Individual participant data meta-analysis to examine linear or non-linear treatment-covariate interactions at multiple time-points for a continuous outcome.

Individual participant data (IPD) meta-analysis projects obtain, harmonise, and synthesise original data from multiple studies. Many IPD meta-analyses of randomised trials are initiated to identify treatment effect modifiers at the individual level, thus requiring statistical modelling of interactions between treatment effect and participant-level covariates. Using a two-stage approach, the interaction is estimated in each trial separately and combined in a meta-analysis. In practice, two complications often arise with continuous outcomes: examining non-linear relationships for continuous covariates and dealing with multiple time-points. We propose a two-stage multivariate IPD meta-analysis approach that summarises non-linear treatment-covariate interaction functions at multiple time-points for continuous outcomes. A set-up phase is required to identify a small set of time-points; relevant knot positions for a spline function, at identical locations in each trial; and a common reference group for each covariate. Crucially, the multivariate approach can include participants or trials with missing outcomes at some time-points. In the first stage, restricted cubic spline functions are fitted and their interaction with each discrete time-point is estimated in each trial separately. In the second stage, the parameter estimates defining these multiple interaction functions are jointly synthesised in a multivariate random-effects meta-analysis model accounting for within-trial and across-trial correlation. These meta-analysis estimates define the summary non-linear interactions at each time-point, which can be displayed graphically alongside confidence intervals. The approach is illustrated using an IPD meta-analysis examining effect modifiers for exercise interventions in osteoarthritis, which shows evidence of non-linear relationships and small gains in precision by analysing all time-points jointly.

Development and initial evaluation of a clinical prediction model for risk of treatment resistance in first-episode psychosis: Schizophrenia Prediction of Resistance to Treatment (SPIRIT).

BACKGROUND: A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication. AIMS: To develop and evaluate a model that could predict the risk of TRS in routine clinical practice. METHOD: We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model. RESULTS: We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723-0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism. CONCLUSIONS: We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

Musculoskeletal Health and Work: Development and Internal-External Cross-Validation of a Model to Predict Risk of Work Absence and Presenteeism in People Seeking Primary Healthcare.

PURPOSE: To develop and validate prediction models for the risk of future work absence and level of presenteeism, in adults seeking primary healthcare with musculoskeletal disorders (MSD). METHODS: Six studies from the West-Midlands/Northwest regions of England, recruiting adults consulting primary care with MSD were included for model development and internal-external cross-validation (IECV). The primary outcome was any work absence within 6 months of their consultation. Secondary outcomes included 6-month presenteeism and 12-month work absence. Ten candidate predictors were included: age; sex; multisite pain; baseline pain score; pain duration; job type; anxiety/depression; comorbidities; absence in the previous 6 months; and baseline presenteeism. RESULTS: For the 6-month absence model, 2179 participants (215 absences) were available across five studies. Calibration was promising, although varied across studies, with a pooled calibration slope of 0.93 (95% CI: 0.41-1.46) on IECV. On average, the model discriminated well between those with work absence within 6 months, and those without (IECV-pooled C-statistic 0.76, 95% CI: 0.66-0.86). The 6-month presenteeism model, while well calibrated on average, showed some individual-level variation in predictive accuracy, and the 12-month absence model was poorly calibrated due to the small available size for model development. CONCLUSIONS: The developed models predict 6-month work absence and presenteeism with reasonable accuracy, on average, in adults consulting with MSD. The model to predict 12-month absence was poorly calibrated and is not yet ready for use in practice. This information may support shared decision-making and targeting occupational health interventions at those with a higher risk of absence or presenteeism in the 6 months following consultation. Further external validation is needed before the models' use can be recommended or their impact on patients can be fully assessed.

Stratified health care for low back pain using the STarT Back approach: Holy Grail or doomed to fail?

