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BACKGROUND: Malnutrition, including obesity and undernutrition, among children is increasing in prevalence and is common among children on renal replacement therapy. The effect of malnutrition on the pre-transplant immune system and how the pediatric immune system responds to the insult of both immunosuppression and allotransplantation is unknown. We examined the relationship of nutritional status with post-transplant outcomes and characterized the peripheral immune cell phenotypes of children from the Immune Development of Pediatric Transplant (IMPACT) study. METHODS: Ninety-eight patients from the IMPACT study were classified as having obesity, undernutrition, or normal nutrition-based pre-transplant measurements. Incidence of infectious and alloimmune outcomes at 1-year post-transplantation was compared between nutritional groups using Grays test and Fine-Gray subdistribution hazards model. Event-free survival was estimated by Kaplan-Meier method and compared between groups. Differences in immune cell subsets between nutritional groups over time were determined using generalized estimating equations accounting for the correlation between repeated measurements. RESULTS: We did not observe that nutritional status was associated with infectious or alloimmune events or event-free survival post-transplant. We demonstrated that children with obesity had distinct T-and B-cell signatures relative to those with undernutrition and normal nutrition, even when controlling for immunosuppression. Children with obesity had a lower frequency of CD8 Tnaive cells 9-month post-transplant (p

Depletional induction using antithymocyte globulin (ATG) reduces rates of acute rejection in adult kidney transplant recipients, yet little is known about its effects in children. Using a longitudinal cohort of 103 patients in the Immune Development in Pediatric Transplant (IMPACT) study, we compared T cell phenotypes after ATG or non-ATG induction. We examined the effects of ATG on the early clinical outcomes of alloimmune events (development of de novo donor specific antibody and/or biopsy proven rejection) and infection events (viremia/viral infections). Long-term patient and graft outcomes were examined using the Scientific Registry of Transplant Recipients. After ATG induction, although absolute counts of CD4 and CD8 T cells were lower, patients had higher percentages of CD4 and CD8 memory T cells with a concomitant decrease in frequency of naïve T cells compared to non-ATG induction. In adjusted and unadjusted models, ATG induction was associated with increased early event-free survival, with no difference in long-term patient or allograft survival. Decreased CD4+ naïve and increased CD4+ effector memory T cell frequencies were associated with improved clinical outcomes. Though immunologic parameters are drastically altered with ATG induction, long-term clinical benefits remain unclear in pediatric patients.

Objectives: We sought to identify the impact of preeclampsia on infant and maternal health among women with rheumatic diseases. Methods: A retrospective single-center cohort study was conducted to describe pregnancy and infant outcomes among women with systemic lupus erythematosus (SLE) with and without preeclampsia as compared to women with other rheumatic diseases with and without preeclampsia. Results: We identified 263 singleton deliveries born to 226 individual mothers (mean age 31 years, 35% non-Hispanic Black). Overall, 14% of women had preeclampsia; preeclampsia was more common among women with SLE than other rheumatic diseases (27% vs 8%). Women with preeclampsia had a longer hospital stay post-delivery. Infants born to mothers with preeclampsia were delivered an average of 3.3 weeks earlier than those without preeclampsia, were 4 times more likely to be born preterm, and twice as likely to be admitted to the neonatal intensive care unit. The large majority of women with SLE in this cohort were prescribed hydroxychloroquine and aspirin, with no clear association of these medications with preeclampsia. Conclusions: We found preeclampsia was an important driver of adverse infant and maternal outcomes. While preeclampsia was particularly common among women with SLE in this cohort, the impact of preeclampsia on the infants of all women with rheumatic diseases was similarly severe. In order to improve infant outcomes for women with rheumatic diseases, attention must be paid to preventing, identifying, and managing preeclampsia. [ABSTRACT FROM AUTHOR]

Individualized treatment decisions can improve health outcomes, but using data to make these decisions in a reliable, precise, and generalizable way is challenging with a single dataset. Leveraging multiple randomized controlled trials allows for the combination of datasets with unconfounded treatment assignment to better estimate heterogeneous treatment effects. This article discusses several nonparametric approaches for estimating heterogeneous treatment effects using data from multiple trials. We extend single‐study methods to a scenario with multiple trials and explore their performance through a simulation study, with data generation scenarios that have differing levels of cross‐trial heterogeneity. The simulations demonstrate that methods that directly allow for heterogeneity of the treatment effect across trials perform better than methods that do not, and that the choice of single‐study method matters based on the functional form of the treatment effect. Finally, we discuss which methods perform well in each setting and then apply them to four randomized controlled trials to examine effect heterogeneity of treatments for major depressive disorder. [ABSTRACT FROM AUTHOR]

