Gunderson, Tina M.

Abstract Objectives To examine multimorbidity in psoriasis and its association with the development of psoriatic arthritis (PsA). Methods A retrospective cohort study was performed using the Rochester Epidemiology Project. Population-based incidence (2000–09) and prevalence (1 January 2010) cohorts of psoriasis were identified by manual chart review. A cohort of individuals without psoriasis (comparators) were identified (1:1 matched on age, sex and county). Morbidities were defined using two or more Clinical Classification Software codes ≥30 days apart within prior 5 years. PsA was defined using ClASsification of Psoriatic ARthritis (CASPAR) criteria. χ2 and rank-sum tests were used to compare morbidities, and age-, sex- and race-adjusted Cox models to examine the association of baseline morbidities in psoriasis with development of PsA. Results Among 817 incident psoriasis patients, the mean age was 45.2 years with 52.0% females, and 82.0% moderate/severe psoriasis. No multimorbidity differences were found between incident psoriasis patients and comparators. However, in the 1088 prevalent psoriasis patients, multimorbidity was significantly more common compared with 1086 comparators (odds ratio 1.35 and 1.48 for two or more and five or more morbidities, respectively). Over a median 13.3-year follow-up, 23 patients (cumulative incidence: 2.9% by 15 years) developed PsA. Multimorbidity (two or more morbidities) was associated with a 3-fold higher risk of developing PsA. Conclusion Multimorbidity was more common in the prevalent but not incident cohort of psoriasis compared with the general population, suggesting that patients with psoriasis may experience accelerated development of multimorbidity. Moreover, multimorbidity at psoriasis onset significantly increased the risk of developing PsA, highlighting the importance of monitoring multimorbid psoriasis patients for the development of PsA.

Abstract Objectives The objectives of this study were to assess the prevalence and incidence of multimorbidity and its association with the SLICC/ACR damage index (SDI) among patients with SLE. Methods Using prevalent and incident population–based cohorts of patients with SLE and their matched comparators, we assessed 57 chronic conditions. Chronic conditions were categorized as SDI-related or SDI-unrelated. Multimorbidity was defined as the presence of two or more chronic conditions. The prevalence of multimorbidity for both cohorts was compared using logistic regression. Cox models were used to examine the development of multimorbidity after SLE incidence. Results The prevalent cohort included 449 patients with established SLE on 1 January 2015. They were three times more likely to have multimorbidity compared with non-SLE comparators [odds ratio (OR) 2.98, 95% CI 2.18–4.11]. The incident cohort included 270 patients with new-onset SLE. At SLE incidence, patients with SLE were more likely to have multimorbidity than comparators (OR 2.27, 95% CI 1.59–3.27). After incidence, the risk of developing multimorbidity was 2-fold higher among patients with SLE than among comparators [hazard ratio (HR) 2.11, 95% CI 1.59–2.80]. The development of multimorbidity was higher in patients with SLE based on SDI-related conditions (HR 2.91, 95% CI 2.17–3.88) than on SDI-unrelated conditions (HR 1.73, 95% CI, 1.32–2.26). Conclusion Patients with SLE had a higher burden of multimorbidity, even before the onset of the disease. The risk disparity continued after SLE classification and was also seen in a prevalent SLE cohort. Multimorbidity was driven both by SDI-related and unrelated conditions.

Objective To identify clusters of comorbidities in patients with rheumatoid arthritis (RA) using 4 methods and to compare to patients without RA. Methods In this retrospective, population‐based study, residents of 8 Minnesota counties with prevalent RA as of January 1, 2015 were identified. Age‐, sex‐, and county‐matched non‐RA comparators were selected from the same underlying population. Diagnostic codes were retrieved for 5 years before January 1, 2015. Using 2 codes ≥30 days apart, 44 previously defined morbidities and 11 nonoverlapping chronic disease categories based on Clinical Classifications Software were defined. Unsupervised machine learning methods of interest included hierarchical clustering, factor analysis, K‐means clustering, and network analysis. Results Two groups of 1,643 patients with and without RA (72% female; mean age 63.1 years in both groups) were studied. Clustering of comorbidities revealed strong associations among mental/behavioral comorbidities and among cardiovascular risk factors and diseases. The clusters were associated with age and sex. Differences between the 4 clustering methods were driven by comorbidities that are rare and those that were weakly associated with other comorbidities. Common comorbidities tended to group together consistently across approaches. The instability of clusters when using different random seeds or bootstrap sampling impugns the usefulness and reliability of these methods. Clusters of common comorbidities between RA and non‐RA cohorts were similar. Conclusion Despite the higher comorbidity burden in patients with RA compared to the general population, clustering comorbidities did not identify substantial differences in comorbidity patterns between the RA and non‐RA cohorts. The instability of clustering methods suggests caution when interpreting clustering using 1 method.

Standard clinical protocols require hearing protection during magnetic resonance imaging (MRI) for patient safety. This investigation prospectively evaluated the auditory function impact of acoustic noise exposure during a 3.0T MRI in healthy adults. Twenty-nine participants with normal hearing underwent a comprehensive audiologic assessment before and immediately following a clinically indicated head MRI. Appropriate hearing protection with earplugs (and pads) was used per standard of practice. To characterize noise hazards, current sound monitoring tools were used to measure levels of pulse sequences measured. A third audiologic test was performed if a significant threshold shift (STS) was identified at the second test, within 30 days post MRI. Some sequences produced high levels (up to 114.5 dBA; 129 dB peak SPL) that required hearing protection but did not exceed 100% daily noise dose. One participant exhibited an STS in the frequency region most highly associated with noise-induced hearing loss. No participants experienced OSHA-defined STS in either ear. Overall, OAE measures did not show evidence of changes in cochlear function after MRI. In conclusion, hearing threshold shifts associated with hearing loss or OAE level shifts reflecting underlying cochlear damage were not detected in any of the 3.0T MRI study participants who used the current recommended hearing protection.

Objective To comprehensively assess multimorbidity burden in patients with rheumatoid arthritis (RA) in order to unify the multimorbidity definition for RA research and clinical practice. Methods In this population-based study, residents of eight Minnesota counties with prevalent RA on 1 January 2015 were identified. Age, sex and county-matched non-RA comparators were selected from the same population. Diagnostic codes were retrieved for 5 years before 1 January 2015. Using two codes ≥30 days apart, 44 previously defined morbidities and 78 non-overlapping chronic disease categories based on Clinical Classification Software were defined. Prevalence of each morbidity in the RA versus non-RA cohorts was compared using false discovery rate to adjust for multiple comparisons. Morbidities more common in RA than non-RA and those with prevalence ≥5% were retained. Results 1643 patients with RA and 1643 non-RA subjects (72% women; mean age 63.1 years) were studied. Using the 44 morbidities, multimorbidity (defined as 2+ morbidities) was present in 1411 (86%) of RA and 1164 (71%) of non-RA subjects (p<0.001) with 5+ morbidities present in 907 (55%) of RA and 619 (38%) of non-RA (p<0.001). Patients with RA had significantly higher prevalence of 24 of the 44 morbidities compared with non-RA, especially interstitial lung disease, fibromyalgia, osteoarthritis and osteoporosis. Among the additional 78 categories, 7 were significantly higher in RA than non-RA, including organic sleep disorders, vitamin D deficiency and foot ulcers. Conclusion Patients with RA have a higher prevalence of multimorbidity compared with non-RA subjects. These results confirm the list of 44 morbidities and add several other morbidities of interest in RA.