Arthritis Care & Research最新文献

Objective: Our objective was to prospectively investigate prediagnostic population-based metabolome for risk of hospitalized gout (ie, most accurate, severe, and costly cases), accounting for serum urate.

Methods: We conducted prediagnostic metabolome-wide analyses among 249,677 UK Biobank participants with nuclear magnetic resonance metabolomic profiling (N = 168 metabolites, including eight amino acids) from baseline blood samples (2006-2010) without a history of gout. We calculated multivariable hazard ratios (HRs) for hospitalized incident gout, before and after adjusting for serum urate levels; we included patients with nonhospitalized incident gout in a sensitivity analysis. Potential causal effects were evaluated with two-sample Mendelian randomization.

Results: Correcting for multiple testing, 107 metabolites were associated with incidence of hospitalized gout (n = 2,735) before urate adjustment, including glycine and glutamine (glutamine HR 0.64, 95% confidence interval [CI] 0.54-0.75, P = 8.3 × 10^-8; glycine HR 0.69, 95% CI 0.61-0.78, P = 3.3 × 10^-9 between extreme quintiles), and glycoprotein acetyls (HR 2.48, 95% CI 2.15-2.87, P = 1.96 × 10^-34). Associations remained significant and directionally consistent following urate adjustment (HR 0.83, 95% CI 0.70-0.98; HR 0.86, 95% CI 0.76-0.98; HR 1.41, 95% CI 1.21-1.63 between extreme quintiles), respectively; corresponding HRs per SD were 0.91 (95% CI 0.86-0.97), 0.94 (95% CI 0.91-0.98), and 1.10 (95% CI 1.06-1.14). Findings persisted when including patients with nonhospitalized incident gout. Mendelian randomization corroborated their potential causal role on hyperuricemia or gout risk; with change in urate levels of -0.05 mg/dL (95% CI -0.08 to -0.01) and -0.12 mg/dL (95% CI -0.22 to -0.03) per SD of glycine and glutamine, respectively, and odds ratios of 0.94 (95% CI 0.88-1.00) and 0.81 (95% CI 0.67-0.97) for gout.

Conclusion: These prospective findings with causal implications could lead to biomarker-based risk prediction and potential supplementation-based interventions with glycine or glutamine.

Objective: This study investigated the association of perceived neighborhood qualities with likelihood of transit walking, leisure walking, neighborhood walking, and meeting physical activity (PA) recommendations among US adults with arthritis.

Methods: This cross-sectional study utilized 2020 National Health Interview Survey data. Included participants were adults reporting clinician-diagnosed arthritis and who reported the ability to walk. Exposures of interest were perceived neighborhood attributes. Outcomes were transit walking, leisure walking, neighborhood walking, and meeting PA recommendations. Standardized mean difference percent (SMD%) was used to assess relationships between exposures and outcomes with SMD% >10% resulting in inclusion in final adjusted multivariate logistic regression models for odds of outcomes. All analyses were weighted to account for complex survey methodology.

Results: The analytic sample included 7,322 adults with arthritis. Fully adjusted logistic regression models showed presence of roads to walk on was associated with meeting PA recommendations (OR=1.26[95%CI=1.07-1.49]). Three attributes were positively associated with transit walking, while safety from crime was negatively associated (OR=2.33[95%CI=1.75-3.10], OR=1.49[95%CI=1.17-1.91], OR=1.67[95%CI=1.34-2.08]), OR=0.70[95%CI=0.53-0.92]). Roads to walk and places to walk and relax were associated with leisure and neighborhood walking (OR=1.46[95%CI=1.21-1.76], OR=1.56[95%CI=1.34-1.82], OR=1.58[95%CI=1.29-1.93], OR=1.63[95%CI=1.40-1.90], respectively).

Conclusion: This study identified several neighborhood characteristics associated with higher likelihood of walking behaviors among adults with arthritis. Factors associated with walking behavior varied by type of walking. The shared correlates between leisure and neighborhood walking imply they occur in the same setting. Patients with arthritis may benefit from exercise recommendations that are informed by the presence or absence of facilitating infrastructure in their neighborhoods.

Objective: Autoimmune or inflammatory rheumatic diseases (AIRDs) increase the risk for poor COVID-19 outcomes. Although rurality is associated with higher post-COVID-19 mortality in the general population, whether rurality elevates this risk among people with AIRD is unknown. We assessed associations between rurality and post-COVID-19 all-cause mortality, up to two years post infection, among people with AIRD using a large nationally sampled US cohort.

Methods: This retrospective study used the National COVID Cohort Collaborative, a medical records repository containing COVID-19 patient data. We included adults with two or more AIRD diagnostic codes and a COVID-19 diagnosis documented between April 2020 and March 2023. Rural residency was categorized using patient residential zip codes. We adjusted for AIRD medications and glucocorticoid prescription, age, sex, race and ethnicity, tobacco or substance use, comorbid burden, and SARS-CoV-2 variant-dominant periods. Multivariable Cox proportional hazards with inverse probability treatment weighting assessed associations between rurality and two-year all-cause mortality.

