Search

Introduction: Rheport is an online rheumatology referral system allowing automatic appointment triaging of new rheumatology patient referrals according to the respective probability of an inflammatory rheumatic disease (IRD). Previous research reported that Rheport was well accepted among IRD patients. Its accuracy was, however, limited, currently being based on an expert-based weighted sum score. This study aimed to evaluate whether machine learning (ML) models could improve this limited accuracy., Materials and Methods: Data from a national rheumatology registry (RHADAR) was used to train and test nine different ML models to correctly classify IRD patients. Diagnostic performance was compared of ML models and the current algorithm was compared using the area under the receiver operating curve (AUROC). Feature importance was investigated using shapley additive explanation (SHAP)., Results: A complete data set of 2265 patients was used to train and test ML models. 30.5% of patients were diagnosed with an IRD, 69.3% were female. The diagnostic accuracy of the current Rheport algorithm (AUROC of 0.534) could be improved with all ML models, (AUROC ranging between 0.630 and 0.737). Targeting a sensitivity of 90%, the logistic regression model could double current specificity (17% vs. 33%). Finger joint pain, inflammatory marker levels, psoriasis, symptom duration and female sex were the five most important features of the best performing logistic regression model for IRD classification., Conclusion: In summary, ML could improve the accuracy of a currently used rheumatology online referral system. Including further laboratory parameters and enabling individual feature importance adaption could increase accuracy and lead to broader usage., Competing Interests: Qinum and RheumaDatenRhePort developed and hold rights for Rheport. WV, CD, and PB-B were involved in the development of Rheport. JK was a member of the scientific board of RheumaDatenRhePort. WV, CD, SK, PB-B, and MW were members of RheumaDatenRhePort GbR. RHADAR GbR received honoraria from UCB Pharma GmbH, Sandoz Deutschland/Hexal AG, Lilly GmbH, and Galapagos Biopharma Germany GmbH, and research support from Novartis Pharma GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Knitza, Janousek, Kluge, von der Decken, Kleinert, Vorbrüggen, Kleyer, Simon, Hueber, Muehlensiepen, Vuillerme, Schett, Eskofier, Welcker and Bartz-Bazzanella.)

This longitudinal analysis compares the prevalence of depressive symptoms in patients with psoriatic arthritis in the context of the COVID-19 pandemic. Data from a national patient register in Germany were analyzed regarding the Patient Health Questionnaire 2 (PHQ-2) to identify cases suspicious for depression at two time points, i.e., before and during the COVID-19 pandemic. Only patients with complete concurrent information on the Disease Activity in Psoriatic Arthritis Score (DAPSA) were included in the analysis. The frequency of depressive symptoms in psoriatic arthritis patients during the COVID-19 pandemic did not differ from the prevalence rates measured before. In addition, prevalence rates for depressive symptoms did not differ when stratifying the patient sample for DAPSA levels of disease activity measured before the pandemic. These results were confirmed further in a sensitivity analysis, limiting the second PHQ-2 assessment to lockdown periods only. However, longitudinal data on the prevalence of depressive symptoms in patients with rheumatic diseases, in general, and psoriatic arthritis, in particular, are scarce in the context of the COVID-19 pandemic. For a sensible comparison of prevalence rates for depressive symptoms in the future, underlying SARS-CoV-2 infection rates and resulting local healthcare disruptions need to be taken into account, besides the potential use of different depression screening tools to evaluate resulting numbers sensibly and draw corresponding conclusions for patient care., Competing Interests: WV, CD, SK, PB-B, CK, KK, SS-M, PA, and MW are members of RheumaDatenRhePort GbR. RHADAR GbR received honoraria from UCB Pharma GmbH, Sandoz Deutschland/Hexal AG, Lilly GmbH, and Galapagos Biopharma Germany GmbH, and research support from Novartis Pharma GmbH. ME received remunerations from RheumaDatenRhePort GbR for statistical data analyses and consultation for previous projects. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Englbrecht, Bartz-Bazzanella, von der Decken, Gauler, Wurth, Aries, Karberg, Kuhn, Schuch, Späthling-Mestekemper, Vorbrüggen, Wendler, Welcker and Kleinert.)