Association of social vulnerability index and masking adherence among children enrolled in COVID-19 community research partnership study.

BACKGROUND: Individuals with high social vulnerability index (SVI) have poorer outcomes with COVID-19. Masking reduces transmission of COVID-19 among children, but how SVI plays a role in masking behavior is unknown. We aimed to measure the association of SVI with masking adherence among children during the COVID-19 pandemic. METHODS: We conducted a multi-site, prospective syndromic surveillance study among children aged 2 - 17 years in the Southeastern United States by daily electronic surveys which solicited symptoms of COVID-19-like illness, infection with or exposure to SARS-CoV-2, masking habits, and any receipt of COVID-19 vaccines. Parents/guardians submitted surveys for their children; adolescents 13 years and older could opt to submit their own surveys. Multivariable and univariate linear models were used to measure the associations of different predictors such as SVI with masking adherence. RESULTS: One thousand four hundred sixty-one children from 6 states and 55 counties predominately from North and South Carolina were included in the analysis. Most children in the cohort were 5 - 11 years old, non-Hispanic White, from urban counties, and with low-moderate SVI. Overall masking adherence decreased over time, and older children had higher masking adherence throughout the study period compared with younger children. Children who resided in urban counties had greater masking adherence throughout the study period than those who resided in suburban or rural counties. Masking adherence was higher among children with both low and medium SVI than those with high SVI. CONCLUSIONS: Despite being at risk for more severe outcomes with COVID-19, children with high SVI had lower levels of masking adherence compared to those with low SVI. Our findings highlight opportunities for improved and targeted messaging in these vulnerable communities.

Psychosocial Factors Predicting Healthcare Usage in Young Adults with Youth-Onset Type 2 Diabetes: The TODAY2 iCount Observational Study.

BACKGROUND: Established diabetes care ("diabetes home") and regular healthcare visits are important to achieve optimal health. Nothing is known about psychosocial factors that predict healthcare usage (HCU) in young adults with youth-onset type 2 diabetes, at risk for early complications. OBJECTIVE: To identify psychosocial predictors of HCU in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY2) cohort. DESIGN: Longitudinal, measured at T1 (baseline) and T2 (1 year later). Logistic and linear regressions, adjusted for potential confounders, identified predictors of sub-optimal HCU (defined as no diabetes home, 0 visits for routine care, or ≥ 1 urgent care visit in prior 6 months). PARTICIPANTS: N = 366 TODAY2 participants with T1 and T2 data (381 consented). Mean age = 26.0 years, 67.8% female, 37.7% non-Hispanic Black, 35.8% Hispanic, 20.2% non-Hispanic white, 6.3% "other," mean HbA1c = 9.4%. MAIN MEASURES: HCU survey; reliable and valid measures of diabetes self-efficacy, depressive symptoms, anxiety symptoms, diabetes distress, beliefs about medicines, diabetes attitudes, material need insecurities, self-management support. KEY RESULTS: 25.4% had no diabetes home, 23.7% had 0 routine care visits, 46% had ≥ 1 urgent care visit (prior 6 months). Beliefs in the necessity of (adjusted odds ratio [OR] = 1.28; 95% confidence interval [CI] = 1.12, 1.46, p < 0.001), and concerns about (OR = 1.29;CI = 1.08,1.54, p = 0.004), diabetes medicines, and its negative psychosocial impacts (OR = 1.57;CI = 1.04, 2.38, p = 0.03), predicted higher odds of having a diabetes home at T2. Beliefs that medicines are harmful predicted lower odds of a diabetes home (OR = 0.56;CI = 0.37,0.85, p = 0.006). Necessity beliefs (OR = 1.2;CI = 1.06,1.36, p = 0.004), and self-management support (OR = 1.5;CI = 1.08,2.07, p = 0.01) predicted higher odds of having ≥ 1 diabetes care visit, harm beliefs predicted lower odds (OR = 0.6;CI = 0.41,0.88, p = 0.01). CONCLUSIONS: Sub-optimal healthcare usage, common in young adults with youth-onset type 2 diabetes, is predicted by beliefs about medicines, diabetes impact, and self-management support. We must address these factors to help this vulnerable group establish stable diabetes care.

Psychosocial factors predict medication adherence in young adults with youth-onset type 2 diabetes: Longitudinal results from the TODAY2 iCount study.

