Maternal smoking during pregnancy and offspring psychiatric disorder: a longitudinal birth cohort study.

BACKGROUND: There is evidence that prenatal stress and smoking during pregnancy both independently increase the risk of offspring psychopathology. Here we examine whether increased levels of self-reported stress is associated with increased smoking in a population of pregnant women, and whether prenatal smoking is associated with offspring psychiatric diagnoses independent of prenatal stress exposure. METHOD: Using a longitudinal birth cohort, we used ordered logistic regressions to examine associations between maternal stress and smoking during pregnancy. We then used logistic regression analyses to examine associations between prenatal smoking and later offspring psychiatric disorders. RESULTS: A dose-response relationship was found between maternally reported stress and smoking during pregnancy. Pregnant women reporting severe stress were more likely to smoke compared to both the moderate stress and no stress groups, and those reporting moderate stress were significantly more likely to smoke compared to the no stress group. Smoking more than 5 cigarettes daily during pregnancy increased the risk of offspring personality disorder (OR 3.08, 95% CI 1.60-5.94) as well as developing any Axis 1 psychiatric disorder, inclusive of mood, anxiety and psychotic disorders (OR 1.45, 95% CI 1.04-2.04). After adjusting for parental psychiatric history and maternal self-reported stress during pregnancy, associations between smoking more than 5 cigarettes daily when pregnancy and offspring personality (OR 2.58 95% CI 1.32-5.06) disorder remained. CONCLUSION: Exposure to cigarette smoking during gestation could impact a child's mental health. Smoking during pregnancy is a prime target for preventative interventions as unlike most other environmental risk factors, it is very amenable to change.

Fitting Marginal Structural and G-Estimation Models Under Complex Treatment Patterns: Investigating the Association Between De Novo Vitamin D Supplement Use After Breast Cancer Diagnosis and All-Cause Mortality Using Linked Pharmacy Claim and Registry Data.

Studies have shown that accounting for time-varying confounding through time-dependent Cox proportional hazards models may provide biased estimates of the causal effect of treatment when the confounder is also a mediator. We explore 2 alternative approaches to addressing this problem while examining the association between vitamin D supplementation initiated after breast cancer diagnosis and all-cause mortality. Women aged 50-80 years were identified in the National Cancer Registry Ireland (n = 5,417) between 2001 and 2011. Vitamin D use was identified from linked prescription data (n = 2,570). We sought to account for the time-varying nature of vitamin D use and time-varying confounding by bisphosphonate use using 1) marginal structural models (MSMs) and 2) G-estimation of structural nested accelerated failure-time models (SNAFTMs). Using standard adjusted Cox proportional hazards models, we found a reduction in all-cause mortality in de novo vitamin D users compared with nonusers (hazard ratio (HR) = 0.84, 95% confidence interval (CI): 0.73, 0.99). Additional adjustment for vitamin D and bisphosphonate use in the previous month reduced the hazard ratio (HR = 0.45, 95% CI: 0.33, 0.63). Results derived from MSMs (HR = 0.44, 95% CI: 0.32, 0.61) and SNAFTMs (HR = 0.45, 95% CI: 0.34, 0.52) were similar. Utilizing MSMs and SNAFTMs to account for time-varying bisphosphonate use did not alter conclusions in this example.

The role of prenatal stress as a pathway to personality disorder: longitudinal birth cohort study.

BACKGROUND: Many studies have reported associations between prenatal stress and the development of psychotic, anxiety and depressive disorders; however, to date no studies have investigated potential associations with personality disorders. AIMS: This study investigated potential associations between exposure to prenatal stress and personality disorder in offspring. METHOD: In a subsample (N = 3626) of a large Finnish birth cohort, we used logistic regression models to examine associations between self-reported maternal stress during pregnancy, collected monthly during antenatal clinic appointments, and personality disorder in offspring. Familial and outcome information were obtained by linking data from the Finnish Hospital Discharge Register and the Finnish Population Register. RESULTS: Compared with those unexposed, children exposed to any maternal stress during gestation had three times the odds of developing a personality disorder (odds ratio 2.76, 95% CI 1.59-4.80, P = 0.000). Those exposed to moderate stress had three times the odds (odds ratio 3.13, 95% CI 1.42-6.88, P = 0.005) and those exposed to severe stress had seven times the odds (odds ratio 7.06, 95% CI 2.10-23.81, P = 0.002) of developing a personality disorder. These associations remained after adjusting for parental psychiatric history, comorbid psychiatric diagnoses, prenatal smoking and antenatal depression. CONCLUSIONS: Exposure to stress during gestation increases the odds of personality disorder in offspring, independent of other psychiatric disorders. These results suggest the assessment of maternal stress and well-being during pregnancy may be useful in identifying those at greatest risk of developing personality disorder, and highlight the importance of prenatal care for good maternal mental health during pregnancy.