ABSTRACT: There have been at least 7 separate randomised controlled trials published between 2011 and 2023 that have examined primary care for nonspecific low back pain informed by the STarT Back approach to stratified care based on risk prediction, compared with care not informed by this approach. The results, across 4 countries, have been contrasting-some demonstrating effectiveness and/or efficiency of this approach, others finding no benefits over comparison interventions. This review considers possible explanations for the differences, particularly whether this is related to poor predictive performance of the STarT Back risk-prediction tool or to variable degrees of success in implementing the whole STarT Back approach (subgrouping and matching treatments to predicted risk of poor outcomes) in different healthcare systems. The review concludes that although there is room for improving and expanding the predictive value of the STarT Back tool, its performance in allocating individuals to their appropriate risk categories cannot alone explain the variation in results of the trials to date. Rather, the learning thus far suggests that challenges in implementing stratified care in clinical practice and in changing professional practice largely explain the contrasting trial results. The review makes recommendations for future research, including greater focus on studying facilitators of implementation of stratified care and developing better treatments for patients with nonspecific low back pain at high risk of poor outcomes.

Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults.

BACKGROUND: Falls are common in older adults and can devastate personal independence through injury such as fracture and fear of future falls. Methods to identify people for falls prevention interventions are currently limited, with high risks of bias in published prediction models. We have developed and externally validated the eFalls prediction model using routinely collected primary care electronic health records (EHR) to predict risk of emergency department attendance/hospitalisation with fall or fracture within 1 year. METHODS: Data comprised two independent, retrospective cohorts of adults aged ≥65 years: the population of Wales, from the Secure Anonymised Information Linkage Databank (model development); the population of Bradford and Airedale, England, from Connected Bradford (external validation). Predictors included electronic frailty index components, supplemented with variables informed by literature reviews and clinical expertise. Fall/fracture risk was modelled using multivariable logistic regression with a Least Absolute Shrinkage and Selection Operator penalty. Predictive performance was assessed through calibration, discrimination and clinical utility. Apparent, internal-external cross-validation and external validation performance were assessed across general practices and in clinically relevant subgroups. RESULTS: The model's discrimination performance (c-statistic) was 0.72 (95% confidence interval, CI: 0.68 to 0.76) on internal-external cross-validation and 0.82 (95% CI: 0.80 to 0.83) on external validation. Calibration was variable across practices, with some over-prediction in the validation population (calibration-in-the-large, -0.87; 95% CI: -0.96 to -0.78). Clinical utility on external validation was improved after recalibration. CONCLUSION: The eFalls prediction model shows good performance and could support proactive stratification for falls prevention services if appropriately embedded into primary care EHR systems.

Prognostic factors for liver, blood and kidney adverse events from glucocorticoid sparing immune-suppressing drugs in immune-mediated inflammatory diseases: a prognostic systematic review.

BACKGROUND: Immune-suppressing drugs can cause liver, kidney or blood toxicity. Prognostic factors for these adverse-events are poorly understood. PURPOSE: To ascertain prognostic factors associated with liver, blood or kidney adverse-events in people receiving immune-suppressing drugs. DATA SOURCES: MEDLINE, Web of Science, EMBASE and the Cochrane library (01 January 1995 to 05 January 2023), and supplementary sources. DATA EXTRACTION AND SYNTHESIS: Data were extracted by one reviewer using a modified CHARMS-PF checklist and validated by another. Two independent reviewers assessed risk of bias using Quality in Prognostic factor Studies tool and assessed the quality of evidence using a Grading of Recommendations Assessment, Development and Evaluation-informed framework. RESULTS: Fifty-six studies from 58 papers were included. High-quality evidence of the following associations was identified: elevated liver enzymes (6 studies) and folate non-supplementation (3 studies) are prognostic factors for hepatotoxicity in those treated with methotrexate; that mercaptopurine (vs azathioprine) (3 studies) was a prognostic factor for hepatotoxicity in those treated with thiopurines; that mercaptopurine (vs azathioprine) (3 studies) and poor-metaboliser status (4 studies) were prognostic factors for cytopenia in those treated with thiopurines; and that baseline elevated liver enzymes (3 studies) are a prognostic factor for hepatotoxicity in those treated with anti-tumour necrosis factors. Moderate and low quality evidence for several other demographic, lifestyle, comorbidities, baseline bloods/serologic or treatment-related prognostic factors were also identified. LIMITATIONS: Studies published before 1995, those with less than 200 participants and not published in English were excluded. Heterogeneity between studies included different cut-offs for prognostic factors, use of different outcome definitions and different adjustment factors. CONCLUSIONS: Prognostic factors for target-organ damage were identified which may be further investigated for their potential role in targeted (risk-stratified) monitoring. PROSPERO REGISTRATION NUMBER: CRD42020208049.

