SARS-CoV-2 antibodies persist up to 12 months after natural infection in healthy employees working in non-medical contact-intensive professions.

OBJECTIVES: This study aimed to evaluate dynamics of antibody levels after exposure to SARS-CoV-2 for 12 months in Dutch non-vaccinated hairdressers and hospitality staff. METHODS: In this prospective cohort study, blood samples were collected every 3 months for 1 year and analyzed using a qualitative total antibody enzyme-linked immunosorbent assay (ELISA) and a quantitative immunoglobulin (Ig)G antibody ELISA. Participants completed questionnaires, providing information on demographics, health, and work. Differences in antibody levels were evaluated using Mann-Whitney U and Wilcoxon signed-rank tests. Beta coefficients (ß) and 95% confidence intervals (CIs) were calculated using linear regression. RESULTS: Ninety-five of 497 participants (19.1%) had ≥1 seropositive measurement before their last visit using the qualitative ELISA. Only 2.1% (2/95) seroreverted during follow-up. Of 95 participants, 82 (86.3%) tested IgG seropositive in the quantitative ELISA too. IgG antibody levels significantly decreased in the first months (P <0.01) but remained detectable for up to 12 months in all participants. Older age (ß, 10-years increment: 24.6, 95% CI: 5.7-43.5) and higher body mass index (ß, 5kg/m² increment: 40.0, 95% CI: 2.9-77.2) were significantly associated with a higher peak of antibody levels. CONCLUSION: In this cohort, SARS-CoV-2 antibodies persisted for up to 1 year after initial seropositivity, suggesting long-term natural immunity.

Evaluating a theory-based hypothesis against its complement using an AIC-type information criterion with an application to facial burn injury.

An information criterion (IC) like the Akaike IC (AIC), can be used to select the best hypothesis from a set of competing theory-based hypotheses. An IC developed to evaluate theory-based order-restricted hypotheses is the Generalized Order-Restricted Information Criterion (GORIC). Like for any IC, the values themselves are not interpretable but only comparable. To improve the interpretation regarding the strength, GORIC weights and related evidence ratios can be computed. However, if the unconstrained hypothesis (the default) is used as competing hypothesis, the evidence ratio is not affected by sample-size nor effect-size in case the hypothesis of interest is (also) in agreement with the data. In practice, this means that in such a case strong support for the order-restricted hypothesis is not reflected by a high evidence ratio. Therefore, we introduce the evaluation of an order-restricted hypothesis against its complement using the GORIC (weights). We show how to compute the GORIC value for the complement, which cannot be achieved by current methods. In a small simulation study, we show that the evidence ratio for the order-restricted hypothesis versus the complement increases for larger samples and/or effect-sizes, while the evidence ratio for the order-restricted hypothesis versus the unconstrained hypothesis remains bounded. An empirical example about facial burn injury illustrates our method and shows that using the complement as competing hypothesis results in much more support for the hypothesis of interest than using the unconstrained hypothesis as competing hypothesis. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Pain in young children with burns: extent, course and influencing factors.

Little evidence is available on the extent, course and influencing factors of pain in young children with burns. At present, reliable and valid measurement instruments to assess pain behavior in these children are available, implying that valuable insight into these questions can now be obtained. The aim of this study is to document the extent and course of pain behavior with the COMFORT-B, and to assess factors that may influence procedural pain. First, cutpoints for COMFORT-B scores were established by Rasch analysis to assess clinically relevant changes. Second, the extent of background and procedural pain behavior was assessed by descriptive statistics. Third, the course and factors that may influence procedural pain behavior were investigated by latent growth modeling. Trained nurses collected pain behavior data in 168 children (mean age 20 months, mean TBSA 6%, mean length of stay 10 days). Cutpoints of COMFORT-B scores were as follows: 6-13 (mild pain), 14-20 (moderate pain) and 21-30 (severe pain). This study suggests that background pain is more adequately treated than procedural pain. Factors that influenced baseline pain scores and/or the course over 8 days included TBSA, the number of surgical procedures, acetaminophen administration by the referring hospital, and the application of hydrofiber dressings. The implications of these findings are discussed.

Cognitive emotion regulation strategies and neuroticism in relation to depressive symptoms following burn injury: a longitudinal study with a 2-year follow-up.

Sustaining burns is considered a stressful life event that has the power to elicit depressive symptoms. This study aimed to identify predictors of depressive symptoms by investigating the role of demographic variables, the number of operations (burn severity), neuroticism, and cognitive emotion regulation styles as possible influencing factors. Data from 242 patients with burns were analyzed employing latent growth modeling. The level of depressive symptoms across the 2-year interval was associated with burn severity, higher levels of neuroticism and rumination, and lower levels of positive refocusing. Notably, rumination partly mediated the effect of neuroticism on the course of depressive symptoms. Correlational analysis suggested a specific effect of burn severity on rumination. The results indicate that screening for symptoms of depression, rumination, and neuroticism in burn patients is useful. Early interventions focusing on cognitive restructuring could assist in improving the cognitive emotional adaptation process following a burn event.

Constrained statistical inference: sample-size tables for ANOVA and regression.

Researchers in the social and behavioral sciences often have clear expectations about the order/direction of the parameters in their statistical model. For example, a researcher might expect that regression coefficient ß1 is larger than ß2 and ß3. The corresponding hypothesis is H: ß1 > {ß2, ß3} and this is known as an (order) constrained hypothesis. A major advantage of testing such a hypothesis is that power can be gained and inherently a smaller sample size is needed. This article discusses this gain in sample size reduction, when an increasing number of constraints is included into the hypothesis. The main goal is to present sample-size tables for constrained hypotheses. A sample-size table contains the necessary sample-size at a pre-specified power (say, 0.80) for an increasing number of constraints. To obtain sample-size tables, two Monte Carlo simulations were performed, one for ANOVA and one for multiple regression. Three results are salient. First, in an ANOVA the needed sample-size decreases with 30-50% when complete ordering of the parameters is taken into account. Second, small deviations from the imposed order have only a minor impact on the power. Third, at the maximum number of constraints, the linear regression results are comparable with the ANOVA results. However, in the case of fewer constraints, ordering the parameters (e.g., ß1 > ß2) results in a higher power than assigning a positive or a negative sign to the parameters (e.g., ß1 > 0).