The Effectiveness of α2 Agonists As Sedatives in Pediatric Critical Care: A Propensity Score-Matched Cohort Study.

OBJECTIVES: There is limited evidence supporting the widespread use of α2 agonists (clonidine and dexmedetomidine) in pediatric critical care sedation. This study sought to test the association between the use of α2 agonists and enhanced sedation. DESIGN: A retrospective observational cohort study was conducted. Noninferiority of time adequately sedated (COMFORT Behavior Score 11-16) while mechanically ventilated was assessed. Secondarily, dosing of opioids and benzodiazepines was examined. SETTING: Two tertiary PICUs. PATIENTS: Children were classified into an exposed group, who received an α2 agonist as part of their sedation regimen, and an unexposed group. Groups were matched using propensity score analysis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: One-thousand eighty-five patients were included. The exposed group were adequately sedated 74% (95% CI, 72-75%) of the study time compared with the unexposed group at 70% (95% CI, 67-72%) giving a ratio of 1.06 (95% CI, 1.02-1.10) and a noninferior time adequately sedated. A decrease in time oversedated was observed with 8.1% (95% CI, 4.3-11.9%) less time classified as oversedated in the exposed group. Reduction in morphine use of 0.25 µg/kg/hr (95% CI, -0.68 to 1.18 µg/kg/hr) was not statistically significant. Midazolam use did not decrease and was statistically higher. CONCLUSIONS: Use of α2 agonists was associated with similar time adequately sedated as a matched unexposed group although no reduction in morphine or benzodiazepine coadministration was observed. There was a shift toward lighter sedation with α2 agonist use.

Canonical Causal Diagrams to Guide the Treatment of Missing Data in Epidemiologic Studies.

With incomplete data, the "missing at random" (MAR) assumption is widely understood to enable unbiased estimation with appropriate methods. While the need to assess the plausibility of MAR and to perform sensitivity analyses considering "missing not at random" (MNAR) scenarios has been emphasized, the practical difficulty of these tasks is rarely acknowledged. With multivariable missingness, what MAR means is difficult to grasp, and in many MNAR scenarios unbiased estimation is possible using methods commonly associated with MAR. Directed acyclic graphs (DAGs) have been proposed as an alternative framework for specifying practically accessible assumptions beyond the MAR-MNAR dichotomy. However, there is currently no general algorithm for deciding how to handle the missing data given a specific DAG. Here we construct "canonical" DAGs capturing typical missingness mechanisms in epidemiologic studies with incomplete data on exposure, outcome, and confounding factors. For each DAG, we determine whether common target parameters are "recoverable," meaning that they can be expressed as functions of the available data distribution and thus estimated consistently, or whether sensitivity analyses are necessary. We investigate the performance of available-case and multiple-imputation procedures. Using data from waves 1-3 of the Longitudinal Study of Australian Children (2004-2008), we illustrate how our findings can guide the treatment of missing data in point-exposure studies.

Socio-economic gradients in prevalent tuberculosis in Zambia and the Western Cape of South Africa.

OBJECTIVE: To describe the associations between socio-economic position and prevalent tuberculosis in the 2010 ZAMSTAR Tuberculosis Prevalence Survey, one of the first large tuberculosis prevalence surveys in Southern Africa in the HIV era. METHODS: The main analyses used data on 34 446 individuals in Zambia and 30 017 individuals in South Africa with evaluable tuberculosis culture results. Logistic regression was used to estimate adjusted odds ratios for prevalent TB by two measures of socio-economic position: household wealth, derived from data on assets using principal components analysis, and individual educational attainment. Mediation analysis was used to evaluate potential mechanisms for the observed social gradients. RESULTS: The quartile with highest household wealth index in Zambia and South Africa had, respectively, 0.55 (95% CI 0.33-0.92) times and 0.70 (95% CI 0.54-0.93) times the adjusted odds of prevalent TB of the bottom quartile. College or university-educated individuals in Zambia and South Africa had, respectively, 0.25 (95% CI 0.12-0.54) and 0.42 (95% CI 0.25-0.70) times the adjusted odds of prevalent TB of individuals who had received only primary education. We found little evidence that these associations were mediated via several key proximal risk factors for TB, including HIV status. CONCLUSION: These data suggest that social determinants of TB remain important even in the context of generalised HIV epidemics.

