Nutrition can play a pivotal role in the management of pain associated with chronic rheumatic diseases. There is a growing body of research linking certain nutrients from the diet to inflammation. Certain nutrients have been shown to improve pain associated with inflammation. Furthermore, certain dietary patterns have been shown to improve pain across multiple rheumatic conditions. Finally, maintaining a low body mass is associated with improved pain associated with chronic rheumatic diseases.

BACKGROUND: The ability to predict rheumatoid arthritis (RA) flares between clinic visits based on real-time, longitudinal patient-generated data could potentially allow for timely interventions to avoid disease worsening.
OBJECTIVE: This exploratory study aims to investigate the feasibility of using machine learning methods to classify self-reported RA flares based on a small data set of daily symptom data collected on a smartphone app.
METHODS: Daily symptoms and weekly flares reported on the Remote Monitoring of Rheumatoid Arthritis (REMORA) smartphone app from 20 patients with RA over 3 months were used. Predictors were several summary features of the daily symptom scores (eg, pain and fatigue) collected in the week leading up to the flare question. We fitted 3 binary classifiers: logistic regression with and without elastic net regularization, a random forest, and naive Bayes. Performance was evaluated according to the area under the curve (AUC) of the receiver operating characteristic curve. For the best-performing model, we considered sensitivity and specificity for different thresholds in order to illustrate different ways in which the predictive model could behave in a clinical setting.
RESULTS: The data comprised an average of 60.6 daily reports and 10.5 weekly reports per participant. Participants reported a median of 2 (IQR 0.75-4.25) flares each over a median follow-up time of 81 (IQR 79-82) days. AUCs were broadly similar between models, but logistic regression with elastic net regularization had the highest AUC of 0.82. At a cutoff requiring specificity to be 0.80, the corresponding sensitivity to detect flares was 0.60 for this model. The positive predictive value (PPV) in this population was 53%, and the negative predictive value (NPV) was 85%. Given the prevalence of flares, the best PPV achieved meant only around 2 of every 3 positive predictions were correct (PPV 0.65). By prioritizing a higher NPV, the model correctly predicted over 9 in every 10 non-flare weeks, but the accuracy of predicted flares fell to only 1 in 2 being correct (NPV and PPV of 0.92 and 0.51, respectively).
CONCLUSIONS: Predicting self-reported flares based on daily symptom scorings in the preceding week using machine learning methods was feasible. The observed predictive accuracy might improve as we obtain more data, and these exploratory results need to be validated in an external cohort. In the future, analysis of frequently collected patient-generated data may allow us to predict flares before they unfold, opening opportunities for just-in-time adaptative interventions. Depending on the nature and implication of an intervention, different cutoff values for an intervention decision need to be considered, as well as the level of predictive certainty required.

