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Cardiovascular risk prediction models for people with severe mental illness: results from the prediction and management of cardiovascular risk in people with severe mental illnesses (PRIMROSE) research program.

ABSTRACT: People with severe mental illness (SMI), including schizophrenia and bipolar disorder, have excess rates of cardiovascular disease (CVD). Risk prediction models validated for the general population may not accurately estimate cardiovascular risk in this group.To develop and validate a risk model exclusive to predicting CVD events in people with SMI incorporating established cardiovascular risk factors and additional variables.We used anonymous/deidentified data collected between January 1, 1995, and December 31, 2010, from the Health Improvement Network (THIN) to conduct a primary care, prospective cohort and risk score development study in the United Kingdom. Participants included 38,824 people with a diagnosis of SMI (schizophrenia, bipolar disorder, or other nonorganic psychosis) aged 30 to 90 years. During a median follow-up of 5.6 years, 2324 CVD events (6.0%) occurred.Ten-year risk of the first cardiovascular event (myocardial infarction, angina pectoris, cerebrovascular accidents, or major coronary surgery). Predictors included age, sex, height, weight, systolic blood pressure, diabetes mellitus, smoking, body mass index (BMI), lipid profile, social deprivation, SMI diagnosis, prescriptions for antidepressants and antipsychotics, and reports of heavy alcohol use.We developed 2 CVD risk prediction models for people with SMI: the PRIMROSE BMI model and the PRIMROSE lipid model. These models mutually excluded lipids and BMI. In terms of discrimination, from cross-validations for men, the PRIMROSE lipid model D statistic was 1.92 (95% CI, 1.80-2.03) and C statistic was 0.80 (95% CI, 0.76-0.83) compared with 1.74 (95% CI, 1.63-1.86) and 0.78 (95% CI, 0.75-0.82) for published Cox Framingham risk scores. The corresponding results in women were 1.87 (95% CI, 1.76-1.98) and 0.79 (95% CI, 0.76-0.82) for the PRIMROSE lipid model and 1.58 (95% CI, 1.48-1.68) and 0.77 (95% CI, 0.73-0.81) for the Cox Framingham model. Discrimination statistics for the PRIMROSE BMI model were comparable to those for the PRIMROSE lipid model. Calibration plots suggested that both PRIMROSE models were superior to the Cox Framingham models.The PRIMROSE BMI and lipid CVD risk prediction models performed better in SMI compared with models that include only established CVD risk factors. Further work on the clinical effectiveness and cost-effectiveness of the PRIMROSE models is needed to ascertain the best thresholds for offering CVD interventions.

SUBMITTER: Osborn DP

PROVIDER: S-EPMC4353842 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

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Cardiovascular risk prediction models for people with severe mental illness: results from the prediction and management of cardiovascular risk in people with severe mental illnesses (PRIMROSE) research program.

Osborn David P J DP Hardoon Sarah S Omar Rumana Z RZ Holt Richard I G RI King Michael M Larsen John J Marston Louise L Morris Richard W RW Nazareth Irwin I Walters Kate K Petersen Irene I

JAMA psychiatry 20150201 2

<h4>Importance</h4>People with severe mental illness (SMI), including schizophrenia and bipolar disorder, have excess rates of cardiovascular disease (CVD). Risk prediction models validated for the general population may not accurately estimate cardiovascular risk in this group.<h4>Objective</h4>To develop and validate a risk model exclusive to predicting CVD events in people with SMI incorporating established cardiovascular risk factors and additional variables.<h4>Design, setting, and particip ...[more]

