Article
Glucose and lipid disturbances after 1 year of antipsychotic treatment in a drug-naïve population.
Department of Psychiatry, Marques de Valdecilla University Hospital, Avda. Valdecilla s/n, 39008, University of Cantabria, Spain.
Schizophrenia Research (impact factor:
4.75).
12/2008;
107(2-3):115-21.
DOI:10.1016/j.schres.2008.09.028
pp.115-21
Source: PubMed
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Citations (0)
- Cited In (3)
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Article: Diffuse abnormality of low to moderately organized white matter in schizophrenia.
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ABSTRACT: Increasing evidence suggests that abnormal white matter is central to the pathophysiology and, potentially, the pathogenesis of schizophrenia (SCZ). The spatial distribution of observed abnormalities and the type of white matter involved remain to be elucidated. Seventeen chronically ill individuals with SCZ and 17 age- and gender-matched controls were studied using a 3T magnetic resonance imaging diffusion tensor imaging protocol designed to examine the abnormalities of white matter by region and by level of architectural infrastructure as assessed by fractional anisotropy (FA) in native space. After assessing whole-brain FA, FA was divided into quartiles, capturing all brain regions with FA values from 0 to 0.25, 0.25 to 0.5, 0.5 to 0.75, and 0.75 to 1.0. Mean whole-brain FA was 4.6% smaller in the SCZ group than in healthy controls. This difference was largely accounted for by FA values from the second quartile (between 0.25 and 0.5). Second quartile FA was decreased in all 130 brain regions of the template in the SCZ group, with the difference reaching statistical significance in 41 regions. Correspondingly, the amount of brain tissue with an FA of ∼0.4 was significantly reduced in the SCZ group, while the amount of brain tissue falling in the lowest quartile of FA was increased. These findings strongly imply a diffuse loss of white matter integrity in SCZ. Our finding that the loss of integrity disproportionately involves white matter of low to moderate organization suggests an approach to the specificity of white matter abnormalities in SCZ based on microstructure rather than spatial distribution.Brain connectivity. 01/2011; 1(6):511-9. -
Article: Metabolic Syndrome and Metabolic Abnormalities in Bipolar Disorder: A Meta-Analysis of Prevalence Rates and Moderators.
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ABSTRACT: OBJECTIVE Patients with bipolar disorder have high levels of cardiovascular disease risk factors. The presence of metabolic syndrome significantly influences future cardiovascular disease morbidity and mortality. The authors sought to clarify the prevalence and moderators of metabolic syndrome in bipolar patients, accounting for subgroup differences. METHOD The authors searched MEDLINE, PsycINFO, EMBASE, and CINAHL through April 2012 for research reporting metabolic syndrome prevalence rates in bipolar patients. Medical subject headings "metabolic syndrome" and "bipolar" were used in the title, abstract, or index term fields. Manual searches were conducted using the reference lists from identified articles. RESULTS The search yielded 81 articles in 37 publications (N=6,983). The overall metabolic syndrome rate was 37.3% (95% confidence interval [CI]=36.1-39.0) using any standardized metabolic syndrome criteria. Compared with general population groups, bipolar patients had higher metabolic syndrome rates (odds ratio=1.98; 95% CI=1.74-2.25). In bipolar patients, older age had a modest effect on the metabolic syndrome rate. The strongest moderator was the region in which the study took place, with the highest rates observed in New Zealand and Australia (64.2% [95% CI=38.3-83.9]) and North America (49.3% [95% CI=29.7-69.3]). Metabolic syndrome was significantly more prevalent in patients currently treated with antipsychotics (45.3% [95% CI=39.6-50.9] than in patients who were antipsychotic free (32.4% [95% CI=27.5-37.4]; odds ratio=1.72 [95% CI=1.24-2.38]). CONCLUSIONS These findings strongly support the claim that patients with bipolar disorder are at high risk for metabolic syndrome and related cardiovascular morbidity and mortality and require regular monitoring and adequate preventive efforts and treatment for cardio-metabolic risk factors. These findings further suggest that the risk of metabolic syndrome is greater in bipolar patients taking prescribed antipsychotic medication.American Journal of Psychiatry 01/2013; · 12.54 Impact Factor -
Article: A positive association between homeostasis model assessment of insulin resistance score and the Trp64Arg polymorphism of the β3-Adrenergic receptor gene in schizophrenia patients in Taiwan.
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ABSTRACT: To investigate the possible association between the Trp64Arg polymorphism of the β3-adrenergic receptor gene and the homeostasis model assessment of insulin resistance (HOMA-IR) index in schizophrenia patients in Taiwan. A total of 203 inpatients who met DSM-IV diagnostic criteria for schizophrenia were recruited from a psychiatry center in Taiwan from September 2002 to August 2003. All patients had been treated with antipsychotics for at least 6 months. The genotyping of the Trp64Arg polymorphism of the β3-adrenergic receptor gene was done by the polymerase chain reaction-restriction fragment length polymorphism method with the restriction enzyme MvaI. The HOMA-IR index was used to indicate the degree of insulin resistance. After adjusting for sex, age, and body mass index status, the association between the HOMA-IR index and the Trp64Arg polymorphism of the β3-adrenergic receptor gene was still positive (regression coefficient = -0.65, P = .033). The polymorphism of the β3-adrenergic receptor gene may be related to the development of insulin resistance in chronic schizophrenia patients in Taiwan.The Primary Care Companion to The Journal of Clinical Psychiatry 01/2010; 12(4).
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Keywords
1 year
antipsychotic medication
antipsychotic treatment
fasting glucose parameters
Fasting glycaemia
fasting lipid parameters
first episode drug-naïve subjects
first episode program
first year
glucose metabolism
HDL cholesterol
LDL cholesterol
lipid parameters
mean values
metabolic adverse effects
pathological values
statistically significant differences
statistically significant increase
total cholesterol
Weight gain