BACKGROUND: Real-world data for filgotinib, a Janus kinase (JAK)1 inhibitor, are limited in patients with rheumatoid arthritis (RA).
OBJECTIVE: To explore real-world filgotinib use in patients with RA in Germany.
METHODS: This retrospective chart review included patients aged ≥ 18 years with confirmed moderate to severe RA who initiated filgotinib before December 1, 2021, with ≥ 6 months of medical records available prior to filgotinib initiation or after initial diagnosis. Patient characteristics, prior treatments, reasons for initiating/discontinuing filgotinib, disease activity, dose adjustments and concomitant treatments were recorded.
RESULTS: In total, 301 patients from 20 German rheumatology outpatient units were included. One-third were aged ≥ 65 years and almost half had ≥ 1 cardiovascular (CV) risk factor. Most patients initiated filgotinib as monotherapy (83.7%; 12.7% of whom with glucocorticoids) and at the 200 mg dose (84.7%); higher proportions of those initiating the 100 versus 200 mg dose were aged ≥ 65 years and had renal impairment or ≥ 1 CV risk factor. Oral administration (78.4%), fast onset of action (66.8%) and administration as monotherapy (65.4%) were the most common reasons for initiating filgotinib. At 12 months, 41 (18.4%) patients had discontinued filgotinib, most commonly due to lack of effectiveness. After 6‑months of follow-up, 36.8% of patients had achieved Clinical Disease Activity Index (CDAI) remission and 45.6% had achieved CDAI low disease activity.
CONCLUSIONS: In clinical practice in Germany, reasons for initiating filgotinib in patients with RA were related to dosing flexibility and general JAK inhibitor attributes. Filgotinib was used predominantly as monotherapy and was effective and generally well tolerated; however, longer-term data in larger, prospective cohorts are needed.
UNASSIGNED: HINTERGRUND: Es existieren nur begrenzt Real-World-Daten zur Anwendung des Januskinase(JAK)-1-Inhibitors Filgotinib (FIL) bei Patienten mit rheumatoider Arthritis (RA).
UNASSIGNED: Untersuchung zur Real-World-Anwendung von FIL bei Patienten mit RA in Deutschland (DE).
METHODS: In das retrospektive Chart-Review eingeschlossen waren Patienten ≥ 18 Jahre mit bestätigter moderater bis schwerer RA, mit Beginn von FIL vor dem 1. Dezember 2021 und Daten von ≥ 6 Monaten vor FIL-Initiierung oder nach Erstdiagnose. Neben Patientencharakteristika wurden Vortherapien, Gründe für Initiierung/Absetzen von FIL, Krankheitsaktivität, Dosisanpassungen und Begleittherapien erfasst.
UNASSIGNED: Einbezogen wurden 301 Patienten aus 20 rheumatologischen Praxen in DE, ein Drittel ≥ 65 Jahre und nahezu die Hälfte mit ≥ 1 kardiovaskulären (CV) Risikofaktor. FIL wurde hauptsächlich als Monotherapie (83,7 %; 12,7 % davon mit Glukokortikoiden) in der 200-mg-Dosierung (84,7 %) begonnen. Patienten mit 100 mg FIL waren häufiger ≥ 65 Jahre alt und wiesen eine Niereninsuffizienz oder ≥ 1 CV-Risikofaktor auf. Häufigste Gründe für FIL waren orale Gabe (78,4 %), schneller Wirkeintritt (66,8 %) und Monotherapie (65,4 %). Nach 12 Monaten hatten 41 Patienten (18,4 %) FIL abgesetzt, hauptsächlich wegen unzureichender Wirksamkeit. Über 6 Monate erreichten 36,8 % der Patienten eine CDAI-Remission (Clinical Disease Activity Index) und 45,6 % eine CDAI-LDA („low disease activity“, geringe Krankheitsaktivität).
UNASSIGNED: Gründe für die Therapie mit FIL bei RA in DE waren Dosisflexibilität und allgemeine JAK-Inhibitor-Eigenschaften. FIL wurde hauptsächlich als Monotherapie eingesetzt, war wirksam und i. Allg. gut verträglich. Prospektive Langzeitdaten aus größeren Kohorten sind jedoch noch erforderlich.

BACKGROUND: Early extubation (EEx) is defined as the removal of the endotracheal tube within 8 h postoperatively. The present study involved determining the availability and threshold of the vasoactive-inotropic score (VIS) for predicting EEx in adults after elective rheumatic heart valve surgery.
METHODS: The present study was designed as a single-center retrospective cohort study which was conducted with adults who underwent elective rheumatic heart valve surgery with CPB. The highest VIS in the immediate postoperative period was used in the present study. The primary outcome, the availability of VIS for EEx prediction and the optimal threshold value were determined using ROC curve analysis. The gray zone analysis of the VIS was performed by setting the false negative or positive rate R = 0.05, and the perioperative risk factors for prolonged EEx were identified by multivariate logistic analysis. The postoperative complications and outcomes were compared between different VIS groups.
RESULTS: Among the 409 patients initially screened, 379 patients were ultimately included in the study. The incidence of EEx was determined to be 112/379 (29.6%). The VIS had a good predictive value for EEx (AUC = 0.864, 95% CI: [0.828, 0.900], P < 0.001). The optimal VIS threshold for EEx prediction was 16.5, with a sensitivity of 71.54% (65.85-76.61%) and a specificity of 88.39% (81.15-93.09%). The upper and lower limits of the gray zone for the VIS were determined as (12, 17.2). The multivariate logistic analysis identified age (OR, 1.060; 95% CI: 1.017-1.106; P = 0.006), EF% (OR, 0.798; 95% CI: 0.742-0.859; P < 0.001), GFR (OR, 0.933; 95% CI: 0.906-0.961; P < 0.001), multiple valves surgery (OR, 4.587; 95% CI: 1.398-15.056; P = 0.012), and VIS > 16.5 (OR, 12.331; 95% CI: 5.015-30.318; P < 0.001) as the independent risk factors for the prolongation of EEx. The VIS ≤ 16.5 group presented a greater success rate for EEx, a shorter invasive ventilation support duration, and a lower incidence of complications than did the VIS > 16.5 group, while the incidence of reintubation was similar between the two groups.
CONCLUSIONS: In adults, after elective rheumatic heart valve surgery, the highest VIS in the immediate postoperative period was a good predictive value for EEx, with a threshold of 16.5.

