Background

Arthritis affects 20 % of the adult US population and is associated with comorbid depression. Depression screening guidelines have been endorsed for high-risk groups, including persons with arthritis, in the hopes that screening will increase recognition and use of appropriate interventions.

Objective

To examine national rates of depression and depression screening for patients with arthritis between 2006 and 2010.

Participants and design

We used nationally representative cross-sections of ambulatory visits in the United States from the National Ambulatory Medical Care Survey from 2006 to 2010, which included 18,507 visits with a diagnosis of arthritis. When weighted to the US population, this total represents approximately 644 million visits.

Measurements

Visits where arthritis was listed among diagnoses. Outcomes were survey-weighted estimates of depression and prevalence of depression screening among patients with arthritis across patient and physician characteristics.

Key results

Of the 644,419,374 visits with arthritis listed, 83,574,127 (13 %) were associated with a comorbid diagnosis of depression. The odds ratio for comorbid depression with arthritis was 1.42 (95 % CI 1.3, 1.5). Depression screening occurred at 3,835,000 (1 %) visits associated with arthritis. When examining the rates of depression screening between ambulatory visits with and without arthritis listed, there was no difference in depression screening rates; both were approximately 1 %. There was no difference in screening rates by provider type. Compared to visits with other common, chronic conditions, the prevalence of depression at arthritis visits was high (13 per 100 visits), although the prevalence of depression screening at arthritis visits was low (0.68 per 100 visits).

Conclusions

Despite the high prevalence of depression with arthritis, screening for depression was performed at few arthritis visits, representing missed opportunities to detect a common, serious comorbidity. Improved depression screening by providers would identify affected patients, and may lead to appropriate interventions such as mental health referrals and/or treatment with anti-depressants.

Objective

To develop and evaluate interventions to improve quality of care in 4 priority areas in an urban safety net adult rheumatology clinic serving a racially/ethnically and socioeconomically diverse patient population.

Methods

The Institute for Healthcare Improvement's Model for Improvement was used to redesign clinical processes to achieve prespecified benchmarks in the following areas from 2015 to 2017: 13-valent pneumococcal conjugate vaccine (PCV13) administration among immunocompromised patients; disease activity monitoring with the Clinical Disease Activity Index (CDAI) for patients with rheumatoid arthritis; latent tuberculosis infection (LTBI) screening for new biologic users with RA; and reproductive health counseling among women receiving potentially teratogenic medications. We measured performance for each using standardized metrics, defined as the proportion of eligible patients receiving recommended care.

Results

There were 1205 patients seen in the clinic between 2015 and 2017. Regarding demographics, 71% were women, 88% identified as racial/ethnic minorities, and 45% were eligible for at least 1 of the quality measures. Shewart charts for the PCV13 and CDAI measures showed evidence of improved healthcare delivery over time. Benchmarks were achieved for the CDAI and LTBI measures with 93% and 91% performance, respectively. Performance for the PCV13 and reproductive health counseling measures was 78% and 46%, respectively, but did not meet prespecified improvement targets.

Conclusion

Through an interprofessional approach, we were able to achieve durable improvements in key rheumatology quality measures largely by enhancing workflow, engaging nonphysician providers, and managing practice variation.

IMPORTANCE: Case reports that externalize expert diagnostic reasoning are utilized for clinical reasoning instruction but are difficult to search based on symptoms, final diagnosis, or differential diagnosis construction. Computational approaches that uncover how experienced diagnosticians analyze the medical information in a case as they formulate a differential diagnosis can guide educational uses of case reports. OBJECTIVE: To develop a reasoning-encoded case database for advanced clinical reasoning instruction by applying natural language processing (NLP), a sub-field of artificial intelligence, to a large case report library. DESIGN: We collected 2525 cases from the New England Journal of Medicine (NEJM) Clinical Pathological Conference (CPC) from 1965 to 2020 and used NLP to analyze the medical terminology in each case to derive unbiased (not prespecified) categories of analysis used by the clinical discussant. We then analyzed and mapped the degree of category overlap between cases. RESULTS: Our NLP algorithms identified clinically relevant categories that reflected the relationships between medical terms (which included symptoms, signs, test results, pathophysiology, and diagnoses). NLP extracted 43,291 symptoms across 2525 cases and physician-annotated 6532 diagnoses (both primary and related diagnoses). Our unsupervised learning computational approach identified 12 categories of medical terms that characterized the differential diagnosis discussions within individual cases. We used these categories to derive a measure of differential diagnosis similarity between cases and developed a website ( universeofcpc.com ) to allow visualization and exploration of 55 years of NEJM CPC case series. CONCLUSIONS: Applying NLP to curated instances of diagnostic reasoning can provide insight into how expert clinicians correlate and coordinate disease categories and processes when creating a differential diagnosis. Our reasoning-encoded CPC case database can be used by clinician-educators to design a case-based curriculum and by physicians to direct their lifelong learning efforts.

