Type-2 diabetes mellitus in schizophrenia: Increased prevalence and major risk factor of excess mortality in a naturalistic 7-year follow-up

Schoepf, Dieter; Potluri, Rahul; Uppal, Hardeep; Natalwala, Ammar; Narendran, Parth; Heun, Reinhard

doi:10.1016/j.eurpsy.2011.02.009

Cited by 76 publications

(59 citation statements)

References 57 publications

(75 reference statements)

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“…Type 2 diabetes was also more frequent in comparison with all hospitalised patients. Type 2 diabetes was the most common disease in schizophrenia patients who died during 7-year observations, representing 24% of this group, versus 10.5% of deaths in the control group, with RR=2.2 (Schoepf et al 2012). In another study (2000)(2001)(2002)(2003)(2004)(2005), the risk (HR) for patients diagnosed with schizophrenia and diabetes was 1.52 (95%CI 1.17-1.97) versus patients with diabetes only (regardless of diabetes type, after adjustment for age of diabetes diagnosis, gender, smoking status, deprivation, obesity and the use of statins) (Vinogradova et al 2010).…”

Section: Diabetesmentioning

confidence: 99%

“…In other studies on schizophrenia cohorts represented country (Vinogradova et al 2010, Tenback et al 2012, region or populations of selected hospitals (Høye et al 2011, Schoepf et al 2012. Apart from schizophrenia, they also analysed mortality in people diagnosed with: substance abuse (Chang et …”

Section: Study Characteristicsmentioning

confidence: 99%

“…The studies used national, local, hospital (Schoepf et al 2012), university (Høye et al 2011) and insurance agency (Tenback et al 2012) medical data records. An access to data from various records for the same patients was possible due to ID numbers and record linkage systems.…”

Section: Medical Data Recordsmentioning

confidence: 99%

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Causes of Mortality in Schizophrenia: An Updated Review of European Studies

et al. 2017

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Section: Diabetesmentioning

confidence: 99%

Section: Study Characteristicsmentioning

confidence: 99%

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Causes of Mortality in Schizophrenia: An Updated Review of European Studies

et al. 2017

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“…PNRC2 is a nuclear receptor coactivator that regulates energy expenditure and adiposity in mice (Zhou et al 2008), which are the keys to understand obesity, insulin resistance, and type 2 diabetes. VIPR2, DGCR6 and PRODH are known to be significantly associated with schizophrenia (Vacic et al 2011;Welsh et al 2011;Liu et al 2002), a mental disorder that is associated with decreased risk of type 1 diabetes (Juvonen et al 2007) and increased risk of type 2 diabetes (Schoepf et al 2012).…”

Section: Type 1 Diabetes Resequencing Datamentioning

confidence: 99%

Dynamic Bayesian Testing of Sets of Variants in Complex Diseases

Ghosh

Hákonarson

2014

Genetics

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Rare genetic variants have recently been studied for genome-wide associations with human complex diseases. Existing rare variant methods are based on the hypothesis-testing framework that predefined variant sets need to be tested separately. The power of those methods is contingent upon accurate selection of variants for testing, and frequently, common variants are left out for separate testing. In this article, we present a novel Bayesian method for simultaneous testing of all genome-wide variants across the whole frequency range. The method allows for much more flexible grouping of variants and dynamically combines them for joint testing. The method accounts for correlation among variant sets, such that only direct associations with the disease are reported, whereas indirect associations due to linkage disequilibrium are not. Consequently, the method can obtain much improved power and flexibility and simultaneously pinpoint multiple disease variants with high resolution. Additional covariates of categorical, discrete, and continuous values can also be added. We compared our method with seven existing categories of approaches for rare variant mapping. We demonstrate that our method achieves similar power to the best methods available to date when testing very rare variants in small SNP sets. When moderately rare or common variants are included, or when testing a large collection of variants, however, our method significantly outperforms all existing methods evaluated in this study. We further demonstrate the power and the usage of our method in a whole-genome resequencing study of type 1 diabetes.

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“…A mortality gap of over 10 years exists between those with and without psychiatric disorders [14]. Type 2 diabetes is associated with a two-fold increase in mortality in Schizophrenia [15]. A Danish study compared the overall and cause specific mortality in individuals with serious mental illness and diabetes and those of the general population.…”

Section: Introductionmentioning

confidence: 99%

Lester Adaptation of Cardio Metabolic Measurements: An Inpatient Interventional Framework for Women with Mental Illness

M¹,

Lotfy²,

L³

2017

Endocrinol Metab Syndr

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Aims of the study: To assess the prevalence of metabolic syndrome and implement a framework for screening and management of cardio metabolic risks in women on psychiatric in-patient wards.Background: An estimated 29-48% of psychiatric in-patients have metabolic syndrome. Severe mood disorders and psychotic illnesses are independent risk factors. 20-25% of the world's adult population have metabolic syndrome and they are twice as likely to die from and three times as likely to have a heart attack or stroke compared with people without the syndrome. This study gives an overview of the application of Lester Tool on busy in-patient units and interventional approaches adapted by the team.

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Type-2 diabetes mellitus in schizophrenia: Increased prevalence and major risk factor of excess mortality in a naturalistic 7-year follow-up

Cited by 76 publications

References 57 publications

Causes of Mortality in Schizophrenia: An Updated Review of European Studies

Causes of Mortality in Schizophrenia: An Updated Review of European Studies

Dynamic Bayesian Testing of Sets of Variants in Complex Diseases

Lester Adaptation of Cardio Metabolic Measurements: An Inpatient Interventional Framework for Women with Mental Illness

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