Minimal Intervention of Patient Education for Low Back Pain: A Systematic Review With Meta-analysis.

OBJECTIVE: To explore the effects of minimal intervention of patient education (MIPE) for reducing disability and pain intensity in patients with low back pain (LBP). DESIGN: Intervention systematic review with meta-analysis of randomized controlled trials. LITERATURE SEARCH: We searched the MEDLINE, Embase, CENTRAL, CINAHL, and PsycINFO databases from inception to May 2023. STUDY SELECTION CRITERIA: Trials comparing MIPE, consisting of a single session of patient education, to no or other interventions in patients with LBP. DATA SYNTHESIS: Random effects meta-analysis was conducted where possible. A noninferiority margin of 5 points (0-100 scale) was considered for noninferiority hypotheses. We assessed risk of bias using the revised Cochrane risk-of-bias tool (RoB 2), and certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework. RESULTS: A total of 21 trials were included. There were no differences between MIPE and no intervention for effects on disability and pain intensity. There was low-certainty evidence that MIPE had inferior effects on short-term disability (mean difference = 3.62; 95% CI: 0.85, 6.38; 15 trials; n = 3066; I2 = 75%) and pain intensity (mean difference = 9.43; 95% CI: 1.31, 17.56; 10 trials; n = 1394; I2 = 90%) than other interventions. No differences were found for subsequent time points. CONCLUSION: As an intervention delivered in isolation, and without tailoring (ie, one-size-fits-all intervention), MIPE on average did not provide benefits for reducing disability and pain intensity over no or other interventions. We encourage clinicians to consider using additional/other or more tailored treatments when helping people manage LBP. J Orthop Sports Phys Ther 2024;54(2):1-13. Epub 16 November 2023. doi:10.2519/jospt.2023.11865.

Discontinuation of anti-tumour necrosis factor alpha treatment owing to blood test abnormalities, and cost-effectiveness of alternate blood monitoring strategies.

BACKGROUND: There is no evidence base to support the use of 6-monthly monitoring blood tests for the early detection of liver, blood and renal toxicity during established anti-tumour necrosis factor alpha (TNFα) treatment. OBJECTIVES: To evaluate the incidence and risk factors of anti-TNFα treatment cessation owing to liver, blood and renal side-effects, and to estimate the cost-effectiveness of alternate intervals between monitoring blood tests. METHODS: A secondary care-based retrospective cohort study was performed. Data from the British Association of Dermatologists Biologic and Immunomodulators Register (BADBIR) were used. Patients with at least moderate psoriasis prescribed their first anti-TNFα treatment were included. Treatment discontinuation due to a monitoring blood test abnormality was the primary outcome. Patients were followed-up from start of treatment to the outcome of interest, drug discontinuation, death, 31 July 2021 or up to 5 years, whichever came first. The incidence rate (IR) and 95% confidence intervals (CIs) of anti-TNFα discontinuation with monitoring blood test abnormality was calculated. Multivariate Cox regression was used to examine the association between risk factors and outcome. A mathematical model evaluated costs and quality-adjusted life years (QALYs) associated with increasing the length of time between monitoring blood tests during anti-TNFα treatment. RESULTS: The cohort included 8819 participants [3710 (42.1%) female, mean (SD) age 44.76 (13.20) years] that contributed 25 058 person-years (PY) of follow-up and experienced 125 treatment discontinuations owing to a monitoring blood test abnormality at an IR of 5.85 (95% CI 4.91-6.97)/1000 PY. Of these, 64 and 61 discontinuations occurred within the first year and after the first year of treatment start, at IRs of 8.62 (95% CI 6.74-11.01) and 3.44 (95% CI 2.67-4.42)/1000 PY, respectively. Increasing age (in years), diabetes and liver disease were associated with anti-TNFα discontinuation after a monitoring blood test abnormality [adjusted hazard ratios of 1.02 (95% CI 1.01-1.04), 1.68 (95% CI 1.00-2.81) and 2.27 (95% CI 1.26-4.07), respectively]. Assuming a threshold of £20 000 per QALY gained, no monitoring was most cost-effective, but all extended periods were cost-effective vs. 3- or 6-monthly monitoring. CONCLUSIONS: Anti-TNFα drugs were uncommonly discontinued owing to abnormal monitoring blood tests after the first year of treatment. Extending the duration between monitoring blood tests was cost-effective. Our results produce evidence for specialist society guidance to reduce patient monitoring burden and healthcare costs.

