Diagnostics and Treatments of COVID-19: A Living Systematic Review of Economic Evaluations

ObjectivesAs healthcare systems continue to respond to the COVID-19 pandemic, cost-effectiveness evidence will be needed to identify which tests and treatments for COVID-19 offer value for money. We sought to review economic evaluations of diagnostic tests and treatments for COVID-19, critically appraising the methodological approaches used and reporting cost-effectiveness estimates, using a “living” systematic review approach.MethodsKey databases (including MEDLINE, EconLit, Embase) were last searched on July 12, 2021. Gray literature and model repositories were also searched. Only full economic evaluations published in English were included. Studies were quality assessed and data were extracted into standard tables. Results were narratively summarized. The review was completed by 2 reviewers independently, with disagreements resolved through discussion with a senior reviewer.ResultsOverall, 3540 records were identified, with 13 meeting the inclusion criteria. After quality assessment, 6 were excluded because of very severe limitations. Of the 7 studies included, 5 were cost-utility analyses and 2 were cost-effectiveness analyses. All were model-based analyses. A total of 5 evaluated treatments (dexamethasone, remdesivir, hypothetical) and 2 evaluated hypothetical testing strategies. Cost-effectiveness estimates were sensitive to the treatment effect on survival and hospitalization, testing speed and accuracy, disease severity, and price.ConclusionsPresently, there are few economic evaluations for COVID-19 tests and treatments. They suggest treatments that confer a survival benefit and fast diagnostic tests may be cost effective. Nevertheless, studies are subject to major evidence gaps and take inconsistent analytical approaches. The evidence may improve for planned updates of this “living” review.     

Associations of park features with park use and park-based physical activity in an urban environment in Asia: A cross-sectional study

Park use is associated with health, yet our understanding of park features related to their use is limited. Singapore's parks were audited for 30 micro-features, then geospatial analysis characterized micro-features scores for parks nearest to participants' homes. Adults (3,435) reported their park use and park-based physical activity. Using linear regression models, we found living near a park with higher micro-features scores was associated with more time in parks and park-based physical activity. Specific micro-features were associated with more park time (wildlife areas, water features, forested areas, unpaved trails (2–2.6 h/month, p < 0.05)) and with physical activity in parks (water features, forested areas, large playground, open green spaces (1.8–2.2 h/month, p < 0.05)). These findings could inform parks planning to support population-health.     

Diet Quality of Elite Australian Athletes Evaluated Using the Athlete Diet Index

While athletes’ nutrient intakes have been widely reported, few studies have assessed the diet quality of athletes. This is the first study to evaluate the diet quality of athletes using the purpose-built Athlete Diet Index (ADI). A convenience sample of 165 elite athletes from Australian sporting institutions completed the ADI online, with subsequent automated results provided to their respective accredited sports dietitians (ASDs). At the completion of athlete participation, ASDs (n = 12) responded to a range of survey items using a Likert scale (i.e., 1 = strongly agree to 5 = strongly disagree) to determine the suitability of the ADI in practice. Differences in ADI scores for demographics and sport-specific variables were investigated using independent t-tests, analysis of variance (ANOVA) and Bonferroni multiple comparisons. Spearman’s rank correlation was used to assess the association between total scores and demographics. The mean total ADI score was 91.4 ± 12.2 (range 53–117, out of a possible 125). While there was no difference in total scores based on demographics or sport-specific variables; team sport athletes scored higher than individual sport athletes (92.7 vs. 88.5, p < 0.05). Athletes training fewer hours (i.e., 0–11 h/week) scored higher on Dietary Habits sub-scores compared with athletes training more hours (≥12 h/week; p < 0.05), suggesting that athletes who train longer may be at risk of a compromised dietary pattern or less than optimal nutrition practices that support training. Most (75%) ASDs surveyed strongly agreed with the perceived utility of the ADI for screening athletes and identifying areas for nutrition support, confirming its suitability for use in practice.     

Dietary Aspects to Incorporate in the Creation of a Mobile Image-Based Dietary Assessment Tool to Manage and Improve Diabetes

Diabetes is the seventh leading cause of death in United States. Dietary intake and behaviors are essential components of diabetes management. Growing evidence suggests dietary components beyond carbohydrates may critically impact glycemic control. Assessment tools on mobile platforms have the ability to capture multiple aspects of dietary behavior in real-time throughout the day to inform and improve diabetes management and insulin dosing. The objective of this narrative review was to summarize evidence related to dietary behaviors and composition to inform a mobile image-based dietary assessment tool for managing glycemic control of both diabetes types (type 1 and type 2 diabetes). This review investigated the following topics amongst those with diabetes: (1) the role of time of eating occasion on indicators of glycemic control; and (2) the role of macronutrient composition of meals on indicators of glycemic control. A search for articles published after 2000 was completed in PubMed with the following sets of keywords “diabetes/diabetes management/diabetes prevention/diabetes risk”, “dietary behavior/eating patterns/temporal/meal timing/meal frequency”, and “macronutrient composition/glycemic index”. Results showed eating behaviors and meal macronutrient composition may affect glycemic control. Specifically, breakfast skipping, late eating and frequent meal consumption might be associated with poor glycemic control while macronutrient composition and order of the meal could also affect glycemic control. These factors should be considered in designing a dietary assessment tool, which may optimize diabetes management to reduce the burden of this disease.     

