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P.3.013 Interaction between alcohol and opioids in opioid-dependent subjects
Clinical neuropsychopharmacology coherence were independent of total white matter values for controls, but not for autism. These changes were related to the repetitive behaviour that characterises this disorder, suggesting overall that developmental changes in corticostriatal white matter are involved in repetitive behaviour in autism. Reference(s) [1] Langen M, Schnack HG, Nederveen H, Bos D, Lahuis BE, de Jonge M, et al. (2009): Changes in the Developmental Trajectories of Striatum in Autism. Biological Psychiatry. 66:327–333. [2] Kubicki M, Park H, Westin CF, Nestor PG, Mulkern RV, Maier SE, et al. (2005): DTI and MTR abnormalities in schizophrenia: Analysis of white matter integrity. NeuroImage. 26:1109–1118. P.3.013 Interaction between alcohol and opioids in opioid-dependent subjects R. Lees1 ° , T. Williams1 , G. Henderson2 , M. Hickman3 , 1 University of Bristol, A. Lingford-Hughes1 . Psychopharmacology Unit, Bristol, United Kingdom; 2 University of Bristol, Department of Physiology and Pharmacology, Bristol, United Kingdom; 3 University of Bristol, Department of Social Medicine, Bristol, United Kingdom Introduction: Fatal heroin overdose is the leading cause of death in UK opioid users. Concomitant use of central nervous system depressants, in particular alcohol, is identified as a key risk factor for heroin overdose. Studies of heroin overdose deaths have reported a significant inverse relationship between blood alcohol and blood morphine concentrations at postmortem [1,2]. It is plausible alcohol and heroin may interact pharmacologically to enhance overdose risk, however other psychological or social factors may be important. The primary aim of this on-going study was to investigate the proposed alcohol-heroin interaction, using an alcohol challenge in opioid-dependent participants. Saccadic eye movements (SEM) and respiratory measures were used to provide an indication of sensitivity to alcohol. Preliminary results from initial participants are reported. Methods: 8 opioid-dependent participants receiving opioid-substitution therapy (5 receiving 25−85 mg methadone daily, 3 receiving 16 mg buprenorphine daily), and 8 healthy controls were recruited. Participants were administered alcohol in the form of a 400ml drink containing 0.8 g/kg alcohol (vodka), consumed in 8 equal aliquots over 30 minutes. Alcohol level was measured using a breath alcometer. Measures of alcohol effect
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were recorded at baseline and at regular time points after alcohol consumption (45, 60, 75, 90, 105, 120, 135 and 150 minutes). The effects of alcohol were recorded objectively using SEM parameters (peak velocity, peak acceleration, peak deceleration, saccade error, reaction time), using a previously defined protocol [3]. Respiratory parameters (heart rate, respiration rate, oxygen saturation, nasal paCO2 ) were recorded. Results were analysed using repeated measures one-way ANOVA with Bonferroni’s multiple comparison test. Results: Breath alcohol concentration (BAC) significantly increased in all participants following consumption of 0.8 g/kg alcohol (p < 0.0001). BAC was significantly higher in the healthy control group when compared to opioid-dependent participants (p < 0.0001). Controlling for BAC (paCO2 /BAC), nasal paCO2 significantly increased in opioid-dependent participants when compared to healthy controls (p < 0.0001) with significant increases at 105, 120, 135 minutes post-alcohol consumption. Heart rate significantly increased following alcohol consumption, with opioid-dependent participants heart rate significantly increased when compared to controls (heart rate/BAC, p < 0.05). Both respiration rate (respiration rate/BAC) and oxygen saturation (oxygen saturation/BAC) did not significantly change following alcohol consumption (p>0.05). SEM parameters (SEM parameter/BAC) were impaired in all participants, with significant decreases in peak velocity, peak acceleration, peak deceleration, and reaction time following alcohol consumption (p < 0.05). Peak velocity, peak deceleration and reaction time were significantly impaired in healthy controls compared to opioid dependent participants (p < 0.05). Conclusions: As expected, SEM parameters were significantly impaired following alcohol consumption. Opioid dependent participants demonstrated significantly less impairment, likely due to alcohol tolerance. Despite possible alcohol tolerance, significant respiratory effects were observed. The significant increase in nasal paCO2 observed in those using opioids suggests alcohol interacts physiologically with opioids to depress respiration. This indicates alcohol may interact with opioids to facilitate respiratory depression. This has implications when considering both heroin overdose and risk factors for opioid users. Disclosure statement: Funded by a MRC Programme grant (GO40075) and studentship. Reference(s) [1] Ruttenber AJ, Luke JL. 1984. Heroin-related deaths: new epidemiologic insights. Science 226(4670): 14−20. [2] Zador D, Sunjic S, Darke S. 1996. Heroin-related deaths in New South Wales, 1992: toxicological
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findings and circumstances. The Medical Journal of Australia 164(4): 204–207. [3] Wilson SJ, Glue P, Ball D, Nutt DJ. 1993. Saccadic eye movement parameters in normal subjects. Electroencephalography and Clinical Neurophysiology 86: 69−74.