Development and External Validation of Individualized Prediction Models for Pain Intensity Outcomes in Patients With Neck Pain, Low Back Pain, or Both in Primary Care Settings.

OBJECTIVE: The purpose of this study was to develop and externally validate multivariable prediction models for future pain intensity outcomes to inform targeted interventions for patients with neck or low back pain in primary care settings. METHODS: Model development data were obtained from a group of 679 adults with neck or low back pain who consulted a participating United Kingdom general practice. Predictors included self-report items regarding pain severity and impact from the STarT MSK Tool. Pain intensity at 2 and 6 months was modeled separately for continuous and dichotomized outcomes using linear and logistic regression, respectively. External validation of all models was conducted in a separate group of 586 patients recruited from a similar population with patients' predictor information collected both at point of consultation and 2 to 4 weeks later using self-report questionnaires. Calibration and discrimination of the models were assessed separately using STarT MSK Tool data from both time points to assess differences in predictive performance. RESULTS: Pain intensity and patients reporting their condition would last a long time contributed most to predictions of future pain intensity conditional on other variables. On external validation, models were reasonably well calibrated on average when using tool measurements taken 2 to 4 weeks after consultation (calibration slope = 0.848 [95% CI = 0.767 to 0.928] for 2-month pain intensity score), but performance was poor using point-of-consultation tool data (calibration slope for 2-month pain intensity score of 0.650 [95% CI = 0.549 to 0.750]). CONCLUSION: Model predictive accuracy was good when predictors were measured 2 to 4 weeks after primary care consultation, but poor when measured at the point of consultation. Future research will explore whether additional, nonmodifiable predictors improve point-of-consultation predictive performance. IMPACT: External validation demonstrated that these individualized prediction models were not sufficiently accurate to recommend their use in clinical practice. Further research is required to improve performance through inclusion of additional nonmodifiable risk factors.

Risk-stratified monitoring for thiopurine toxicity in immune-mediated inflammatory diseases: prognostic model development, validation, and, health economic evaluation.

