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P.1.k.025 Pitfalls of using absolute risk score for risk assessment and subtyping
P.1.k. Basic and clinical neuroscience − Epidemiology attentional shifting. This study aims to investigate associations between attentional control and suicidality in German soldiers after deployment in Afghanistan. In addition, specific associations between suicidality and each attentional focusing and attentional shifting were examined. Methods: Data are part of the follow-up assessment of a longitudinal study investigating mental health and its determinants in German soldiers deployed in Afghanistan (PID-PTSD+3 study) [1]. Follow-up assessment was conducted about 12 months after return from deployment (n = 360). Mental health including suicidality was assessed using standardized diagnostic interviews (M-CIDI) and established questionnaires. Suicidality consisted of suicidal ideation and suicidal behaviours. Attentional control was measured with the Attentional Control Scale [2], which provides subscales for differentiating between attentional shifting and attentional focusing. Complete data for the present analysis were available for n = 205 participants. Soldiers were all male with a mean age of 28.2 years (SD = 5.7). Data were analysed with logistic regressions predicting suicidality (yes/no) and adjusting for age, educational level and marital status. Results: 12.2% (n = 25) of the soldiers reported either suicidal ideation or suicidal behaviours. Mean of the attentional control scale was 54.9 (SD = 5.4). Attentional control and suicidality were significantly associated (OR= 0.89, 95% CI= 0.82–0.97, p < 0.01). That is, an increase of one point on the attentional control scale was associated with a decrease in the risk for suicidality of about 11% (about 60% per standard deviation). In particular, attentional shifting and suicidality were significantly associated (OR= 0.83, 95% CI= 0.74–0.94, p < 0.01). This result suggests that an increase of one point on the subscale attentional shifting is associated with a decrease in the risk for suicidality of about 17%. However, attentional focusing and suicidality were not significantly associated. Discussion: Results extend previous evidence indicating that attentional control, i.e. attentional shifting, is inversely associated with suicidality. A stronger ability of attentional shifting may prevent individuals from attending to self-related rumination and connected dysfunctional emotional states. Flexible shifting may allow for disengaging the attention from information related to despair and hopelessness and attend to positive information. This may reduce the risk for initiating actions based on a narrowed mind. Future research should replicate these findings and examine the contribution of attentional shifting to suicidality longitudinally and experimentally to clarify its causal role. It should also investigate whether trainings of attentional control could serve to reduce the risk for suicide. References [1] Keilp, J.G., Gorlyn, M., Russell, M., Oquendo, M.A., Burke, A.K., Harkavy-Friedman, J., & Mann, J.J. (2013). Neuropsychological function and suicidal behavior: attention control, memory and executive dysfunction in suicide attempt. Psychol Med, 43, 539–551. [2] Wittchen, H.U., Sch¨onfeld, S., Thurau, C., Trautmann, S., Galle, M., Mark, K., . . . & Kirschbaum, C. (2012). Prevalence, incidence and determinants of PTSD and other mental disorders: design and methods of the PID-PTSD+ 3 study. International journal of methods in psychiatric research, 21(2), 98–116. [3] Derryberry, D., & Reed, M.A. (2002). Anxiety-related attentional biases and their regulation by attentional control. Journal of abnormal psychology, 111(2), 225.