High-Fat Foods and FODMAPs Containing Gluten Foods Primarily Contribute to Symptoms of Irritable Bowel Syndrome in Korean Adults

Dietary control plays an important role in the treatment of irritable bowel syndrome (IBS). However, few studies have examined the relationship between dietary intake and symptoms of IBS in Koreans. The current cross-sectional study aimed to examine the diet in food consumption and nutrient intake in Korean adults aged 20 to 40 with IBS. The data collected were completed by 857 subjects using a community-based web survey. The questionnaire covered functional bowel disorders based on Rome III, the semi-quantitative Food Frequency Questionnaire (SQ-FFQ), and the food items causing symptoms. In total, 186 of 857 subjects (21.7%) were diagnosed with IBS. The non-IBS group had a fat intake of 76.9 ± 47.9 g/day, while the IBS group had a fat intake of 86.6 ± 55.1 g/day (p = 0.014). The non-IBS group had a total fermentable oligosaccharide, disaccharide, monosaccharide, and polyol (FODMAP) intake of 12.6 ± 9.7 g/day, whereas the IBS group had a total FODMAP intake of 13.9 ± 9.9 g/day (p = 0.030). Foods that contributed to the onset of symptoms in the IBS group were instant noodles (70.8%), Chinese noodles with vegetables and seafood (68.7%), pizza (67.2%), and black bean sauce noodles (66.3%) which are mostly classified as high fat and high gluten foods. The dietary intake of IBS patients differs from that of non-IBS subjects. Increased intake of gluten-containing or high-fat foods due to the westernized diet caused more IBS symptoms than high FODMAPs and dairy products in Korean adults in their 20 s to 40 s.     

Dietary Patterns Derived from UK Supermarket Transaction Data with Nutrient and Socioeconomic Profiles

Poor diet is a leading cause of death in the United Kingdom (UK) and around the world. Methods to collect quality dietary information at scale for population research are time consuming, expensive and biased. Novel data sources offer potential to overcome these challenges and better understand population dietary patterns. In this research we will use 12 months of supermarket sales transaction data, from 2016, for primary shoppers residing in the Yorkshire and Humber region of the UK (n = 299,260), to identify dietary patterns and profile these according to their nutrient composition and the sociodemographic characteristics of the consumer purchasing with these patterns. Results identified seven dietary purchase patterns that we named: Fruity; Meat alternatives; Carnivores; Hydrators; Afternoon tea; Beer and wine lovers; and Sweet tooth. On average the daily energy intake of loyalty card holders -who may buy as an individual or for a household- is less than the adult reference intake, but this varies according to dietary purchase pattern. In general loyalty card holders meet the recommended salt intake, do not purchase enough carbohydrates, and purchase too much fat and protein, but not enough fibre. The dietary purchase pattern containing the highest amount of fibre (as an indicator of healthiness) is bought by the least deprived customers and the pattern with lowest fibre by the most deprived. In conclusion, supermarket sales data offer significant potential for understanding population dietary patterns.     

The Design and Development of a Food Composition Database for an Electronic Tool to Assess Food Intake in New Caledonian Families

The food environment in New Caledonia is undergoing a transition, with movement away from traditional diets towards processed and discretionary foods and beverages. This study aimed to develop an up-to-date food composition database that could be used to analyze food and nutritional intake data of New Caledonian children and adults. Development of this database occurred in three phases: Phase 1, updating and expanding the number of food items to represent current food supply; Phase 2, refining the database items and naming and assigning portion size images for food items; Phase 3, ensuring comprehensive nutrient values for all foods, including saturated fat and total sugar. The final New Caledonian database comprised a total of 972 food items, with 40 associated food categories and 25 nutrient values and 615 items with portion size images. To improve the searchability of the database, the names of 593 food items were shortened and synonyms or alternate spelling were included for 462 foods. Once integrated into a mobile app-based multiple-pass 24-h recall tool, named iRecall.24, this country-specific food composition database would support the assessment of food and nutritional intakes of families in New Caledonia, in a cross-sectional and longitudinal manner, and with translational opportunities for use across the wider Pacific region.     