Background: Patients established on thiopurines (e.g., azathioprine) are recommended to undergo three-monthly blood tests for the early detection of blood, liver, or kidney toxicity. These side-effects are uncommon during long-term treatment. We developed a prognostic model that could be used to inform risk-stratified decisions on frequency of monitoring blood-tests during long-term thiopurine treatment, and, performed health-economic evaluation of alternate monitoring intervals. Methods: This was a retrospective cohort study set in the UK primary-care. Data from the Clinical Practice Research Datalink Aurum and Gold formed development and validation cohorts, respectively. People age ≥18 years, diagnosed with an immune mediated inflammatory disease, prescribed thiopurine by their general practitioner for at-least six-months between January 1, 2007 and December 31, 2019 were eligible. The outcome was thiopurine discontinuation with abnormal blood-test results. Patients were followed up from six-months after first primary-care thiopurine prescription to up to five-years. Penalised Cox regression developed the risk equation. Multiple imputation handled missing predictor data. Calibration and discrimination assessed model performance. A mathematical model evaluated costs and quality-adjusted life years associated with lengthening the interval between blood-tests. Findings: Data from 5982 (405 events over 16,117 person-years) and 3573 (269 events over 9075 person-years) participants were included in the development and validation cohorts, respectively. Fourteen candidate predictors (21 parameters) were included. The optimism adjusted R2 and Royston D statistic in development data were 0.11 and 0.76, respectively. The calibration slope and Royston D statistic (95% Confidence Interval) in the validation data were 1.10 (0.84-1.36) and 0.72 (0.52-0.92), respectively. A 2-year period between monitoring blood-test was most cost-effective in all deciles of predicted risk but the gain between monitoring annually or biennially reduced in higher risk deciles. Interpretation: This prognostic model requires information that is readily available during routine clinical care and may be used to risk-stratify blood-test monitoring for thiopurine toxicity. These findings should be considered by specialist societies when recommending blood monitoring during thiopurine prescription to bring about sustainable and equitable change in clinical practice. Funding: National Institute for Health and Care Research.

Mechanisms of action of therapeutic exercise for knee and hip OA remain a black box phenomenon: an individual patient data mediation study with the OA Trial Bank.

OBJECTIVES: To evaluate mediating factors for the effect of therapeutic exercise on pain and physical function in people with knee/hip osteoarthritis (OA). METHODS: For Subgrouping and TargetEd Exercise pRogrammes for knee and hip OsteoArthritis (STEER OA), individual participant data (IPD) were sought from all published randomised controlled trials (RCTs) comparing therapeutic exercise to non-exercise controls in people with knee/hip OA. Using the Counterfactual framework, the effect of the exercise intervention and the percentage mediated through each potential mediator (muscle strength, proprioception and range of motion (ROM)) for knee OA and muscle strength for hip OA were determined. RESULTS: Data from 12 of 31 RCTs of STEER OA (1407 participants) were available. Within the IPD data sets, there were generally statistically significant effects from therapeutic exercise for pain and physical function in comparison to non-exercise controls. Of all potential mediators, only the change in knee extension strength was statistically and significantly associated with the change in pain in knee OA (ß -0.03 (95% CI -0.05 to -0.01), 2.3% mediated) and with physical function in knee OA (ß -0.02 (95% CI -0.04 to -0.00), 2.0% mediated) and hip OA (ß -0.03 (95% CI -0.07 to -0.00), no mediation). CONCLUSIONS: This first IPD mediation analysis of this scale revealed that in people with knee OA, knee extension strength only mediated ±2% of the effect of therapeutic exercise on pain and physical function. ROM and proprioception did not mediate changes in outcomes, nor did knee extension strength in people with hip OA. As 98% of the effectiveness of therapeutic exercise compared with non-exercise controls remains unexplained, more needs to be done to understand the underlying mechanisms of actions.

Supported self-management for all with musculoskeletal pain: an inclusive approach to intervention development: the EASIER study.

BACKGROUND: Supported self-management interventions for patients with musculoskeletal (MSK) conditions may not adequately support those with limited health literacy, leading to inequalities in care and variable outcomes. The aim of this study was to develop a model for inclusive supported self-management intervention(s) for MSK pain that take account of health literacy. METHODS: A mixed methods study with four work-packages was conducted: work package 1: secondary analysis of existing data to identify potential targets for intervention; work package 2: evidence synthesis to assess effective components of self-management interventions taking into account health literacy; work package 3: views of community members and healthcare professionals (HCPs) on essential components; work package 4: triangulation of findings and an online modified Delphi approach to reach consensus on key components of a logic model. FINDINGS: Findings identified targets for intervention as self-efficacy, illness perceptions, and pain catastrophizing. A range of intervention components were identified (e.g. information in diverse formats offered at specific times, action planning and visual demonstrations of exercise). Support should be multi-professional using a combination of delivery modes (e.g. remote, face-to-face). CONCLUSIONS: This research has developed a patient-centred model for a multi-disciplinary, multi-modal approach to supported self-management for patients with MSK pain and varying levels of health literacy. The model is evidence-based and acceptable to both patients and HCPs, with potential for significant impact on the management of MSK pain and for improving patient health outcomes. Further work is needed to establish its efficacy.

