Social network interventions to support cardiac rehabilitation and secondary prevention in the management of people with heart disease.

BACKGROUND: Globally, cardiovascular diseases (CVD, that is, coronary heart (CHD) and circulatory diseases combined) contribute to 31% of all deaths, more than any other cause. In line with guidance in the UK and globally, cardiac rehabilitation programmes are widely offered to people with heart disease, and include psychosocial, educational, health behaviour change, and risk management components. Social support and social network interventions have potential to improve outcomes of these programmes, but whether and how these interventions work is poorly understood.  OBJECTIVES: To assess the effectiveness of social network and social support interventions to support cardiac rehabilitation and secondary prevention in the management of people with heart disease. The comparator was usual care with no element of social support (i.e. secondary prevention alone or with cardiac rehabilitation).  SEARCH METHODS: We undertook a systematic search of the following databases on 9 August 2022: CENTRAL, MEDLINE, Embase, and the Web of Science. We also searched ClinicalTrials.gov and the WHO ICTRP. We reviewed the reference lists of relevant systematic reviews and included primary studies, and we contacted experts to identify additional studies.  SELECTION CRITERIA: We included randomised controlled trials (RCTs) of social network or social support interventions for people with heart disease. We included studies regardless of their duration of follow-up, and included those reported as full text, published as abstract only, and unpublished data. DATA COLLECTION AND ANALYSIS: Using Covidence, two review authors independently screened all identified titles. We retrieved full-text study reports and publications marked 'included', and two review authors independently screened these, and conducted data extraction. Two authors independently assessed risk of bias, and assessed the certainty of the evidence using GRADE. Primary outcomes were all-cause mortality, cardiovascular-related mortality, all-cause hospital admission, cardiovascular-related hospital admission, and health-related quality of life (HRQoL) measured at > 12 months follow-up.  MAIN RESULTS: We included 54 RCTs (126 publications) reporting data for a total of 11,445 people with heart disease. The median follow-up was seven months and median sample size was 96 participants. Of included study participants, 6414 (56%) were male, and the mean age ranged from 48.6 to 76.3 years. Studies included heart failure (41%), mixed cardiac disease (31%), post-myocardial infarction (13%), post-revascularisation (7%), CHD (7%), and cardiac X syndrome (1%) patients. The median intervention duration was 12 weeks. We identified notable diversity in social network and social support interventions, across what was delivered, how, and by whom.  We assessed risk of bias (RoB) in primary outcomes at > 12 months follow-up as either 'low' (2/15 studies), 'some concerns' (11/15), or 'high' (2/15). 'Some concerns' or 'high' RoB resulted from insufficient detail on blinding of outcome assessors, data missingness, and absence of pre-agreed statistical analysis plans. In particular, HRQoL outcomes were at high RoB. Using the GRADE method, we assessed the certainty of evidence as low or very low across outcomes. Social network or social support interventions had no clear effect on all-cause mortality (risk ratio (RR) 0.75, 95% confidence interval (CI) 0.49 to 1.13, I2 = 40%) or cardiovascular-related mortality (RR 0.85, 95% CI 0.66 to 1.10, I2 = 0%) at > 12 months follow-up. The evidence suggests that social network or social support interventions for heart disease may result in little to no difference in all-cause hospital admission (RR 1.03, 95% CI 0.86 to 1.22, I2 = 0%), or cardiovascular-related hospital admission (RR 0.92, 95% CI 0.77 to 1.10, I2 = 16%), with a low level of certainty. The evidence was very uncertain regarding the impact of social network interventions on HRQoL at > 12 months follow-up (SF-36 physical component score: mean difference (MD) 31.53, 95% CI -28.65 to 91.71, I2 = 100%, 2 trials/comparisons, 166 participants; mental component score MD 30.62, 95% CI -33.88 to 95.13, I2 = 100%, 2 trials/comparisons, 166 participants).  Regarding secondary outcomes, there may be a decrease in both systolic and diastolic blood pressure with social network or social support interventions. There was no evidence of impact found on psychological well-being, smoking, cholesterol, myocardial infarction, revascularisation, return to work/education, social isolation or connectedness, patient satisfaction, or adverse events.  Results of meta-regression did not suggest that the intervention effect was related to risk of bias, intervention type, duration, setting, and delivery mode, population type, study location, participant age, or percentage of male participants.  AUTHORS' CONCLUSIONS: We found no strong evidence for the effectiveness of such interventions, although modest effects were identified in relation to blood pressure. While the data presented in this review are indicative of potential for positive effects, the review also highlights the lack of sufficient evidence to conclusively support such interventions for people with heart disease. Further high-quality, well-reported RCTs are required to fully explore the potential of social support interventions in this context. Future reporting of social network and social support interventions for people with heart disease needs to be significantly clearer, and more effectively theorised, in order to ascertain causal pathways and effect on outcomes.