北京市东城区公共场所冷却塔使用状况及健康风险评估

目的了解北京市东城区公共场所冷却塔使用及卫生状况,评估各场所冷却塔军团菌病健康风险。方法2018年5—9月,采集东城区内三类共26家公共场所冷却塔冷却水,填写相关调查问卷,通过冷却塔军团菌病健康风险指数模型计算各场所健康风险。结果本次研究中各场所冷却水样本嗜肺军团菌检测均为阴性,合格率为100%。游离性余氯平均为0.15 mg/L。酒店类场所冷却塔规模、加药方式和频率与其他场所有明显差别。26家公共场所健康综合风险平均为61.49,其中军团菌增殖风险、含菌气溶胶传播风险、暴露人群易感风险分别为16.13、22.66和22.70。不同场所冷却塔军团菌病健康风险评估结果存在一定差异,医院类场所健康风险指数高于酒店和商场(F=3.78,P<0.05)。结论冷却塔军团菌病健康风险高低主要受公共场所周围易感人群影响,该地区相关卫生部门应加强对相关易感人群的保护,对各类场所相关政策法规进行制定、完善和实施。     

Use of a Telemedicine Risk Assessment Tool to Predict the Risk of Hospitalization of 496 Outpatients With COVID-19: Retrospective Analysis

BackgroundRisk assessment of patients with acute COVID-19 in a telemedicine context is not well described. In settings of large numbers of patients, a risk assessment tool may guide resource allocation not only for patient care but also for maximum health care and public health benefit.ObjectiveThe goal of this study was to determine whether a COVID-19 telemedicine risk assessment tool accurately predicts hospitalizations.MethodsWe conducted a retrospective study of a COVID-19 telemedicine home monitoring program serving health care workers and the community in Atlanta, Georgia, with enrollment from March 24 to May 26, 2020; the final call range was from March 27 to June 19, 2020. All patients were assessed by medical providers using an institutional COVID-19 risk assessment tool designating patients as Tier 1 (low risk for hospitalization), Tier 2 (intermediate risk for hospitalization), or Tier 3 (high risk for hospitalization). Patients were followed with regular telephone calls to an endpoint of improvement or hospitalization. Using survival analysis by Cox regression with days to hospitalization as the metric, we analyzed the performance of the risk tiers and explored individual patient factors associated with risk of hospitalization.ResultsProviders using the risk assessment rubric assigned 496 outpatients to tiers: Tier 1, 237 out of 496 (47.8%); Tier 2, 185 out of 496 (37.3%); and Tier 3, 74 out of 496 (14.9%). Subsequent hospitalizations numbered 3 out of 237 (1.3%) for Tier 1, 15 out of 185 (8.1%) for Tier 2, and 17 out of 74 (23%) for Tier 3. From a Cox regression model with age of 60 years or older, gender, and reported obesity as covariates, the adjusted hazard ratios for hospitalization using Tier 1 as reference were 3.74 (95% CI 1.06-13.27; P=.04) for Tier 2 and 10.87 (95% CI 3.09-38.27; P<.001) for Tier 3.ConclusionsA telemedicine risk assessment tool prospectively applied to an outpatient population with COVID-19 identified populations with low, intermediate, and high risk of hospitalization.     

How Assessment-Schedule Matching Limits Bias When Comparing Progression-Free Survival in Single-Arm Studies: An Application in Second-Line Urothelial Carcinoma Treatments

ObjectivesPopulation-adjusted comparisons of progression-free survival (PFS) from single-arm trials of cancer treatments can be derived using matching-adjusted indirect comparisons (MAICs); however, results are still susceptible to bias, particularly if the trials had different tumor assessment schedules. This study aims to assess the effects of assessment-schedule matching (ASM) on the relative effectiveness on the PFS of avelumab versus approved comparator immunotherapies or chemotherapy after population matching in the second-line (2L) setting for metastatic urothelial carcinoma.MethodsThe MAIC used patient-level data for avelumab from the JAVELIN Solid Tumor trial (NCT01772004). PFS was compared with published curves for other treatments to obtain population-adjusted hazard ratios (HRs). The MAIC was repeated after conducting ASM for differences in tumor assessment scheduled first at 6 weeks for avelumab and durvalumab and at 8 or 9 weeks for other treatments.ResultsMAIC adjustment alone altered the HR estimates up to 23%, whereas MAIC plus ASM resulted in up to 32.7% reductions from naive comparisons. Even in cases in which MAIC had little effect, ASM brought an additional change of 11.1% to 15.4%. Overall, the HR range of avelumab versus other treatments changed from 0.83 to 1.25 for naive comparisons to 0.76 to 0.99 after ASM plus MAIC, numerically favoring avelumab.ConclusionsSmall variations in assessment schedules can introduce bias in unanchored indirect treatment comparisons of interval-censored time-to-event outcomes. In this study, adjusted PFS was comparable across second-line urothelial carcinoma treatment options, numerically favoring avelumab versus immunotherapies and chemotherapy agents. Correcting this bias is especially important when HRs are applied in cost-effectiveness models to transition patients between states.