AIM: To identify psychosocial predictors of medication adherence in young adults with youth-onset type 2 diabetes in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY2) cohort. METHODS: Participants (mean age: 26 years) completed validated psychosocial measures. Unannounced telephone pill counts were completed at T1 (baseline) and T2 (follow-up, approximately 1 year later) to assess adherence to oral hypoglycaemia agents (OHAs). Adherence to insulin was assessed by self-report. Logistic and linear regressions identified factors that predicted 'low adherence' (<80% of pills/insulin) and per cent adherence, adjusted for potential confounders. RESULTS: Of 171 participants with OHA adherence scores at T1 and T2 (65% women, 43% Hispanic and 35% non-Hispanic Black), 65.4% were low adherent. After adjustment (including T1 adherence), concerns about diabetes medicines (adverse effects, dependence) at T1 predicted higher odds of being low adherent (categorical) at T2 (p = 0.019). Housing insecurity (p = 0.045) and reporting ≥2 need insecurities (p = 0.027) at T1 predicted lower per cent adherence (continuous) at T2. Of 157 participants with insulin adherence scores at T1 and T2 (69% women, 38% Hispanic and 38% non-Hispanic Black), 36.3% were low adherent. After adjustment (including T1 adherence), beliefs that medicines are overused predicted higher odds of insulin low adherence at T2 (p = 0.013), and beliefs that medicines are harmful (p = 0.004) and overused (p = 0.010) predicted lower per cent insulin adherence at T2. CONCLUSIONS: Suboptimal medication adherence, common in young adults with youth-onset type 2 diabetes, is predicted by interfering beliefs about medicines and social factors. We must address these beliefs and unmet needs to develop tailored interventions for this vulnerable group.

Characterisation of infection-induced SARS-CoV-2 seroprevalence amongst children and adolescents in North Carolina.

Few prospective studies have documented the seropositivity among those children infected with severe acute respiratory syndrome coronavirus 2. From 2 April 2021 to 24 June 2021, we prospectively enrolled children between the ages of 2 and 17 years at three North Carolina healthcare systems. Participants received at least four at-home serological tests detecting the presence of antibodies against, but not differentiating between, the nucleocapsid or spike antigen. A total of 1,058 participants were enrolled in the study, completing 2,709 tests between 1 May 2021 and 31 October 2021. Using multilevel regression with poststratification techniques and considering our assay sensitivity and sensitivity, we estimated that the seroprevalence of infection-induced antibodies among unvaccinated children and adolescents aged 2-17 years in North Carolina increased from 15.2% (95% credible interval, CrI 9.0-22.0) in May 2021 to 54.1% (95% CrI 46.7-61.1) by October 2021, indicating an average infection-to-reported-case ratio of 5. A rapid rise in seropositivity was most pronounced in those unvaccinated children aged 12-17 years, based on our estimates. This study underlines the utility of serial, serological testing to inform a broader understanding of the regional immune landscape and spread of infection.

Trajectories of eGFR and risk of albuminuria in youth with type 2 diabetes: results from the TODAY cohort study.

BACKGROUND: We conducted exploratory analyses to identify distinct trajectories of estimated glomerular filtration rate (eGFR) and their relationship with hyperfiltration, subsequent rapid eGFR decline, and albuminuria in participants with youth-onset type 2 diabetes enrolled in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) study. METHODS: Annual serum creatinine, cystatin C, urine albumin, and creatinine measurements were obtained from 377 participants followed for ≥ 10 years. Albuminuria and eGFR were calculated. Hyperfiltration peak is the greatest eGFR inflection point during follow-up. Latent class modeling was applied to identify distinct eGFR trajectories. RESULTS: At baseline, participants' mean age was 14 years, type 2 diabetes duration was 6 months, mean HbA1c was 6%, and mean eGFR was 120 ml/min/1.73 m2. Five eGFR trajectories associated with different rates of albuminuria were identified, including a "progressive increasing eGFR" group (10%), three "stable eGFR" groups with varying starting mean eGFR, and an "eGFR steady decline" group (1%). Participants who exhibited the greatest peak eGFR also had the highest levels of elevated albuminuria at year 10. This group membership was characterized by a greater proportion of female and Hispanic participants. CONCLUSIONS: Distinct eGFR trajectories that associate with albuminuria risk were identified, with the eGFR trajectory characterized by increasing eGFR over time associating with the highest level of albuminuria. These descriptive data support the current recommendations to estimate GFR annually in young persons with type 2 diabetes and provide insight into eGFR-related factors which may contribute to predictive risk strategies for kidney disease therapies in youth with type 2 diabetes. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00081328, date registered 2002. A higher resolution version of the Graphical abstract is available as Supplementary information.

