Background:WHO survey showed that the prevalence of anxiety and depression in Chinese population and Chinese patients with chronic diseases were between 3.1% - 4.2% and 3.1% - 7.3%, respectively. Ankylosing Spondylitis Disease Activity Score (ASDAS) and Hospital Anxiety and Depression Scale (HADS) are commonly used to evaluate AS patients’ disease activity and mental health. All those assessments were mainly performed by health professionals (HCPs) with paper questionnaire previously. SSDM is a novel smart disease management tool that allows patients to do self-assessments on ASDAS and HADS by mobile terminals.Objectives:To estimate the prevalence of anxiety and depression in Chinese patients with AS and to analyze the potential association between disease activity and mental health.Methods:Under the guidance and training by HCPs, AS patients downloaded SSDM and performed self-assessments bundle of ASDAS and HADS with SSDM. ASDAS<=1.3, 1.3-2.1, 2.1-3.5 and >3.5 are defined as inactive (IDA), moderate (MDA), high (HDA) and very high (VHDA) disease activity, respectively. ASDAS score <=1.3 represents inactive disease status and achievement of T2T. HADS score >=8 can be diagnosed with anxiety or depression.Results:From June 2016 to Jan 2020, 1,931 AS patients (1,118 male, 813 female) with a mean age of 34.09 ± 11.86 (12-82) years and the median disease duration of 2.61 years from 207 hospitals performed bundle self-assessments for 2,477 times in total. According to the HADS and ASDAS assessment results, the prevalence of anxiety and depression in all patients was 36.7% and 39.3% respectively, which was significantly higher than that in the WHO survey in Chinese population and chronic disease patients. The proportion of patients achieved and failed on T2T was 29% and 71%, respectively. The prevalence of anxiety (A) and depression (D) was 25% and 23% among T2T achievers; and 37% and 32% among T2T failures, respectively (pA<0.05, pD<0.05).According to ASDAS, in IDA, MDA, HDA and VHDA subgroups, the prevalence of anxiety and depression was 27%, 36%, 41%, 52% and 29%, 38%, 45%, 56%, respectively. The correlation coefficients of anxiety (A) and depression (D) with ASDAS were rA=0.9908 and rD=0.9964. It suggested that with the increase of disease activity, the proportion of AS patients with anxiety and depression increased significantly. (Figure 1)Figure 1.The prevalence of anxiety and depression according to ASDAS.Conclusion:The prevalence of anxiety and depression in AS patients was significantly higher than that in the WHO survey in Chinese population and chronic disease patients. Higher prevalence of anxiety and depression were associated with higher levels of disease activity. SSDM is an effective mobile interface to monitor and study entanglement of disease activity and mental health in AS patients, which build a foundation for proactive interventions in future.Acknowledgments:Smart system of disease management (SSDM) was developed by Shanghai Gothic Internet Technology Co., Ltd.Disclosure of Interests:None declared
Background:WHO survey showed that the prevalence of anxiety and depression in Chinese population and Chinese patients with chronic diseases were between 3.1% - 4.2% and 3.1% - 7.3%, respectively. SLEDAI-2K and Hospital Anxiety and Depression Scale (HADS) are commonly used to evaluate SLE patients’ disease activity and mental health. All the Assessments were mainly performed by health professionals (HCPs) with paper questionnaire previously. SSDM is a novel smart disease management tool that allows patients to do self-assessments on SLEDAI-2K and HADS by mobile App.Objectives:To investigate the prevalence of anxiety and depression in Chinese patients with SLE and to analyze the potential association between disease activity of SLE and mental health.Methods:Under the guidance and training by HCPs, SLE patients downloaded SSDM and performed self-assessments bundle of SLEDAI-2K and HADS with SSDM. SLEDAI-2K <=4, 5-9, 10-14 and >=15 are defined SLE inactive, low (LDA), moderate (MDA) and high (HDA) disease activity, respectively. SLEDAI-2K score <= 4 is set as the main criteria for Lupus Low Disease Activity State (LLDAS) and achievement of T2T. HADS score >=8 can be diagnosed with anxiety or depression.Results:From June 2016 to Jan 2020, 3,332 SLE patients (199 male, 3,133 female) with a mean age of 36.34 ± 12.80 (10-91) years and the median disease duration of 3.43 years from 216 hospitals performed bundle self-assessments for 4,967 times in total. According to the HADS and SLEDAI-2K Assessment results, the prevalence of anxiety and depression in all patients was 36.7% and 39.3% respectively, which was significantly higher than that in the WHO survey in Chinese population and chronic disease patients. The proportion of patients achieved and failed on LLDAS was 53% and 47%, respectively. The prevalence of anxiety (A) and depression (D) was 