Accelerometer-Measured Physical Activity Data Sets (Global Physical Activity Data Set Catalogue) That Include Markers of Cardiometabolic Health: Systematic Scoping Review.

BACKGROUND: Cardiovascular disease accounts for 17.9 million deaths globally each year. Many research study data sets have been collected to answer questions regarding the relationship between cardiometabolic health and accelerometer-measured physical activity. This scoping review aimed to map the available data sets that have collected accelerometer-measured physical activity and cardiometabolic health markers. These data were then used to inform the development of a publicly available resource, the Global Physical Activity Data set (GPAD) catalogue. OBJECTIVE: This review aimed to systematically identify data sets that have measured physical activity using accelerometers and cardiometabolic health markers using either an observational or interventional study design. METHODS: Databases, trial registries, and gray literature (inception until February 2021; updated search from February 2021 to September 2022) were systematically searched to identify studies that analyzed data sets of physical activity and cardiometabolic health outcomes. To be eligible for inclusion, data sets must have measured physical activity using an accelerometric device in adults aged ≥18 years; a sample size >400 participants (unless recruited participants in a low- and middle-income country where a sample size threshold was reduced to 100); used an observational, longitudinal, or trial-based study design; and collected at least 1 cardiometabolic health marker (unless only body mass was measured). Two reviewers screened the search results to identify eligible studies, and from these, the unique names of each data set were recorded, and characteristics about each data set were extracted from several sources. RESULTS: A total of 17,391 study reports were identified, and after screening, 319 were eligible, with 122 unique data sets in these study reports meeting the review inclusion criteria. Data sets were found in 49 countries across 5 continents, with the most developed in Europe (n=53) and the least in Africa and Oceania (n=4 and n=3, respectively). The most common accelerometric brand and device wear location was Actigraph and the waist, respectively. Height and body mass were the most frequently measured cardiometabolic health markers in the data sets (119/122, 97.5% data sets), followed by blood pressure (82/122, 67.2% data sets). The number of participants in the included data sets ranged from 103,712 to 120. Once the review processes had been completed, the GPAD catalogue was developed to house all the identified data sets. CONCLUSIONS: This review identified and mapped the contents of data sets from around the world that have collected potentially harmonizable accelerometer-measured physical activity and cardiometabolic health markers. The GPAD catalogue is a web-based open-source resource developed from the results of this review, which aims to facilitate the harmonization of data sets to produce evidence that will reduce the burden of disease from physical inactivity.

Detecting Algorithmic Errors and Patient Harms for AI-Enabled Medical Devices in Randomized Controlled Trials: Protocol for a Systematic Review.

BACKGROUND: Artificial intelligence (AI) medical devices have the potential to transform existing clinical workflows and ultimately improve patient outcomes. AI medical devices have shown potential for a range of clinical tasks such as diagnostics, prognostics, and therapeutic decision-making such as drug dosing. There is, however, an urgent need to ensure that these technologies remain safe for all populations. Recent literature demonstrates the need for rigorous performance error analysis to identify issues such as algorithmic encoding of spurious correlations (eg, protected characteristics) or specific failure modes that may lead to patient harm. Guidelines for reporting on studies that evaluate AI medical devices require the mention of performance error analysis; however, there is still a lack of understanding around how performance errors should be analyzed in clinical studies, and what harms authors should aim to detect and report. OBJECTIVE: This systematic review will assess the frequency and severity of AI errors and adverse events (AEs) in randomized controlled trials (RCTs) investigating AI medical devices as interventions in clinical settings. The review will also explore how performance errors are analyzed including whether the analysis includes the investigation of subgroup-level outcomes. METHODS: This systematic review will identify and select RCTs assessing AI medical devices. Search strategies will be deployed in MEDLINE (Ovid), Embase (Ovid), Cochrane CENTRAL, and clinical trial registries to identify relevant papers. RCTs identified in bibliographic databases will be cross-referenced with clinical trial registries. The primary outcomes of interest are the frequency and severity of AI errors, patient harms, and reported AEs. Quality assessment of RCTs will be based on version 2 of the Cochrane risk-of-bias tool (RoB2). Data analysis will include a comparison of error rates and patient harms between study arms, and a meta-analysis of the rates of patient harm in control versus intervention arms will be conducted if appropriate. RESULTS: The project was registered on PROSPERO in February 2023. Preliminary searches have been completed and the search strategy has been designed in consultation with an information specialist and methodologist. Title and abstract screening started in September 2023. Full-text screening is ongoing and data collection and analysis began in April 2024. CONCLUSIONS: Evaluations of AI medical devices have shown promising results; however, reporting of studies has been variable. Detection, analysis, and reporting of performance errors and patient harms is vital to robustly assess the safety of AI medical devices in RCTs. Scoping searches have illustrated that the reporting of harms is variable, often with no mention of AEs. The findings of this systematic review will identify the frequency and severity of AI performance errors and patient harms and generate insights into how errors should be analyzed to account for both overall and subgroup performance. TRIAL REGISTRATION: PROSPERO CRD42023387747; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=387747. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/51614.