Association of psychosocial factors with medication adherence in emerging adults with youth-onset type 2 diabetes: The iCount study.

AIMS: To assess associations of psychosocial factors with medication adherence in young adults with youth-onset type 2 diabetes in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY2) cohort. METHODS: Participants (mean age 26 years) completed validated psychosocial measures. Adherence to oral hypoglycemia agents (OHAs) was assessed with 3-monthly unannounced phone pill counts; insulin adherence by self-report. Logistic and linear regressions identified factors associated with "low-adherence" (<80% of pills/insulin) controlling for confounders. RESULTS: Of 212 participants taking OHAs (67% female, 39% Hispanic, 36% non-Hispanic Black), 69.8% were low-adherent. After adjustment, beliefs that medicines are necessary was associated with lower odds of low-adherence (p = 0.040, dichotomous). Less self-management support (p = 0.008), no healthcare coverage (p = 0.001), ≥1 (p = 0.008)/≥2 (p = 0.045) need insecurities were associated with higher odds of low-adherence. Factors associated with lower % adherence (continuous) were beliefs that medicines are harmful (p < 0.001)/overused (p = 0.007)/less necessary (p = 0.022), low self-management support (p = 0.003), food insecurity (p = 0.036), no healthcare coverage (p < 0.001), ≥1 (p = 0.003)/≥2 (p = 0.018) need insecurities. Of 192 taking insulin (69% female, 36% Hispanic, 41% non-Hispanic Black, 16% non-Hispanic white), 37.0% were low-adherent. Beliefs that medicines are overused (p = 0.009), that diabetes is not serious (p = 0.010), low diabetes self-efficacy (p = 0.035), high distress (p = 0.027), low self-management support (p = 0.001), food insecurity (p = 0.020), ≥1 (p = 0.011)/≥2 (p = 0.015) insecurities increased odds of insulin low-adherence. CONCLUSIONS: Poor medication adherence, common in young adults with youth-onset type 2 diabetes, is associated with interfering beliefs, diabetes distress and social factors. We must address these factors to develop tailored interventions for this vulnerable group.

Randomization-based inference in the presence of selection bias.

For the analysis of clinical trials, the study participants are usually assumed to be representative sample of a target population. This assumption is rarely fulfilled in clinical trials, and particularly not if the sample size is small. In addition, covariate imbalances may affect the trial. Randomization tests provide a nonparametric analysis method of the treatment effect that does not rely on population-based assumptions. We propose a nonparametric statistical model that yields a formal basis for randomization tests. We adapt the model for the presence of covariate imbalance in the form of selection bias and investigate the effects of bias on the rejection probability of the randomization test using Monte Carlo simulations. Finally, we show that ancillary statistics can be used to control for the influence of bias. We show that covariate imbalance leads to an inflation of the type I error probability. The proposed nonparametric model allows for the use of ancillary statistics that yield an unbiased adjusted randomization test.

A roadmap to using randomization in clinical trials.

BACKGROUND: Randomization is the foundation of any clinical trial involving treatment comparison. It helps mitigate selection bias, promotes similarity of treatment groups with respect to important known and unknown confounders, and contributes to the validity of statistical tests. Various restricted randomization procedures with different probabilistic structures and different statistical properties are available. The goal of this paper is to present a systematic roadmap for the choice and application of a restricted randomization procedure in a clinical trial. METHODS: We survey available restricted randomization procedures for sequential allocation of subjects in a randomized, comparative, parallel group clinical trial with equal (1:1) allocation. We explore statistical properties of these procedures, including balance/randomness tradeoff, type I error rate and power. We perform head-to-head comparisons of different procedures through simulation under various experimental scenarios, including cases when common model assumptions are violated. We also provide some real-life clinical trial examples to illustrate the thinking process for selecting a randomization procedure for implementation in practice. RESULTS: Restricted randomization procedures targeting 1:1 allocation vary in the degree of balance/randomness they induce, and more importantly, they vary in terms of validity and efficiency of statistical inference when common model assumptions are violated (e.g. when outcomes are affected by a linear time trend; measurement error distribution is misspecified; or selection bias is introduced in the experiment). Some procedures are more robust than others. Covariate-adjusted analysis may be essential to ensure validity of the results. Special considerations are required when selecting a randomization procedure for a clinical trial with very small sample size. CONCLUSIONS: The choice of randomization design, data analytic technique (parametric or nonparametric), and analysis strategy (randomization-based or population model-based) are all very important considerations. Randomization-based tests are robust and valid alternatives to likelihood-based tests and should be considered more frequently by clinical investigators.

