Cardiac Sarcoidosis: When and How to Treat Inflammation

Sarcoidosis is a complex, multisystem inflammatory disease with a heterogeneous clinical spectrum. Approximately 25% of patients with systemic sarcoidosis will have cardiac involvement that portends a poorer outcome. The diagnosis, particularly of isolated cardiac sarcoidosis, can be challenging. A paucity of randomised data exist on who, when and how to treat myocardial inflammation in cardiac sarcoidosis. Despite this, corticosteroids continue to be the mainstay of therapy for the inflammatory phase, with an evolving role for steroid-sparing and biological agents. This review explores the immunopathogenesis of inflammation in sarcoidosis, current evidence-based treatment indications and commonly used immunosuppression agents. It explores a multidisciplinary treatment and monitoring approach to myocardial inflammation and outlines current gaps in our understanding of this condition, emerging research and future directions in this field

Identification of Functional and Expression Polymorphisms Associated With Risk for Antineutrophil Cytoplasmic Autoantibodyâ Associated Vasculitis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136726/1/art40034_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136726/2/art40034-sup-0002-suppinfo02.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136726/3/art40034-sup-0001-suppinfo01.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136726/4/art40034.pd

Reliability and responsiveness of the D12 and validity of its scores as a measure of dyspnoea severity in patients with rheumatoid arthritis-related interstitial lung disease

Background Interstitial lung disease due to rheumatoid arthritis (RA-ILD) affects a substantial minority of patients with RA, inducing life-altering symptoms, impairing quality of life (QOL) and forcing patients to confront the potential for shortened survival. Dyspnoea is the predominant respiratory symptom of RA-ILD and a strong driver of QOL impairment in patients with it. The D12 is a 12-item questionnaire that assesses the physical and affective components of dyspnoea. It was one of a battery of patient-reported outcomes used in the double-blind, placebo-controlled TRAIL 1 trial of pirfenidone for RA-ILD. There is little information on the reliability, validity or responsiveness of the D12 in RA-ILD.Methods In accordance with COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) methodology, we conducted analyses on data from the TRAIL 1 trial to assess the measurement properties of the D12.Results Internal consistency (α=0.95, 0.95, 0.95, 0.95 and 0.96 at baseline, 13, 26, 39 and 52 weeks) and test-retest reliability 0.85 (0.71 to 0.92) exceeded acceptability criteria. Well over the 75% benchmark of hypotheses (43/46=93%) around D12 measurement properties were confirmed. Known-groups validity was supported by significant differences between subgroups of patients with differing levels of dyspnoea (eg, St. George’s Respiratory Questionnaire (SGRQ) Activity score ≥50 vs <50, 9.36 (1.27) points, p<0.0001, with a large effect size=1.7) and physiological impairment at baseline. Longitudinal validity was supported by significant associations between D12 and anchor scores over time (eg, at 52 weeks, correlation between D12 change and SGRQ Activity change was 0.54, p<0.0001; between D12 change and Routine Assessment of Patient Index Data (RAPID) Functioning Component was 0.41, p<0.0001). A battery of analyses confirmed the responsiveness of D12 scores for capturing change in dyspnoea over time. We estimated the minimal within-patient change threshold for worsening as 3 points.Conclusions D12 scores possess acceptable measurement properties in RA-ILD, such that it can be used with confidence in this population to assess dyspnoea severity defined by its physical and affective components. As validation is an ongoing process, and never accomplished in a single study, additional research on the psychometric properties of the D12 in RA-ILD is encouraged

Development and validation of algorithms to build an electronic health record based cohort of patients with systemic sclerosis

Objectives To evaluate methods of identifying patients with systemic sclerosis (SSc) using International Classification of Diseases, Tenth Revision (ICD-10) codes (M34*), electronic health record (EHR) databases and organ involvement keywords, that result in a validated cohort comprised of true cases with high disease burden. Methods We retrospectively studied patients in a healthcare system likely to have SSc. Using structured EHR data from January 2016 to June 2021, we identified 955 adult patients with M34* documented 2 or more times during the study period. A random subset of 100 patients was selected to validate the ICD-10 code for its positive predictive value (PPV). The dataset was then divided into a training and validation sets for unstructured text processing (UTP) search algorithms, two of which were created using keywords for Raynaud’s syndrome, and esophageal involvement/symptoms. Results Among 955 patients, the average age was 60. Most patients (84%) were female; 75% of patients were White, and 5.2% were Black. There were approximately 175 patients per year with the code newly documented, overall 24% had an ICD-10 code for esophageal disease, and 13.4% for pulmonary hypertension. The baseline PPV was 78%, which improved to 84% with UTP, identifying 788 patients likely to have SSc. After the ICD-10 code was placed, 63% of patients had a rheumatology office visit. Patients identified by the UTP search algorithm were more likely to have increased healthcare utilization (ICD-10 codes 4 or more times 84.1% vs 61.7%, p Conclusion EHRs can be used to identify patients with SSc. Using unstructured text processing keyword searches for SSc clinical manifestations improved the PPV of ICD-10 codes alone and identified a group of patients most likely to have SSc and increased healthcare needs

Cohort assembly.

Overview of multi-stage process for SSc ICD-10 code validation and algorithm testing and validation. Patients were selected from healthsystem databases if the ICD-10 code was present at least twice in encounters, billing codes or the problem list. Of the 2138 potential patients 1183 were excluded and a random selection of 100 patients underwent code validation. The 955 patient cohort was divided in half for testing of two algorithms using disease manifestation keywords and internal validation of highest performing algorithm. When applied to the entire cohort, 788 patients were identified as likely cases. ICD-10 = International Classification of Diseases, Tenth Revision.</p

Performance characteristics of ICD-10 code and algorithms.

Performance characteristics of ICD-10 code and algorithms.</p