Risk stratified monitoring for methotrexate toxicity in immune mediated inflammatory diseases: prognostic model development and validation using primary care data from the UK.

OBJECTIVE: To develop and validate a prognostic model to inform risk stratified decisions on frequency of monitoring blood tests during long term methotrexate treatment. DESIGN: Retrospective cohort study. SETTING: Electronic health records within the UK's Clinical Practice Research Datalink (CPRD) Gold and CPRD Aurum. PARTICIPANTS: Adults (≥18 years) with a diagnosis of an immune mediated inflammatory disease who were prescribed methotrexate by their general practitioner for six months or more during 2007-19. MAIN OUTCOME MEASURE: Discontinuation of methotrexate owing to abnormal monitoring blood test result. Patients were followed-up from six months after their first prescription for methotrexate in primary care to the earliest of outcome, drug discontinuation for any other reason, leaving the practice, last data collection from the practice, death, five years, or 31 December 2019. Cox regression was performed to develop the risk equation, with bootstrapping used to shrink predictor effects for optimism. Multiple imputation handled missing predictor data. Model performance was assessed in terms of calibration and discrimination. RESULTS: Data from 13 110 (854 events) and 23 999 (1486 events) participants were included in the development and validation cohorts, respectively. 11 candidate predictors (17 parameters) were included. In the development dataset, the optimism adjusted R2 was 0.13 and the optimism adjusted Royston D statistic was 0.79. The calibration slope and Royston D statistic in the validation dataset for the entire follow-up period was 0.94 (95% confidence interval 0.85 to 1.02) and 0.75 (95% confidence interval 0.67 to 0.83), respectively. The prognostic model performed well in predicting outcomes in clinically relevant subgroups defined by age group, type of immune mediated inflammatory disease, and methotrexate dose. CONCLUSION: A prognostic model was developed and validated that uses information collected during routine clinical care and may be used to risk stratify the frequency of monitoring blood test during long term methotrexate treatment.

SupportPrim-a computerized clinical decision support system for stratified care for patients with musculoskeletal pain complaints in general practice: study protocol for a randomized controlled trial.

BACKGROUND: Musculoskeletal disorders represented 149 million years lived with disability world-wide in 2019 and are the main cause of years lived with disability worldwide. Current treatment recommendations are based on "one-size fits all" principle, which does not take into account the large degree of biopsychosocial heterogeneity in this group of patients. To compensate for this, we developed a stratified care computerized clinical decision support system for general practice based on patient biopsychosocial phenotypes; furthermore, we added personalized treatment recommendations based on specific patient factors to the system. In this study protocol, we describe the randomized controlled trial for evaluating the effectiveness of computerized clinical decision support system for stratified care for patients with common musculoskeletal pain complaints in general practice. The aim of this study is to test the effect of a computerized clinical decision support system for stratified care in general practice on subjective patient outcome variables compared to current care. METHODS: We will perform a cluster-randomized controlled trial with 44 general practitioners including 748 patients seeking their general practitioner due to pain in the neck, back, shoulder, hip, knee, or multisite. The intervention group will use the computerized clinical decision support system, while the control group will provide current care for their patients. The primary outcomes assessed at 3 months are global perceived effect and clinically important improvement in function measured by the Patient-Specific Function Scale (PSFS), while secondary outcomes include change in pain intensity measured by the Numeric Rating Scale (0-10), health-related quality of life (EQ-5D), general musculoskeletal health (MSK-HQ), number of treatments, use of painkillers, sick-leave grading and duration, referral to secondary care, and use of imaging. DISCUSSION: The use of biopsychosocial profile to stratify patients and implement it in a computerized clinical decision support system for general practitioners is a novel method of providing decision support for this patient group. The study aim to recruit patients from May 2022 to March 2023, and the first results from the study will be available late 2023. TRIAL REGISTRATION: The trial is registered in ISRCTN 11th of May 2022: 14,067,965.