Systematic review of imaging tests to predict the development of rheumatoid arthritis in people with unclassified arthritis.

OBJECTIVE: To estimate and compare the diagnostic accuracy of magnetic resonance imaging (MRI) and ultrasound, for the prediction of rheumatoid arthritis (RA) in unclassified arthritis (UA). METHODS: MEDLINE, Embase and BIOSIS were searched from 1987 to May 2019. Studies evaluating any imaging test in participants with UA were eligible. Reference standards were RA classification criteria or methotrexate initiation. Two authors independently extracted data and assessed validity using QUADAS-2. Sensitivities and specificities were calculated for each imaging characteristic and joint area. Summary estimates with 95% confidence intervals (CI) were estimated where possible. RESULTS: Nineteen studies were included; 13 evaluated MRI (n=1,143; 454 with RA) and 6 evaluated ultrasound (n=531; 205 with RA). Studies were limited by unclear recruitment procedures, inclusion of patients with RA at baseline, differential verification, lack of blinding and consensus grading. Study heterogeneity largely precluded meta-analysis, however summary sensitivity and specificity for MRI synovitis in at least one joint were 93% (95% CI 88%, 96%) and 25% (95% CI 13%, 41%) (3 studies). Specificities may be higher for other MRI characteristics but data are limited. Ultrasound results were difficult to synthesise due to different diagnostic thresholds and reference standards. CONCLUSION: The evidence for MRI or ultrasound as single tests for predicting RA in people with UA is heterogeneous and of variable methodological quality. Larger studies using consensus grading and consistently defined RA diagnosis are needed to identify whether combinations of imaging characteristics, either alone or in combination with other clinical findings, can better predict RA in this population.

Effectiveness of physical activity interventions delivered or prompted by health professionals in primary care settings: systematic review and meta-analysis of randomised controlled trials.

OBJECTIVE: To examine the effectiveness of physical activity interventions delivered or prompted by primary care health professionals for increasing moderate to vigorous intensity physical activity (MVPA) in adult patients. DESIGN: Systematic review and meta-analysis of randomised controlled trials. DATA SOURCES: Databases (Medline and Medline in progress, Embase, PsycINFO, CINAHL, SPORTDiscus, Sports Medicine and Education Index, ASSIA, PEDro, Bibliomap, Science Citation Index, Conference Proceedings Citation Index), trial registries (Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, TRoPHI), and grey literature (OpenGrey) sources were searched (from inception to September 2020). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials of aerobic based physical activity interventions delivered or prompted by health professionals in primary care with a usual care control group or another control group that did not involve physical activity. STUDY SELECTION AND ANALYSIS: Two independent reviewers screened the search results, extracted data from eligible trials and assessed the risk of bias using the Cochrane risk of bias tool (version 2). Inverse variance meta-analyses using random effects models examined the primary outcome of difference between the groups in MVPA (min/week) from baseline to final follow-up. The odds of meeting the guidelines for MVPA at follow-up were also analysed. RESULTS: 14 566 unique reports were identified and 46 randomised controlled trials with a range of follow-ups (3-60 months) were included in the meta-analysis (n=16 198 participants). Physical activity interventions delivered or prompted by health professionals in primary care increased MVPA by 14 min/week (95% confidence interval 4.2 to 24.6, P=0.006). Heterogeneity was substantial (I2=91%, P<0.001). Limiting analyses to trials that used a device to measure physical activity showed no significant group difference in MVPA (mean difference 4.1 min/week, 95% confidence interval -1.7 to 9.9, P=0.17; I2=56%, P=0.008). Trials that used self-report measures showed that intervention participants achieved 24 min/week more MVPA than controls (95% confidence interval 6.3 to 41.8, P=0.008; I2=72%, P<0.001). Additionally, interventions increased the odds of patients meeting guidelines for MVPA by 33% (95% confidence interval 1.17 to 1.50, P<0.001; I2=25%, P=0.11) versus controls. 14 of 46 studies were at high risk of bias but sensitivity analyses excluding these studies did not alter the results. CONCLUSIONS: Physical activity interventions delivered or prompted by health professionals in primary care appear effective at increasing participation in self-reported MVPA. Such interventions should be considered for routine implementation to increase levels of physical activity and improve health outcomes in the population. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021209484.

