Testosterone Trajectories and Reference Ranges in a Large Longitudinal Sample of Male Adolescents

Pubertal dynamics plays an important role in physical and psychological development of children and adolescents. We aim to provide reference ranges of plasma testosterone in a large longitudinal sample. Furthermore, we describe a measure of testosterone trajectories during adolescence that can be used in future investigations of development.We carried out longitudinal measurements of plasma testosterone in 2,216 samples obtained from 513 males (9 to 17 years of age) from the Avon Longitudinal Study of Parents and Children. We used integration of a model fitted to each participant's testosterone trajectory to calculate a measure of average exposure to testosterone over adolescence. We pooled these data with corresponding values reported in the literature to provide a reference range of testosterone levels in males between the ages of 6 and 19 years.The average values of total testosterone in the ALSPAC sample range from 0.82 nmol/L (Standard Deviation [SD]: 0.09) at 9 years of age to 16.5 (SD: 2.65) nmol/L at 17 years of age; these values are congruent with other reports in the literature. The average exposure to testosterone is associated with different features of testosterone trajectories such as Peak Testosterone Change, Age at Peak Testosterone Change, and Testosterone at 17 years of age as well as the timing of the growth spurt during puberty.The average exposure to testosterone is a useful measure for future investigations using testosterone trajectories to examine pubertal dynamics

Bolus-Infusion Delays of Alteplase during Thrombolysis in Acute Ischaemic Stroke and Functional Outcome at 3 Months

Background. The efficacy of alteplase in acute ischaemic stroke (AIS) is highly time dependent. Hence, alteplase is administered as soon as possible with a bolus followed by an infusion. Delays between bolus and infusion may occur, but the extent of these delays and the impact on outcome are unclear. Aims. We investigated the extent of bolus-infusion delays and the relationship between delays and stroke outcome. Method. We reviewed medical records of 276 patients who received alteplase for AIS at our centre between April, 2008, and June, 2013. Complete demographic and clinical data including 3-month modified Rankin Score (mRS) from 229 patients were analysed comparing delays of 0–8 and >8 minutes. Results. Overall mean (SD) bolus-infusion delay was 9 (7) minutes. Baseline characteristics were similar apart from more severe strokes in delays >8 minutes. Three-month outcomes were not significantly different although delays >8 minutes had lower functional independence rate (mRS 0-1: 23.1% versus 28.1%; adjusted OR 1.2 (95% CI 0.6 to 2.4, P=0.68)) and higher mortality rate (18% versus 11%, OR 1.0, 95% CI 0.6 to 1.7, P=0.95). Conclusions. In this single centre series, bolus-infusion delays of alteplase in AIS were common and no effect of bolus-infusion delays on independence and mortality was found

Analysis of trends in adolescent suicides and accidental deaths in England and Wales, 1972–2011

Background Previous analyses of adolescent suicides in England and Wales have focused on short time periods. Aims To investigate trends in suicide and accidental deaths in adolescents between 1972 and 2011. Method Time trend analysis of rates of suicides and deaths from accidental poisoning and hanging in 10- to 19-year-olds by age, gender and deprivation. Rate ratios were estimated for 1982–1991, 1992–2001 and 2002–2011 with 1972–1981 as comparator. Results Suicide rates have remained stable in 10- to 14-year-olds, with strong evidence for a reduction in accidental deaths. In males aged 15–19, suicide rates peaked in 2001 before declining. Suicide by hanging is the most common method of suicide. Rates were higher in males and in 15- to 19-year-olds living in more deprived areas. Conclusions Suicide rates in adolescents are at their lowest since the early 1970s with no clear evidence that changes in coroners' practices underlie this trend

Retrospective cohort study evaluating clinical, biochemical and pharmacological prognostic factors for prostate cancer progression using primary care data

Objectives To confirm the association of previously reported prognostic factors with future progression of localised prostate cancer using primary care data and identify new potential prognostic factors for further assessment in prognostic model development and validation.Design Retrospective cohort study, employing Cox proportional hazards regression controlling for age, prostate specific antigen (PSA), and Gleason score, was stratified by diagnostic stage.Setting Primary care in England.Participants Males with localised prostate cancer diagnosedbetween 01/01/1987 and 31/12/2016 within the Clinical Practice ResearchDatalink database, with linked data from the National Cancer Registration andAnalysis Service and Office for National Statistics.Primary and secondary outcomes Primary outcome measure was prostate cancer mortality. Secondary outcome measures were all-cause mortality and commencing systemic therapy. Up-staging after diagnosis was not used as a secondary outcome owing to significant missing data.Results 10 901 men (mean age 74.38±9.03 years) with localised prostate cancer were followed up for a mean of 14.12 (±6.36) years. 2331 (21.38%) men underwent systemic therapy and 3450 (31.65%) died, including 1250 (11.47%) from prostate cancer. Factors associated with an increased risk of prostate cancer mortality included age; high PSA; current or ex-smoker; ischaemic heart disease; high C reactive protein; high ferritin; low haemoglobin; high blood glucose and low albumin.Conclusions This study identified several new potential prognostic factors for prostate cancer progression, as well as confirming some known prognostic factors, in an independent primary care data set. Further research is needed to develop and validate a prognostic model for prostate cancer progression

Parkinson's disease subtypes in the Oxford Parkinson disease centre (OPDC) discovery cohort

Background: Within Parkinson’s there is a spectrum of clinical features at presentation which may represent sub-types of the disease. However there is no widely accepted consensus of how best to group patients. Objective: Use a data-driven approach to unravel any heterogeneity in the Parkinson’s phenotype in a well-characterised, population-based incidence cohort. Methods: 769 consecutive patients, with mean disease duration of 1.3 years, were assessed using a broad range of motor, cognitive and non-motor metrics. Multiple imputation was carried out using the chained equations approach to deal with missing data. We used an exploratory and then a confirmatory factor analysis to determine suitable domains to include within our cluster analysis. K-means cluster analysis of the factor scores and all the variables not loading into a factor was used to determine phenotypic subgroups. Results: Our factor analysis found three important factors that were characterised by: psychological well-being features; non-tremor motor features, such as posture and rigidity; and cognitive features. Our subsequent five cluster model identified groups characterised by (1) mild motor and non-motor disease (25.4%), (2) poor posture and cognition (23.3%), (3) severe tremor (20.8%), (4) poor psychological well-being, RBD and sleep (18.9%), and (5) severe motor and non-motor disease with poor psychological well-being (11.7%). Conclusion: Our approach identified several Parkinson’s phenotypic sub-groups driven by largely dopaminergic-resistant features (RBD, impaired cognition and posture, poor psychological well-being) that, in addition to dopaminergic-responsive motor features may be important for studying the aetiology, progression, and medication response of early Parkinson’s

Estimating the impact of antiretroviral treatment on adult mortality trends in South Africa: A mathematical modelling study

Substantial reductions in adult mortality have been observed in South Africa since the mid-2000s, but there has been no formal evaluation of how much of this decline is attributable to the scale-up of antiretroviral treatment (ART), as previous models have not been calibrated to vital registration data. We developed a deterministic mathematical model to simulate the mortality trends that would have been expected in the absence of ART, and with earlier introduction of ART