Determining cardiovascular risk in patients with unattributed chest pain in UK primary care: an electronic health record study.

AIMS: Most adults presenting in primary care with chest pain symptoms will not receive a diagnosis ('unattributed' chest pain) but are at increased risk of cardiovascular events. To assess within patients with unattributed chest pain, risk factors for cardiovascular events and whether those at greatest risk of cardiovascular disease can be ascertained by an existing general population risk prediction model or by development of a new model. METHODS AND RESULTS: The study used UK primary care electronic health records from the Clinical Practice Research Datalink linked to admitted hospitalizations. Study population was patients aged 18 plus with recorded unattributed chest pain 2002-2018. Cardiovascular risk prediction models were developed with external validation and comparison of performance to QRISK3, a general population risk prediction model. There were 374 917 patients with unattributed chest pain in the development data set. The strongest risk factors for cardiovascular disease included diabetes, atrial fibrillation, and hypertension. Risk was increased in males, patients of Asian ethnicity, those in more deprived areas, obese patients, and smokers. The final developed model had good predictive performance (external validation c-statistic 0.81, calibration slope 1.02). A model using a subset of key risk factors for cardiovascular disease gave nearly identical performance. QRISK3 underestimated cardiovascular risk. CONCLUSION: Patients presenting with unattributed chest pain are at increased risk of cardiovascular events. It is feasible to accurately estimate individual risk using routinely recorded information in the primary care record, focusing on a small number of risk factors. Patients at highest risk could be targeted for preventative measures.

It is known that patients with chest pain without a recognized cause are at increased risk of future cardiovascular events (for example, heart disease) and so this study aimed to find out whether those patients at greatest risk could be determined using information in their health records. It is possible to accurately estimate a person's risk of future cardiovascular events using the information entered into their health records, and this risk can be estimated using only a small number of factors.Patients at highest risk could now be targeted for management to help prevent future cardiovascular events.

Symptom patterns and life with post-acute COVID-19 in children aged 8-17 years: a mixed-methods study protocol.

BACKGROUND: While there is a substantial body of knowledge about acute COVID-19, less is known about long-COVID, where symptoms continue beyond 4 weeks. AIM: To describe longer-term effects of COVID-19 infection in children and young people (CYP) and identify their needs in relation to long-COVID. DESIGN & SETTING: This study comprises an observational prospective cohort study and a linked qualitative study, identifying participants aged 8-17 years in the West Midlands of England. METHOD: CYP will be invited to complete online questionnaires to monitor incidences and symptoms of COVID-19 over a 12-month period. CYP who have experienced long-term effects of COVID will be invited to interview, and those currently experiencing symptoms will be asked to document their experiences in a diary. Professionals who work with CYP will be invited to explore the impact of long-COVID on the wider experiences of CYP, in a focus group. Descriptive statistics will be used to describe the incidence and rates of resolution of symptoms, and comparisons will be made between exposed and non-exposed groups. Logistic regression models will be used to estimate associations between candidate predictors and the development of long-COVID, and linear regression will be used to estimate associations between candidate predictors. Qualitative data will be analysed thematically using the constant comparison method. CONCLUSION: This study will describe features and symptoms of long-COVID and explore the impact of long-COVID within the lives of CYP and their families, to provide better understanding of long-COVID and inform clinical practice.

Diabetes as a risk factor for the onset of frozen shoulder: a systematic review and meta-analysis.