UNASSIGNED: There are currently no guidelines on peri-arthroscopic management of immunosuppressive (IS) treatment in rheumatic disease patients.
UNASSIGNED: The purpose of this study is to characterize the rheumatic disease patient population undergoing arthroscopy, compare the incidence of postoperative complications among patients who either remained on IS perioperatively, held IS perioperatively or were not on IS at baseline, and compare the incidence of postoperative complications by rheumatic disease type, medication type, and procedure.
UNASSIGNED: We conducted a retrospective review of all arthroscopic sports medicine surgeries in patients with a rheumatic disease diagnosis at our institution over an 11-year period. Patients on IS at baseline were grouped into those who remained on IS perioperatively or held all IS before the date of their surgery. These two groups were compared to patients who were not on IS at baseline. Incidence of postoperative complications was calculated for the three cohorts and by medication class, rheumatic disease type, and procedure risk. Analysis of variance (ANOVA), chi-squared, and Fisher\'s exact tests were used to determine the statistical significance of between-group differences in postoperative complication incidence.
UNASSIGNED: We identified 1,316 rheumatic disease patients undergoing arthroscopy, with 214 of them taking IS medications at baseline. In total, 8.4% (n = 110) remained on IS perioperatively, 7.9% (n = 104) held IS perioperatively, and 83.7% (n = 1102) were not on IS at baseline. In all cohorts, seven patients experienced postoperative complications; six of whom experienced infections. Two (1.82%) occurred in patients remaining on IS perioperatively, zero infections occured in patients who held all IS, and four (0.36%) occured in patients who were not on any IS at baseline. There was no statistically significant difference in postoperative infections or complication rates among the three cohorts or further subgroups.
UNASSIGNED: The risk of postoperative complications including infectious, major, and minor complications in patients on IS at the time of arthroscopy is low and acceptable.

UNASSIGNED: Osteoporosis is a common diagnosis and comorbidity observed in patients with rheumatic diseases. It is frequently associated with conditions such as rheumatoid arthritis, spondyloarthropathy, systemic lupus erythematosus, and other autoimmune rheumatic diseases.
UNASSIGNED: The incidence of osteoporosis is influenced by factors such as uncontrolled disease, prolonged and higher doses of steroid use, immobility, advanced age, and postmenopausal status. Achieving good control of the underlying disease, minimizing or avoiding the use of steroids for extended periods, and ensuring adequate supplementation of vitamin D and calcium are crucial in reducing the incidence of osteoporosis. Regular screening and appropriate management of osteoporosis can significantly decrease the associated morbidity and mortality.

UNASSIGNED: Social media data may augment understanding of the disease and treatment experiences and quality of life of youth with chronic medical conditions. Little is known about the willingness to share social media data for health research among youth with chronic medical conditions and the differences in health status between sharing and nonsharing youth with chronic medical conditions.
UNASSIGNED: We aimed to evaluate the associations between patient-reported measures of disease symptoms and functioning and the willingness to share social media data.
UNASSIGNED: Between February 2018 and August 2019, during routine clinic visits, survey data about social media use and the willingness to share social media data (dependent variable) were collected from adolescents in a national rheumatic disease registry. Survey data were analyzed with patient-reported measures of disease symptoms and functioning and a clinical measure of disease activity, which were collected through a parent study. We used descriptive statistics and multivariate logistic regression to compare patient-reported outcomes between youth with chronic medical conditions who opted to share social media data and those who did not opt to share such data.
UNASSIGNED: Among 112 youths, (age: mean 16.1, SD 1.6 y; female: n=72, 64.3%), 83 (74.1%) agreed to share social media data. Female participants were more likely to share (P=.04). In all, 49 (43.8%) and 28 (25%) participants viewed and posted about rheumatic disease, respectively. Compared to nonsharers, sharers reported lower mobility (T-score: mean 49.0, SD 9.4 vs mean 53.9, SD 8.9; P=.02) and more pain interference (T-score: mean 45.7, SD 8.8 vs mean 40.4, SD 8.0; P=.005), fatigue (T-score: mean 49.1, SD 11.0 vs mean 39.7, SD 9.7; P<.001), depression (T-score: mean 48.1, SD 8.9 vs mean 42.2, SD 8.4; P=.003), and anxiety (T-score: mean 45.2, SD 9.3 vs mean 38.5, SD 7.0; P<.001). In regression analyses adjusted for age, sex, study site, and Physician Global Assessment score, each 1-unit increase in symptoms was associated with greater odds of willingness to share social media data, for measures of pain interference (Adjusted Odds Ratio [AOR] 1.07, 95% CI 1.001-1.14), fatigue (AOR 1.08, 95% CI 1.03-1.13), depression (AOR 1.07, 95% CI 1.01-1.13), and anxiety (AOR 1.10, 95% CI 1.03-1.18).
UNASSIGNED: High percentages of youth with rheumatic diseases used and were willing to share their social media data for research. Sharers reported worse symptoms and functioning compared to those of nonsharers. Social media may offer a potent information source and engagement pathway for youth with rheumatic diseases, but differences between sharing and nonsharing youth merit consideration when designing studies and evaluating social media-derived findings.