19% and 27% among LLDAS achievers; 41% and 47% among LLDAS failures, respectively (pA<0.01, pD<0.01).According to SLEDAI-2K, in LLDAS, LDA, MDA and HDA subgroups, the prevalence of anxiety and depression was 19%, 30%, 37%, 54% and 27%, 36%, 44%, 61%, respectively. The correlation coefficients of anxiety (A) and depression (D) with SLEDAI-2K were rA=0.9957 and rD=0.9819. It suggested that with the increase of disease activity, the proportion of SLE patients with anxiety and depression increased significantly. (Figure 1)Conclusion:Conclusion: Higher prevalence of anxiety and depression were Associated with higher levels of disease activity in SLE patients. SSDM is an effective mobile interface to monitor and study entanglement of disease activity and mental health in SLE patients, which build a foundation for proactive interventions physically and mentally in future.References:Acknowledgments:SSDM was developed by Shanghai Gothic Internet Technology Co., Ltd.Disclosure of Interests:None declared
Background:Treating to target (T2T) is routine in RA, but no comparable standard has been defined for SLE. In 2015, the definition of Lupus Low Disease Activity State (LLDAS) was generated by Asia-Pacific Lupus Collaboration, and the preliminary validation demonstrated its attainment to be associated with improved outcomes in SLE. A SLEDAI-2K score lower than 4 is the main criteria for LLDAS. SSDM is an interactive mobile disease management application, including application systems for both the doctors and patients.Objectives:To evaluate the patterns of T2T and related influential factors among SLE patients after applying SSDM in real world.Methods:Patients were trained to master SSDM by healthcare professionals in clinics. The first assessment for SLEDAI-2K was performed as the baseline. Patients were required to perform repeated self-assessments after leaving the clinics. The data is synchronized to the SSDM of authorized rheumatologists. Based on the patients’ data, rheumatologists will provide medical advices to the patients.Results:From July 2015 to Jan 2020, 32,559 SLE patients enrolled in SSDM. The mean age is 36.35 years old and median disease duration is 3.85 years. Among them 1,937 SLE patients from 134 hospitals across China were followed up for more than 12 months, and the demographics were summarized in table 1.Table 1.Baseline\Final follow-upn%x <= 4%5 <= x <= 9%10 <= x <= 14%15 <= x%x <= 4104053.69%82078.85%13512.98%504.81%353.37%5 <= x <= 935718.43%23064.43%6016.81%328.96%359.80%10 <= x <= 1422211.46%12054.05%3817.12%4018.02%2410.81%15 <= x31816.42%15649.06%4915.41%4714.78%6620.75%Total1937100%132668.46%28214.56%1698.72%1608.26%The ratio of T2T achievers was 53.69% (1,040/1,937) at the baseline and improved significantly to 68.46% (1,326/1,937) after a 12-month follow-up, p<0.01. Among T2T achievers at the baseline, 78.85% (820/1,040) maintained T2T, and 21.15% (220/1,040) relapsed. Of patients who didn’t achieve T2T at baseline, 56.41% (506/897) of the patients achieve T2T after 12-month follow-up.The impact of the online interaction and the frequency of self-assessment for SLEDAI-2K on T2T has been analyzed. Compared with 1,475 patients who didn’t interact online with their physicians through SSDM, 462 patients with online interaction achieved higher rate of T2T improvement (19.48% vs 13.29%, p<0.05). The more frequent of the self-assessments being performed by patients, the higher improvement of T2T rate will be. The improvement rates of T2T in the subgroups which self-assessed with SSDM by quarterly, bimonthly and monthly were 8.56%, 16.14% and 23.24% respectively. The improvement rate (y) of T2T was positively correlated with the frequency of self-assessment for SLEDAI-2K(x) independently, r = 0.9998. (Figure 1)Conclusion:After proactive disease management via SSDM for more than 12 months, the rate of T2T in SLE patients increased significantly. Online interaction between patients and physicians contributed in promoting T2T improvement rate. The patients who performed more self-assessments through SSDM had higher probability of T2T achievement. SSDM is a valuable tool for long term SLE follow-up through empowering patients.References:Acknowledgments:SSDM was developed by Shanghai Gothic Internet Technology Co., Ltd.Disclosure of Interests:None declared