Regression Discontinuity Designs in Health: A Systematic Review.

BACKGROUND: Regression discontinuity designs are non-randomized study designs that permit strong causal inference with relatively weak assumptions. Interest in these designs is growing but there is limited knowledge of the extent of their application in health. We aimed to conduct a comprehensive systematic review of the use of regression discontinuity designs in health research. METHODS: We included studies that used regression discontinuity designs to investigate the physical or mental health outcomes of any interventions or exposures in any populations. We searched 32 health, social science, and gray literature databases (1 January 1960 to 1 January 2019). We critically appraised studies using eight criteria adapted from the What Works Clearinghouse Standards for regression discontinuity designs. We conducted a narrative synthesis, analyzing the forcing variables and threshold rules used in each study. RESULTS: The literature search retrieved 7658 records, producing 325 studies that met the inclusion criteria. A broad range of health topics was represented. The forcing variables used to implement the design were age, socioeconomic measures, date or time of exposure or implementation, environmental measures such as air quality, geographic location, and clinical measures that act as a threshold for treatment. Twelve percent of the studies fully met the eight quality appraisal criteria. Fifteen percent of studies reported a prespecified primary outcome or study protocol. CONCLUSIONS: This systematic review demonstrates that regression discontinuity designs have been widely applied in health research and could be used more widely still. Shortcomings in study quality and reporting suggest that the potential benefits of this method have not yet been fully realized.

ERS guidelines on the diagnosis and treatment of chronic cough in adults and children.

These guidelines incorporate the recent advances in chronic cough pathophysiology, diagnosis and treatment. The concept of cough hypersensitivity has allowed an umbrella term that explains the exquisite sensitivity of patients to external stimuli such a cold air, perfumes, smoke and bleach. Thus, adults with chronic cough now have a firm physical explanation for their symptoms based on vagal afferent hypersensitivity. Different treatable traits exist with cough variant asthma (CVA)/eosinophilic bronchitis responding to anti-inflammatory treatment and non-acid reflux being treated with promotility agents rather the anti-acid drugs. An alternative antitussive strategy is to reduce hypersensitivity by neuromodulation. Low-dose morphine is highly effective in a subset of patients with cough resistant to other treatments. Gabapentin and pregabalin are also advocated, but in clinical experience they are limited by adverse events. Perhaps the most promising future developments in pharmacotherapy are drugs which tackle neuronal hypersensitivity by blocking excitability of afferent nerves by inhibiting targets such as the ATP receptor (P2X3). Finally, cough suppression therapy when performed by competent practitioners can be highly effective. Children are not small adults and a pursuit of an underlying cause for cough is advocated. Thus, in toddlers, inhalation of a foreign body is common. Persistent bacterial bronchitis is a common and previously unrecognised cause of wet cough in children. Antibiotics (drug, dose and duration need to be determined) can be curative. A paediatric-specific algorithm should be used.

Taxation of unprocessed sugar or sugar-added foods for reducing their consumption and preventing obesity or other adverse health outcomes.

