-alpha, interleukins, adiponectin, and endocan. Notably, one study demonstrated that weight loss led to reductions in IL-6, IL-1 receptor antagonist, and CRP, suggesting that obesity-related inflammation may be at least partially reversible. This review provides preliminary evidence linking chronic inflammation, metabolic dysregulation, and vascular stress to obesity in peri- and postmenopausal women. These proteomic signatures enhance understanding of menopausal weight gain and highlight the potential of proteomics to guide personalized interventions. However, larger, well-designed prospective studies are needed to confirm these associations and clarify causal pathways.

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.

Background and Objectives: Proteomics encompasses the exploration of protein composition, regulation, function, and pathways. Its influence spans diverse clinical fields and holds promise in addressing various women’s health conditions, including cancers, osteoporosis, and cardiovascular disorders. However, no comprehensive summary of proteomics and menopausal health exists. Our objective was to summarize proteomic profiles associated with diseases and disorders in peri- and postmenopausal women. Materials and Methods: We conducted a comprehensive search of databases including PubMed, Google Scholar, the Cochrane database, Elsevier, and ScienceDirect until 2022. A total of 253 studies were identified, and 41 studies met the inclusion criteria to identify data of interest. These included the study design, disease, and proteomics/proteins of significance, as described by the authors. Results: The 41 studies covered diverse areas, including bone disorders (10 studies), cardiovascular diseases (5 studies), oncological malignancies (10 studies), and various conditions, such as obesity, nonalcoholic liver disease, the effects of hormone replacement therapy, and neurological diseases (16 studies). The results of our study indicate that proteomic profiles correlate with heart disease in peri- and postmenopausal women, with distinct sex differences. Furthermore, proteomic profiles significantly differ between women with and without osteoporosis. Additionally, patients with breast, ovarian, and endometrial cancer exhibit notable variations in proteomic profiles compared to those without these conditions. Conclusions: Proteomics has the potential to enhance risk assessment and disease monitoring in peri- and postmenopausal women. By analyzing unique protein profiles, clinicians can identify individuals with heightened susceptibility to specific diseases or those already affected by established conditions. This review suggests that there is sufficient preliminary data related to proteomics in peri- and postmenopausal women for early identification of cardiovascular disease, osteoporosis, and cancers, disease monitoring, and tailoring individualized therapies. Rigorous validation studies involving large populations are essential before drawing definitive conclusions regarding the clinical applicability of proteomic findings.

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.

Physical exercise is an indispensable element in the multidisciplinary treatment of fibromyalgia syndrome (FMS). The present study examined if men diagnosed with FMS engaged in any type of physical activity or exercise, the perceived effects from exercise, and who specifically recommended exercise. A qualitative cross-cultural study was performed in fibromyalgia clinical units in Spain and the United States. A total of 17 participants, 10 men from Spain and 7 men from the US, were included. In Spain, a focus group was completed in two parts, one month apart in 2018. In the US, five individual interviews and one joint interview with two men were completed in 2018. Three central themes appeared in the qualitative data: (1) Understanding what constitutes physical activity or exercise, (2) Facilitating or discouraging the performance of physical exercise, and (3) Effects of physical activity or exercise on psychological and social symptoms. The actual practice of exercise by patients with FMS is often perceived as leading to pain and fatigue, rather than a treatment facilitator. Physical activity and exercise can provide benefits, including relaxation, socialization, and increased muscle tone. However, minor opioids limit physical activity as they cause addiction, drowsiness, and decrease physical activity in Spanish men. Recommendations in a clinical setting should incorporate exercise as well as physical activity via daily life activities.

Background: Cannabidiol (CBD), one of the major cannabinoids derived from the cannabis plant, is available over the counter. CBD is often used by patients for the management of insomnia, yet research supporting CBDs effectiveness as a treatment for insomnia is inadequate. Objective: The objective of this review was to critically evaluate the literature regarding the therapeutic benefits of CBD in the management of insomnia. Methods: A comprehensive search of the following databases from inception to December 29, 2021, was conducted: Ovid MEDLINE ® and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, and Scopus. The search included randomized controlled trials, nonrandomized experimental studies, cross-sectional studies, cohort studies, case series, and case reports. Risk of bias was assessed with the Agency for Healthcare Research and Quality design-specific recommended criteria. Results: Thirty-four studies were eligible for inclusion. All studies reported improvement in the insomnia symptoms of at least a portion of their participants. Of the 34 studies, 19 studies used CBD predominant therapy and 21 studies used nearly equal ratios of CBD to Δ 9 -tetrahydrocannabinol (THC). Of the studies that performed hypothesis testing, 4 of 7 studies with a CBD predominant arm and 12 of 16 studies with a nearly equal ratio of CBD to THC arm reported significant improvement in insomnia outcomes. However, only 2 of the 34 studies focused on patients with insomnia, of which 1 study was a case report. Additionally, several studies used nonvalidated subjective measures, and most studies failed to include objective measures for symptom assessment. Conclusions: The results of our systematic review suggest that CBD alone or with equal quantities of THC may be beneficial in alleviating the symptoms of insomnia. Nevertheless, future research assessing CBDs effectiveness in population of patients specifically with insomnia utilizing validated subjective and objective measures is necessary before definitive inferences can be made.

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.

Abstract Objective To evaluate the association between hypovitaminosis D and outcomes of symptom severity, mood disorders, fatigue, and quality of life in fibromyalgia (FM) patients. Methods Five hundred ninety-three FM patients were surveyed from May 2012 to November 2013. Patients with serum vitamin D &lt;25 ng/mL were considered to have hypovitaminosis D. The primary outcome was FM symptom severity (FIQ-R questionnaire). Secondary outcomes included quality of life (SF-36), fatigue (MFI-20), anxiety (GAD-7), and depression (PHQ-9). Independent t tests and chi-square tests were performed for continuous and categorical variables, respectively. Regression analysis was performed adjusting for age, gender, body mass index, ethnicity, and season. A post hoc analysis examined for correlation between outcomes and serum vitamin D (ng/mL) as a continuous variable. Results One hundred twenty-two patients (20.6%) had hypovitaminosis D. In our adjusted regression analysis, the total FIQ-R score in patients with hypovitaminosis D was higher compared with control patients with adequate serum vitamin D (57.85 ± 18.09 vs 62.79 ± 18.10, P = 0.04). Adjusted regression analysis revealed higher total GAD-7 (P = 0.01) and higher total PHQ-9 scores (P = 0.04) in patients with hypovitaminosis D compared with control patients. There were no differences based on severity of depression or anxiety. No differences in fatigue or quality of life were identified. Unadjusted post hoc analysis revealed that as serum vitamin D increased, there was an association with lower total FIQ-R (β coefficient = –0.11, P = 0.02) and lower SF-36 subscale scores of role-physical (β coefficient = –0.10, P = 0.03). Adjusted post hoc analysis revealed no significant associations. Conclusions Hypovitaminosis D may be a risk factor for worse symptom severity, anxiety, and depression in FM patients.