Admixture analysis of age at onset in schizophrenia: evidence of three subgroups in a first-episode sample.

OBJECTIVE: The objective was to assess the presence of different subgroups, via age-at-onset (AAO) analysis, in a schizophrenia population consecutively recruited through an Early Psychosis Service in London, Canada. METHOD: Admixture analysis was applied in order to identify a model of separate normal distribution of AAO characterized by different means, variances and population proportions to allow for evaluation of different subgroups in a sample of 187 unrelated patients with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, diagnosis of schizophrenia. RESULTS: The best-fitting model suggested three subgroups with means and standard deviations of 16.8 ± 1.9, 22.3 ± 2.1 and 32.7 ± 5.9 years comprising 41%, 30% and 29% of the schizophrenia sample, respectively. These three subgroups were categorized as early, intermediate and late onset with cutoffs determined by admixture analysis to be 19 and 26 years of age, respectively. In our investigation, the definition of early-onset schizophrenia is the main outcome. We considered the clinical variables mainly related to the heritability and neurobiology of schizophrenia. Single status was strongly associated with early onset (P<.001). The male gender (P=.023), as well as a history of drug abuse (P=.004), was significantly associated with early onset. Interestingly, lower academic achievement was also associated with early-onset schizophrenia (P<.001). CONCLUSION: Overall, our study showed that a typical early-onset schizophrenia patient is more likely to be a single male, with a history of drug abuse and birth complications, and lower academic achievement as compared to the late-onset subgroup.

Comparative assessment of 2-dimensional echocardiography vs cardiac magnetic resonance imaging in measuring left ventricular mass in patients with and without end-stage renal disease.

BACKGROUND: While echocardiography (ECHO)-measured left ventricular mass (LVM) predicts adverse cardiovascular events that are common in hemodialysis (HD) recipients, cardiac magnetic resonance imaging (CMR) is now considered the reference standard for determination of LVM. This study aimed to evaluate concordance between LVM measurements across ECHO and CMR among chronic HD recipients and matched controls. METHODS: A single-centre, cross-sectional study of 41 chronic HD patients and 41 matched controls with normal kidney function was performed to compare LVM measurements and left ventricular hypertrophy (LVH) designation by ECHO and CMR. RESULTS: In both groups, ECHO, compared with CMR, overestimated LVM. Bland-Altman analysis demonstrated wider agreement limits in LVM measurements by ECHO and CMR in the chronic HD group (mean difference, 60.8 g; limits -23 g to 144.6 g) than in the group with normal renal function (mean difference, 51.4 g; limits -10.5 g to 113.3 g). LVH prevalence by ECHO and CMR in the chronic HD group was 37.5% and 22.5%, respectively, while 17.5% and 12.5% had LVH by ECHO and CMR, respectively, in the normal kidney function group. Intermodality agreement in the designation of LVH was modest in the chronic HD patients (κ = 0.42, P = 0.005) but strong (κ = 0.81, P < 0.001) in the patients with preserved kidney function. Agreement was strong in assessing LVH by ECHO and CMR only in those with normal kidney function. CONCLUSIONS: Our results suggest that the limitations of LVM measurement by ECHO may be more pronounced in patients receiving HD, and provide additional support for the use of CMR in research and clinical practice when rigourous assessment of LVM is essential.