Results: Among the 86,467 SARS-CoV-2-infected persons with AIRD, we observed a higher risk for two-year post-COVID-19 mortality in rural versus urban dwellers. Rural-residing persons with AIRD had higher two-year all-cause mortality risk (adjusted hazard ratio 1.24, 95% confidence interval 1.19-1.29). Glucocorticoid, immunosuppressive, and rituximab prescriptions were associated with a higher risk for two-year post-COVID-19 mortality, whereas risk with nonbiologic or biologic disease-modifying antirheumatic drugs was lower.

Conclusion: Rural residence in people with AIRD was independently associated with higher two-year post-COVID-19 mortality in a large US cohort after adjusting for background risk factors. Policymakers and health care providers should consider these findings when designing interventions to improve outcomes in people with AIRD following SARS-CoV-2 infection, especially among high-risk rural residents.

Objective: The aim was to estimate odds ratios of associations between family history of arthritis, osteoporosis, and carpal tunnel syndrome and prevalence in a real-world population, uncovering family histories of related conditions that may increase risk due to shared heritability, condition pathophysiology, or social/environmental factors.

Methods: Using data from 156,307 participants in the All of Us (AoU) Research Program, we examined associations between self-reported first-degree family history of 5 common types of arthritis (fibromyalgia, gout, osteoarthritis (OA), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE)), osteoporosis, and carpal tunnel syndrome and prevalence. We evaluate associations across 7 conditions and performed stratified analyses by race and ethnicity, sex, socioeconomic differences, body mass index, and type of affected relative.

Results: Over 38% of AoU participants reported a family history of any arthritis, osteoporosis, or carpal tunnel syndrome. Adults with a family history of any arthritis, osteoporosis, and carpal tunnel syndrome exhibited 3.68 to 7.59 (4.90, on average) odds of having the same condition, and 0.70 to 2.10 (1.24, on average) odds of having a different condition. The strongest associations observed were between family history of OA and prevalence of OA (OR 7.59, 95%CI 7.32-7.88), and family history of SLE and prevalence of SLE (OR 6.34, 95%CI 5.17-7.74). We additionally uncover race and ethnicity and sex disparities in family history associations.

Conclusion: Family history of several related conditions was associated with increased risk for arthritis, osteoporosis, and carpal tunnel syndrome, underscoring the importance of family history of related conditions for primary prevention.

Objective: The 2023 American College of Rheumatology/EULAR antiphospholipid syndrome (APS) classification criteria development, which aimed to identify patients with high likelihood of APS for research, employed a four-phase methodology. Phase I and II resulted in 27 proposed candidate criteria, which are organized into laboratory and clinical domains. Here, we summarize the last stage of phase III efforts, employing a consensus-based multicriteria decision analysis (MCDA) to weigh candidate criteria and identify an APS classification threshold score.

Methods: We evaluated 192 unique, international real-world patients referred for "suspected APS" with a wide range of APS manifestations. Using proposed candidate criteria, subcommittee members rank ordered 20 representative patients from highly unlikely to highly likely to have APS. During an in-person meeting, the subcommittee refined definitions and participated in an MCDA exercise to identify relative weights of candidate criteria. Using consensus decisions and pairwise criteria comparisons, 1000Minds software assigned criteria weights, and we rank ordered 192 patients by their additive scores. A consensus-based threshold score for APS classification was set.

Results: Premeeting evaluation of 20 representative patients demonstrated variability in APS assessment. MCDA resolved 81 pairwise decisions; relative weights identified domain item hierarchy. After assessing 192 patients by weights and additive scores, the Steering Committee reached consensus that APS classification should require separate clinical and laboratory scores, rather than a single-aggregate score, to ensure high specificity.

Conclusion: Using MCDA, candidate criteria preliminary weights were determined. Unlike other disease classification systems using a single-aggregate threshold score, separate clinical and laboratory domain thresholds were incorporated into the new APS classification criteria.

Objective: Examine levels of candidate blood-based biomarkers (CBB) in juvenile idiopathic arthritis (JIA) treated with tofacitinib.

Methods: JIA patients who participated in clinical trial NCT02592434 received tofacitinib from baseline to week 18. Serial serum samples were assayed for CBB (S100A8/9, S100A12, IL-18, SAA, resistin, VEGF, Angiopoietin-1, Angiopoietin-2, MMP8, MMP2, TIMP1, Leptin, CXCL9, sIL2R, ICAM-1, sTNFr, IL-6, IL-23, MCP1, CCL18, and CCL20). Association of CBB with JIA response to treatment from baseline to week 18 were assessed.

Results: This study included 166 patients with polyarticular-course JIA. Paired serum samples from 143 patients were available at both baseline and week 18. There were 35% (50/143) of patients with a JIA-American College of Rheumatology 90 (JIA-ACR90) level improvement while 90/121/137 (63%/85%/96%) achieved JIA-ACR70/50/30 improvement at wk18. Despite small numerical differences by JIA category, there were no baseline CBB values that independently predicted a decrease in JADAS-27 or JIA-ACR90 response by week 18. Decrease in resistin level (baseline to week 18) was significantly associated with wk18 improvement in JADAS-27 and JIA-ACR90 response, after adjusting for age, sex, JIA disease duration and baseline resistin [(r² 0.79, SE, 0.070, p<0.01 and OR(95%CI) = 1.134(1.018, 1.264)]. HLA-B27 positivity was significantly associated with not achieving a JIA-ACR90 response at week 18 (p=0.0097).

