Network Analysis for Better Understanding the Complex Psycho-Biological Mechanisms behind Fibromyalgia Syndrome

The aim of this study was to assess potential associations between sensory, cognitive, health-related, and physical variables in women with fibromyalgia syndrome (FMS) using a network analysis for better understanding the complexity of psycho-biological mechanisms. Demographic, clinical, pressure pain threshold (PPT), health-related, physical, and psychological/cognitive variables were collected in 126 women with FMS. A network analysis was conducted to quantify the adjusted correlations between the modeled variables and to assess the centrality indices (i.e., the degree of connection with other symptoms in the network and the importance in the system modeled as a network. This model showed several local associations between the variables. Multiple positive correlations between PPTs were observed, being the strongest weight between PPTs over the knee and tibialis anterior ([Formula: see text] 0.28). Catastrophism was associated with higher hypervigilance ([Formula: see text]: 0.23) and lower health-related EuroQol-5D ([Formula: see text]: −0.24). The most central variables were PPT over the tibialis anterior (the highest strength centrality), hand grip (the highest harmonic centrality) and Time Up and Go (the highest betweenness centrality). This study, applying network analysis to understand the complex mechanisms of women with FMS, supports a model where sensory-related, psychological/cognitive, health-related, and physical variables are connected. Implications of the current findings, e.g., developing treatments targeting these mechanisms, are discussed

Patient Profiling Based on Spectral Clustering for an Enhanced Classification of Patients with Tension-Type Headache

Profiling groups of patients in clusters can provide meaningful insights into the features of the population, thus helping to identify people at risk of chronification and the development of specific therapeutic strategies. Our aim was to determine if spectral clustering is able to distinguish subgroups (clusters) of tension-type headache (TTH) patients, identify the profile of each group, and argue about potential di erent therapeutic interventions. A total of 208 patients (n = 208) with TTH participated. Headache intensity, frequency, and duration were collected with a 4-week diary. Anxiety and depressive levels, headache-related burden, sleep quality, health-related quality of life, pressure pain thresholds (PPTs), dynamic pressure thresholds (DPT) and evoked-pain, and the number of trigger points (TrPs) were evaluated. Spectral clustering was used to identify clusters of patients without any previous assumption. A total of three clusters of patients based on a main difference on headache frequency were identified: one cluster including patients with chronic TTH (cluster 2) and two clusters including patients with episodic TTH (clusters 0-1). Patients in cluster 2 showed worse scores in all outcomes than those in clusters 0-1. A subgroup of patients with episodic TTH exhibited pressure pain hypersensitivity (cluster 0) similarly to those with chronic TTH (cluster 2). Spectral clustering was able to confirm subgrouping of patients with TTH by headache frequency and to identify a group of patients with episodic TTH with higher sensitization, which may need particular attention and specific therapeutic programs for avoiding potential chronification

Is the association between health-related quality of life and fatigue mediated by depression in patients with multiple sclerosis? A Spanish cross-sectional study

OBJECTIVES: To determine the mediating effects of depression on health-related quality of life and fatigue in individuals with multiple sclerosis (MS). DESIGN: A cross-sectional study. SETTING: Tertiary urban hospital. PARTICIPANTS: One hundred and eight patients (54% women) with MS participated in this study. OUTCOME MEASURES: Demographic and clinical data (weight, height, medication and neurological impairment), fatigue (Fatigue Impact Scale), depression (Beck Depression Inventory-II) and health-related quality of life (Short-Form Health Survey 36) were collected. RESULTS: Fatigue was significantly associated with bodily pain, physical function, mental health and depression. Depression was associated with bodily pain and mental health. The path analysis found direct effects from physical function, bodily pain and depression to fatigue (all, P<0.01). The path model analysis revealed that depression exerted a mediator effect from bodily pain to fatigue (B=-0.04, P<0.01), and from mental health to fatigue (B=-0.16, P<0.01). The amount of fatigue explained by all predictors in the path model was 37%. CONCLUSIONS: This study found that depression mediates the relationship between some health-related quality of life domains and fatigue in people with MS. Future longitudinal studies focusing on proper management of depressive symptoms in individuals with MS will help determine the clinical implications of these finding