Background Child with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection typically have mild symptoms that do not require medical attention, leaving a gap in our understanding of the spectrum of SARS-CoV-2-related illnesses that the viruses causes in children. Methods We conducted a prospective cohort study of children and adolescents (aged <21 years) with a SARS-CoV-2-infected close contact. We collected nasopharyngeal or nasal swabs at enrollment and tested for SARS-CoV-2 using a real-time polymerase chain reaction assay. Results Of 382 children, 293 (77%) were SARS-CoV-2-infected. SARS-CoV-2-infected children were more likely to be Hispanic (P <.0001), less likely to have asthma (P =.005), and more likely to have an infected sibling contact (P =.001) than uninfected children. Children aged 6-13 years were frequently asymptomatic (39%) and had respiratory symptoms less often than younger children (29% vs 48%; P =.01) or adolescents (29% vs 60%; P <.001). Compared with children aged 6-13 years, adolescents more frequently reported influenza-like (61% vs 39%; P <.001) , and gastrointestinal (27% vs 9%; P =.002), and sensory symptoms (42% vs 9%; P <.0001) and had more prolonged illnesses (median [interquartile range] duration: 7 [4-12] vs 4 [3-8] days; P = 0.01). Despite the age-related variability in symptoms, wWe found no difference in nasopharyngeal viral load by age or between symptomatic and asymptomatic children. Conclusions Hispanic ethnicity and an infected sibling close contact are associated with increased SARS-CoV-2 infection risk among children, while asthma is associated with decreased risk. Age-related differences in clinical manifestations of SARS-CoV-2 infection must be considered when evaluating children for coronavirus disease 2019 and in developing screening strategies for schools and childcare settings. [ABSTRACT FROM AUTHOR]

Autophagy associated genes (ATGs) played an important role in the repair process of DNA damage and decreased autophagy may weaken the repair process and aggravate DNA damage. Based on this, we hypothesized that DNA damage levels might be modified by genetic variants in autophagy associated genes. In order to validate our hypothesis, 307 subjects were recruited from three different cities (Zhuhai, Wuhan and Tianjin) in China. Demographic data, individual 24-h PM 2.5 exposure and peripheral blood DNA damage levels were also detected. Seven potentially functional polymorphisms in four essential autophagy associated genes ( ATG5 , ATG7 , ATG8 and ATG13 ) were screened to evaluate the relationship between the polymorphisms of autophagy associated genes and DNA damage levels. This association was assessed by using multivariable linear regression model, age, sex, smoke and PM 2.5 exposure levels were adjusted in each city. We found that rs12599322 in ATG8 (A > G, β = 0.263, 95% CI: 0.108–0.419, P = 8.98 × 10 − 4 ) and rs7484002 in ATG13 (A > G, β = 0.396, 95% CI: 0.085–0.708, P = 0.013) were significantly associated with higher DNA damage levels. Furthermore, functional annotations showed that both rs12599322 and rs7484002 located at transcription factor binding sites (TFBS), indicating that they could regulate the expression of related genes through TF regulation. Following allelic trend analysis revealed that the DNA damage levels were significantly aggravated with the increasing number of risk variants in autophagy associated genes ( P for trend: 8.09 × 10 − 5 ). Our findings suggested that the polymorphisms in ATGs may influence DNA damage levels in one of the Chinese population. [ABSTRACT FROM AUTHOR]

Purpose: Unanticipated health care resource utilization, in the form of either emergency department utilization (EDU) or hospital admission (HA), may be an indicator of lower-quality cancer care. The objective of this study was to develop a predictive model for EDU and HAs within 14 days of receipt of systemic therapy for patients with solid tumors., Methods: We abstracted electronic health data on oncology encounters from all patients receiving systemic therapy for solid tumors from March 1, 2015, to August 21, 2020, in the Duke University Health System. We defined a primary composite outcome of an EDU or HA within 14 days after the encounter and then developed a predictive model for the primary outcome using least absolute shrinkage and selection operator regression. To evaluate the model, we calculated the area under the receiver operator curve and the calibration slope., Results: Twelve thousand eight hundred ninety unique patients with 134,641 oncology encounters were included. Five thousand one hundred fifty of these patients (40.0%) had at least one EDU or HA within 14 days of at least one treatment. Forty-six variables were incorporated into the final model. The top predictors, in order of absolute value of the predictive coefficients, were temperature, systolic blood pressure, cancer group, and marital status. The model's AUC was 0.73 (95% CI, 0.722 to 0.732), indicating good sensitivity and specificity to outcome., Conclusion: The model developed in this study demonstrated good sensitivity in identifying patients with solid tumors who are at highest risk for EDU or HA and could be implemented in clinical practice to allow for preventive outpatient interventions.

Objective: To develop and validate a model to predict obstetric anal sphincter injuries (OASIS) using only information available at the time of admission for labour., Design: A clinical predictive model using a retrospective cohort., Setting: A US health system containing one community and one tertiary hospital., Sample: A total of 22 873 pregnancy episodes with in-hospital delivery at or beyond 21 weeks of gestation., Methods: Thirty antepartum risk factors were identified as candidate variables, and a prediction model was built using logistic regression predicting OASIS versus no OASIS. Models were fit using the overall study population and separately using hospital-specific cohorts. Bootstrapping was used for internal validation and external cross-validation was performed between the two hospital cohorts., Main Outcome Measures: Model performance was estimated using the bias-corrected concordance index (c-index), calibration plots and decision curves., Results: Fifteen risk factors were retained in the final model. Decreasing parity, previous caesarean birth and cardiovascular disease increased risk of OASIS, whereas tobacco use and black race decreased risk. The final model from the total study population had good discrimination (c-index 0.77, 95% confidence interval [CI] 0.75-0.78) and was able to accurately predict risks between 0 and 35%, where average risk for OASIS was 3%. The site-specific model fit using patients only from the tertiary hospital had c-stat 0.74 (95% CI 0.72-0.77) on community hospital patients, and the community hospital model was 0.77 (95%CI 0.76-0.80) on the tertiary hospital patients., Conclusions: OASIS can be accurately predicted based on variables known at the time of admission for labour. These predictions could be useful for selectively implementing OASIS prevention strategies., (© 2022 John Wiley & Sons Ltd.)