P.3.014 Long term follow up of adolescent depression: history of drug prescriptions A. P¨aa¨ ren1 ° , H. Bohman1 , U. Jonsson1 , A.L. von Knorring1 , L. von Knorring2 . 1 Uppsala University/ University Hospital, Department of Neuroscience Child and Adolescent Psychiatry, Uppsala, Sweden; 2 Uppsala University/University Hospital, Department of Neuroscience Psychiatry, Uppsala, Sweden Aim: To analyze prescription rate of drugs to subjects with adolescent depression followed over 15 years. Method: In 1991–1992, 2 465 adolescents in Uppsala, Sweden, were screened for the presence of depressive disorders. After screening and interview, 362 individuals were identified as depressed, 261 with major depressive disorders and 101 with dysthymia or subsyndromal depressive disorders, and 250 were selected as controls. Fifteen years later the prescription of drug use has been evaluated by means of a national register kept by the National Health and Welfare Board. Results: The former depressed female adolescents had significantly higher numbers of prescriptions for prescription drugs compared to the controls (z = 3.34; p < 0.001). There were statistical differences between controls for mood drug prescriptions like antidepressants (c2 = 6.16; p < 0.01), anticonvulsants (c2 = 6.29; p < 0.01) and thyroid therapy (c2 = 5.58; p < 0.02) Also, there were other drug prescriptions that make statistical difference like antibacterial (c2 = 6.17; p < 0.01), antimycotics (c2 = 4.44; p < 0.05) for systemic use corticosteroids for dermatological preparations (c2 = 4.93; p < 0.02) and mineral supplements (c2 = 5.58; p < 0.02). Former depressed men did not differ in the use of prescription drugs as compared to the controls. In addition the former depressed men had significantly lower number of recipes for prescription drugs as compared to the former depressed women. Discussion: Different hypotheses and possible courses discuss why depressed females have a higher numbers prescription of drugs like augmentation, co-morbid disorders and side effects. Augmentation strategies are widely practiced in order to optimize antidepressant response. In our study we found statistically more prescriptions of different drugs like anticonvulsants (mood stabilizes) and
thyroid hormone, that clinician could use for treatment depression in female group. An alternative hypothesis is that subjects with depression presenting more co-morbid disorders, are more likely to use antidepressants and other drugs. It has also been shown that people with allergy, hay fever, asthma, ulcers, elevated blood pressure and coronary heart disease as well as sub-clinical hypothyroidism and inflammation have been linked to increased risk of depression. Antidepressants have been prescribed in support for pain treatment and chronic stress. An another alternative hypotheses is that antidepressants use presents some side effects like increase the risk of falls and subsequent fractures because of cardiovascular, anticholinergic and antihistaminergic side effects. But there is evidence that antidepressants increase risk of fracture as well as another mechanism than falling. The use of antidepressants was associated with a low bone mineral density and sometimes it needs medical correction with mineral supplements. Conclusion: The results indicate that females with adolescent depression have more mental and somatic illnesses 15 years later, as determined from their use of prescription drugs. Males with adolescent depression on the other hand do not use more prescription drugs 15 years later. It may be due to the fact that alcohol, drug abuse and behavioral disturbances are more common in males, which might lead to treatment outside of the health care system. It is also possible that the illnesses in the males are under diagnosed and under-treated. Reference(s) [1] Olsson G.I., von Knorring A-L.1999 May. Acta Psychiatr Scand. Adolescent depression: prevalence in Swedish high-school students. 99(5):324−31. [2] Weisler R.H., Cutler A.J., Ballenger J.C., Post R.M. 2006 CNS Spectr. The use of antiepileptic drugs in bipolar disorders: a review based on evidence from controlled trials. 11: 788–799. [3] Danese A., Moffitt T.E., Pariante C.M., Ambler A. 2008 Arch Gen Psychiatry. Elevated inflammation levels in depressed adults with a history of childhood maltreatment. 65 (4): 409–416.