Objective

To determine the prevalence of obesity and how accurately standard anthropometric measures identify obesity among men and women with rheumatoid arthritis (RA).

Methods

Dual x-ray absorptiometry (DXA) was performed for 141 persons with RA (56 men and 85 women). Two anthropometric proxies of obesity (body mass index [BMI] and waist circumference [WC]) were compared to a DXA-based obesity criterion. Receiver operating characteristic curves determined optimal cut points for each anthropometric measure, relative to DXA. The association of body fat and anthropometric obesity measures with disease status and cardiovascular risk was assessed in multiple regression analyses, controlling for age and glucocorticoid use. All analyses were performed separately for men and women.

Results

A total of 20%, 32%, and 44% of women and 41%, 36%, and 80% of men were classified as obese by BMI, WC, and DXA, respectively. Cut points were identified for anthropometric measures to better approximate DXA estimates of percent body fat (BMI ≥26.1 kg/m(2) for women and ≥24.7 kg/m(2) for men; WC ≥83 cm for women and ≥96 cm for men). For women and men, higher percent fat was associated with poorer RA status. Anthropometric measures were more closely linked to RA status for women, but identified cardiovascular risk for both women and men.

Conclusion

A large percentage of this RA sample was overfat; DXA-defined obesity was twice as common in men as in women. Utility of revised BMI and WC cut points compared to traditional cut points remains to be examined in prospective studies, but results suggest that lower, sex-specific cut points may be warranted to better identify individuals at risk for poor RA and/or cardiovascular outcomes.

Objective

Cross-sectional studies have observed that muscle weakness is associated with worse physical function among women with systemic lupus erythematosus (SLE). The present study examines whether reduced upper and lower extremity muscle strength predict declines in function over time among adult women with SLE.

Methods

One hundred forty-six women from a longitudinal SLE cohort participated in the study. All measures were collected during in-person research visits approximately 2 years apart. Upper extremity muscle strength was assessed by grip strength. Lower extremity muscle strength was assessed by peak knee torque of extension and flexion. Physical function was assessed using the Short Physical Performance Battery (SPPB). Regression analyses modeled associations of baseline upper and lower extremity muscle strength with followup SPPB scores controlling for baseline SPPB, age, SLE duration, SLE disease activity (Systemic Lupus Activity Questionnaire), physical activity level, prednisone use, body composition, and depression. Secondary analyses tested whether associations of baseline muscle strength with followup in SPPB scores differed between intervals of varying baseline muscle strength.

Results

Lower extremity muscle strength strongly predicted changes over 2 years in physical function even when controlling for covariates. The association of reduced lower extremity muscle strength with reduced physical function in the future was greatest among the weakest women.

Conclusion

Reduced lower extremity muscle strength predicted clinically significant declines in physical function, especially among the weakest women. Future studies should test whether therapies that promote preservation of lower extremity muscle strength may prevent declines in function among women with SLE.

Objective

Data describing relationships between muscle strength, muscle mass, and physical disability among individuals with systemic lupus erythematosus (SLE) are limited. The present study examines the relationship of muscle strength and muscle mass with physical disability among adult women with SLE.