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P.1.k.025 Pitfalls of using absolute risk score for risk assessment and subtyping C. Siu1 ° , C. Brambilla2 1 UCS Research, New Jersey, USA; 2 Applied Mathematics and Information Technologies Institute National Research Council, Statistics, Milan, Italy Background: Absolute risk estimation is a cornerstone for risk stratification and subtyping in primary prevention of cardiovascular disease. In a Lancet Comment published on Nov 30, 2013, Ridker and Cook [1] reported that the new ACC/AHA prediction algorithm systematically overestimated the risk for atherosclerotic cardiovascular disease (ASCVD) in 5 primary prevention cohorts, which featured better smoking, cholesterol and blood pressure profiles compared to the cohorts used in deriving the guidelines. The Framingham Risk Score, a well-established risk prevention tool for guiding the assessment and management of risk for coronary heart disease (CHD), is based on absolute risk, [2] i.e. the probability of developing CHD over a given period of time. This might not be most appropriate for the individuals in schizophrenia population, since the original Framingham Cox Survival mode [3] was developed based on a white middle-class population. Methods: The objectives of this paper were: (1) examine the recalibration procedure for absolute risk survival model, using the FRS risk estimate as an example; (2) evaluate the validity of using these absolute risk estimates in populations in which no baseline risk has been established, and (3) investigate whether risk ratio (relative to an optimal risk profile as the reference risk state) can provide more accurate risk estimate than the usual absolute risk score for individual with serious mental illness. To recalibrate the FRS risk estimates for a new study population, we need to replace (1) the Framingham baseline risk (RISK_0) and (2) the mean risk factors G_MEAN (e.g. mean age, proportion of smoker, proportion of subjects in each lipid and hypertension risk categories) with values from this new study population. Results: We compared the mean (or proportion) for each of the categories of the FRS risk factors in the CATIE and FHS studies: mean age 40 in CATIE versus 49 in FHS, respectively; total cholesterol >240 mg/dL, 20% versus 26%; HDL <35 mg/dL, 25% versus 11%; Stage I−IV hypertension, 28% versus 32%; Diabetes mellitus, women 16% and men 11% versus women 4% and men 5%; and smoker, women 56% and men 73% versus women 38% and men 40%. Specifically, for age 55−59, the low 10-year FHS risk is 7% for both men and women. Replacing the FHS RISK_0 and GMEAN with new hypothetical study values (RISK0 = 0.95 and GMEAN = 11), the low 10-year CHD risk for women aged 55−59 is 13%. We developed a simple proof to show that risk ratio (relative to the normal reference risk state) does not depend on baseline risk (RISK_0) and mean risk factors GMEAN when the cumulative hazard is small, and hence is more useful when comparing across populations. Conclusions: Our findings suggest that risk ratio (relative to normal reference risk) might be more appropriate than absolute risk for prediction of cardiovascular risk in schizophrenia patients using Framingham Scoring Model. References [1] Ridker PM, Cook NR. Statins: new American guidelines for prevention of cardiovascular disease. Lancet 2013 (Nov 30); 382: 1762–1765. [2] Daumit GL, Goff DC, Meyer JM, et al. Antipsychotic effects on estimated 10 year coronary heart disease risk in the CATIE schizophrenia study. Schizophr Res. 2008; 105: 175–187.
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P.1.k. Basic and clinical neuroscience − Epidemiology
[3] Grundy SM, Pasternak R, Greenland P, et al. Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation 1999; 100: 1481–1492.
and neuropsychiatric symptoms in the elderly. Further studies focussing on drug use in elderly, and possible association between cardiovascular and neuropsychiatric disorders will increase the success in geriatric pharmacotherapy. References
P.1.k.026 Neuropsychiatric disorders and prescription drugs among geriatric patients Z. Ozt¨urk1 ° , A. Ural T¨urkyilmaz2 1 Izmir Ataturk Training and Research Hospital, Clinical Pharmacology and Toxicology, Izmir, Turkey; 2 Izmir Ataturk Training and Research Hospital Basin Sitesi Polyclinic, Neurology, Izmir, Turkey Geriatric neuropsychopharmacology is a still nascent field. Neurological and psychiatric disorders increase in prevalence with advancing age. Other comorbid conditions and acute illness also occur more commonly in the elderly. Therefore, they are more likely to take many different drugs. Progressive physiological changes occur with aging in various organ systems and age-related changes can have a significant effect on drug therapy. There are a few studies about the drug utilization in the geriatric population. Careful attention needs to be paid to potentially inappropriate drug use in older patients and adverse drug events associated with polypharmacy. The aim of this study was to determine the presenting complaints, medical diagnoses, use of medications by geriatric patients admitted to neurology and psychiatry outpatient clinic. A retrospective study was planned. Data were obtained from the medical records of patients (age 65) referred to neurology and psychiatry outpatient clinic at Izmir Atat¨urk Training and Research Hospital Basin Sitesi Polyclinic, between October 2013 and December 2013. Demographic characteristics, diagnoses, prescription drugs were recorded, and the SPSS 16.0 statical software was used for data analysis. Number, percent, mean and standard deviation were used as descriptive statistics. A total of 722 patients were included in our study. 