While many deep-learning-based computer-aided detection systems (CAD) have been developed and commercialized for abnormality detection in chest radiographs (CXR), their ability to localize a target abnormality is rarely reported. Localization accuracy is important in terms of model interpretability, which is crucial in clinical settings. Moreover, diagnostic performances are likely to vary depending on thresholds which define an accurate localization. In a multi-center, stand-alone clinical trial using temporal and external validation datasets of 1,050 CXRs, we evaluated localization accuracy, localization-adjusted discrimination, and calibration of a commercially available deep-learning-based CAD for detecting consolidation and pneumothorax. The CAD achieved image-level AUROC (95% CI) of 0.960 (0.945, 0.975), sensitivity of 0.933 (0.899, 0.959), specificity of 0.948 (0.930, 0.963), dice of 0.691 (0.664, 0.718), moderate calibration for consolidation, and image-level AUROC of 0.978 (0.965, 0.991), sensitivity of 0.956 (0.923, 0.978), specificity of 0.996 (0.989, 0.999), dice of 0.798 (0.770, 0.826), moderate calibration for pneumothorax. Diagnostic performances varied substantially when localization accuracy was accounted for but remained high at the minimum threshold of clinical relevance. In a separate trial for diagnostic impact using 461 CXRs, the causal effect of the CAD assistance on clinicians’ diagnostic performances was estimated. After adjusting for age, sex, dataset, and abnormality type, the CAD improved clinicians’ diagnostic performances on average (OR [95% CI] = 1.73 [1.30, 2.32]; p < 0.001), although the effects varied substantially by clinical backgrounds. The CAD was found to have high stand-alone diagnostic performances and may beneficially impact clinicians’ diagnostic performances when used in clinical settings.

There have been consistent efforts to assess treatment effect heterogeneity (TEH) of Head Start using the data from the Head Start Impact Study (HSIS), a randomized controlled trial of a federally funded child development program for a nationally representative sample of low-income parents and their 3- and 4-year-old children in the United States. Including 28 studies on TEH of Head Start, this review found that multiple high-risk subgroups (e.g., children with lower cognitive abilities, Spanish-speaking dual language learners) experienced larger gains across a range of developmental and parental outcomes, but mixed results for several subgroups. Most studies focused on subgroup analyses, cognitive and social-emotional outcomes, and short-term effects. Further studies on distributional effects, health and parental outcomes, and long-term effects are warranted. Finally, suggestions for future research on TEH of Head Start are discussed, which are applicable to other child development programs and policy evaluations.

The societal disruptions resulting from the coronavirus disease 2019 (COVID-19) pandemic may have caused changes in smoking and alcohol consumption. Using data from the Koreans’ Happiness Survey, a nationally representative survey in South Korea, we (1) described population-level smoking and drinking behaviors; (2) assessed changes in smoking and drinking behaviors during the COVID-19 pandemic; and (3) identified employment, economic, and sociodemographic factors associated with these changes using multinomial logistic regression. The overall amount of smoking and drinking decreased during the pandemic, but the changes were heterogeneous across subgroups. Male gender, receipt of the basic living allowance, self-employment, unemployment, and chronic disease status were associated with increased smoking, while higher household income, temporary worker status, living with someone (versus alone), and having fewer offline friends were associated with decreased smoking. Male gender, self-employment, living alone, having more offline friends, and chronic disease status were associated with increased drinking, while younger age, male gender, low and high household income (i.e., a U-shaped relationship), long-term rent with a deposit, temporary worker status, and chronic disease status were associated with decreased drinking. Our findings provide evidence on changes in smoking and drinking during the COVID-19 pandemic in South Korea and differential changes across subgroups.

Heterogeneity in treatment effects of the Head Start, a federally funded early childhood development program in the United States, has previously been found in the Head Start Impact Study (HSIS), a nationally representative randomized controlled trial. While individual characteristics have been extensively examined as sources of effect heterogeneity, treatment effects may vary as a function of outcome distribution (i.e., distributional effect). Using quantile regressions, we investigated distributional effects of the Head Start on eight child developmental outcomes for first year, second year, third year, and the 3rd grade year follow-up in the HSIS data. For PPVT and Applied Problems, the effects varied substantially across quantiles in the first follow-up, but they were positive overall. The effects at the lower quantiles were larger and were sustained beyond the first follow-up (PPVT [95% CI] at 10th and 90th quantiles: 8.74 [6.22, 11.27], 3.32 [0.82, 5.81]) in the first follow-up and 5.72 [2.66, 8.77], −1.66 [-3.69, 0.37] in the second follow-up). For Behavior Problems, the effects were only positive for the lower quantiles in the first follow-up, but they became null in the latter follow-ups. For Letter-Word Identification, Spelling, and Pre-Academic, the effects were positive in the first follow-up with moderate variation across quantiles. In the second follow-up, only the effects at the lower quantiles were statistically significant, although they faded in the latter follow-ups. For Oral Comprehension and Social Skills, effects were null for all follow-ups. The Head Start had meaningful distributional effects for a range of child developmental outcomes, and distributional effects should be routinely assessed for better understanding of child developmental programs.

Background: Rheumatoid arthritis (RA) is associated with diverse extra-articular manifestations, including interstitial lung disease (ILD). No previous studies have examined the bidirectional relationship between RA and ILD using the Mendelian randomization (MR) analyses. Therefore, we aimed to investigate this subject using a two-sample bidirectional MR method. Methods: We performed bidirectional two-sample MR using summary statistics from genome-wide association studies (GWASs). The data are publicly available, de-identified, and from European (EUR) and East Asian (EAS) ancestries. Results: A total of 474,450 EUR participants and 351,653 EAS participants were included for either forward or reverse MR analysis. In our primary analysis, we found significant evidence of an increased risk of ILD associated with RA among individuals of EUR ancestry (OR_MR-cML = 1.08; 95% confidence interval [CI] = 1.03–1.14; p = 0.003) and EAS ancestry (OR_MR-cML = 1.37; 95% CI = 1.23–1.54; p < 0.001). Additionally, the reverse MR showed significant evidence of an increased risk of RA associated with ILD among those of EUR ancestry (OR_MR-cML = 1.12; 95% CI = 1.05–1.19; p < 0.001). However, only one instrumental variable was selected in the EAS ILD GWAS, and there was no increased risk of RA associated with ILD in those of EAS ancestry (OR_MR-cML = 1.02; 95% CI = 0.91–1.14; p = 0.740). Conclusions: Our findings indicate that RA and ILD have a bidirectional causal inference when using the MR analysis of GWAS datasets. The findings are only relevant for genetic predisposition; thus, further research is needed to determine the impact of non-genetic predispositions.