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      Association Between Epidural Analgesia During Labor and Risk of Autism Spectrum Disorders in Offspring

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          Sensitivity Analysis in Observational Research: Introducing the E-Value.

          Sensitivity analysis is useful in assessing how robust an association is to potential unmeasured or uncontrolled confounding. This article introduces a new measure called the "E-value," which is related to the evidence for causality in observational studies that are potentially subject to confounding. The E-value is defined as the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. A large E-value implies that considerable unmeasured confounding would be needed to explain away an effect estimate. A small E-value implies little unmeasured confounding would be needed to explain away an effect estimate. The authors propose that in all observational studies intended to produce evidence for causality, the E-value be reported or some other sensitivity analysis be used. They suggest calculating the E-value for both the observed association estimate (after adjustments for measured confounders) and the limit of the confidence interval closest to the null. If this were to become standard practice, the ability of the scientific community to assess evidence from observational studies would improve considerably, and ultimately, science would be strengthened.
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            Incidence Rates and Cumulative Incidences of the Full Spectrum of Diagnosed Mental Disorders in Childhood and Adolescence

            This nationwide cohort study estimates age- and sex-specific incidence rates and risks of being diagnosed with any mental disorder during childhood and adolescence using Danish population health registers. What are the age- and sex-specific incidence rates and cumulative incidences of the full spectrum of diagnosed mental disorders during childhood and adolescence? In this nationwide cohort study of 1.3 million individuals in Denmark, the risk (cumulative incidence) of being diagnosed with a mental disorder before 18 years of age was 14.63% in girls and 15.51% in boys. Distinct age- and sex-specific patterns of occurrence were found across mental disorders in children and adolescents. These findings suggest that precise estimates of rates and risks of all mental disorders during childhood and adolescence are essential for future planning of services and care and for etiological research. Knowledge about the epidemiology of mental disorders in children and adolescents is essential for research and planning of health services. Surveys can provide prevalence rates, whereas population-based registers are instrumental to obtain precise estimates of incidence rates and risks. To estimate age- and sex-specific incidence rates and risks of being diagnosed with any mental disorder during childhood and adolescence. This cohort study included all individuals born in Denmark from January 1, 1995, through December 31, 2016 (1.3 million), and followed up from birth until December 31, 2016, or the date of death, emigration, disappearance, or diagnosis of 1 of the mental disorders examined (14.4 million person-years of follow-up). Data were analyzed from September 14, 2018, through June 11, 2019. Age and sex. Incidence rates and cumulative incidences of all mental disorders according to the ICD-10 Classification of Mental and Behavioral Disorders: Diagnostic Criteria for Research, diagnosed before 18 years of age during the study period. A total of 99 926 individuals (15.01%; 95% CI, 14.98%-15.17%), including 41 350 girls (14.63%; 95% CI, 14.48%-14.77%) and 58 576 boys (15.51%; 95% CI, 15.18%-15.84%), were diagnosed with a mental disorder before 18 years of age. Anxiety disorder was the most common diagnosis in girls (7.85%; 95% CI, 7.74%-7.97%); attention-deficit/hyperactivity disorder (ADHD) was the most common in boys (5.90%; 95% CI, 5.76%-6.03%). Girls had a higher risk than boys of schizophrenia (0.76% [95% CI, 0.72%-0.80%] vs 0.48% [95% CI, 0.39%-0.59%]), obsessive-compulsive disorder (0.96% [95% CI, 0.92%-1.00%] vs 0.63% [95% CI, 0.56%-0.72%]), and mood disorders (2.54% [95% CI, 2.47%-2.61%] vs 1.10% [95% CI, 0.84%-1.21%]). Incidence peaked earlier in boys than girls in ADHD (8 vs 17 years of age), intellectual disability (5 vs 14 years of age), and other developmental disorders (5 vs 16 years of age). The overall risk of being diagnosed with a mental disorder before 6 years of age was 2.13% (95% CI, 2.11%-2.16%) and was higher in boys (2.78% [95% CI, 2.44%-3.15%]) than in girls (1.45% [95% CI, 1.42%-1.49%]). This nationwide population-based cohort study provides a first comprehensive assessment of the incidence and risks of mental disorders in childhood and adolescence. By 18 years of age, 15.01% of children and adolescents in this study were diagnosed with a mental disorder. The incidence of several neurodevelopmental disorders peaked in late adolescence in girls, suggesting possible delayed detection. The distinct signatures of the different mental disorders with respect to sex and age may have important implications for service planning and etiological research.
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              Perinatal and neonatal risk factors for autism: a comprehensive meta-analysis.

              The etiology of autism is unknown, although perinatal and neonatal exposures have been the focus of epidemiologic research for over 40 years. To provide the first review and meta-analysis of the association between perinatal and neonatal factors and autism risk. PubMed, Embase, and PsycInfo databases were searched for studies that examined the association between perinatal and neonatal factors and autism through March 2007. Forty studies were eligible for the meta-analysis. For each exposure, a summary effect estimate was calculated using a random-effects model. Heterogeneity in effect estimates across studies was examined, and, if found, a meta-regression was conducted to identify measured methodological factors that could explain between-study variability. Over 60 perinatal and neonatal factors were examined. Factors associated with autism risk in the meta-analysis were abnormal presentation, umbilical-cord complications, fetal distress, birth injury or trauma, multiple birth, maternal hemorrhage, summer birth, low birth weight, small for gestational age, congenital malformation, low 5-minute Apgar score, feeding difficulties, meconium aspiration, neonatal anemia, ABO or Rh incompatibility, and hyperbilirubinemia. Factors not associated with autism risk included anesthesia, assisted vaginal delivery, postterm birth, high birth weight, and head circumference. There is insufficient evidence to implicate any 1 perinatal or neonatal factor in autism etiology, although there is some evidence to suggest that exposure to a broad class of conditions reflecting general compromises to perinatal and neonatal health may increase the risk. Methodological variations were likely sources of heterogeneity of risk factor effects across studies.
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                Author and article information

                Journal
                JAMA Pediatrics
                JAMA Pediatr
                American Medical Association (AMA)
                2168-6203
                October 12 2020
                Affiliations
                [1 ]Department of Anesthesiology, Kaiser Permanente Baldwin Park Medical Center, Baldwin Park, California
                [2 ]Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena
                [3 ]Department of Internal Medicine, Kaiser Permanente Baldwin Park Medical Center, Baldwin Park, California
                [4 ]Department of Pediatrics, Kaiser Permanente Baldwin Park Medical Center, Baldwin Park, California
                [5 ]Department of Obstetrics & Gynecology, Kaiser Permanente Baldwin Park Medical Center, Baldwin Park, California
                [6 ]Department of Anesthesiology, Wake Forest School of Medicine, Winston-Salem, North Carolina
                Article
                10.1001/jamapediatrics.2020.3231
                33044486
                14ad5cd8-4f92-4d50-b15d-3400a98665f1
                © 2020
                History

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