Randomization tests for multiarmed randomized clinical trials.

We examine the use of randomization-based inference for analyzing multiarmed randomized clinical trials, including the application of conditional randomization tests to multiple comparisons. The view is taken that the linkage of the statistical test to the experimental design (randomization procedure) should be recognized. A selected collection of randomization procedures generalized to multiarmed treatment allocation is summarized, and generalizations for two randomization procedures that heretofore were designed for only two treatments are developed. We explain the process of computing the randomization test and conditional randomization test via Monte Carlo simulation, developing an efficient algorithm that makes multiple comparisons possible that would not be possible using a standard algorithm, demonstrate the preservation of type I error rate, and explore the relationship of statistical power to the randomization procedure in the presence of a time trend and outliers. We distinguish between the interpretation of the p-value in the randomization test and in the population test and verify that the randomization test can be approximated by the population test on some occasions. Data from two multiarmed clinical trials from the literature are reanalyzed to illustrate the methodology.

Randomization: The forgotten component of the randomized clinical trial.

"…The customary test for an observed difference…is based on an enumeration of the probabilities, on the initial hypothesis that two treatments do not differ in their effects,…of all the various results which would occur if the trial were repeated indefinitely with different random samples of the same size as those actually used." -Peter Armitage ("Sequential tests in prophylactic and therapeutic trials" in Quarterly Journal of Medicine, 1954;23(91):255-274). Randomization has been the hallmark of the clinical trial since Sir Bradford Hill adopted it in the 1946 streptomycin trial. An exploration of the early literature yields three rationales, ie, (i) the incorporation of randomization provides unpredictability in treatment assignments, thereby mitigating selection bias; (ii) randomization tends to ensure similarity in the treatment groups on known and unknown confounders (at least asymptotically); and (iii) the act of randomization itself provides a basis for inference when random sampling is not conducted from a population model. Of these three, rationale (iii) is often forgotten, ignored, or left untaught. Today, randomization is a rote exercise, scarcely considered in protocols or medical journal articles. Yet, the literature of the last century is rich with statistical articles on randomization methods and their consequences, authored by some of the pioneers of the biostatistics and statistics world. In this paper, we review some of this literature and describe very simple methods to rectify some of the oversight. We describe how randomization-based inference can be used for virtually any outcome of interest in a clinical trial. Special mention is made of nonstandard clinical trials situations.

Impact of body composition on survival and morbidity after liver resection in hepatocellular carcinoma patients.

BACKGROUND: Hepatocellular carcinoma is the most common innate liver tumor. Due to improved surgical techniques, even extended resections are feasible, and more patients can be treated with curative intent. As the liver is the central metabolic organ, preoperative metabolic assessment is crucial for risk stratification. Sarcopenia, obesity and sarcopenic obesity characterize body composition and metabolic status. Here we present the impact of body composition on survival after liver resection in patients with hepatocellular carcinoma. METHODS: A retrospective database analysis of 70 patients who were assigned for liver resection due to hepatocellular carcinoma was conducted. For assessment of sarcopenia and obesity, skeletal muscle surface area was measured at lumbar vertebra 3 level (L3) in preoperative four-phase contrast enhanced abdominal CT scans, and L3 muscle index and body fat percentage were calculated. RESULTS: Univariate analysis comparing the survival curves using the score test demonstrated superior postoperative overall survival for sarcopenic (P = 0.035) and sarcopenic obese (P = 0.048) patients as well as a trend favoring obese (P = 0.130) subjects. Whereas multivariate analysis could not identify significant difference in postoperative survival regarding sarcopenia, obesity or sarcopenic obesity. Only large tumor size, multifocal disease and male gender were risk factors for long-term survival. CONCLUSIONS: Sarcopenia, obesity and sarcopenic obesity are indeed no risk factors for poor postoperative survival in this study. Our data do not support the evaluation of sarcopenia, obesity and sarcopenic obesity before liver resection in hepatocellular carcinoma patients.