BackgroundCombination therapy with DMARDs for treating RA is considered as standard of care. However, certain rates of adverse events (AEs) are unavoidable. The stigma is which drug should be stopped first once AEs emerge. The decisions made by clinicians are always empirically.ObjectivesTo develop an algorithm for decision making on drug withdraw sequence in face of adverse events with combination therapy based on data mining and machine learning from the SSDM.MethodsSSDM is an interactive mobile disease management tool, including the doctors’ and patients’ application system (App). The patients can input medical records and perform self-evaluation via App. The data synchronises to the mobiles of authorised rheumatologists through cloud and advices could be delivered. In order to develop the master algorithm, abnormal white blood cell (WBC) counts in blood were first targeted. WBC and medication data was collected, extracted, validated, and then based on Bayesian networks, data mining, modelling, calculating, analysing were performed. WBC under 4,000/ml is defined as leukocytopenia (LP), and over 10,000/ml as infection predisposing (IP).ResultsFrom Jun 2014 to Jan 2018, 24,731 RA patients from 486 centres registered in SSDM. 6099 are male and 18 632 are female with mean age of 49.28±16.08 (18 to 99) years. 19 different drugs and 126 types of combination therapies are identified. Lab test results showed LP happened in 87 and IP in 123 treatment regiments. Among them we selected prednisone (Pred), leflunomide (LEF), methotrexate (MTX) and hydroxycholoqine (HCQ) as an example to develop a master algorithm based on Bayesian networks and learning model. Figure 1 shows Bayesian network and data processing, in which, quartet are correlating with 15 different regiments. Based on Bayesian method and network data, the calculation for LP and IP probabilities is generated through 32 modelling, and the algorithm for drug withdraw strategies are generated. Drug withdraw sequence for LP is HCQ, then LEF and then Pre, and the risks of LP are reduced by 64%, 52% and 26%, respectively. For IP, withdraw sequence is Pred, then MTX and then LEF, and the risks of IP are reduced by 57%, 63%, and 14%, respectively.Abstract AB0322 – Figure 1Bayesian network and data processing: patients’ number (black bold as blow showed) and the rate of either LP or IP in 15 regiments.Pred: prednisone; HCQ: hydroxycholoqine; MTX: methotrexate; LEF: leflunomide; LP: leukocytopenia; IP: infection predisposingConclusionsBig data system can be built using SSDM via empowering patient. Through data mining, networking, modelling, and Bayesian calculation, a master algorithm for drug withdraw strategy in reduction of adverse events with combination therapy is developed, which can be applied on the other AEs in SSDM and may replicated in other diseases. Following the continuing data inputs and machine leaning, an artificial intelligent system in assisting clinical decision making may be achieved.Limitations: This study only focus on rate of AE without considerin...
BackgroundHepatic, hematologic and other adverse events (AE) during treatment in RA patients are unavoidable. And monitoring AE in long-term treatment is quite necessary as a part of chronic disease management. SSDM is a smart mobile tool to help patients upload their therapeutic regimens, lab test records and report AEs. Our previous study showed that patients in China can master the application of SSDM after training.ObjectivesTo determine and compare the incidence of adverse events during treatment of RA with different therapeutic regimens, focusing on mono and combination therapy.MethodsThe SSDM includes interfaces of both physicians’ and patients’ application. Patients were educated to enter the data of lab test records and treatment regiments once a month, all data can be synchronised automatically to the authorised physicians’ mobile tool, which formed a large patient reported database. The rheumatologists can also adjust treatment regiments base on patients’ profile.ResultsFrom Aug 2014 to Jan 2018, a total of 7048 RA patients from 480 centres in China were entered in the cohort study. These patients contributed more than 12 600 patient-years (PY) of total followup. The mean age was 48.98±16.08 (18 to 99) years and the median disease duration was 23.27 months. The treatment regimens include mono or combination of leflunomide(LEF), MTX, hydroxycholoqine (HCQ), sulfasalazine(SSZ), glucocorticoid(GC), biologic DMARD, Tripterygium wilfordii, meloxicam, celecoxib, iguratimod, etc. In this database the five most common treatment regimens is LEF monotherapy (3801 PY), MTX monotherapy (1321 PY), LEF +MTX (1086 PY), HCQ monotherapy (715 PY), LEF +HCQ (576 PY). The incidence rate of hepatic events was lower for LEF monotherapy (35 events/1000 PY) than MTX (52 events/1000 PY) and LEF +MTX combination therapy (115 events/1000 PY) (p<0.01). The incidence rate of leukopenia was lower for LEF monotherapy (42 events/1000 PY) and MTX monotherapy (39 events/1000 PY) than LEF +MTX combination therapy (84 events/1000 PY) (p<0.01).ConclusionsThe findings show that mono or combination of csDMARDs are the most commonly used drugs in Chinese RA patients. And AEs may be well described in this patient report database because of the large sample sizes and empowering patient themselves. RA patients can get better safety in the long-term treatment via SSDM.Disclosure of InterestNone declared
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