Analyses of Sensitivity to the Missing-at-Random Assumption Using Multiple Imputation With Delta Adjustment: Application to a Tuberculosis/HIV Prevalence Survey With Incomplete HIV-Status Data.

Multiple imputation with delta adjustment provides a flexible and transparent means to impute univariate missing data under general missing-not-at-random mechanisms. This facilitates the conduct of analyses assessing sensitivity to the missing-at-random (MAR) assumption. We review the delta-adjustment procedure and demonstrate how it can be used to assess sensitivity to departures from MAR, both when estimating the prevalence of a partially observed outcome and when performing parametric causal mediation analyses with a partially observed mediator. We illustrate the approach using data from 34,446 respondents to a tuberculosis and human immunodeficiency virus (HIV) prevalence survey that was conducted as part of the Zambia-South Africa TB and AIDS Reduction Study (2006-2010). In this study, information on partially observed HIV serological values was supplemented by additional information on self-reported HIV status. We present results from 2 types of sensitivity analysis: The first assumed that the degree of departure from MAR was the same for all individuals with missing HIV serological values; the second assumed that the degree of departure from MAR varied according to an individual's self-reported HIV status. Our analyses demonstrate that multiple imputation offers a principled approach by which to incorporate auxiliary information on self-reported HIV status into analyses based on partially observed HIV serological values.

On the joint use of propensity and prognostic scores in estimation of the average treatment effect on the treated: a simulation study.

Propensity and prognostic score methods seek to improve the quality of causal inference in non-randomized or observational studies by replicating the conditions found in a controlled experiment, at least with respect to observed characteristics. Propensity scores model receipt of the treatment of interest; prognostic scores model the potential outcome under a single treatment condition. While the popularity of propensity score methods continues to grow, prognostic score methods and methods combining propensity and prognostic scores have thus far received little attention. To this end, we performed a simulation study that compared subclassification and full matching on a single estimated propensity or prognostic score with three approaches combining the estimated propensity and prognostic scores: full matching on a Mahalanobis distance combining the estimated propensity and prognostic scores (FULL-MAHAL); full matching on the estimated prognostic propensity score within propensity score calipers (FULL-PGPPTY); and subclassification on an estimated propensity and prognostic score grid with 5 × 5 subclasses (SUBCLASS(5*5)). We considered settings in which one, both, or neither score model was misspecified. The data generating mechanisms varied in the degree of linearity and additivity in the true treatment assignment and outcome models. FULL-MAHAL and FULL-PGPPTY exhibited strong to superior performance in root mean square error terms across all simulation settings and scenarios. Methods combining propensity and prognostic scores were no less robust to model misspecification than single-score methods even when both score models were incorrectly specified. Our findings support the joint use of propensity and prognostic scores in estimation of the average treatment effect on the treated.

Systematic Review and Meta-analysis: Psychosis Risk in Children and Adolescents With an At-Risk Mental State.

OBJECTIVE: The "At Risk Mental State" (ARMS) approach to psychosis, also called "Clinical/Ultra High Risk," has had a major impact on psychosis services internationally. Despite well-established developmental differences in the prevalence and expression of psychotic symptoms from childhood into adulthood, there has been no systematic review of psychosis transitions specifically in children and adolescents up to age of 18 years. Evidence for this age group is crucial for developmentally appropriate clinical decisions by child and adolescent psychiatrists. METHOD: Systematic review and meta-analysis of psychosis risk among children diagnosed with ARMS up to age 18 years, with pooled transition rates after 1-year, 2-year and ≥5-year follow-up. RESULTS: We retrieved 1,107 records and identified 16 articles from 9 studies reporting transition rates on 436 individuals with ARMS aged 9 to 18 years. The pooled transition rate to psychosis at 1 year was 9.5% (95% CI = 5.5%-14.2%, 7 studies included), at 2-years 12.1% (95% CI = 6.7%-18.6%, 4 studies included), and at ≥5 years 16.1% (95% CI = 5.6%-30.0%, 4 studies included). We did not find evidence that the diagnosis of ARMS was associated with increased risk of psychosis once risk-enriching recruitment strategies were taken into account. CONCLUSION: At 5-year follow-up, 1 in 6 youths diagnosed with an ARMS had transitioned to psychosis, but we did not find evidence that this risk was related to ARMS diagnosis as opposed to sampling/recruitment strategies. Our findings indicate a need for caution in applying ARMS methodology to children and adolescents. and highlight the need for developmentally sensitive approaches when considering psychosis risk.

Potential for prediction of psychosis and bipolar disorder in Child and Adolescent Mental Health Services: a longitudinal register study of all people born in Finland in 1987.