Gender differences in variables associated with sleep quality in chronic tension type headache

We aimed to evaluate gender differences in the relationships between headache features, sleep quality, anxiety, depressive symptoms, and burden of headache in 193 patients (73 percent women) with chronic tension type headache (CTTH). Sleep quality was assessed with the Pittsburgh Sleep Quality Index. Headache features were collected with a four-week diary. The Hospital Anxiety and Depression Scale was used to assess anxiety/depressive symptoms. Headache Disability Inventory was used to evaluate the burden of headache. In men with CTTH, sleep quality was positive correlated with headache frequency (r = 0.310; p = .018), emotional (r = 0.518; p < .001) and physical (r = 0.468; p < .001) burden of headache, and depressive symptoms (r = 0.564; p < .001). In women, positive correlations were observed between sleep quality and headache intensity (r = 0.282; p < .001), headache frequency (r = 0.195; p = .021), emotional burden (r = 0.249; p = .004), and depressive symptoms (r = 0.382; p < .001). The results of stepwise regression analyses revealed that depressive symptoms and emotional burden of headache explained 37.2 percent of the variance in sleep quality in men (p < .001), whereas depressive symptoms and headache intensity explained 17.4 percent of the variance in sleep quality in women (p < .001) with CTTH. Gender differences associated with poor sleep should be considered for proper management of individuals with CTTH

Mathematical Modeling for Neuropathic Pain: Bayesian Linear Regression and Self-Organizing Maps Applied to Carpal Tunnel Syndrome

A better understanding of the connection between risk factors associated with pain andfunction may assist therapists in optimizing therapeutic programs. This study applied mathematicalmodeling to analyze the relationship of psychological, psychophysical, and motor variables with pain,function, and symptom severity using Bayesian linear regressions (BLR) and self-organizing maps(SOMs) in carpal tunnel syndrome (CTS). The novelty of this work was a transfer of the symmetrymathematical background to a neuropathic pain condition, whose symptoms can be either unilateralor bilateral. Duration of symptoms, pain intensity, function, symptom severity, depressive levels,pinch tip grip force, and pressure pain thresholds (PPTs) over the ulnar, radial, and median nervetrunks, the cervical spine, the carpal tunnel, and the tibialis anterior were collected in 208 womensuffering from CTS. The first BLR model revealed that symptom severity, PPTs over the radialnerve, and function had significant correlations with pain intensity. The second BLR showed thatsymptom severity, depressive levels, pain intensity, and years with pain were associated with function.The third model demonstrated that pain intensity and function were associated with symptom severity.The SOMs visualized these correlations among variables, i.e., clinical, psychophysical, and physical,and identified a subgroup of women with CTS exhibiting worse clinical features, higher pressuresensitivity, and lower pinch tip grip force. Therefore, the application of mathematical modelingidentified some interactions among the intensity of pain, function, and symptom severity in womenwith CTS

Association of Neuropathic Pain Symptoms with Sensitization Related Symptomatology in Women with Fibromyalgia

