589 research outputs found
A Growth Curve Model with Fractional Polynomials for Analysing Incomplete Time-Course Data in Microarray Gene Expression Studies
Identifying the various gene expression response patterns is a challenging issue in expression microarray time-course experiments. Due to heterogeneity in the regulatory reaction among thousands of genes tested, it is impossible to manually characterize a parametric form for each of the time-course pattern in a gene by gene manner. We introduce a growth curve model with fractional polynomials to automatically capture the various time-dependent expression patterns and meanwhile efficiently handle missing values due to incomplete observations. For each gene, our procedure compares the performances among fractional polynomial models with power terms from a set of fixed values that offer a wide range of curve shapes and suggests a best fitting model. After a limited simulation study, the model has been applied to our human in vivo irritated epidermis data with missing observations to investigate time-dependent transcriptional responses to a chemical irritant. Our method was able to identify the various nonlinear time-course expression trajectories. The integration of growth curves with fractional polynomials provides a flexible way to model different time-course patterns together with model selection and significant gene identification strategies that can be applied in microarray-based time-course gene expression experiments with missing observations
Psychotic experiences are associated with health anxiety and functional somatic symptoms in preadolescence
Background: Health anxiety (HA) is an increasing public health problem related to increased health service costs, and associated with functional somatic symptoms (FSS) and considerable personal suffering. Abnormal bodily experiences which may resemble HA and FSS are common in psychotic disorders, but a potential link between HA and psychosis vulnerability in childhood is largely unexplored. The current study estimates the association between subclinical psychotic experiences (PE) and HA and FSS in a general population cohort of preadolescents. Methods: The study population consisted of 1,572 11–12-year-old children from the Copenhagen Child Cohort 2000. PE were comprehensibly assessed as either present or not present using the Kiddie Schedule of Affective Disorders and Schizophrenia psychosis section. HA and FSS were assessed by self-report on validated questionnaires. Additional variables on general psychopathology, puberty, and chronic somatic illness were also obtained. Results: Psychotic experiences were associated with the top 10% high scores of HA (Odds Ratio (OR) 3.2; 95% CI: 2.1–4.8) and FSS (OR 4.6; 95% CI: 3.1–6.9) in univariate analyses. After mutual adjustment, the association was reduced to (HA: OR 2.3; 95% CI: 1.5–3.5; FSS: OR 3.7; 95% CI: 2.4–4.7), suggesting interdependence. Further adjustment for potential confounders and general psychopathology only reduced the associations slightly: HA OR 2.2 (95% CI: 1.4–3.4); FSS OR 3.3 (95% CI: 2.1–5.2). Secondary analyses of subdimensions of HA showed that PE were associated with fears (OR 3.0; 95% CI: 2.0–4.6) and daily impact of HA symptoms (OR 5.0; 95% CI: 3.4–7.5), but not help seeking (OR 1.2; 95% CI: 0.7–2.1). Conclusions: This is the first study to investigate the associations between PE and HA and FSS, respectively. PE were significantly associated with HA and FSS over and above general psychopathology in preadolescence. Individuals with PE expressed high levels of health-related fears and daily impact, but no corresponding help-seeking behavior
The predictive validity of the Strengths and Difficulties Questionnaire in preschool age to identify mental disorders in preadolescence
The Strengths and Difficulties Questionnaire (SDQ) is a brief, widely used instrument to screen for mental health problems in children and adolescents. The SDQ predictive algorithms developed for the SDQ, synthesize information from multiple informants regarding psychiatric symptoms and their impact on daily life. This study aimed to explore the validity of the SDQ predictive algorithms used in preschool age to predict mental disorders in preadolescence. The study population comprises 1176 children from the Copenhagen Child Cohort 2000 (CCC2000) assessed at age 5-7 years by the SDQ and reassessed at 11-12 years with the Development and Well Being Assessment (DAWBA) for evaluation of ICD-10 mental disorders. Odds Ratios (ORs), sensitivities, specificities, positive predictive values (PPVs) and negative predictive values (NPVs) were calculated for the SDQ predictive algorithms regarding ICD-10 diagnoses of hyperkinetic-inattentive-, behavioural- and emotional disorders. Significant ORs ranging from 2.3-36.5 were found for the SDQ predictive algorithms in relation to the corresponding diagnoses. The highest ORs were found for hyperkinetic and inattentive disorders, and the lowest for emotional disorders. Sensitivities ranging from 4.5-47.4, specificities ranging from 83.0-99.5, PPVs ranging from 5.0-45.5 and NPVs ranging from 90.6-99.0 were found for the SDQ predictive algorithms in relation to the diagnoses. The results support that the SDQ predictive algorithms are useful for screening at preschool-age to identify children at an increased risk of mental disorders in preadolescence. However, early screening with the SDQ predictive algorithms cannot stand alone, and repeated assessments of children are needed to identify, especially internalizing, mental health problems
Bivalirudin started during emergency transport for primary PCI.
BACKGROUND: Bivalirudin, as compared with heparin and glycoprotein IIb/IIIa inhibitors, has been shown to reduce rates of bleeding and death in patients undergoing primary percutaneous coronary intervention (PCI). Whether these benefits persist in contemporary practice characterized by prehospital initiation of treatment, optional use of glycoprotein IIb/IIIa inhibitors and novel P2Y12 inhibitors, and radial-artery PCI access use is unknown. METHODS: We randomly assigned 2218 patients with ST-segment elevation myocardial infarction (STEMI) who were being transported for primary PCI to receive either bivalirudin or unfractionated or low-molecular-weight heparin with optional glycoprotein IIb/IIIa inhibitors (control group). The primary outcome at 30 days was a composite of death or major bleeding not associated with coronary-artery bypass grafting (CABG), and the principal secondary outcome was a composite of death, reinfarction, or non-CABG major bleeding. RESULTS: Bivalirudin, as compared with the control intervention, reduced the risk of the primary outcome (5.1% vs. 8.5%; relative risk, 0.60; 95% confidence interval [CI], 0.43 to 0.82; P=0.001) and the principal secondary outcome (6.6% vs. 9.2%; relative risk, 0.72; 95% CI, 0.54 to 0.96; P=0.02). Bivalirudin also reduced the risk of major bleeding (2.6% vs. 6.0%; relative risk, 0.43; 95% CI, 0.28 to 0.66; P<0.001). The risk of acute stent thrombosis was higher with bivalirudin (1.1% vs. 0.2%; relative risk, 6.11; 95% CI, 1.37 to 27.24; P=0.007). There was no significant difference in rates of death (2.9% vs. 3.1%) or reinfarction (1.7% vs. 0.9%). Results were consistent across subgroups of patients. CONCLUSIONS: Bivalirudin, started during transport for primary PCI, improved 30-day clinical outcomes with a reduction in major bleeding but with an increase in acute stent thrombosis. (Funded by the Medicines Company; EUROMAX ClinicalTrials.gov number, NCT01087723.)
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