PMID: 25536289

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Project description:Interventions: We are assessing the impact of the National Bowel Cancer Screening Program (NBCSP) by comparing participation rates of people with and without Severe Mental Illness (SMI) and looking at health outcomes. We will be using data collected from Aug 2006 - latest available. We are linking data using Commonwealth data (NBCSP, Medicare Benefits Schedule, Pharmaceutical Benefits Scheme, Australian Cancer Database & the National Death Index) to compare bowel cancer screening participation in people with SMI to those from the general population. We will additionally link these to the NSW cancer registry and hospital data to examine care pathways from diagnosis through treatment and end-of-life care. We will also conduct a consultation with people with experience of SMI and Colorectal cancer and people with SMI in peer support roles who can provide their perspective on the barriers faced by people with SMI to gaining timely screening, diagnosis and optimal care. These participants will be recruited from New South Wales consumer organisations and organisations with a strong focus on provision of peer support and advocacy. We will use a semi structured group interview schedule to facilitate discussion of a single focus group of 15 people. The group will consist of both people with lived experience who have direct experience of bowel cancer (n=10), as well as other people with lived experience who have supported people in this situation – as peer support workers or in other consumer advocacy/support roles (n=5). We will use this qualitative arm of the study to further develop our understanding of the quantitative findings. The consultation will also develop ideas on how to improve access to care. Primary outcome(s): Participation rates in the National Bowel Cancer Screening Program assessed using data from the NBCSP.[Person-years will be calculated from entry into the study (2006) (the date of commencement of the NBCSP) or from the year that people become eligible for screening (i.e. age 50), whichever occurs later.. This is a retrospective cohort study, so all of the outcomes have already occurred and were recorded in the administrative data. This will be assessed when we receive the data.];Colonoscopy rates assessed using data from the NBCSP [Person-years will be calculated from entry into the study (2006 the date of commencement of the NBCSP), or from the year that people become eligible for screening (i.e. age 50), whichever occurs later, until colonoscopy. This is a retrospective cohort study, so all of the outcomes have already occurred and have been recorded in the administrative data.];Cancer diagnosis using data from the Australian Cancer Database[Person-years will be calculated from entry into the study (2006 the date of commencement of the NBCSP), or from the year that people become eligible for screening (i.e. age 50), whichever occurs later, until cancer diagnosis. This is a retrospective cohort study, so all of the outcomes have already occurred and have been recorded in the administrative data.] Study Design: Purpose: Screening;Duration: Longitudinal;Selection: Case control;Timing: Both

Project description:BACKGROUND:An advance directive is a document specifying a person's preferences for treatment, should he or she lose capacity to make such decisions in the future. They have been used in end-of-life settings to direct care but should be well suited to the mental health setting. OBJECTIVES:To examine the effects of advance treatment directives for people with severe mental illness. SEARCH STRATEGY:We searched the Cochrane Schizophrenia Group's Register (February 2008), the Cochrane Library (Issue 1 2008), BIOSIS (1985 to February 2008), CINAHL (1982 to February 2008), EMBASE (1980 to February 2008), MEDLINE (1966 to February 2008), PsycINFO (1872 to February 2008), as well as SCISEARCH and Google - Internet search engine (February 2008). We inspected relevant references and contacted first authors of included studies. SELECTION CRITERIA:We included all randomised controlled trials (RCTs), involving adults with severe mental illness, comparing any form of advance directive with standard care for health service and clinical outcomes. DATA COLLECTION AND ANALYSIS:We extracted data independently. For homogenous dichotomous data we calculated fixed-effect relative risk (RR) and 95% confidence intervals (CI) on an intention-to-treat basis. For continuous data, we calculated weighted mean differences (WMD) and their 95% confidence interval again using a fixed-effect model. MAIN RESULTS:We were able to include two trials involving 321 people with severe mental illnesses. There was no significant difference in hospital admission (n=160, 1 RCT, RR 0.69 0.5 to 1.0), or number of psychiatric outpatient attendances between participants given advanced treatment directives or usual care. Similarly, no significant differences were found for compliance with treatment, self harm or number of arrests. Participants given advanced treatment directives needed less use of social workers time (n=160, 1 RCT, WMD -106.00 CI -156.2 to -55.8) than the usual care group, and violent acts were also lower in the advanced directives group (n=160, 1 RCT, RR 0.27 CI 0.1 to 0.9, NNT 8 CI 6 to 92). The number of people leaving the study early were not different between groups (n=321, 2 RCTs, RR 0.92 CI 0.6 to 1.6). AUTHORS' CONCLUSIONS:There are too few data available to make definitive recommendations. More intensive forms of advance directive appear to show promise, but currently practice must be guided by evidence other than that derived from randomised trials. More trials are indicated to determine whether higher intensity interventions, such as joint crisis planning, have an effect on outcomes of clinical relevance.