OBJECTIVE: The aim of the present study was to illustrate the (potential) diagnostic role of high resolution US images in assessing the elementary lesions of dactylitis.
METHODS: Using high-frequency US machines/probes, we matched the micro-anatomical cadaveric architecture of the digit with multiple sonographic findings of dactylitis. High-sensitive color/power Doppler assessments have also been performed to evaluate the digital microvasculature.
CONCLUSIONS: Modern US equipment/features guarantee prompt and in-depth B-mode and color/power Doppler imaging of tiny anatomical structures of the digit which are usually not properly visible with standard US machines. More specifically, hypervascularization of the digital subcutaneous tissue, fibrous pulleys of flexor tendons, dorsal synovial pads as well as pathological changes of the distal entheseal anchorage network can be accurately detected.
CONCLUSIONS: In clinical practice, high-end US equipment can be used to accurately assess the digits in patients with dactylitis. This way, simple and convenient sonographic diagnosis of different elementary lesions can be timely established.

Cardiac magnetic resonance (CMR) is emerging as the modality of choice to assess early cardiovascular involvement in patients with autoimmune rheumatic diseases (ARDs) that often has a silent presentation and may lead to changes in management. Besides being reproducible and accurate for functional and volumetric assessment, the strength of CMR is its unique ability to perform myocardial tissue characterization that allows the identification of inflammation, edema, and fibrosis. Several CMR biomarkers may provide prognostic information on the severity and progression of cardiovascular involvement in patients with ARDs. In addition, CMR may add value in assessing treatment response and identification of cardiotoxicity related to therapy with immunomodulators that are commonly used to treat these conditions. In this review, we aim to discuss the following objectives: •Illustrate imaging findings of multi-parametric CMR approach in the diagnosis of cardiovascular involvement in various ARDs;•Review the CMR signatures for risk stratification, prognostication, and guiding treatment strategies in ARDs;•Describe the utility of routine and advanced CMR sequences in identifying cardiotoxicity related to immunomodulators and disease-modifying agents in ARDs;•Discuss the limitations of CMR, recent advances, current research gaps, and potential future developments in the field.

BACKGROUND: Chronic pain is a common symptom of rheumatic diseases that impacts patients\' quality of life. While non-pharmacological approaches are often recommended as first-line treatments, pharmacological interventions are important for pain management. However, the effectiveness and safety of different pharmacological treatments for chronic pain in rheumatic diseases are unclear.
METHODS: This review critically synthesizes the current evidence base to guide clinicians in selecting appropriate pharmacological treatments for their patients, considering the expected benefits and potential risks and side effects.
RESULTS: For osteoarthritis, nonsteroidal anti-inflammatory drugs (NSAIDs), acetaminophen, opioids, and antidepressants are commonly used, with NSAIDs being the most recommended. In addition, topical agents, such as topical NSAIDs, are recommended for localized pain relief. For fibromyalgia, amitriptyline, serotonin and noradrenaline reuptake inhibitors (SNRIs), and gabapentinoids are commonly used, with SNRIs being the most recommended. For back pain, nonsteroidal anti-inflammatory drugs (NSAIDs), acetaminophen, opioids are used only for acute of flare-up pain, whereas neuropathic pain drugs are only used for chronic radicular pain. For inflammatory rheumatic diseases, disease-modifying antirheumatic drugs (DMARDs) and biological agents are recommended to slow disease progression and manage symptoms.
CONCLUSIONS: While DMARDs and biological agents are recommended for inflammatory rheumatic diseases, pharmacological treatments for other rheumatic diseases only alleviate symptoms and do not provide a cure for the underlying condition. The use of pharmacological treatments should be based on the expected benefits and evaluation of side effects, with non-pharmacological modalities also being considered, especially for fibromyalgia.