Objective Our objective was to estimate and compare the prevalence of fibromyalgia by two different methods, in Olmsted County, Minnesota. Methods The first method was a retrospective review of medical records of potential cases of fibromyalgia in Olmsted County using Rochester Epidemiology Project (from January 1, 2005, to December 31, 2009) to estimate the prevalence of diagnosed fibromyalgia in clinical practice. The second method was a random survey of adults in Olmsted County using the fibromyalgia research survey criteria to estimate the percentage of responders who met fibromyalgia research survey criteria. Results Of the 3,410 potential patients identified by the first method, 1,115 had a fibromyalgia diagnosis documented in the medical record by a health care provider. The age- and sex-adjusted prevalence of diagnosed fibromyalgia by this method was 1.1%. By the second method, of the 2,994 people who received the survey by mail, 830 (27.6%) responded and 44 (5.3%) met fibromyalgia research survey criteria. The age- and sex-adjusted prevalence of fibromyalgia in the general population of Olmsted County by this method was estimated at 6.4%. Conclusion To the best of our knowledge, this is the first report of the rate at which fibromyalgia is being diagnosed in a community. This is also the first report of prevalence as assessed by the fibromyalgia research survey criteria. Our results suggest that patients, particularly men, who meet the fibromyalgia research survey criteria are unlikely to have been given a diagnosis of fibromyalgia.

The purpose of this study was to evaluate the attitudes of physicians at an academic medical center toward complementary and alternative medicine (CAM) therapies and the physicians' knowledge base regarding common CAM therapies. A link to a Web-based survey was e-mailed to 660 internists at Mayo Clinic in Rochester, MN, USA. Physicians were asked about their attitudes toward CAM in general and their knowledge regarding specific CAM therapies. The level of evidence a physician would require before incorporating such therapies into clinical care was also assessed. Of the 233 physicians responding to the survey, 76% had never referred a patient to a CAM practitioner. However, 44% stated that they would refer a patient if a CAM practitioner were available at their institution. Fifty-seven percent of physicians thought that incorporating CAM therapies would have a positive effect on patient satisfaction, and 48% believed that offering CAM would attract more patients. Most physicians agreed that some CAM therapies hold promise for the treatment of symptoms or diseases, but most of them were not comfortable in counseling their patients about most CAM treatments. Prospective, randomized controlled trials were considered the level of evidence required for most physicians to consider incorporating a CAM therapy into their practice. The results of this survey provide insight into the attitudes of physicians toward CAM at an academic medical center. This study highlights the need for educational interventions and the importance of providing physicians ready access to evidence-based information regarding CAM.

Objective. To examine the association between body mass index (BMI) and symptom severity and quality of life (QOL) in patients with fibromyalgia. Methods. We assessed BMI status and its association with symptom severity and QOL in 888 patients with fibromyalgia who were seen in a fibromyalgia treatment program and who completed the Fibromyalgia Impact Questionnaire (FIQ) and the Short Form 36 (SF-36) health survey. Results. The BMI distribution of nonobese (BMI <25.0 kg/m 2 ), overweight (BMI 25.0 -29.9 kg/m 2 ), moderately obese (BMI 30.0 -34.9 kg/m 2 ), and severely obese (BMI >35.0 kg/m 2 ) patients was 28.4% (n ‫؍‬ 252), 26.8% (n ‫؍‬ 238), 22.2% (n ‫؍‬ 197), and 22.6% (n ‫؍‬ 201), respectively. Age was significantly different among the 4 groups, with those having a greater BMI being older (P ‫؍‬ 0.004). After adjustment for age, group differences were significant in the number of tender points (P ‫؍‬ 0.003) and the FIQ and SF-36 scores. The groups with the greater BMI had greater fibromyalgia-related symptoms with worse FIQ total scores (P < 0.001), as well as worse scores in the FIQ subscales of physical function (P < 0.001), work missed (P ‫؍‬ 0.04), job ability (P ‫؍‬ 0.003), pain (P < 0.001), stiffness (P < 0.001), and depression (P ‫؍‬ 0.03). These groups also had poorer SF-36 scores in physical functioning (P < 0.001), pain index (P ‫؍‬ 0.005), general health perceptions (P ‫؍‬ 0.003), role emotional (P ‫؍‬ 0.04), and physical component summary (P < 0.001). Post hoc analysis among the 4 groups showed that differences resided primarily in the severely obese group compared with the other groups. Conclusion. In patients with fibromyalgia, severe obesity (BMI >35.0 kg/m 2 ) is associated with higher levels of fibromyalgia symptoms and lower levels of QOL.

