The effectiveness of a multidisciplinary foot care program for children and adolescents with juvenile idiopathic arthritis: an exploratory trial

Objectives: To evaluate the effectiveness of multidisciplinary foot-care, and to evaluate the methodological considerations of a trial of multidisciplinary care in juvenile idiopathic arthritis. Design: Exploratory randomised controlled trial. Subjects/Patients: Children/adolescents with juvenile idiopathic arthritis and inflammatory joint disease affecting the foot/ankle. Methods: Standard medical care was compared with a 12 month program of multidisciplinary foot-care informed by musculoskeletal ultrasound. This program was centred on strict disease control through rigorous examination and interventions delivered by a team comprised of a paediatric rheumatologist, podiatrist, physiotherapist and musculoskeletal ultrasonographer. Patients were assessed on foot impairment and disability scores using the Juvenile Arthritis Foot Disability Index. Results: Forty-four participants, aged 3-17 years were randomly assigned to receive the experimental (n = 21) or usual care (n = 23) interventions. There was an overall improvement in levels of foot related impairments in both groups over 12 months. Between-group differences in change scores for the Juvenile Arthritis Foot Disability Index were not statistically significant at 6 or 12 month follow-ups. Conclusion: The integrated multidisciplinary foot care interventions described in this trial were safe, but did not improve foot impairment levels relative to usual care. This trial identified several methodological challenges including recruitment/retention, difficulties with outcome tools and potential confounders.</p

The impact of ultrasound imaging on the assessment of the carpometacarpal joint in hand osteoarthritis

Emerging evidence suggests that ultrasound imaging is being increasingly used to assess peripheral joints in clinical practice. However, much of the research focus has been on patients with inflammatory arthritis. Recent studies have explored the use of ultrasound in the evaluation of symptomatic hand osteoarthritis. Assessment of this condition can be challenging particularly with the possibility of coexisting soft tissues pathologies that may arise. The clinical management of hand osteoarthritis with corticosteroid injections as a targeted intervention for symptom modification is routine practice. However, evidence of clinical efficacy is limited. This study evaluated ultrasound imaging as a diagnostic tool in addition to clinical examination in patients with symptomatic hand osteoarthritis. A consecutive sample of forty patients attending Glasgow Royal Infirmary Rheumatology Department were recruited to this study. The primary aim of this study was to establish if the symptoms of carpometacarpal joint osteoarthritis could be improved by identifying and treating coexisting pathologies such as median nerve entrapment and/or De Quervain's tenosynovitis. The study was divided into three stages: Stage 1 investigated the carpometacarpal joint and associated pathologies; Stage 2 identified whether knowledge of the ultrasound scan influenced clinical decision- making and planning of corticosteroid injections following the random allocation of patients to two groups; and Stage 3 measured the level of disease burden to the individual using the Australian/Canadian Osteoarthritis Hand Index over 12 weeks following intervention. The study findings demonstrated that ultrasound scanning when used in addition to routine clinical examination is beneficial to image the associated pathologies of median nerve entrapment and De Quervain's tenosynovitis in osteoarthritis of the carpometacarpal joint. Ultrasound was found to influence the clinical decision making in targeting corticosteroid injections for the management of symptomatic hand osteoarthritis. However, prior knowledge of ultrasound findings did not result in improved clinical outcomes as measured by the AUSCAN. The detection of additional pathologies in carpometacarpal joint disease may allow for earlier targeted treatment with corticosteroid injections aimed at improving hand symptoms and function.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Same data, different conclusions : radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed