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P.3.d.011 Follow up screening for the metabolic syndrome in patients receiving antipsychotic treatment
P.3.d. Psychotic disorders and antipsychotics − Antipsychotics (basic) with L-741626 (a potent and selective D2 receptor antagonist) treatment. It is noteworthy that quinpirole was previously reported to possess anorectic effects in rats similar doses. In agreement with the above findings, interaction studies revealed that quinpirole (4 mg/kg) and olanzapine (2 mg/kg) had opposite effects on the firing rate of NI neurons. This study provides the first evidence that antipsychotic drugs influence NI firing and that D2 receptor antagonism contributes to antipsychotic drug-induced suppression of firing in the NI. Together with the previous literature on the role of relaxin-3 in feeding behaviour, these data suggest that D2 receptors in the NI may play a role in the regulation of appetite. Table 1. Cumulative dose response effects of antipsychotic drugs and selective D2 receptor ligands on the firing of NI neurons Test Treatments (mg/kg) which suppressed the firing of NI neurons compound Vehicle, 0.25 0.5 1 2 4 8 16 1 ml/kg Clozapine 85.66 − 51.37 ±3.54 ±13.03 Olanzapine 84.78 − 84.20 ±6.43 ±9.82 Quetiapine 118.51 − 81.01 ±17.61 ±13.78 Risperi100.75 − 80.72 done ±11.62 ±11.45 Chlor101.39 − − promazine ±6.81 Fluphen- 83.72 − 79.76 azine ±5.06 ±11.12 L-741626 97.47 82.15 68.48 ±5.24 ±5.00 ±8.43 Treatment (mg/kg) which Vehicle 0.0625 0.125 Quinpirole
36.63 34.10 34.65 ±14.71 ±13.11 ±13.97 75.08 81.49 53.42 ±10.60 ±13.66 ±10.09 68.74 74.49 87.63 ±7.30 ±10.50 ±13.39 70.49 60.26 51.97 ±12.41 ±11.33 ±12.94 98.23 92.24 76.70 ±13.61 ±6.56 ±6.46 60.60 41.05 37.64 ±11.98 ±11.55 ±12.58 61.71 61.66 48.44 ±10.13 ±10.32 ±9.99 augmented the firing of NI 0.25
0.5
1
35.38 ±14.81 44.41 ±11.57 79.99 ±13.15 51.46 ±13.65 63.71 ±8.06 43.49 ±11.83 45.73 ±10.36 neurons 2
38.18 ±15.75 51.50 ±10.43 72.27 ±12.85 49.27 ±13.51 56.70 ±10.25 45.57 ±9.30 −
32
64
51.61 ±16.41 41.29 ±8.42 76.97 ±20.01 38.28 ±12.14 54.02 ±11.33 34.17 ±10.31 −
48.18 ±14.50 32.49 ±8.30 − 34.35 ±12.09 − − −
4
144.57 122.2 150.80 231.69 268.31 340.74 462.58 599.08 ±31.35 ±27.37 ±60.37 ±88.99 ±91.41 ±106.53 ±129.78 ±181.23
Values represent mean percentage firing rate normalised to baseline±standard error, n = 5−7. The values indicated in bold are significantly (P < 0.05) different from vehicle treatment as determined by within subject contrasts following repeated measures analysis of variance.
Disclosure statement: This paper is financially supported by a grant from the Biomedical Research Council, Singapore (BMRC 07/1/21/19/512) References [1] van der Westhuizen, E.T., Halls, M.L., Samuel, C.S., Bathgate, R.A., Unemori, E.N., Sutton, S.W., Summers, R.J., 2008 Relaxin family peptide receptors − from orphans to therapeutic targets. Drug Discovery Today 13, 640–651. [2] Dawe, G.S., Huff, K.D., Vandergriff, J.L., Sharp, T., O’Neill, M.J., Rasmussen, K., 2001 Olanzapine activates the rat locus coeruleus: in vivo electrophysiology and c-Fos immunoreactivity. Biological Psychiatry 50, 510–520.
P.3.d.011 Follow up screening for the metabolic syndrome in patients receiving antipsychotic treatment L. Konstantinidou1 ° , T. Tsouvalas Athanasios1 , G. Georgiou Georgia1 , B. Birmpili Euaggelia-Maria2 . 1 General Hospital Of Serres, Community Mental Health Center, Serres, Greece; 2 General Hospital Of Serres, 2 Aristotle University of Thessaloniki School of Physical Education and Sport Sciences, Serres, Greece Purpose: The purpose of the study is to examine the prevalence of metabolic syndrome (MS) in individuals with serious and persistent mental health illness (SPMI) and associated risk factors to document emerging problems as a basis for preventive and/or therapeutic interventions. MS is a modifiable risk factor for medical disease in people with SMPI, so the utilisation of prevention approaches with
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established effectiveness in the general population is necessary to be implanted in this population as well. People with serious mental illness (SPMI) are at increased risk for medical conditions such as hypertension, diabetes, heart problems, and obesity [1], [2] and [3]. It is well known that SPMI and some of the antipsychotic medication can increase the risk for metabolic syndrome (SM). Classic and atypical medication can induce weight gain with some agents having greater propensity to do so than others. Methods: The study was conducted at the community based Mental Health Center in Serres, Greece (member of the Hellenic Health Promotion Hospital Network). 45 patients with SPMI, who consented to participate in the study, were examined on June 2009 and on December 2009. The following clinical and demographic characteristics were examined: gender (male-female), age (18−80), weight, DMI, years from the beginning of SPMI, hospitalization, state of work, (employed, unemployed, retirement), place of residence (village, town, city), way of residence (with the family, alone, at state apartments) and marital status (married, unmarried, divorced). The key elements that compose the metabolic syndrome were recorded in these patients concerning the: fasting glucose (100 mg/dl), triglycerides (150 mg/dl), blood pressure (130/85 mmHg), high density lipoprotein (>40 mg/dl for men, >50 mg/dl for women), and waist circumference (male 94 cm, female 80 cm) [3], with a follow up after 6 months by the Mental Health Center of Serres, Greece. A correlation between the prevalence of the metabolic syndrome to the antipsychotic treatment was made as well. Results: The presence and the seriousness of the MS were related to: a) the kind of the antipsychotic drugs (atypical or classic) b) the duration time of the antipsychotic medication, c) the demographic records. Findings indicate that there in an increase in the MS pprevalence between the first assessment and the follow up assessment. Conclusions: Increasingly, physical disorders such as obesity, hyper-lipidemias, hypertension, and type 2 diabetes mellitus are becoming recognized as significant comorbidities in people with serious mental illnesses, including psychotic disorders such as schizophrenia. The findings reveal that MS prevention should be emphasized for these patients. During the long term outpatient treatment provided in the mental health center, psychiatrists and health visitors can use primary and secondary approaches in patients with mental illness. The establishment of structured and routine assessments of the risks of co morbidity for metabolic syndrome risk in relation to the antipsychotic treatment will improve outcomes among individuals with mental illness. References [1] Cohn, T.A., Sernyak, M.J., 2006 Metabolic monitoring for patients treated with antipsychotic medications. The Canadian Journal of Psychiatry 51, 492–501. [2] Cohn, T., et al. 2004 Characterizing coronary heart disease risk in chronic schizophrenia: high prevalence of the metabolic syndrome. The Canadian Journal of Psychiatry 49, 753−60. [3] Sokal, J., et al., 2004 Comorbidity of medical illnesses among adults with serious mental illness who are receiving community psychiatric services. The Canadian Journal of Nervous and Mental Disease 192, 421−7.
36.63 34.10 34.65 ±14.71 ±13.11 ±13.97 75.08 81.49 53.42 ±10.60 ±13.66 ±10.09 68.74 74.49 87.63 ±7.30 ±10.50 ±13.39 70.49 60.26 51.97 ±12.41 ±11.33 ±12.94 98.23 92.24 76.70 ±13.61 ±6.56 ±6.46 60.60 41.05 37.64 ±11.98 ±11.55 ±12.58 61.71 61.66 48.44 ±10.13 ±10.32 ±9.99 augmented the firing of NI 0.25
0.5
1
35.38 ±14.81 44.41 ±11.57 79.99 ±13.15 51.46 ±13.65 63.71 ±8.06 43.49 ±11.83 45.73 ±10.36 neurons 2
38.18 ±15.75 51.50 ±10.43 72.27 ±12.85 49.27 ±13.51 56.70 ±10.25 45.57 ±9.30 −
32
64
51.61 ±16.41 41.29 ±8.42 76.97 ±20.01 38.28 ±12.14 54.02 ±11.33 34.17 ±10.31 −
48.18 ±14.50 32.49 ±8.30 − 34.35 ±12.09 − − −
4
144.57 122.2 150.80 231.69 268.31 340.74 462.58 599.08 ±31.35 ±27.37 ±60.37 ±88.99 ±91.41 ±106.53 ±129.78 ±181.23
Values represent mean percentage firing rate normalised to baseline±standard error, n = 5−7. The values indicated in bold are significantly (P < 0.05) different from vehicle treatment as determined by within subject contrasts following repeated measures analysis of variance.
Disclosure statement: This paper is financially supported by a grant from the Biomedical Research Council, Singapore (BMRC 07/1/21/19/512) References [1] van der Westhuizen, E.T., Halls, M.L., Samuel, C.S., Bathgate, R.A., Unemori, E.N., Sutton, S.W., Summers, R.J., 2008 Relaxin family peptide receptors − from orphans to therapeutic targets. Drug Discovery Today 13, 640–651. [2] Dawe, G.S., Huff, K.D., Vandergriff, J.L., Sharp, T., O’Neill, M.J., Rasmussen, K., 2001 Olanzapine activates the rat locus coeruleus: in vivo electrophysiology and c-Fos immunoreactivity. Biological Psychiatry 50, 510–520.
P.3.d.011 Follow up screening for the metabolic syndrome in patients receiving antipsychotic treatment L. Konstantinidou1 ° , T. Tsouvalas Athanasios1 , G. Georgiou Georgia1 , B. Birmpili Euaggelia-Maria2 . 1 General Hospital Of Serres, Community Mental Health Center, Serres, Greece; 2 General Hospital Of Serres, 2 Aristotle University of Thessaloniki School of Physical Education and Sport Sciences, Serres, Greece Purpose: The purpose of the study is to examine the prevalence of metabolic syndrome (MS) in individuals with serious and persistent mental health illness (SPMI) and associated risk factors to document emerging problems as a basis for preventive and/or therapeutic interventions. MS is a modifiable risk factor for medical disease in people with SMPI, so the utilisation of prevention approaches with
S503
established effectiveness in the general population is necessary to be implanted in this population as well. People with serious mental illness (SPMI) are at increased risk for medical conditions such as hypertension, diabetes, heart problems, and obesity [1], [2] and [3]. It is well known that SPMI and some of the antipsychotic medication can increase the risk for metabolic syndrome (SM). Classic and atypical medication can induce weight gain with some agents having greater propensity to do so than others. Methods: The study was conducted at the community based Mental Health Center in Serres, Greece (member of the Hellenic Health Promotion Hospital Network). 45 patients with SPMI, who consented to participate in the study, were examined on June 2009 and on December 2009. The following clinical and demographic characteristics were examined: gender (male-female), age (18−80), weight, DMI, years from the beginning of SPMI, hospitalization, state of work, (employed, unemployed, retirement), place of residence (village, town, city), way of residence (with the family, alone, at state apartments) and marital status (married, unmarried, divorced). The key elements that compose the metabolic syndrome were recorded in these patients concerning the: fasting glucose (100 mg/dl), triglycerides (150 mg/dl), blood pressure (130/85 mmHg), high density lipoprotein (>40 mg/dl for men, >50 mg/dl for women), and waist circumference (male 94 cm, female 80 cm) [3], with a follow up after 6 months by the Mental Health Center of Serres, Greece. A correlation between the prevalence of the metabolic syndrome to the antipsychotic treatment was made as well. Results: The presence and the seriousness of the MS were related to: a) the kind of the antipsychotic drugs (atypical or classic) b) the duration time of the antipsychotic medication, c) the demographic records. Findings indicate that there in an increase in the MS pprevalence between the first assessment and the follow up assessment. Conclusions: Increasingly, physical disorders such as obesity, hyper-lipidemias, hypertension, and type 2 diabetes mellitus are becoming recognized as significant comorbidities in people with serious mental illnesses, including psychotic disorders such as schizophrenia. The findings reveal that MS prevention should be emphasized for these patients. During the long term outpatient treatment provided in the mental health center, psychiatrists and health visitors can use primary and secondary approaches in patients with mental illness. The establishment of structured and routine assessments of the risks of co morbidity for metabolic syndrome risk in relation to the antipsychotic treatment will improve outcomes among individuals with mental illness. References [1] Cohn, T.A., Sernyak, M.J., 2006 Metabolic monitoring for patients treated with antipsychotic medications. The Canadian Journal of Psychiatry 51, 492–501. [2] Cohn, T., et al. 2004 Characterizing coronary heart disease risk in chronic schizophrenia: high prevalence of the metabolic syndrome. The Canadian Journal of Psychiatry 49, 753−60. [3] Sokal, J., et al., 2004 Comorbidity of medical illnesses among adults with serious mental illness who are receiving community psychiatric services. The Canadian Journal of Nervous and Mental Disease 192, 421−7.