Current strategies to predict psychosis identify only a small proportion of individuals at risk. Additional strategies are needed to increase capacity for pre-diction and prevention of serious mental illness, ideally during childhood and adolescence. One possible approach would be to investigate systems in which psychosis risk factors are concentrated during childhood. One notable such system is represented by Child and Adolescent Mental Health Services (CAMHS). Although psychotic disorders are uncommon in CAMHS, many risk factors for psychosis are highly prevalent in young people who enter this system. We hypothesized, therefore, that youth attending CAMHS would be a high-risk group for psychosis if followed into adulthood and, furthermore, that CAMHS systems would capture a substantial proportion of future psychosis cases. We constructed a total population cohort study of all Finns born in 1987 (N=55,875), linking together extensive register data on health care contacts from birth through age 28 years. We identified all individuals diagnosed with a psychotic or bipolar disorder by age 28 (N=1,785). The risk of psychosis/bipolar disorder by age 28 years was 1.8% for individuals who had not attended CAMHS during childhood or adolescence, whereas it was 12.8% for those with a history of any outpatient CAMHS contact (odds ratio, OR=7.9, 95% CI: 7.2-8.7). Furthermore, the risk of psychosis/bipolar disorder by age 28 years was 2.3% for individuals without a history of inpatient CAMHS admission, whereas it was 24.0% for those with a history of inpatient CAMHS admission (OR=13.3, 95% CI: 11.9-14.9), and 36.5% for those with a history of inpatient CAMHS admission in adolescence (age 13-17 years) (OR=24.2, 95% CI: 21.2-27.6). Individuals who attended CAMHS but received no mental disorder diagnosis had an equally high risk of subsequently developing a psychosis/bipolar disorder as individuals who did receive a diagnosis (OR=0.9, 99.5% CI: 0.7-1.1). Compared to other CAMHS attendees, individuals who developed psychosis or bipolar disorder were more likely to have had an initial CAMHS diagnosis of depressive or other mood disorder (OR=2.3, 99.5% CI: 1.6-3.0) and disruptive behaviour disorder (OR=1.7, 99.5% CI: 1.2-2.5). Of all psychosis/bipolar diagnoses by age 28 years, 50.2% occurred in individuals who had, at some point in childhood or adolescence, attended CAMHS, indicating that CAMHS represent not only a high-risk but also a high-capacity system for prediction of psychosis/bipolar disorder. These findings suggest an enormous, untapped potential for large-scale psychosis/bipolar disorder prediction and prevention research within existing specialist CAMHS.

Childhood temperament and its association with adult psychiatric disorders in a prospective cohort study.

BACKGROUND: Childhood temperament and its component factors have previously been shown to be associated with depression and anxiety disorders in later life. Studies have also suggested possible links between childhood temperament and later psychosis. AIMS: To investigate the association between childhood temperament and its individual component factors, measured at age 5, and later psychiatric disorders. METHOD: Using a sample from a Finnish birth cohort (N = 1014), we used logistic regression models to examine associations between maternal reported childhood temperament at age 5, and later psychiatric diagnosis, ascertained through linkage with the Finnish Hospital Discharge Register (FHDR). RESULTS: Individuals with a childhood temperament rated as difficult at age 5 had almost 5-times the odds of developing a psychotic disorder in adulthood compared to those with a temperament rated as average by their mothers (OR = 4.91, 95% CI = 1.51-15.91). The individual temperament factors of approach withdrawal, adaptability and quality of mood were each independently associated with later psychotic disorder while the factors of regularity and threshold were associated with increased risk for mood disorders. CONCLUSIONS: This study reports association between early childhood temperament and risk for psychosis and suggests that early childhood temperament may be a good target for early intervention to reduce the risk of psychiatric disorders.

Evaluation of the effect of insulin sensitivity-enhancing lifestyle- and dietary-related adjuncts on antidepressant treatment response: protocol for a systematic review and meta-analysis.

