This rapid review aimed to examine the usefulness of the Edmonton Obesity Staging System (EOSS) for stratifying the presence and severity of weight-related health problems in clinical and community settings. We searched PubMed, CINAHL and ProQuest for records from 2009 to May 2020. We considered observational studies in participants with overweight or obesity that investigated the risk of any clinical outcome associated with increasing EOSS. We reviewed and appraised 20 observational studies (cohort = 4, case series = 7, cross-sectional = 9) published between 2011 and 2020. Of 12 studies in clinical populations, the EOSS was most consistently associated with an increased risk of postoperative complications following bariatric surgery, especially for EOSS 3-4, and inversely associated with weight loss, treatment time and resolution of hypertension following bariatric surgery and clinical weight management. Of eight studies in community populations, the EOSS most consistently predicted mortality outcomes, especially for EOSS 3, and was associated with polypharmacy, service use and poorer work outcomes. Studies reported diverse EOSS definitions and outcomes, which slightly weakens the overall evidence base. The EOSS should be routinely used for predicting risks and benefits of surgical and nonsurgical weight management, but it should be applied with caution for population health planning.
Background Although relatively new, digital health interventions are demonstrating rapid growth because of their ability to facilitate access and overcome issues of location, time, health status, and most recently, the impact of a major pandemic. With the increased uptake of digital technologies, digital health has the potential to improve the provision of supportive cancer care. Objective This systematic review aims to evaluate digital health interventions for supportive cancer care. Methods Published literature between 2000 and 2020 was systematically searched in MEDLINE, PubMed, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, and Scopus. Eligible publications were randomized controlled trials of clinician-led digital health interventions to support adult cancer patients. The interventions included were determined by applying a digital health conceptual model. Studies were appraised for quality using the revised Cochrane risk of bias tool. Results Twenty randomized controlled trials met the inclusion criteria for the analysis. Interventions varied by duration, frequency, degree of technology use, and applied outcome measures. Interventions targeting a single tumor stream, predominantly breast cancer, and studies involving the implementation of remote symptom monitoring have dominated the results. In most studies, digital intervention resulted in significant positive outcomes in patient-reported symptoms, levels of fatigue and pain, health-related quality of life, functional capacity, and depression levels compared with the control. Conclusions Digital health interventions are helpful and effective for supportive care of patients with cancer. There is a need for high-quality research. Future endeavors could focus on the use of valid, standardized outcome measures, maintenance of methodological rigor, and strategies to improve patient and health professional engagement in the design and delivery of supportive digital health interventions. Trial Registration PROSPERO CRD42020149730; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=149730
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