484 (67%) of them were female. The mean age of the patients was 74.85±5.69 (65−98) years. The rates of diagnoses were found to be as follows: headache 19.5%, vertigo 17.0%, anxiety disorder 10.6%, organic mental disorder 9.7%, dementia 9.4%, polyneuropathy 9.2%. The total number of drugs prescribed were 1682 and ranged from 0 to 10 drugs per patient. Four patients received 10 different medicines. Multiple drug use increases with age and chronic disease diagnosis. 15.3% of patients did not receive any medication. 17.8% of them received one drug, 25.3% two drugs, 19.8% three drugs, 10.5% four drugs, 4.5% five drugs, 6.5% six and more drugs. The most commonly prescribed drugs were central nervous system drugs such as antidementia, antiepileptic, antivertigo, opioid analgesics (18.9%), cardiovascular system drugs (15.1%), nonsteroidal anti-inflammatory drugs (14.4%), psychotropic drugs (13.6%), respectively. Based on our results, among the geriatric patients with neurological and psychiatric disorders, the number of cardiovascular drugs was higher than expected. This finding suggested that cardiovascular disease is major clinical problem in elderly patients. In Turkey, Ayse et al [1]. reported that the most commonly comorbid diseases of geriatric patients presenting with neurological problems were hypertension (71.8%) and coronary artery disease (28.9%). On the other hand, polypharmacy and associated medical complications were common in the geriatric population [2]. In this study, we aimed to increase awareness of prescription drugs
¨ [1] Demir Akca AS, Emre U, Unal A, Aciman E, Akca F. 2012 Comorbid diseases and drug usage among geriatric patients presenting with neurological problems at the emergency department. Turkish Journal of Geriatrics 15(2), 151–155. [2] Jhaveri BN, Patel TK, Barvaliya MJ, Tripathi CB. 2014 Drug utilization pattern and pharmacoeconomic analysis in geriatric medical in-patients of a tertiary care hospital of India. J Pharmacol Pharmacother 5(1), 15−20.
P.1.k.027 The disease network of mental disorders in Korea M. Choi1 ° , M. Gim1 South-Korea
1 Sanggye
Paik Hospital, psychiatry, Seoul,
Background: Recently, network medicine is drawing more attention, leading to many attempts to approach medicine in view of networks among genes, disease, and individuals. Mental disorders are known to have high rates of comorbidity. However, the network among mental disorders has not been discovered enough. Studying the structure defined by entire sets of comorbidities might help the understanding of mental disorders from a perspective that is complementary to other approaches. The purpose of this study is to figure out the network among mental disorders in Korea. Method: The data about prevalence and comorbidity of mental disorders were obtained from 2006, 2011 epidemiological survey of mental disorders in Korea, which 22 psychiatric disorders based on Diagnostic and Statistical Manual (DSM) IV were analyzed. We used network analysis by drawing a network graph to describe the relationships among mental disorders. Nodes were disease phenotypes identified by DSM-IV, and links connect phenotypes that showed significant comorbidity. In order to describe the weight of the links, we used odds ratio to quantify the distance between two diseases. The network centrality values were also analyzed in two manners. Degree centrality with the weight of the links between disorders was analyzed. Later, degree centrality without the weight of the links between disorders was analyzed. The disease network of mental disorders was classified into subgroups in order to be compared to major classes of DSM IV. Results: The results showed that in 2011, the degree of centrality was the highest in major depressive disorder, followed by nicotine dependence and generalized anxiety disorder, whereas it was highest in major depressive disorder, followed by nicotine dependence and alcohol dependence in 2006. In 2011, degree centrality reflecting the odds ratio was highest in conversion disorder, followed by panic disorder and social phobia, whereas it was highest in conversion disorder, social phobia posttraumatic stress disorder in 2006. We can visually recognize these results from the graphs made by network analysis. In this study, we were not able to classify mental disorder into subgroups based on its link connection. Because, mental disorders are closely linked with each other regardless of major classes of DSM IV. Conclusion: Major depressive disorder and nicotine dependence appeared to be highly connected with other mental disorders. Mental disorders with high degree of centrality should be considered for their comorbidity. Understanding the Psychiatric network is expected to bring a clue to providing effective mental
