10 research outputs found

    How the weather affects the pain of citizen scientists using a smartphone app.

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    Patients with chronic pain commonly believe their pain is related to the weather. Scientific evidence to support their beliefs is inconclusive, in part due to difficulties in getting a large dataset of patients frequently recording their pain symptoms during a variety of weather conditions. Smartphones allow the opportunity to collect data to overcome these difficulties. Our study Cloudy with a Chance of Pain analysed daily data from 2658 patients collected over a 15-month period. The analysis demonstrated significant yet modest relationships between pain and relative humidity, pressure and wind speed, with correlations remaining even when accounting for mood and physical activity. This research highlights how citizen-science experiments can collect large datasets on real-world populations to address long-standing health questions. These results will act as a starting point for a future system for patients to better manage their health through pain forecasts

    Trajectories of self-reported pain-related health outcomes and longitudinal effects on medication use in rheumatoid arthritis: a prospective cohort analysis using the Australian Rheumatology Association Database (ARAD)

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    Objective To determine distinct trajectories of self-reported pain-related health status in rheumatoid arthritis (RA), their relationship with sociodemographic factors and medication use.Methods 988 Australian Rheumatology Association Database participants with RA (71% female, mean age 54 years, mean disease duration 2.3 years) were included. Distinct multi-trajectories over 15-year follow-up for five different self-reported pain-related health outcome measures (Health Assessment Questionnaire Disability Index, visual analogue scores for pain, arthritis, global health and the Assessment of Quality of Life utility index) were identified using latent variable discrete mixture modelling. Random effects models were used to determine associations with medication use and biologic therapy modification during follow-up.Results Four, approximately equally sized, pain/health status groups were identified, ranging from ‘better’ to ‘poorer’, within which changes over time were relatively small. Important determinants of those with poorer pain/health status included female gender, obesity, smoking, socioeconomic indicators and comorbidities. While biologic therapy use was similar between groups during follow-up, biologic therapy modifications (plinear<0.001) and greater tendency of non-tumour necrosis factor inhibitor use (plinear<0.001) were observed in those with poorer pain/health status. Similarly, greater use of opioids, prednisolone and non-steroidal anti-inflammatory drugs was seen in those with poorer pain/health status.Conclusion In the absence of disease activity information, distinct trajectories of varying pain/health status were seen from the outset and throughout the disease course in this RA cohort. More biologic therapy modifications and greater use in anti-inflammatories, opioids and prednisolone were seen in those with poorer pain/health status, reflecting undesirable lived experience of persistent pain in RA

    Gout prevalence and predictors of urate-lowering therapy use: results from a population-based study

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    Abstract Background Gout has an increasing global prevalence. Underutilization of urate-lowering therapy (ULT) is thought to be common, via both suboptimal dosing and poor medication adherence. The aims of this study were to determine the prevalence of self-reported gout and the key predictors of ULT use in those with gout in a representative population survey in South Australia. Methods Data were obtained from the Spring 2015 South Australian Health Omnibus Survey, a multilevel, systematic, survey in a representative population sample involving face-to-face interviews (n = 3005). This study analyzed responses from respondents aged ≥ 25 years (n = 2531) about self-reported gout, ULT use, sociodemographic factors, lifestyle factors, and comorbidities, using survey weighting. Univariate and subsequent adjusted logistic regression analyses on self-reported gout were performed. ULT use was divided into three categories (never use, prior use, and current use) and these data were analyzed using a multinomial logistic regression model. Results Self-reported gout prevalence was 6.8% (95% CI 5.8, 7.9). The mean age of respondents with gout was 64 years (standard deviation 16) and 82% were male. As expected, older age, male gender, lower socioeconomic status (SES), and higher body mass index (BMI) were associated with gout, as were high alcohol consumption, current smoking, other forms of arthritis, and hypertension or hypercholesterolemia medication, after adjustment for sociodemographic variables. Two thirds of respondents with gout reported ULT use (36% current; 29% previous) with only 55% continuing treatment. Predictors of ULT use included male gender, low SES, and concomitant cholesterol-lowering therapy. Respondents with gout with a higher BMI were more likely to remain on ULT. Conclusions Despite gout being a common, potentially disabling joint disease, only 55% of respondents with gout in this study adhered to ULT. Identification of key predictors of ULT use will provide guidance on prescribing strategy in clinical practice and on the quality of gout care in the community

    Improving benefit-harm assessment of glucocorticoid therapy incorporating the patient perspective: The OMERACT glucocorticoid core domain set

