25
views
0
recommends
+1 Recommend
1 collections
    0
    shares

      Journal of Pain Research (submit here)

      This international, peer-reviewed Open Access journal by Dove Medical Press focuses on reporting of high-quality laboratory and clinical findings in all fields of pain research and the prevention and management of pain. Sign up for email alerts here.

      52,235 Monthly downloads/views I 2.832 Impact Factor I 4.5 CiteScore I 1.2 Source Normalized Impact per Paper (SNIP) I 0.655 Scimago Journal & Country Rank (SJR)

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Characterizing classes of fibromyalgia within the continuum of central sensitization syndrome

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          While fibromyalgia (FM) is characterized by chronic widespread pain and tenderness, its presentation among patients as a continuum of diseases rather than a single disease contributes to the challenges of diagnosis and treatment. The purpose of this analysis was to distinguish and characterize classes of FM within the continuum using data from chronic pain patients.

          Methods

          FM patients were identified from administrative claims data from the ProCare Systems’ network of Michigan pain clinics between January 1999 and February 2015. Identification was based on either use of traditional criteria (ie, ICD-9 codes) or a predictive model indicative of patients having FM. Patients were classified based on similarity of comorbidities (symptom severity), region of pain (widespread pain), and type and number of procedures (treatment intensity) using unsupervised learning. Text mining and a review of physician notes were conducted to assist in understanding the FM continuum.

          Results

          A total of 2,529 FM patients with 79,570 observations or clinical visits were evaluated. Four main classes of FM patients were identified: Class 1) regional FM with classic symptoms; Class 2) generalized FM with increasing widespread pain and some additional symptoms; Class 3) FM with advanced and associated conditions, increasing widespread pain, increased sleep disturbance, and chemical sensitivity; and Class 4) FM secondary to other conditions.

          Conclusion

          FM is a disease continuum characterized by progressive and identifiable classifications. Four classes of FM can be differentiated by pain and symptom severity, specific comorbidities, and use of clinical procedures.

          Most cited references17

          • Record: found
          • Abstract: found
          • Article: not found

          Subgrouping of fibromyalgia patients on the basis of pressure-pain thresholds and psychological factors.

          Although the American College of Rheumatology (ACR) criteria for fibromyalgia are used to identify individuals with both widespread pain and tenderness, individuals who meet these criteria are not a homogeneous group. Patients differ in their accompanying clinical symptoms, as well as in the relative contributions of biologic, psychological, and cognitive factors to their symptom expression. Therefore, it seems useful to identify subsets of fibromyalgia patients on the basis of which of these factors are present. Previous attempts at identifying subsets have been based solely on psychological and cognitive features. In this study, we attempt to identify patient subsets by incorporating these features as well as the degree of hyperalgesia/tenderness, which is a key neurobiologic feature of this illness. Ninety-seven individuals meeting the ACR criteria for fibromyalgia finished the same battery of self-report and evoked-pain testing. Analyzed variables were obtained from several domains, consisting of 1) mood (evaluated by the Center for Epidemiologic Studies Depression Scale [for depression] and the State-Trait Personality Inventory [for symptoms of trait-related anxiety]), 2) cognition (by the catastrophizing and control of pain subscales of the Coping Strategies Questionnaire), and 3) hyperalgesia/tenderness (by dolorimetry and random pressure-pain applied at suprathreshold values). Cluster analytic procedures were used to distinguish subgroups of fibromyalgia patients based on these domains. Three clusters best fit the data. Multivariate analysis of variance (ANOVA) confirmed that each variable was differentiated by the cluster solution (Wilks' lambda [degrees of freedom 6,89] = 0.123, P < 0.0001), with univariate ANOVAs also indicating significant differences (all P < 0.05). One subgroup of patients (n = 50) was characterized by moderate mood ratings, moderate levels of catastrophizing and perceived control over pain, and low levels of tenderness. A second subgroup (n = 31) displayed significantly elevated values on the mood assessments, the highest values on the catastrophizing subscale, the lowest values for perceived control over pain, and high levels of tenderness. The third group (n = 16) had normal mood ratings, very low levels of catastrophizing, and the highest level of perceived control over pain, but these subjects showed extreme tenderness on evoked-pain testing. These data help support the clinical impression that there are distinct subgroups of patients with fibromyalgia. There appears to be a group of fibromyalgia patients who exhibit extreme tenderness but lack any associated psychological/cognitive factors, an intermediate group who display moderate tenderness and have normal mood, and a group in whom mood and cognitive factors may be significantly influencing the symptom report.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The science of fibromyalgia.