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P.1.k.025 Pitfalls of using absolute risk score for risk assessment and subtyping C. Siu1 ° , C. Brambilla2 1 UCS Research, New Jersey, USA; 2 Applied Mathematics and Information Technologies Institute National Research Council, Statistics, Milan, Italy Background: Absolute risk estimation is a cornerstone for risk stratification and subtyping in primary prevention of cardiovascular disease. In a Lancet Comment published on Nov 30, 2013, Ridker and Cook [1] reported that the new ACC/AHA prediction algorithm systematically overestimated the risk for atherosclerotic cardiovascular disease (ASCVD) in 5 primary prevention cohorts, which featured better smoking, cholesterol and blood pressure profiles compared to the cohorts used in deriving the guidelines. The Framingham Risk Score, a well-established risk prevention tool for guiding the assessment and management of risk for coronary heart disease (CHD), is based on absolute risk, [2] i.e. the probability of developing CHD over a given period of time. This might not be most appropriate for the individuals in schizophrenia population, since the original Framingham Cox Survival mode [3] was developed based on a white middle-class population. Methods: The objectives of this paper were: (1) examine the recalibration procedure for absolute risk survival model, using the FRS risk estimate as an example; (2) evaluate the validity of using these absolute risk estimates in populations in which no baseline risk has been established, and (3) investigate whether risk ratio (relative to an optimal risk profile as the reference risk state) can provide more accurate risk estimate than the usual absolute risk score for individual with serious mental illness. To recalibrate the FRS risk estimates for a new study population, we need to replace (1) the Framingham baseline risk (RISK_0) and (2) the mean risk factors G_MEAN (e.g. mean age, proportion of smoker, proportion of subjects in each lipid and hypertension risk categories) with values from this new study population. Results: We compared the mean (or proportion) for each of the categories of the FRS risk factors in the CATIE and FHS studies: mean age 40 in CATIE versus 49 in FHS, respectively; total cholesterol >240 mg/dL, 20% versus 26%; HDL <35 mg/dL, 25% versus 11%; Stage I−IV hypertension, 28% versus 32%; Diabetes mellitus, women 16% and men 11% versus women 4% and men 5%; and smoker, women 56% and men 73% versus women 38% and men 40%. Specifically, for age 55−59, the low 10-year FHS risk is 7% for both men and women. Replacing the FHS RISK_0 and GMEAN with new hypothetical study values (RISK0 = 0.95 and GMEAN = 11), the low 10-year CHD risk for women aged 55−59 is 13%. We developed a simple proof to show that risk ratio (relative to the normal reference risk state) does not depend on baseline risk (RISK_0) and mean risk factors GMEAN when the cumulative hazard is small, and hence is more useful when comparing across populations. Conclusions: Our findings suggest that risk ratio (relative to normal reference risk) might be more appropriate than absolute risk for prediction of cardiovascular risk in schizophrenia patients using Framingham Scoring Model. References [1] Ridker PM, Cook NR. Statins: new American guidelines for prevention of cardiovascular disease. Lancet 2013 (Nov 30); 382: 1762–1765. [2] Daumit GL, Goff DC, Meyer JM, et al. Antipsychotic effects on estimated 10 year coronary heart disease risk in the CATIE schizophrenia study. Schizophr Res. 2008; 105: 175–187.
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P.1.k. Basic and clinical neuroscience − Epidemiology
[3] Grundy SM, Pasternak R, Greenland P, et al. Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology. Circulation 1999; 100: 1481–1492.
and neuropsychiatric symptoms in the elderly. Further studies focussing on drug use in elderly, and possible association between cardiovascular and neuropsychiatric disorders will increase the success in geriatric pharmacotherapy. References
P.1.k.026 Neuropsychiatric disorders and prescription drugs among geriatric patients Z. Ozt¨urk1 ° , A. Ural T¨urkyilmaz2 1 Izmir Ataturk Training and Research Hospital, Clinical Pharmacology and Toxicology, Izmir, Turkey; 2 Izmir Ataturk Training and Research Hospital Basin Sitesi Polyclinic, Neurology, Izmir, Turkey Geriatric neuropsychopharmacology is a still nascent field. Neurological and psychiatric disorders increase in prevalence with advancing age. Other comorbid conditions and acute illness also occur more commonly in the elderly. Therefore, they are more likely to take many different drugs. Progressive physiological changes occur with aging in various organ systems and age-related changes can have a significant effect on drug therapy. There are a few studies about the drug utilization in the geriatric population. Careful attention needs to be paid to potentially inappropriate drug use in older patients and adverse drug events associated with polypharmacy. The aim of this study was to determine the presenting complaints, medical diagnoses, use of medications by geriatric patients admitted to neurology and psychiatry outpatient clinic. A retrospective study was planned. Data were obtained from the medical records of patients (age 65) referred to neurology and psychiatry outpatient clinic at Izmir Atat¨urk Training and Research Hospital Basin Sitesi Polyclinic, between October 2013 and December 2013. Demographic characteristics, diagnoses, prescription drugs were recorded, and the SPSS 16.0 statical software was used for data analysis. Number, percent, mean and standard deviation were used as descriptive statistics. A total of 722 patients were included in our study. 