Methods

A total of 146 women from a longitudinal SLE cohort participated in the study. All measures were collected during an in-person research visit. Lower extremity muscle strength was assessed by peak knee torque of extension and flexion and by chair-stand time. Total lean body mass, appendicular lean mass, and fat mass (kg/m(2) ) were measured by whole-body dual x-ray absorptiometry. Self-reported physical disability was assessed using the Short Form 36 health survey (SF-36) physical functioning subscale, and the Valued Life Activities (VLA) disability scale. Spearman's rank correlation coefficients tested the correlations between muscle strength, muscle mass, and disability scores. Regression analyses modeled the effect of lower extremity muscle strength and mass on SF-36 and VLA disability scores controlling for age, SLE duration, SLE disease activity measured with the Systemic Lupus Activity Questionnaire, physical activity level, prednisone use, body composition, and depression.

Results

On all measures, reduced lower extremity muscle strength was associated with poorer SF-36 and VLA disability scores. Trends persisted after adjustment for covariates. Muscle mass was moderately correlated with muscle strength, but did not contribute significantly to adjusted regression models.

Conclusion

Lower extremity muscle strength, but not muscle mass, was strongly associated with physical disability scores. While further studies are needed, these findings suggest that improving muscle strength may reduce physical disability among women with SLE.

Objective

Dermatomyositis (DM) and polymyositis (PM) are debilitating inflammatory myopathies associated with significant mortality. We evaluated the relative contribution of infection to hospital mortality in a large population-based study of individuals with PM/DM.

Methods

Data derive from the 2007 to 2011 Healthcare Cost and Utilization Project National Inpatient Samples and include all hospital discharges that met a validated administrative definition of PM/DM. The primary outcome was hospital mortality. Variables for infections and comorbidities were generated from discharge diagnoses using validated administrative definitions. Logistic regression was used to investigate the relationship between infection and mortality in individuals with PM/DM, adjusting for sociodemographics, utilization variables, and comorbidities. Relative risks (RRs) were calculated to compare the overall prevalence of specific infections and associated mortality in PM/DM hospitalizations with those seen in the general hospitalized population.

Results

A total of 15,407 hospitalizations with PM/DM met inclusion criteria for this study and inpatient mortality was 4.5% (700 deaths). In adjusted logistic regression analyses, infection (odds ratio [OR] 3.4, 95% confidence interval [95% CI] 2.9-4.0) was the strongest predictor of hospital mortality among individuals with PM/DM. Bacterial infection (OR 3.5, 95% CI 3.0-4.1), comprised primarily of pneumonia and bacteremia, and opportunistic fungal infections (OR 2.5, 95% CI 1.5-4.0) were independently associated with hospital mortality. The overall burden of infection in hospitalizations with PM/DM was significantly increased in comparison with the general hospitalized population (RR 1.5, 95% CI 1.4-1.6).

Conclusion

Among hospitalized individuals with PM/DM, infection is the leading cause of mortality. Strategies to mitigate infection risk in both the clinic and hospital settings should be evaluated to improve disease outcomes.

Objective

We sought to develop a list of 5 tests, treatments, or services commonly used in rheumatology practice whose necessity or value should be questioned and discussed by physicians and patients.

Methods

We used a multistage process combining consensus methodology and literature reviews to arrive at the American College of Rheumatology's (ACR) Top 5 list. Rheumatologists from diverse practice settings generated items using the Delphi method. Items with high content agreement and perceived high prevalence advanced to a survey of ACR members, who comprise >90% of the US rheumatology workforce. To increase the response rate, a nested random sample of 390 rheumatologists received more intensive survey followup. The samples were combined and weighting procedures were applied to ensure generalizability. Items with high ratings underwent literature review. Final items were then selected and formulated by the task force.

Results

One hundred five unique items were proposed and narrowed down to 22 items during the Delphi rounds. A total of 1,052 rheumatologists (17% of those contacted) participated in the member-wide survey, whereas 33% of those in the nested random sample participated; respondent characteristics were similar in both samples. Based on survey results and available scientific evidence, 5 items (relating to antinuclear antibodies, Lyme disease, magnetic resonance imaging, bone absorptiometry, and biologic therapy for rheumatoid arthritis) were selected for inclusion.

Conclusion

The ACR Top 5 list is intended to promote discussions between physicians and patients about health care practices in rheumatology whose use should be questioned and to assist rheumatologists in providing high-value care.