ERDO - a framework to select an appropriate randomization procedure for clinical trials.

BACKGROUND: Randomization is considered to be a key feature to protect against bias in randomized clinical trials. Randomization induces comparability with respect to known and unknown covariates, mitigates selection bias, and provides a basis for inference. Although various randomization procedures have been proposed, no single procedure performs uniformly best. In the design phase of a clinical trial, the scientist has to decide which randomization procedure to use, taking into account the practical setting of the trial with respect to the potential of bias. Less emphasis has been placed on this important design decision than on analysis, and less support has been available to guide the scientist in making this decision. METHODS: We propose a framework that weights the properties of the randomization procedure with respect to practical needs of the research question to be answered by the clinical trial. In particular, the framework assesses the impact of chronological and selection bias on the probability of a type I error. The framework is applied to a case study with a 2-arm parallel group, single center randomized clinical trial with continuous endpoint, with no-interim analysis, 1:1 allocation and no adaptation in the randomization process. RESULTS: In so doing, we derive scientific arguments for the selection of an appropriate randomization procedure and develop a template which is illustrated in parallel by a case study. Possible extensions are discussed. CONCLUSION: The proposed ERDO framework guides the investigator through a template for the choice of a randomization procedure, and provides easy to use tools for the assessment. The barriers for the thorough reporting and assessment of randomization procedures could be further reduced in the future when regulators and pharmaceutical companies employ similar, standardized frameworks for the choice of a randomization procedure.

Psychosocial Factors and Glycemic Control in Young Adults With Youth-Onset Type 2 Diabetes.

Importance: Youth-onset type 2 diabetes is associated with poor glycemic control and early onset of complications. Identification of psychosocial factors associated with poor glycemic control is needed to inform efficacious interventions. Objective: To identify psychosocial factors associated with glycated hemoglobin (HbA1c) levels in young adults with youth-onset type 2 diabetes. Design, Setting, and Participants: For the iCount cohort study, HbA1c levels were measured twice (at baseline [T1] and at 1 year [T2]) during the last years (2017-2019) of the observational phase of the multicenter Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY2) study. Participants were young adults who had been diagnosed with type 2 diabetes during childhood or adolescence. Data were analyzed from December 2021 to September 2023. Main Outcomes and Measures: Glycemic control was examined categorically (high [≥8.0%] vs low [<8.0%] HbA1c), continuously (HbA1c level), and over time (change in HbA1c: decreased ≥0.5%, remained stable, or increased ≥0.5%). Psychosocial measures included beliefs about medicines, depression and anxiety symptoms, diabetes distress, diabetes self-efficacy, self-management support, and unmet material needs. Multivariable logistic and linear regression models evaluated the association of each psychosocial factor with the probability of T2 HbA1c of 8.0% or greater, T2 HbA1c level, and change in HbA1c. Results: Of the 411 TODAY2 participants approached, 381 enrolled in the iCount study, and 348 with T1 and T2 HbA1c data comprised the analysis group. The 348 participants had a mean (SD) age of 26.1 (2.5) years and a mean (SD) HbA1c of 9.4% (2.8%). Most participants (229 [65.8%]) were women. In adjusted multivariable regressions, greater beliefs that diabetes medicines are necessary (odds ratio [OR], 1.19 [95% CI, 1.03-1.37]; P = .02), concerns about medicines (OR, 1.20 [95% CI, 1.00-1.45]; P = .049), diabetes distress (OR, 1.08 [95% CI, 1.02-1.15]; P = .006), and high distress (OR, 2.18 [95% CI, 1.15-4.13]; P = .02) increased the odds of high HbA1c at T2. Greater support (OR, 0.67 [95% CI, 0.46-0.97]; P = .04) and diabetes self-efficacy (OR, 0.91 [95% CI, 0.84-0.99]; P = .02) decreased the odds of high HbA1c at T2. Diabetes distress was associated with higher HbA1c level at T2 (coefficient, 0.08 [95% CI, 0.02-0.13]; P = .01). Beliefs that diabetes medicines are necessary (OR, 1.20 [95% CI, 1.03-1.39]; P = .02) and concerns about medicines (OR, 1.22 [95% CI, 1.00-1.47]; P = .048) increased the odds of an HbA1c decrease of at least 0.5% over 1 year. Conclusions and Relevance: In this cohort study of young adults with youth-onset type 2 diabetes, beliefs about medicines, high diabetes distress, low diabetes self-efficacy, and self-management support were associated with high HbA1c over time. Future research should assess whether interventions that address these factors result in improved glycemic control in this at-risk group.