Fatigue is a disabling, multifaceted symptom that is highly prevalent and stubbornly persistent. Although fatigue is a frequent complaint among patients with fibromyalgia, it has not received the same attention as pain. Reasons for this include lack of standardized nomenclature to communicate about fatigue, lack of evidence-based guidelines for fatigue assessment, and a deficiency in effective treatment strategies. Fatigue does not occur in isolation; rather, it is present concurrently in varying severity with other fibromyalgia symptoms such as chronic widespread pain, unrefreshing sleep, anxiety, depression, cognitive difficulties, and so on. Survey-based and preliminary mechanistic studies indicate that multiple symptoms feed into fatigue and it may be associated with a variety of physiological mechanisms. Therefore, fatigue assessment in clinical and research settings must consider this multi-dimensionality. While no clinical trial to date has specifically targeted fatigue, randomized controlled trials, systematic reviews, and meta-analyses indicate that treatment modalities studied in the context of other fibromyalgia symptoms could also improve fatigue. The Outcome Measures in Rheumatology (OMERACT) Fibromyalgia Working Group and the Patient Reported Outcomes Measurement Information System (PROMIS) have been instrumental in propelling the study of fatigue in fibromyalgia to the forefront. The ongoing efforts by PROMIS to develop a brief fibromyalgia-specific fatigue measure for use in clinical and research settings will help define fatigue, allow for better assessment, and advance our understanding of fatigue.

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IntroductionThe aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains.MethodsFemale patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire–Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria.ResultsA total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P <0.0001) among the four clusters. The four clusters divided the sample into severity levels: Cluster 1 reflects the lowest average levels across all symptoms, and cluster 4 reflects the highest average levels. Clusters 2 and 3 capture moderate symptoms levels. Clusters 2 and 3 differed mainly in profiles of anxiety and depression, with Cluster 2 having lower levels of depression and anxiety than Cluster 3, despite higher levels of pain. The results of the cluster analysis of the external sample (n = 478) looked very similar to those found in the original cluster analysis, except for a slight difference in sleep problems. This was despite having patients in the validation sample who were significantly younger (P <0.0001) and had more severe symptoms (higher FIQ-R total scores (P = 0.0004)).ConclusionsIn our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.

ObjectivesThe objective of this study was to evaluate the problem of multiple chronic conditions and polypharmacy in patients with fibromyalgia.DesignRetrospective medical record review.SettingOlmsted County, Minnesota.Participants1111 adults with fibromyalgia.Primary and secondary outcome measuresNumber and type of chronic medical and psychiatric conditions, medication use.ResultsMedical 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%).ConclusionsThe 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.

Objective To estimate the prevalence and incidence of chronic fatigue syndrome in Olmsted County, Minnesota using the 1994 Case Definition and describe exclusionary and comorbid conditions observed in patients who presented for evaluation of long standing fatigue. Patients and Methods Retrospective chart review of potential cases identified from January 1, 1998- December 31, 2002 using the Rochester Epidemiology Project, a population-based database. Patients were classified as having chronic fatigue syndrome if the medical record review documented fatigue of 6 months’ duration, at least 4 of 8 chronic fatigue syndrome-defining symptoms, and symptoms interfered with daily work or activities. Patients not meeting all of the criteria were classified as “insufficient/idiopathic fatigue.” Results Of 686 potential patients identified, 151 (22%) met criteria for chronic fatigue syndrome or insufficient/idiopathic fatigue. The overall prevalence and incidence of chronic fatigue syndrome and insufficient/idiopathic fatigue were 71.34 and 13.16, and 73.70 and 13.58 per 100,000 persons, respectively. 70% of potential cases had an exclusionary condition and, almost half the patients who met either criterion had at least 1 non exclusionary comorbid condition. Conclusion The incidence and prevalence of chronic fatigue syndrome and insufficient/idiopathic fatigue are relatively low in Olmsted County. Careful clinical evaluation to identify whether fatigue could be attributed to exclusionary or co morbid conditions rather than chronic fatigue syndrome itself will ensure appropriate assessment for patients without chronic fatigue syndrome.