Conclusion: Among the CBB included, only resistin was significantly associated with treatment response, and no CBB was identified that forecasts JIA improvement after initiation of tofacitinib. The association of HLA-B27 positivity with lower response to tofacitinib in JIA is intriguing and merits further study.

Objective: This study aimed to identify variables that predict gout remission in people with erosive gout receiving urate-lowering therapy.

Methods: We analyzed data from a two-year, double-masked randomized-controlled trial of people with erosive gout, randomized to a serum urate target of <0.20 mmol/L or <0.30 mmol/L using oral urate-lowering therapies. All participants had dual-energy computed tomography (DECT) scans of the feet and ankles at baseline. The proportion of participants achieving gout remission according to the 2016 preliminary gout remission criteria and simplified gout remission criteria (without the patient reported outcomes) was analyzed. Logistic regression models were used to evaluate predictors of gout remission in year 2.

Results: The preliminary gout remission criteria were fulfilled in 11 of 97 participants (11%) at year 1 and 21 of 92 participants (23%) at year 2. The simplified criteria were fulfilled in 26 of 97 participants (27%) in year 1 and 40 of 92 participants (44%) in year 2. In multivariable regression models, baseline DECT monosodium urate crystal volume was the only significant independent predictor of gout remission at year 2, using either criteria. Each 1-cm³ increase in the baseline DECT monosodium urate crystal volume decreased the odds of fulfilling the 2016 preliminary gout remission criteria (odds ratio [OR] 0.65, 95% confidence interval [CI] 0.46-0.93; P = 0.02) and the simplified gout remission criteria (OR 0.57, 95% CI 0.41-0.78; P < 0.001).

Conclusion: In people with erosive gout on urate-lowering therapy, higher baseline DECT monosodium urate crystal volume is associated with lower odds of gout remission after two years of treatment, defined by either the preliminary gout remission criteria or simplified gout remission criteria.

Objective: We aimed to examine whether lower-limb muscle quantity and quality assessed by bioelectrical impedance analysis (BIA) were associated with knee extension strength and if the association differed with knee osteoarthritis (OA) severity.

Methods: We included 1,525 participants (63.6% women; mean age, 68.0±5.3 years) from the Nagahama Prospective Cohort. Knee extension strength was measured during maximum voluntary isometric contraction. Lower limb muscle mass and extracellular-to-intracellular water (ECW/ICW) ratio were used as indicators of muscle quantity and quality, respectively, and assessed via a BIA device. We executed multiple linear regression analyses to investigate the association of muscle quantity and quality with knee extension strength. Additionally, participants were classified into three groups with respect to OA severity and symptoms: control, early, and advanced OA groups; subgroup analyses were also executed.

Results: The muscle mass (p<0.001) and ECW/ICW ratio (p=0.009) were significantly associated with knee extension strength. In the subgroup analysis, the muscle mass was significantly associated with knee extension strength (p<0.001), but there was no association between ECW/ICW ratio and knee extension strength (p=0.731) in the control group. In the early and advanced OA groups, the muscle mass (both p<0.001) and ECW/ICW ratio (early OA: p=0.034, advanced OA: p=0.015) were significantly associated with knee extension strength.

Conclusions: Lower limb muscle quality was associated with knee extension strength, and the association was stronger in patients with knee OA. These findings suggest that both muscle quantity as well as quality should be assessed to better understand muscle function in patients with knee OA.

Objective: This systematic review aimed to identify the existing patient-reported outcome measures (PROMs) used in hip or knee arthroplasty for adults with osteoarthritis and assess their content validity using the modified International Classification of Functioning, Disability, and Health (ICF) core set for osteoarthritis (OA).

Methods: Four databases were systematically searched to identify disease or joint-specific PROMs evaluating function after hip or knee arthroplasty. Two reviewers independently evaluated the content of PROMs based on established ICF linking rules.

Results: From 449 studies included in this review, 50 PROMs were identified. The mobility chapter of activities and participation was the most common component, followed by the sensory function and pain chapter of body function and structure. The most frequent ICF activity and participation categories were d451 going up and down stairs, d4701 using private motorized transportation, d4104 standing, and d4154 maintaining a standing position. However, 11 ICF categories of the modified OA core set were not captured in any PROMs. This ICF-based content analysis of PROMs revealed that included activity and participation categories vary widely, with little overlap among PROMs. The Knee Injury and Osteoarthritis Outcome Score and the Hip Disability and Osteoarthritis Outcome Score had the most coverage for activity and participation (36.7%).

Conclusion: Even though our search identified 50 specific PROMs, there remain gaps in content related to activity and participation coverage. By providing a content analysis of the PROMs used after hip or knee arthroplasty, this study may help clinicians select PROMs based on covered categories and relevant clinical objectives.