BACKGROUND: Global prevalence of overweight and obesity are alarming. For tackling this public health problem, preventive public health and policy actions are urgently needed. Some countries implemented food taxes in the past and some were subsequently abolished. Some countries, such as Norway, Hungary, Denmark, Bermuda, Dominica, St. Vincent and the Grenadines, and the Navajo Nation (USA), specifically implemented taxes on unprocessed sugar and sugar-added foods. These taxes on unprocessed sugar and sugar-added foods are fiscal policy interventions, implemented to decrease their consumption and in turn reduce adverse health-related, economic and social effects associated with these food products. OBJECTIVES: To assess the effects of taxation of unprocessed sugar or sugar-added foods in the general population on the consumption of unprocessed sugar or sugar-added foods, the prevalence and incidence of overweight and obesity, and the prevalence and incidence of other diet-related health outcomes. SEARCH METHODS: We searched CENTRAL, Cochrane Database of Systematic Reviews, MEDLINE, Embase and 15 other databases and trials registers on 12 September 2019. We handsearched the reference list of all records of included studies, searched websites of international organisations and institutions, and contacted review advisory group members to identify planned, ongoing or unpublished studies. SELECTION CRITERIA: We included studies with the following populations: children (0 to 17 years) and adults (18 years or older) from any country and setting. Exclusion applied to studies with specific subgroups, such as people with any disease who were overweight or obese as a side-effect of the disease. The review included studies with taxes on or artificial increases of selling prices for unprocessed sugar or food products that contain added sugar (e.g. sweets, ice cream, confectionery, and bakery products), or both, as intervention, regardless of the taxation level or price increase. In line with Cochrane Effective Practice and Organisation of Care (EPOC) criteria, we included randomised controlled trials (RCTs), cluster-randomised controlled trials (cRCTs), non-randomised controlled trials (nRCTs), controlled before-after (CBA) studies, and interrupted time series (ITS) studies. We included controlled studies with more than one intervention or control site and ITS studies with a clearly defined intervention time and at least three data points before and three after the intervention. Our primary outcomes were consumption of unprocessed sugar or sugar-added foods, energy intake, overweight, and obesity. Our secondary outcomes were substitution and diet, expenditure, demand, and other health outcomes. DATA COLLECTION AND ANALYSIS: Two review authors independently screened all eligible records for inclusion, assessed the risk of bias, and performed data extraction.Two review authors independently assessed the certainty of the evidence using the GRADE approach. MAIN RESULTS: We retrieved a total of 24,454 records. After deduplicating records, 18,767 records remained for title and abstract screening. Of 11 potentially relevant studies, we included one ITS study with 40,210 household-level observations from the Hungarian Household Budget and Living Conditions Survey. The baseline ranged from January 2008 to August 2011, the intervention was implemented on September 2011, and follow-up was until December 2012 (16 months). The intervention was a tax - the so-called 'Hungarian public health product tax' - on sugar-added foods, including selected foods exceeding a specific sugar threshold value. The intervention includes co-interventions: the taxation of sugar-sweetened beverages (SSBs) and of foods high in salt or caffeine. The study provides evidence on the effect of taxing foods exceeding a specific sugar threshold value on the consumption of sugar-added foods. After implementation of the Hungarian public health product tax, the mean consumption of taxed sugar-added foods (measured in units of kg) decreased by 4.0% (standardised mean difference (SMD) -0.040, 95% confidence interval (CI) -0.07 to -0.01; very low-certainty evidence). The study was at low risk of bias in terms of performance bias, detection bias and reporting bias, with the shape of effect pre-specified and the intervention unlikely to have any effect on data collection. The study was at unclear risk of attrition bias and at high risk in terms of other bias and the independence of the intervention. We rated the certainty of the evidence as very low for the primary and secondary outcomes. The Hungarian public health product tax included a tax on sugar-added foods but did not include a tax on unprocessed sugar. We did not find eligible studies reporting on the taxation of unprocessed sugar. No studies reported on the primary outcomes of consumption of unprocessed sugar, energy intake, overweight, and obesity. No studies reported on the secondary outcomes of substitution and diet, demand, and other health outcomes. No studies reported on differential effects across population subgroups. We could not perform meta-analyses or pool study results. AUTHORS' CONCLUSIONS: There was very limited evidence and the certainty of the evidence was very low. Despite the reported reduction in consumption of taxed sugar-added foods, we are uncertain whether taxing unprocessed sugar or sugar-added foods has an effect on reducing their consumption and preventing obesity or other adverse health outcomes. Further robustly conducted studies are required to draw concrete conclusions on the effectiveness of taxing unprocessed sugar or sugar-added foods for reducing their consumption and preventing obesity or other adverse health outcomes.

A systematic review and quality assessment of individualised breast cancer risk prediction models.