Project description:Background: Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental illnesses (SMI) associated with elevated cardiovascular disease (CVD) risk, including obesity. Leptin and adiponectin are secreted by adipose tissue, with pro- and anti-inflammatory properties, respectively. The second generation antipsychotics (AP) olanzapine, clozapine, and quetiapine have been associated with high leptin levels in SMI. However, the link between inflammatory dysregulation of leptin and adiponectin and CVD risk in SMI, and how this risk is influenced by body mass and AP medication, is still not completely understood. We investigated herein if leptin, adiponectin or their ratio (L/A ratio) could predict increased CVD risk in SCZ, BD, and in subgroups according to use of antipsychotic (AP) treatment, independent of other cardio-metabolic risk factors. Methods: We measured fasting plasma levels of leptin and adiponectin, and calculated the L/A ratio in n = 1,092 patients with SCZ and BD, in subgroups according to AP treatment, and in n = 176 healthy controls (HC). Differences in the levels of adipokines and L/A between groups were examined in multivariate analysis of covariance, and the correlations between adipokines and body mass index (BMI) with linear regression. CVD risk was defined by total cholesterol/high-density lipoprotein (TC/HDL) and triglyceride/HDL (TG/HDL) ratios. The adipokines and L/A ratios ability to discriminate individuals with TG/HDL and TC/HDL ratios above threshold levels was explored by ROC analysis, and we investigated the possible influence of other cardio-metabolic risk factors on the association in logistic regression analyses. Results: We observed higher leptin levels and L/A ratios in SMI compared with HC but found no differences in adiponectin. Both adipokines were highly correlated with BMI. The low adiponectin levels showed a fair discrimination in ROC analysis of individuals with CVD risk, with AUC between 0.7 and 0.8 for both TC/HDL and TG/HDL, in all groups examined regardless of diagnosis or AP treatment. Adiponectin remained significantly associated with an elevated TC/HDL and TG/HDL ratio in SMI, also after further adjustment with other cardio-metabolic risk factors. Conclusions: Adiponectin is not dysregulated in SMI but is associated with CVD risk regardless of AP treatment regime.

Project description:BackgroundWe conducted a trial to test the electronic Illness Management and Recovery (e-IMR) intervention to provide conclusions on the potential efficacy of eHealth for people with severe mental illness (SMI). In the e-IMR intervention, we used the standard IMR program content and methodology and combined face-to-face sessions with internet-based strategies on the constructed e-IMR internet platform. During the trial, the e-IMR platform was sparsely used.ObjectiveThis study aimed to evaluate the added value of the e-IMR intervention and the barriers and facilitators that can explain the low use of the e-IMR platform.MethodsThis process evaluation was designed alongside a multicenter, cluster randomized controlled trial. In this study, we included all available participants and trainers from the intervention arm of the trial. Baseline characteristics were used to compare users with nonusers. Qualitative data were gathered at the end of the semistructured interviews. Using theoretical thematic analyses, the data were analyzed deductively using a pre-existing coding frame.ResultsOut of 41 eligible participants and 14 trainers, 27 participants and 11 trainers were interviewed. Of the 27 participants, 10 were identified as users. eHealth components that had added value were the persuasive nature of the goal-tracking sheets, monitoring, and the peer testimonials, which had the potential to enhance group discussions and disclosure by participants. The low use of the e-IMR platform was influenced by the inflexibility of the platform, the lack of information technology (IT) resources, the group context, participants' low computer skills and disabilities, and the hesitant eHealth attitude of the trainers.ConclusionsThe extent of eHealth readiness and correlations with vulnerabilities in persons with SMI need further investigation. This study shows that flexible options were needed for the use of e-IMR components and that options should be provided only in response to a participant's need. Use of the e-IMR intervention in the future is preconditioned by checking the available IT resources (such as tablets for participants) providing computer or internet guidance to participants outside the group sessions, evaluating the eHealth attitude and skills of trainers, and tailoring eHealth training to increase the skills of future e-IMR trainers.Trial registrationNetherlands Trial Register NTR4772; https://www.trialregister.nl/trial/4621.International registered report identifier (irrid)RR2-10.1186/s12913-016-1267-z.

Dataset Information

Cardiovascular risk prediction models for people with severe mental illness: results from the prediction and management of cardiovascular risk in people with severe mental illnesses (PRIMROSE) research program.

Publications

Cardiovascular risk prediction models for people with severe mental illness: results from the prediction and management of cardiovascular risk in people with severe mental illnesses (PRIMROSE) research program.

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