We aimed to analyze potential correlations between S-LANSS and PainDETECT with proxies for pain sensitization, e.g., the Central Sensitization Inventory (CSI) and pressure pain hyperalgesia (construct validity), pain-related or psychological variables (concurrent validity) in women with fibromyalgia (FMS). One-hundred-and-twenty-six females with FMS completed demographic, pain-related variables, psychological, and sensitization outcomes as well as the S-LANSS and the PainDETECT questionnaires. S-LANSS was positively associated with BMI (r = 0.206), pain intensity (r = 0.206 to 0.298) and CSI score (r = 0.336) and negatively associated with all PPTs (r = −0.180 to −0.336). PainDETECT was negatively associated with age (r = −0.272) and all PPTs (r = −0.226 to −0.378) and positively correlated with pain intensity (r = 0.258 to 0.439), CSI (r = 0.538), anxiety (r = 0.246) and depression (r = 0.258). 51.4% of the S-LANSS was explained by PainDETECT (45.3%), posterior iliac PPT (0.2%) and mastoid PPT (5.9%), whereas the 56.4% of PainDETECT was explained by S-LANSS (43.4%), CSI (10.4%), and pain intensity (2.6%). This study found good convergent association between S-LANSS and PainDETECT in women with FMS. Additionally, S-LANSS was associated with PPTs whereas PainDETECT was associated with pain intensity and CSI, suggesting that both questionnaires assess different spectrums of the neuropathic and pain sensitization components of a condition and hence provide synergistic information

Trajectory of post-COVID brain fog, memory loss, and concentration loss in previously hospitalized COVID-19 survivors:the LONG-COVID-EXP multicenter study

OBJECTIVE: This study aimed to apply Sankey plots and exponential bar plots for visualizing the trajectory of post-COVID brain fog, memory loss, and concentration loss in a cohort of previously hospitalized COVID-19 survivors.METHODS: A sample of 1,266 previously hospitalized patients due to COVID-19 during the first wave of the pandemic were assessed at 8.4 (T1), 13.2 (T2), and 18.3 (T3) months after hospital discharge. They were asked about the presence of the following self-reported cognitive symptoms: brain fog (defined as self-perception of sluggish or fuzzy thinking), memory loss (defined as self-perception of unusual forgetfulness), and concentration loss (defined as self-perception of not being able to maintain attention). We asked about symptoms that individuals had not experienced previously, and they attributed them to the acute infection. Clinical and hospitalization data were collected from hospital medical records.RESULTS: The Sankey plots revealed that the prevalence of post-COVID brain fog was 8.37% (n = 106) at T1, 4.7% (n = 60) at T2, and 5.1% (n = 65) at T3, whereas the prevalence of post-COVID memory loss was 14.9% (n = 189) at T1, 11.4% (n = 145) at T2, and 12.12% (n = 154) at T3. Finally, the prevalence of post-COVID concentration loss decreased from 6.86% (n = 87) at T1, to 4.78% (n = 60) at T2, and to 2.63% (n = 33) at T3. The recovery exponential curves show a decreasing trend, indicating that these post-COVID cognitive symptoms recovered in the following years after discharge. The regression models did not reveal any medical record data associated with post-COVID brain fog, memory loss, or concentration loss in the long term.CONCLUSION: The use of Sankey plots shows a fluctuating evolution of post-COVID brain fog, memory loss, or concentration loss during the first years after the infection. In addition, exponential bar plots revealed a decrease in the prevalence of these symptoms during the first years after hospital discharge. No risk factors were identified in this cohort.</p

Spectral Clustering Reveals Different Profiles of Central Sensitization in Women with Carpal Tunnel Syndrome

Identification of subgroups of patients with chronic pain provides meaningful insights into the characteristics of a specific population, helping to identify individuals at risk of chronification and to determine appropriate therapeutic strategies. This paper proposes the use of spectral clustering (SC) to distinguish subgroups (clusters) of individuals with carpal tunnel syndrome (CTS), making use of the obtained patient profiling to argue about potential management implications. SC is a powerful algorithm that builds a similarity graph among the data points (the patients), and tries to find the subsets of points that are strongly connected among themselves, but weakly connected to others. It was chosen due to its advantages with respect to other simpler clustering techniques, such as k-means, and the fact that it has been successfully applied to similar problems. Clinical (age, duration of symptoms, pain intensity, function, and symptom severity), psycho-physical (pressure pain thresholds¿PPTs¿over the three main nerve trunks of the upper extremity, cervical spine, carpal tunnel, and tibialis anterior), psychological (depressive levels), and motor (pinch tip grip force) variables were collected in 208 women with clinical/electromyographic diagnosis of CTS, whose symptoms usually started unilaterally but eventually evolved into bilateral symmetry. SC was used to identify clusters of patients without any previous assumptions, yielding three clusters. Patients in cluster 1 exhibited worse clinical features, higher widespread pressure pain hyperalgesia, higher depressive levels, and lower pinch tip grip force than the other two. Patients in cluster 2 showed higher generalized thermal pain hyperalgesia than the other two. Cluster 0 showed less hypersensitivity to pressure and thermal pain, less severe clinical features, and more normal motor output (tip grip force). The presence of subgroups of individuals with different altered nociceptive processing (one group being more sensitive to pressure pain and another group more sensitive to thermal pain) could lead to different therapeutic programs

