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.

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.

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.

Fear of falling presents a significant problem for many older adults by reducing physical function and increasing the risk of future falls. Several different types of interventions have improved fear of falling and a summary of efficacious interventions will help clinicians recommend treatment options. Using the Arksey and O'Malley Framework for scoping reviews, the purpose of this review was to identify efficacious interventions for treating fear of falling among community-dwelling older adults in order to provide a list of potential treatment options for care providers. A total of 45 publications were identified for inclusion in this review.

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.