BACKGROUND: Individualised breast cancer risk prediction models may be key for planning risk-based screening approaches. Our aim was to conduct a systematic review and quality assessment of these models addressed to women in the general population. METHODS: We followed the Cochrane Collaboration methods searching in Medline, EMBASE and The Cochrane Library databases up to February 2018. We included studies reporting a model to estimate the individualised risk of breast cancer in women in the general population. Study quality was assessed by two independent reviewers. Results are narratively summarised. RESULTS: We included 24 studies out of the 2976 citations initially retrieved. Twenty studies were based on four models, the Breast Cancer Risk Assessment Tool (BCRAT), the Breast Cancer Surveillance Consortium (BCSC), the Rosner & Colditz model, and the International Breast Cancer Intervention Study (IBIS), whereas four studies addressed other original models. Four of the studies included genetic information. The quality of the studies was moderate with some limitations in the discriminative power and data inputs. A maximum AUROC value of 0.71 was reported in the study conducted in a screening context. CONCLUSION: Individualised risk prediction models are promising tools for implementing risk-based screening policies. However, it is a challenge to recommend any of them since they need further improvement in their quality and discriminatory capacity.

Transmission of SARS-CoV-2 in educational settings in 2020: a review.

OBJECTIVES: School closures have been used as a core non-pharmaceutical intervention (NPI) during the COVID-19 pandemic. This review aims at identifying SARS-CoV-2 transmission in educational settings during the first waves of the pandemic. METHODS: This literature review assessed studies published between December 2019 and 1 April 2021 in Medline and Embase, which included studies that assessed educational settings from approximately January 2020 to January 2021. The inclusion criteria were based on the PCC framework (P-Population, C-Concept, C-Context). The study Population was restricted to people 1-17 years old (excluding neonatal transmission), the Concept was to assess child-to-child and child-to-adult transmission, while the Context was to assess specifically educational setting transmission. RESULTS: Fifteen studies met inclusion criteria, ranging from daycare centres to high schools and summer camps, while eight studies assessed the re-opening of schools in the 2020-2021 school year. In principle, although there is sufficient evidence that children can both be infected by and transmit SARS-CoV-2 in school settings, the SAR remain relatively low-when NPI measures are implemented in parallel. Moreover, although the evidence was limited, there was an indication that younger children may have a lower SAR than adolescents. CONCLUSIONS: Transmission in educational settings in 2020 was minimal-when NPI measures were implemented in parallel. However, with an upsurge of cases related to variants of concern, continuous surveillance and assessment of the evidence is warranted to ensure the maximum protection of the health of students and the educational workforce, while also minimising the numerous negative impacts that school closures may have on children.

Challenges in applying the GRADE approach in public health guidelines and systematic reviews: a concept article from the GRADE Public Health Group.

BACKGROUND AND OBJECTIVE: This article explores the need for conceptual advances and practical guidance in the application of the GRADE approach within public health contexts. METHODS: We convened an expert workshop and conducted a scoping review to identify challenges experienced by GRADE users in public health contexts. We developed this concept article through thematic analysis and an iterative process of consultation and discussion conducted with members electronically and at three GRADE Working Group meetings. RESULTS: Five priority issues can pose challenges for public health guideline developers and systematic reviewers when applying GRADE: (1) incorporating the perspectives of diverse stakeholders; (2) selecting and prioritizing health and "nonhealth" outcomes; (3) interpreting outcomes and identifying a threshold for decision-making; (4) assessing certainty of evidence from diverse sources, including nonrandomized studies; and (5) addressing implications for decision makers, including concerns about conditional recommendations. We illustrate these challenges with examples from public health guidelines and systematic reviews, identifying gaps where conceptual advances may facilitate the consistent application or further development of the methodology and provide solutions. CONCLUSION: The GRADE Public Health Group will respond to these challenges with solutions that are coherent with existing guidance and can be consistently implemented across public health decision-making contexts.

GRADE Guidelines 30: the GRADE approach to assessing the certainty of modeled evidence-An overview in the context of health decision-making.