Sleep disturbances in tension-type headache and migraine

Current research into the pathogenesis of tension-type headache (TTH) and migraine is focused on altered nociceptive pain processing. Among the potential factors that influence sensitization mechanisms, emotional stress, depression, or sleep disorders all have an essential role: they increase the excitability of nociceptive firing and trigger hyperalgesic responses. Sleep disturbances and headache disorders share common brain structures and pathogenic mechanisms and TTH, migraine, and sleep disturbances often occur together; for example, 50% of individuals who have either TTH or migraine have insomnia. Moreover, insomnia and poor sleep quality have been associated with a higher frequency and intensity of headache attacks, supporting the notion that severity and prevalence of sleep problems correlate with headache burden. It should be noted that the association between headaches and sleep problems is bidirectional: headache can promote sleep disturbances, and sleep disturbances can also precede or trigger a headache attack. Therefore, a better understanding of the factors that affect sleep quality in TTH and migraine can assist clinicians in determining better and adequate therapeutic programs. In this review, the role of sleep disturbances in headaches, and the association with depression, emotional stress, and pain sensitivity in individuals with TTH or migraine are discussed

Prognostic Factors for Postoperative Chronic Pain after Knee or Hip Replacement in Patients with Knee or Hip Osteoarthritis: An Umbrella Review

Knee and hip osteoarthritis are highly prevalent in the older population. Management of osteoarthritis-related pain includes conservative or surgical treatment. Although knee or hip joint replacement is associated with positive outcomes, up to 30% of patients report postoperative pain in the first two years. This study aimed to synthesize current evidence on prognostic factors for predicting postoperative pain after knee or hip replacement. An umbrella review of systematic reviews was conducted to summarize the magnitude and quality of the evidence for prognostic preoperative factors predictive of postoperative chronic pain (&gt;6 months after surgery) in patients who had received knee or hip replacement. Searches were conducted in MEDLINE, CINAHL, PubMed, PEDro, SCOPUS, Cochrane Library, and Web of Science databases from inception up to 5 August 2022 for reviews published in the English language. A narrative synthesis, a risk of bias assessment, and an evaluation of the evidence confidence were performed. Eighteen reviews (nine on knee surgery, four on hip replacement, and seven on both hip/knee replacement) were included. From 44 potential preoperative prognostic factors, just 20 were judged as having high or moderate confidence for robust findings. Race, opioid use, preoperative function, neuropathic pain symptoms, pain catastrophizing, anxiety, other pain sites, fear of movement, social support, preoperative pain, mental health, coping strategies, central sensitization-associated symptoms, and depression had high/moderate confidence for an association with postoperative chronic pain. Some comorbidities such as heart disease, stroke, lung disease, nervous system disorders, and poor circulation had high/moderate confidence for no association with postoperative chronic pain. This review has identified multiple preoperative factors (i.e., sociodemographic, clinical, psychological, cognitive) associated with postoperative chronic pain after knee or hip replacement. These factors may be used for identifying individuals at a risk of developing postoperative chronic pain. Further research can investigate the impact of using such prognostic data on treatment decisions and patient outcomes.</p