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    Objective: Our primary objective was to develop an Outcome Measures in Rheumatology (OMERACT) core domain set to capture the impact of glucocorticoids (GC), both positive and negative, on patients with Rheumatic conditions. Methods: The OMERACT Filter 2.1 was used to guide core domain selection. Systematic literature reviews, qualitative studies and quantitative surveys were conducted by the OMERACT GC Impact working group to identify candidate domains for a core domain set. A summary of prior work and Delphi exercise were presented at the OMERACT 2020 virtual GC workshop. A proposed GC Impact core domain set derived from this work was presented for discussion in facilitated breakout groups. Participants voted on the proposed GC Impact core domain set. Results: 113 people, including 23 patient research partners, participated in two virtual workshops conducted at different times on the same day. The proposed mandatory domains to be evaluated in clinical trials involving GCs were: infection, bone fragility, hypertension, diabetes, weight, fatigue, mood disturbance and death. In addition, collection of disease specific outcomes was included in the core domain set as “mandatory in specific circumstances”. The proposed core domain set was endorsed by 100% (23/23) of the patient research partners and 92% (83/90) of the remaining participants, including clinicians, researchers and industry stakeholders. Conclusion: A GC Impact core domain set was endorsed at the OMERACT 2020 virtual workshop. The OMERACT GC Impact working group will now progress to identify, develop and validate measurement tools to best address these domains in clinical trials

    Improving benefit-harm assessment of glucocorticoid therapy incorporating the patient perspective: The OMERACT glucocorticoid core domain set

    No full text
    Objective: Our primary objective was to develop an Outcome Measures in Rheumatology (OMERACT) core domain set to capture the impact of glucocorticoids (GC), both positive and negative, on patients with Rheumatic conditions. Methods: The OMERACT Filter 2.1 was used to guide core domain selection. Systematic literature reviews, qualitative studies and quantitative surveys were conducted by the OMERACT GC Impact working group to identify candidate domains for a core domain set. A summary of prior work and Delphi exercise were presented at the OMERACT 2020 virtual GC workshop. A proposed GC Impact core domain set derived from this work was presented for discussion in facilitated breakout groups. Participants voted on the proposed GC Impact core domain set. Results: 113 people, including 23 patient research partners, participated in two virtual workshops conducted at different times on the same day. The proposed mandatory domains to be evaluated in clinical trials involving GCs were: infection, bone fragility, hypertension, diabetes, weight, fatigue, mood disturbance and death. In addition, collection of disease specific outcomes was included in the core domain set as “mandatory in specific circumstances”. The proposed core domain set was endorsed by 100% (23/23) of the patient research partners and 92% (83/90) of the remaining participants, including clinicians, researchers and industry stakeholders. Conclusion: A GC Impact core domain set was endorsed at the OMERACT 2020 virtual workshop. The OMERACT GC Impact working group will now progress to identify, develop and validate measurement tools to best address these domains in clinical trials

    Improving benefit-harm assessment of glucocorticoid therapy incorporating the patient perspective: The OMERACT glucocorticoid core domain set

    No full text
    Objective: Our primary objective was to develop an Outcome Measures in Rheumatology (OMERACT) core domain set to capture the impact of glucocorticoids (GC), both positive and negative, on patients with Rheumatic conditions. Methods: The OMERACT Filter 2.1 was used to guide core domain selection. Systematic literature reviews, qualitative studies and quantitative surveys were conducted by the OMERACT GC Impact working group to identify candidate domains for a core domain set. A summary of prior work and Delphi exercise were presented at the OMERACT 2020 virtual GC workshop. A proposed GC Impact core domain set derived from this work was presented for discussion in facilitated breakout groups. Participants voted on the proposed GC Impact core domain set. Results: 113 people, including 23 patient research partners, participated in two virtual workshops conducted at different times on the same day. The proposed mandatory domains to be evaluated in clinical trials involving GCs were: infection, bone fragility, hypertension, diabetes, weight, fatigue, mood disturbance and death. In addition, collection of disease specific outcomes was included in the core domain set as “mandatory in specific circumstances”. The proposed core domain set was endorsed by 100% (23/23) of the patient research partners and 92% (83/90) of the remaining participants, including clinicians, researchers and industry stakeholders. Conclusion: A GC Impact core domain set was endorsed at the OMERACT 2020 virtual workshop. The OMERACT GC Impact working group will now progress to identify, develop and validate measurement tools to best address these domains in clinical trials
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