OBJECTIVE: Summarise longitudinal observational studies to determine whether diabetes (types 1 and 2) is a risk factor for frozen shoulder. DESIGN: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, Embase, AMED, PsycINFO, Web of Science Core Collection, CINAHL, Epistemonikos, Trip, PEDro, OpenGrey and The Grey Literature Report were searched on January 2019 and updated in June 2021. Reference screening and emailing professional contacts were also used. ELIGIBILITY CRITERIA: Longitudinal observational studies that estimated the association between diabetes and developing frozen shoulder. DATA EXTRACTION AND SYNTHESIS: Data extraction was completed by one reviewer and independently checked by another using a predefined extraction sheet. Risk of bias was judged using the Quality In Prognosis Studies tool. For studies providing sufficient data, random-effects meta-analysis was used to derive summary estimates of the association between diabetes and the onset of frozen shoulder. RESULTS: A meta-analysis of six case-control studies including 5388 people estimated the odds of developing frozen shoulder for people with diabetes to be 3.69 (95% CI 2.99 to 4.56) times the odds for people without diabetes. Two cohort studies were identified, both suggesting diabetes was associated with frozen shoulder, with HRs of 1.32 (95% CI 1.22 to 1.42) and 1.67 (95% CI 1.46 to 1.91). Risk of bias was judged as high in seven studies and moderate in one study. CONCLUSION: People with diabetes are more likely to develop frozen shoulder. Risk of unmeasured confounding was the main limitation of this systematic review. High-quality studies are needed to confirm the strength of, and understand reasons for, the association. PROSPERO REGISTRATION NUMBER: CRD42019122963.

The effectiveness of corticosteroid injection versus night splints for carpal tunnel syndrome: 24-month follow-up of a randomized trial.

OBJECTIVES: This follow-up study of the INSTinCTS (INjection vs SplinTing in Carpal Tunnel Syndrome) trial compared the effects of corticosteroid injection (CSI) and night splinting (NS) for the initial management of mild-to-moderate CTS on symptoms, resource use and carpal tunnel surgery, over 24 months. METHODS: Adults with mild-to-moderate CTS were randomized 1:1 to a local corticosteroid injection or a night splint worn for 6 weeks. Outcomes at 12 and 24 months included the Boston Carpal Tunnel Questionnaire (BCTQ), hand/wrist pain intensity numeric rating scale (NRS), the number of patients referred for and undergoing CTS surgery, and healthcare utilization. A cost-utility analysis was conducted. RESULTS: One hundred and sixteen participants received a CSI and 118 a NS. The response rate at 24 months was 73% in the CSI arm and 71% in the NS arm. By 24 months, a greater proportion of the CSI group had been referred for (28% vs 20%) and undergone (22% vs 16%) CTS surgery compared with the NS group. There were no statistically significant between-group differences in BCTQ score or pain NRS at 12 or 24 months. CSI was more costly [mean difference £68.59 (95% CI: -120.84, 291.24)] with fewer quality-adjusted life-years than NS over 24 months [mean difference -0.022 (95% CI: -0.093, 0.045)]. CONCLUSION: Over 24 months, surgical intervention rates were low in both groups, but less frequent in the NS group. While there were no differences in the clinical effectiveness of CSI and NS, initial treatment with CSI may not be cost-effective in the long-term compared with NS.

Management of Psoriatic Arthritis in Patients With Comorbidities: An Updated Literature Review Informing the 2021 GRAPPA Treatment Recommendations.

OBJECTIVE: The 2021 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendations provide an evidence-based guide for selecting therapy based on the individual's disease features. Beyond the disease features and associated conditions (eg, uveitis and inflammatory bowel disease), comorbidities play an important role in selecting therapy for an individual patient. METHODS: We performed a systematic literature review. We examined the available evidence to inform treatment selection based on the presence or absence of comorbidities in psoriatic arthritis (PsA). RESULTS: Common comorbidities in PsA that may affect treatment selection include presence of baseline cardiovascular disease (CVD) or high risk for CVD, obesity and metabolic syndrome, liver disease, mood disorders, including depression in particular, chronic infections, malignancies, osteoporosis, and fibromyalgia and/or central sensitization. CONCLUSION: Comorbidities may influence both the effectiveness of a given therapy but also the potential for adverse events. It is important to assess for the presence of comorbidities prior to therapy selection.