Emotional Distress Predicts Reduced Type 2 Diabetes Treatment Adherence in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).

OBJECTIVE: We examined longitudinal associations between emotional distress (specifically, depressive symptoms and diabetes distress) and medication adherence in Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE), a large randomized controlled trial comparing four glucose-lowering medications added to metformin in adults with relatively recent-onset type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: The Emotional Distress Substudy assessed medication adherence, depressive symptoms, and diabetes distress in 1,739 GRADE participants via self-completed questionnaires administered biannually up to 3 years. We examined baseline depressive symptoms and diabetes distress as predictors of medication adherence over 36 months. Bidirectional visit-to-visit relationships were also examined. Treatment satisfaction, beliefs about medication, diabetes care self-efficacy, and perceived control over diabetes were evaluated as mediators of longitudinal associations. RESULTS: At baseline, mean ± SD age of participants (56% of whom were White, 17% Hispanic/Latino, 18% Black, and 66% male) was 58.0 ± 10.2 years, diabetes duration 4.2 ± 2.8 years, HbA1c 7.5% ± 0.5%, and medication adherence 89.9% ± 11.1%. Higher baseline depressive symptoms and diabetes distress were independently associated with lower adherence over 36 months (P < 0.001). Higher depressive symptoms and diabetes distress at one visit predicted lower adherence at the subsequent 6-month visit (P < 0.0001) but not vice versa. Treatment assignment did not moderate relationships. Patient-reported concerns about diabetes medications mediated the largest percentage (11.9%-15.5%) of the longitudinal link between emotional distress and adherence. CONCLUSIONS: Depressive symptoms and diabetes distress both predict lower adherence to glucose-lowering medications over time among adults with T2DM. Addressing emotional distress and concerns about anticipated negative effects of taking these treatments may be important to support diabetes treatment adherence.

Estimated COVID-19 vaccine effectiveness against seroconversion from SARS-CoV-2 Infection, March-October, 2021.

BACKGROUND: Monitoring the effectiveness of COVID-19 vaccines against SARS-CoV-2 infections remains important to inform public health responses. Estimation of vaccine effectiveness (VE) against serological evidence of SARS-CoV-2 infection might provide an alternative measure of the benefit of vaccination against infection. METHODS: We estimated mRNA COVID-19 vaccine effectiveness (VE) against development of SARS-CoV-2 anti-nucleocapsid antibodies in March-October 2021, during which the Delta variant became predominant. Participants were enrolled from four participating healthcare systems in the United States, and completed electronic surveys that included vaccination history. Dried blood spot specimens collected on a monthly basis were analyzed for anti-spike antibodies, and, if positive, anti-nucleocapsid antibodies. We used detection of new anti-nucleocapsid antibodies to indicate SARS-CoV-2 infection, and estimated VE by comparing 154 case-participants with new detection of anti-nucleocapsid antibodies to 1,540 seronegative control-participants matched by calendar period. Using conditional logistic regression, we estimated VE ≥ 14 days after the 2nd dose of an mRNA vaccine compared with no receipt of a COVID-19 vaccine dose, adjusting for age group, healthcare worker occupation, urban/suburban/rural residence, healthcare system region, and reported contact with a person testing positive for SARS-CoV-2. RESULTS: Among individuals who completed a primary series, estimated VE against seroconversion from SARS-CoV-2 infection was 88.8% (95% confidence interval [CI], 79.6%-93.9%) after any mRNA vaccine, 87.8% (95% CI, 75.9%-93.8%) after BioNTech vaccine and 91.7% (95% CI, 75.7%-97.2%) after Moderna vaccine. VE was estimated to be lower ≥ 3 months after dose 2 compared with < 3 months after dose 2, and among participants who were older or had underlying health conditions, although confidence intervals overlapped between subgroups. CONCLUSIONS: VE estimates generated using infection-induced antibodies were consistent with published estimates from clinical trials and observational studies that used virologic tests to confirm infection during the same period. Our findings support recommendations for eligible adults to remain up to date with COVID-19 vaccination.