484 (67%) of them were female. The mean age of the patients was 74.85±5.69 (65−98) years. The rates of diagnoses were found to be as follows: headache 19.5%, vertigo 17.0%, anxiety disorder 10.6%, organic mental disorder 9.7%, dementia 9.4%, polyneuropathy 9.2%. The total number of drugs prescribed were 1682 and ranged from 0 to 10 drugs per patient. Four patients received 10 different medicines. Multiple drug use increases with age and chronic disease diagnosis. 15.3% of patients did not receive any medication. 17.8% of them received one drug, 25.3% two drugs, 19.8% three drugs, 10.5% four drugs, 4.5% five drugs, 6.5% six and more drugs. The most commonly prescribed drugs were central nervous system drugs such as antidementia, antiepileptic, antivertigo, opioid analgesics (18.9%), cardiovascular system drugs (15.1%), nonsteroidal anti-inflammatory drugs (14.4%), psychotropic drugs (13.6%), respectively. Based on our results, among the geriatric patients with neurological and psychiatric disorders, the number of cardiovascular drugs was higher than expected. This finding suggested that cardiovascular disease is major clinical problem in elderly patients. In Turkey, Ayse et al [1]. reported that the most commonly comorbid diseases of geriatric patients presenting with neurological problems were hypertension (71.8%) and coronary artery disease (28.9%). On the other hand, polypharmacy and associated medical complications were common in the geriatric population [2]. In this study, we aimed to increase awareness of prescription drugs
¨ [1] Demir Akca AS, Emre U, Unal A, Aciman E, Akca F. 2012 Comorbid diseases and drug usage among geriatric patients presenting with neurological problems at the emergency department. Turkish Journal of Geriatrics 15(2), 151–155. [2] Jhaveri BN, Patel TK, Barvaliya MJ, Tripathi CB. 2014 Drug utilization pattern and pharmacoeconomic analysis in geriatric medical in-patients of a tertiary care hospital of India. J Pharmacol Pharmacother 5(1), 15−20.
P.1.k.027 The disease network of mental disorders in Korea M. Choi1 ° , M. Gim1 South-Korea
1 Sanggye
Paik Hospital, psychiatry, Seoul,
Background: Recently, network medicine is drawing more attention, leading to many attempts to approach medicine in view of networks among genes, disease, and individuals. Mental disorders are known to have high rates of comorbidity. However, the network among mental disorders has not been discovered enough. Studying the structure defined by entire sets of comorbidities might help the understanding of mental disorders from a perspective that is complementary to other approaches. The purpose of this study is to figure out the network among mental disorders in Korea. Method: The data about prevalence and comorbidity of mental disorders were obtained from 2006, 2011 epidemiological survey of mental disorders in Korea, which 22 psychiatric disorders based on Diagnostic and Statistical Manual (DSM) IV were analyzed. We used network analysis by drawing a network graph to describe the relationships among mental disorders. Nodes were disease phenotypes identified by DSM-IV, and links connect phenotypes that showed significant comorbidity. In order to describe the weight of the links, we used odds ratio to quantify the distance between two diseases. The network centrality values were also analyzed in two manners. Degree centrality with the weight of the links between disorders was analyzed. Later, degree centrality without the weight of the links between disorders was analyzed. The disease network of mental disorders was classified into subgroups in order to be compared to major classes of DSM IV. Results: The results showed that in 2011, the degree of centrality was the highest in major depressive disorder, followed by nicotine dependence and generalized anxiety disorder, whereas it was highest in major depressive disorder, followed by nicotine dependence and alcohol dependence in 2006. In 2011, degree centrality reflecting the odds ratio was highest in conversion disorder, followed by panic disorder and social phobia, whereas it was highest in conversion disorder, social phobia posttraumatic stress disorder in 2006. We can visually recognize these results from the graphs made by network analysis. In this study, we were not able to classify mental disorder into subgroups based on its link connection. Because, mental disorders are closely linked with each other regardless of major classes of DSM IV. Conclusion: Major depressive disorder and nicotine dependence appeared to be highly connected with other mental disorders. Mental disorders with high degree of centrality should be considered for their comorbidity. Understanding the Psychiatric network is expected to bring a clue to providing effective mental