Effectiveness of interventions to reduce household air pollution from solid biomass fuels and improve maternal and child health outcomes in low- and middle-income countries: a systematic review protocol.

BACKGROUND: A variety of public health interventions have been undertaken in low- and middle-income countries (LMICs) to prevent morbidity and mortality associated with household air pollution (HAP) due to cooking, heating and lighting with solid biomass fuels. Pregnant women and children under five are particularly vulnerable to the effects of HAP, due to biological susceptibility and typically higher exposure levels. However, the relative health benefits of interventions to reduce HAP exposure among these groups remain unclear. This systematic review aims to assess, among pregnant women, infants and children (under 5 years) in LMIC settings, the effectiveness of interventions which aim to reduce household air pollutant emissions due to household solid biomass fuel combustion, compared to usual cooking practices, in terms of health outcomes associated with HAP exposure. METHODS: This protocol follows standard systematic review processes and abides by the PRISMA-P reporting guidelines. Searches will be undertaken in MEDLINE, EMBASE, CENTRAL, WHO International Clinical Trials Registry Platform (ICTRP), The Global Index Medicus (GIM), ClinicalTrials.gov and Greenfile, combining terms for pregnant women and children with interventions or policy approaches to reduce HAP from biomass fuels or HAP terms and LMIC countries. Included studies will be those reporting (i) pregnant women and children under 5 years; (ii) fuel transition, structural, educational or policy interventions; and (iii) health events associated with HAP exposure which occur among pregnant women or among children within the perinatal period, infancy and up to 5 years of age. A narrative synthesis will be undertaken for each population-intervention-outcome triad stratified by study design. Clinical and methodological homogeneity within each triad will be used to determine the feasibility for undertaking meta-analyses to give a summary estimate of the effect for each outcome. DISCUSSION: This systematic review will identify the effectiveness of existing HAP intervention measures in LMIC contexts, with discussion on the context of implementation and adoption, and summarise current literature of relevance to maternal and child health. This assessment reflects the need for HAP interventions which achieve measurable health benefits, which would need to be supported by policies that are socially and economically acceptable in LMIC settings worldwide. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020164998.

Effects of physical activity calorie equivalent food labelling to reduce food selection and consumption: systematic review and meta-analysis of randomised controlled studies.

BACKGROUND: There is limited evidence that nutritional labelling on food/drinks is changing eating behaviours. Physical activity calorie equivalent (PACE) food labelling aims to provide the public with information about the amount of physical activity required to expend the number of kilocalories in food/drinks (eg, calories in this pizza requires 45 min of running to burn), to encourage healthier food choices and reduce disease. OBJECTIVE: We aimed to systematically search for randomised controlled trials and experimental studies of the effects of PACE food labelling on the selection, purchase or consumption of food/drinks. METHODS: PACE food labelling was compared with any other type of food labelling or no labelling (comparator). Reports were identified by searching electronic databases, websites and social media platforms. Inverse variance meta-analysis was used to summarise evidence. Weighted mean differences (WMD) and 95% CIs were used to describe between-group differences using a random effects model. RESULTS: 15 studies were eligible for inclusion. When PACE labelling was displayed on food/drinks and menus, significantly fewer calories were selected, relative to comparator labelling (WMD=-64.9 kcal, 95% CI -103.2 to -26.6, p=0.009, n=4606). Presenting participants with PACE food labelling results in the consumption of significantly fewer calories (WMD=-80.4 kcal, 95% CI-136.7 to -24.2, p=0.005, n=486) relative to comparator food labelling. CONCLUSION: Based on current evidence PACE food labelling may reduce the number of kilocalories selected from menus and decrease the number of kilocalories/grams of food consumed by the public, compared with other types of food labelling/no labelling. TRIAL REGISTRATION NUMBER: CRD42018088567.