BACKGROUND: Depression is the leading cause of disability worldwide and is known to be associated with insulin resistance (IR). Insulin resistance worsens the symptoms of depression and reduces the effectiveness of antidepressant medications in some depressed patients. Many studies have assessed the effect of adjunctive exercise, vitamin D supplementation, zinc supplementation, magnesium, probiotics, unsaturated fatty acids, and hygienic-dietary recommendations (sleep hygiene, healthy diet, physical activity, and sunlight exposure, combined or singly used), individually, on antidepressant treatment response. However, despite the reported insulin sensitivity-enhancing potential of these adjuncts, no systematic review has collectively analysed their antidepressant effect with regards to insulin sensitivity. METHODS/DESIGN: In this systematic review, we will analyse the effect of the above-stated adjuncts on antidepressant treatment response (primary outcome) in comparison with treatment as usual with or without adjunctive placebo after identifying the relevant trials from a systematic literature search. Randomised controlled trials involving clinically depressed patients with diagnosis of major depressive, dysthymic or bipolar disorder will be considered. Changes in insulin sensitivity parameters, following treatment, will also be analysed as the secondary outcome. Effect estimates of the included trials will be combined using random-effects meta-analysis, while addressing risk of bias issues. Any significant heterogeneity between studies will be explored using sensitivity and subgroup analyses. DISCUSSION: The findings of this review will contribute to the evidence base regarding the utility of non-pharmacological insulin-sensitising treatments in enhancing conventional antidepressant treatment response.

Effectiveness of α2agonists for sedation in paediatric critical care: study protocol for a retrospective cohort observational study.

INTRODUCTION: Mechanically ventilated children in paediatric intensive care units are commonly administered analgesics and sedative agents to minimise pain and distress and facilitate cooperation with medical interventions. Opioids and benzodiazepines are the most common analgesic and sedative agents but have safety concerns. The α2 agonists clonidine and dexmedetomidine are alternative sedatives in use despite neither having robust evidence to support their use. Studies evaluating effectiveness of α2 agonists to date have not focused on sedation-based outcomes instead focusing on opioid-sparing properties and ventilation outcomes. The aim of this study is to evaluate if an opioid-based sedation regimen, with an α2 agonist adjunct (clonidine or dexmedetomidine), produces a non-inferior proportion of time adequately sedated compared with a control group without an α2 agonist adjunct, while conferring potential additional benefits such as reduced opioid administration and less exposure to potential additional agents such as benzodiazepines. METHODS AND ANALYSIS: We will conduct a retrospective cohort study in two Irish paediatric intensive care units using clinical information on patient characteristics, sedation scores and drug use. Eligible children admitted between January 2014 and June 2016 who were mechanically ventilated and received an opioid infusion will be included. Patients will be categorised into two exposure categories (received an α2 agonist or did not receive an α2 agonist) and the time adequately sedated (measured using the COMFORT Behaviour Score) will be calculated using interpolation of nursing sedation scores at each recorded time point. At least 150 per group is planned for inclusion to ensure adequate study power. Propensity score matching will be used in analysis to account for potential confounding by indication. ETHICS AND DISSEMINATION: The study has been approved by the ethics committees of both hospitals. Dissemination will occur via local, national and international presentations for academic and healthcare audiences as well as through peer reviewed publications.

Germline MC1R status influences somatic mutation burden in melanoma.

The major genetic determinants of cutaneous melanoma risk in the general population are disruptive variants (R alleles) in the melanocortin 1 receptor (MC1R) gene. These alleles are also linked to red hair, freckling, and sun sensitivity, all of which are known melanoma phenotypic risk factors. Here we report that in melanomas and for somatic C>T mutations, a signature linked to sun exposure, the expected single-nucleotide variant count associated with the presence of an R allele is estimated to be 42% (95% CI, 15-76%) higher than that among persons without an R allele. This figure is comparable to the expected mutational burden associated with an additional 21 years of age. We also find significant and similar enrichment of non-C>T mutation classes supporting a role for additional mutagenic processes in melanoma development in individuals carrying R alleles.

Prognostic score-based balance measures can be a useful diagnostic for propensity score methods in comparative effectiveness research.

OBJECTIVE: Examining covariate balance is the prescribed method for determining the degree to which propensity score methods should be successful at reducing bias. This study assessed the performance of various balance measures, including a proposed balance measure based on the prognostic score (similar to a disease risk score), to determine which balance measures best correlate with bias in the treatment effect estimate. STUDY DESIGN AND SETTING: The correlations of multiple common balance measures with bias in the treatment effect estimate produced by weighting by the odds, subclassification on the propensity score, and full matching on the propensity score were calculated. Simulated data were used, based on realistic data settings. Settings included both continuous and binary covariates and continuous covariates only. RESULTS: The absolute standardized mean difference (ASMD) in prognostic scores, the mean ASMD (in covariates), and the mean t-statistic all had high correlations with bias in the effect estimate. Overall, prognostic scores displayed the highest correlations with bias of all the balance measures considered. Prognostic score measure performance was generally not affected by model misspecification, and the prognostic score measure performed well under a variety of scenarios. CONCLUSION: Researchers should consider using prognostic score-based balance measures for assessing the performance of propensity score methods for reducing bias in nonexperimental studies.