Persistence of antibody responses to COVID-19 vaccines among participants in the COVID-19 Community Research Partnership.

Introduction: High levels of immunity to SARS-CoV-2 in the community correlate with protection from COVID-19 illness. Measuring COVID-19 antibody seroprevalence and persistence may elucidate the level and length of protection afforded by vaccination and infection within a population. Methods: We measured the duration of detectable anti-spike antibodies following COVID-19 vaccination in a multistate, longitudinal cohort study of almost 13,000 adults who completed daily surveys and submitted monthly dried blood spots collected at home. Results: Overall, anti-spike antibodies persisted up to 284 days of follow-up with seroreversion occurring in only 2.4% of the study population. In adjusted analyses, risk of seroreversion increased with age (adults aged 55-64: adjusted hazard ratio [aHR] 2.19 [95% confidence interval (CI): 1.22, 3.92] and adults aged > 65: aHR 3.59 [95% CI: 2.07, 6.20] compared to adults aged 18-39). Adults with diabetes had a higher risk of seroreversion versus nondiabetics (aHR 1.77 [95% CI: 1.29, 2.44]). Decreased risk of seroreversion was shown for non-Hispanic Black versus non-Hispanic White (aHR 0.32 [95% CI: 0.13, 0.79]); college degree earners versus no college degree (aHR 0.61 [95% CI: 0.46, 0.81]); and those who received Moderna mRNA-1273 vaccine versus Pfizer-BioNTech BNT162b2 (aHR 0.35 [95% CI: 0.26, 0.47]). An interaction between healthcare worker occupation and sex was detected, with seroreversion increased among male, non-healthcare workers. Conclusion: We established that a remote, longitudinal, multi-site study can reliably detect antibody durability following COVID-19 vaccination. The survey platform and measurement of antibody response using at-home collection at convenient intervals allowed us to explore sociodemographic factors and comorbidities and identify predictors of antibody persistence, which has been demonstrated to correlate with protection against disease. Our findings may help inform public health interventions and policies to protect those at highest risk for severe illness and assist in determining the optimal timing of booster doses.Clinical trials registry: NCT04342884.

Diabetes Distress in Young Adults With Youth-Onset Type 2 Diabetes: TODAY2 Study Results.

OBJECTIVE: To assess the prevalence of high diabetes distress and associated factors in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY2) study cohort of young adults with youth-onset type 2 diabetes. RESEARCH DESIGN AND METHODS: Participants completed the Diabetes Distress Scale (DDS) at end-of-study visits. Factors examined for association with high distress were demographic (sex, race/ethnicity, age, education, income), medical (HbA1c, BMI, complications), psychological (depressive and anxiety symptoms), and social (number in household, offspring, health care coverage, established with diabetes care provider). Univariate logistic regression identified factors associated with high distress that were controlled for in multivariate logistic regressions. RESULTS: Of 438 participants, 66% were female (mean age 26.8 years, 18% non-Hispanic White, 37% non-Hispanic Black, 38% Hispanic). High distress (DDS ≥2) was reported by 105 (24%) participants. Subscales identified 40% with high regimen distress and 29.7% with high emotional burden. A greater percentage of those with high distress were female (P = 0.002), diagnosed with hypertension (P = 0.037) and retinopathy (P = 0.005), treated with insulin, had higher HbA1c, and had moderate to severe depressive and anxiety symptoms (all P < 0.001). In multivariate analyses, female sex (P < 0.001), HbA1c (P < 0.001), anxiety symptoms (P = 0.036), and lack of health care coverage (P = 0.019) were associated with high distress, after controlling for potential confounders. Moderate to severe depressive symptoms were associated with high regimen distress (P = 0.018) and emotional burden (P < 0.001); insulin treatment was associated with high emotional burden (P = 0.027). CONCLUSIONS: Future research should identify modifiable factors associated with high diabetes distress in young adults with youth-onset type 2 diabetes that may inform distress interventions with this medically vulnerable group.

Retinal Thickness and Morphology Changes on OCT in Youth with Type 2 Diabetes: Findings from the TODAY Study.