OBJECTIVES: The objective of the study is to present the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) conceptual approach to the assessment of certainty of evidence from modeling studies (i.e., certainty associated with model outputs). STUDY DESIGN AND SETTING: Expert consultations and an international multidisciplinary workshop informed development of a conceptual approach to assessing the certainty of evidence from models within the context of systematic reviews, health technology assessments, and health care decisions. The discussions also clarified selected concepts and terminology used in the GRADE approach and by the modeling community. Feedback from experts in a broad range of modeling and health care disciplines addressed the content validity of the approach. RESULTS: Workshop participants agreed that the domains determining the certainty of evidence previously identified in the GRADE approach (risk of bias, indirectness, inconsistency, imprecision, reporting bias, magnitude of an effect, dose-response relation, and the direction of residual confounding) also apply when assessing the certainty of evidence from models. The assessment depends on the nature of model inputs and the model itself and on whether one is evaluating evidence from a single model or multiple models. We propose a framework for selecting the best available evidence from models: 1) developing de novo, a model specific to the situation of interest, 2) identifying an existing model, the outputs of which provide the highest certainty evidence for the situation of interest, either "off-the-shelf" or after adaptation, and 3) using outputs from multiple models. We also present a summary of preferred terminology to facilitate communication among modeling and health care disciplines. CONCLUSION: This conceptual GRADE approach provides a framework for using evidence from models in health decision-making and the assessment of certainty of evidence from a model or models. The GRADE Working Group and the modeling community are currently developing the detailed methods and related guidance for assessing specific domains determining the certainty of evidence from models across health care-related disciplines (e.g., therapeutic decision-making, toxicology, environmental health, and health economics).

Applying the ROBINS-I tool to natural experiments: an example from public health.

BACKGROUND: A new tool to assess Risk of Bias In Non-randomised Studies of Interventions (ROBINS-I) was published in Autumn 2016. ROBINS-I uses the Cochrane-approved risk of bias (RoB) approach and focusses on internal validity. As such, ROBINS-I represents an important development for those conducting systematic reviews which include non-randomised studies (NRS), including public health researchers. We aimed to establish the applicability of ROBINS-I using a group of NRS which have evaluated non-clinical public health natural experiments. METHODS: Five researchers, all experienced in critical appraisal of non-randomised studies, used ROBINS-I to independently assess risk of bias in five studies which had assessed the health impacts of a domestic energy efficiency intervention. ROBINS-I assessments for each study were entered into a database and checked for consensus across the group. Group discussions were used to identify reasons underpinning lack of consensus for specific questions and bias domains. RESULTS: ROBINS-I helped to systematically articulate sources of bias in NRS. However, the lack of consensus in assessments for all seven bias domains raised questions about ROBINS-I's reliability and applicability for natural experiment studies. The two RoB domains with least consensus were selection (Domain 2) and performance (Domain 4). Underlying the lack of consensus were difficulties in applying an intention to treat or per protocol effect of interest to the studies. This was linked to difficulties in determining whether the intervention status was classified retrospectively at follow-up, i.e. post hoc. The overall risk of bias ranged from moderate to critical; this was most closely linked to the assessment of confounders. CONCLUSION: The ROBINS-I tool is a conceptually rigorous tool which focusses on risk of bias due to the counterfactual. Difficulties in applying ROBINS-I may be due to poor design and reporting of evaluations of natural experiments. While the quality of reporting may improve in the future, improved guidance on applying ROBINS-I is needed to enable existing evidence from natural experiments to be assessed appropriately and consistently. We hope future refinements to ROBINS-I will address some of the issues raised here to allow wider use of the tool.

Policies on Conflicts of Interest in Health Care Guideline Development: A Cross-Sectional Analysis.

OBJECTIVE: To assess whether organisations that develop health care guidelines have conflict of interest (COI) policies and to review the content of the available COI policies. METHODS: Survey and content analysis of COI policies available in English, French, Spanish, and Italian conducted between September 2014 and June 2015. A 24-item data abstraction instrument was created on the basis of guideline development standards. RESULTS: The survey identified 29 organisations from 19 countries that met the inclusion criteria. From these organisations, 19 policies were eligible for inclusion in the content analysis. Over one-third of the policies (7/19, 37%) did not report or did not clearly report whether disclosure was a prerequisite for membership of the guideline panel. Strategies for the prevention of COI such as divestment were mentioned by only two organisations. Only 21% of policies (4/19) used criteria to determine whether an interest constitutes a COI and to assess the severity of the risk imposed. CONCLUSIONS: The finding that some organisations, in contradiction of widely available standards, still do not have COI policies publicly available is concerning. Also troubling were the findings that some policies did not clearly report critical steps in obtaining, managing and communicating disclosure of relationships of interest. This in addition to the variability encountered in content and accessibility of COI policies may cause confusion and distrust among guideline users. It is in the interest of guideline users and developers to design an agreed-upon, comprehensive, clear, and accessible COI policy.