            Fibromyalgia (FM) is a common chronic widespread pain disorder. Our understanding of FM has increased substantially in recent years with extensive research suggesting a neurogenic origin for the most prominent symptom of FM, chronic widespread pain. Neurochemical imbalances in the central nervous system are associated with central amplification of pain perception characterized by allodynia (a heightened sensitivity to stimuli that are not normally painful) and hyperalgesia (an increased response to painful stimuli). Despite this increased awareness and understanding, FM remains undiagnosed in an estimated 75% of people with the disorder. Clinicians could more effectively diagnose and manage FM if they better understood its underlying mechanisms. Fibromyalgia is a disorder of pain processing. Evidence suggests that both the ascending and descending pain pathways operate abnormally, resulting in central amplification of pain signals, analogous to the "volume control setting" being turned up too high. Patients with FM also exhibit changes in the levels of neurotransmitters that cause augmented central nervous system pain processing; levels of several neurotransmitters that facilitate pain transmission are elevated in the cerebrospinal fluid and brain, and levels of several neurotransmitters known to inhibit pain transmission are decreased. Pharmacological agents that act centrally in ascending and/or descending pain processing pathways, such as medications with approved indications for FM, are effective in many patients with FM as well as other conditions involving central pain amplification. Research is ongoing to determine the role of analogous central nervous system factors in the other cardinal symptoms of FM, such as fatigue, nonrestorative sleep, and cognitive dysfunction.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              The comparative burden of mild, moderate and severe Fibromyalgia: results from a cross-sectional survey in the United States

              Background Fibromyalgia (FM) is characterized by chronic, widespread pain, fatigue, and other symptoms; yet few studies have comprehensively assessed its humanistic burden. This observational study evaluates the impact of FM severity on patients' symptoms, health-related quality of life (HRQoL), and productivity in the United States. Methods 203 FM subjects were recruited from 20 physician offices. Subjects completed a questionnaire including the EuroQol 5D (EQ-5D), Fibromyalgia Impact Questionnaire (FIQ), Multidimensional Assessment of Fatigue (MAF), Medical Outcomes Study Sleep Scale (MOS-SS), and Hospital Anxiety and Depression Scale (HADS) and questions about demographics, pain and other symptoms, HRQoL and productivity. FIQ total scores were used to define FM severity, with 0- < 39, 39- < 59, and 59-100, representing mild, moderate, and severe FM, respectively. Sites recorded subjects' clinical characteristics and FM treatment on case report forms using medical records. Summary statistics were calculated for continuous variables and frequency distributions for categorical variables. Differences across FM severity groups were evaluated using the Kruskal-Wallis or Chi-square tests. Statistical significance was evaluated at the 0.05 level. Results Mean (SD) age was 47.9 (10.9); 95% were female. Most (92%) were prescribed medication for FM; 24% and 66% reported moderate and severe FM, respectively. Mean (SD) scores were: 6.3 (2.1) for pain intensity; 0.35 (0.35) for EQ-5D; 30.7 (14.2) for MAF; 57.5 (18.4) for MOS-SS Sleep Problems Index; 10.2 (4.8) for HADS anxiety and 9.4 (4.4) for HADS depression. Subjects with worse FM severity reported significantly increased pain severity, HRQoL, fatigue, sleep disturbance, anxiety and depression (p < 0.001). Overall, 50% of subjects reported some disruption in their employment due to FM; this differed across severity levels (p < 0.001). Employed subjects missed a mean (SD) of 1.8 (3.9) workdays during the past 4 weeks; this also differed across severity levels (p = 0.03). Conclusions FM imposes a substantial humanistic burden on patients in the United States, and leads to substantial productivity loss, despite treatment. This burden is higher among subjects with worse FM severity.
                Bookmark

                Author and article information

                Journal
                J Pain Res
                J Pain Res
                Journal of Pain Research
                Journal of Pain Research
                Dove Medical Press
                1178-7090
                2018
                23 October 2018
                : 11
                : 2551-2560
                Affiliations
                [1 ]ProCare Systems Inc, Grand Rapids, MI, USA, rrisko@ 123456procarepain.com
                [2 ]Michigan Pain Consultants, Grand Rapids, MI, USA
                [3 ]Statistics, Pfizer Inc., New York, NY, USA
                [4 ]Patient and Health Impact Pfizer Inc., Groton, CT, USA
                Author notes
                Correspondence: Rebecca Risko, ProCare Pain Solutions, 61 Commerce Ave SW, Grand Rapids, MI 49503, USA, Tel +1 616 940 3504, Email rrisko@ 123456procarepain.com
                Article
                jpr-11-2551
                10.2147/JPR.S147199
                6205129
                b4a4cca7-c562-47e6-9d8a-5716d3410ed6
                © 2018 Davis et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                History
                Categories
                Original Research

                Anesthesiology & Pain management
                fibromyalgia,severity,comorbidities,clinical procedures,predictive modeling,disease progression,machine learning

                Comments

                Comment on this article