Objective: To evaluate changes in retinal thickness and morphology using OCT in youth with type 2 diabetes (T2D) and to identify systemic biomarkers correlating with these changes. Design: Retrospective subgroup analysis of a prospective study. Participants: Participants who underwent OCT imaging in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) trial and its follow-up study TODAY2. Methods: In 2010-2011 (TODAY) and 2017-2018 (TODAY2), 6 × 6-mm macular volume OCT scans were acquired, segmented, and analyzed to generate total retinal thickness, inner retinal thickness, and outer retinal thickness. The main retinal morphologies graded were intraretinal cystoid spaces, subretinal fluid, and posterior vitreous detachment (PVD). Main Outcome Measures: Changes in total and individual retinal layer thickness and development of abnormal vitreomacular morphology between TODAY and TODAY2. Results: Participants had a mean age of 17.9 ± 2.4 years and glycated hemoglobin (HbA1c) of 8.2 ± 2.8% in TODAY and a mean age of 25.0 ± 2.4 years and mean HbA1c of 9.5 ± 2.8% in TODAY2. Longitudinally between assessments, there were overall decreases in outer retinal thickness from 167.2 ± 11.5 microns to 158.4 ± 12.8 microns (P < 0.001) and in photoreceptor thickness from 30.3 ± 2.9 microns to 29.8 ± 4.1 microns (P = 0.04) in the central subfield, while in the inner subfield, we noted a decrease in outer retinal thickness from 150.5 ± 10.1 microns to 144.9 ± 10.5 microns (P < 0.001) and an increase in inner retinal thickness from 136.9 ± 11.5 microns to 137.4 ± 12.6 microns (P = 0.01). Multivariate analysis showed that in the center subfield, HbA1c increases were associated with increases in total retinal thickness (r: 0.67, P = 0.001), whereas fasting glucose was positively correlated with inner retinal thickness (r: 0.02, P = 0.02). In the inner subfield, both systolic (r: -0.22, P < 0.001) and diastolic (r: -0.22, P = 0.003) blood pressures were negatively correlated with total retinal thickness. There was an increase in PVD (18.9%) and cystoid spaces (4.2%). Conclusions: Youth with T2D develop retinal thickness changes on OCT, including increases in total retinal and inner retinal thickness in the center subfield that correlate with HbA1c and fasting glucose, respectively. Taken together with the increased prevalence of abnormal vitreomacular morphology in this cohort at risk, these findings emphasize the importance of controlling risk factors to prevent the development of sight-threatening retinal complications.

Association of Obesity and Diabetes with SARS-Cov-2 Infection and Symptoms in the COVID-19 Community Research Partnership.

OBJECTIVE: Obesity and diabetes are established risk factors for severe SARS-CoV-2 outcomes, but less is known about their impact on susceptibility to COVID-19 infection and general symptom severity. We hypothesized that those with obesity or diabetes would be more likely to self-report a positive SARS-CoV-2 test, and among those with a positive test, have greater symptom severity and duration. METHODS: Among 44,430 COVID-19 Community Research Partnership participants, we evaluated the association of self-reported and electronic health record obesity and diabetes with a self-reported positive COVID-19 test at any time. Among the 2,663 participants with a self-reported positive COVID-19 test during the study, we evaluated the association of obesity and diabetes with self-report of symptom severity, duration, and hospitalization. Logistic regression models were adjusted for age, sex, race/ethnicity, socioeconomic status, and healthcare worker status. RESULTS: We found a positive graded association between Body Mass Index (BMI) category and positive COVID-19 test (Overweight OR = 1.14 [1.05-1.25]; Obesity I OR = 1.29 [1.17-2.42]; Obesity II OR = 1.34 [1.19-1.50]; Obesity III OR = 1.53 [1.35-1.73]), and a similar but weaker association with COVID-19 symptoms and severity among those with a positive test. Diabetes was associated with COVID-19 infection but not symptoms after adjustment, with some evidence of an interaction between obesity and diabetes. CONCLUSIONS: While the limitations of this health system convenience sample include generalizability and selection around test-seeking, the strong graded association of BMI and diabetes with self-reported COVID-19 infection suggests that obesity and diabetes may play a role in risk for symptomatic SARS-CoV-2 beyond co-occurrence with socioeconomic factors.