P.3.015 Community treatment orders, ethnicity, conditions and psychotropic medication: the first six months (N = 126) M.X. Patel1 ° , J. Matonhodze2 , J. Gilleen1 , J. Boydell1 , D. Taylor2 , G. Szmukler1 , T.J. Lambert3 , A.S. David1 . 1 Institute of Psychiatry King’s College London, Division of Psychological Medicine, London, United Kingdom; 2 South London and Maudsley NHS Foundation Trust,
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were recorded at baseline and at regular time points after alcohol consumption (45, 60, 75, 90, 105, 120, 135 and 150 minutes). The effects of alcohol were recorded objectively using SEM parameters (peak velocity, peak acceleration, peak deceleration, saccade error, reaction time), using a previously defined protocol [3]. Respiratory parameters (heart rate, respiration rate, oxygen saturation, nasal paCO2 ) were recorded. Results were analysed using repeated measures one-way ANOVA with Bonferroni’s multiple comparison test. Results: Breath alcohol concentration (BAC) significantly increased in all participants following consumption of 0.8 g/kg alcohol (p < 0.0001). BAC was significantly higher in the healthy control group when compared to opioid-dependent participants (p < 0.0001). Controlling for BAC (paCO2 /BAC), nasal paCO2 significantly increased in opioid-dependent participants when compared to healthy controls (p < 0.0001) with significant increases at 105, 120, 135 minutes post-alcohol consumption. Heart rate significantly increased following alcohol consumption, with opioid-dependent participants heart rate significantly increased when compared to controls (heart rate/BAC, p < 0.05). Both respiration rate (respiration rate/BAC) and oxygen saturation (oxygen saturation/BAC) did not significantly change following alcohol consumption (p>0.05). SEM parameters (SEM parameter/BAC) were impaired in all participants, with significant decreases in peak velocity, peak acceleration, peak deceleration, and reaction time following alcohol consumption (p < 0.05). Peak velocity, peak deceleration and reaction time were significantly impaired in healthy controls compared to opioid dependent participants (p < 0.05). Conclusions: As expected, SEM parameters were significantly impaired following alcohol consumption. Opioid dependent participants demonstrated significantly less impairment, likely due to alcohol tolerance. Despite possible alcohol tolerance, significant respiratory effects were observed. The significant increase in nasal paCO2 observed in those using opioids suggests alcohol interacts physiologically with opioids to depress respiration. This indicates alcohol may interact with opioids to facilitate respiratory depression. This has implications when considering both heroin overdose and risk factors for opioid users. Disclosure statement: Funded by a MRC Programme grant (GO40075) and studentship. Reference(s) [1] Ruttenber AJ, Luke JL. 1984. Heroin-related deaths: new epidemiologic insights. Science 226(4670): 14−20. [2] Zador D, Sunjic S, Darke S. 1996. Heroin-related deaths in New South Wales, 1992: toxicological
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Clinical neuropsychopharmacology
findings and circumstances. The Medical Journal of Australia 164(4): 204–207. [3] Wilson SJ, Glue P, Ball D, Nutt DJ. 1993. Saccadic eye movement parameters in normal subjects. Electroencephalography and Clinical Neurophysiology 86: 69−74.
P.3.014 Long term follow up of adolescent depression: history of drug prescriptions A. P¨aa¨ ren1 ° , H. Bohman1 , U. Jonsson1 , A.L. von Knorring1 , L. von Knorring2 . 1 Uppsala University/ University Hospital, Department of Neuroscience Child and Adolescent Psychiatry, Uppsala, Sweden; 2 Uppsala University/University Hospital, Department of Neuroscience Psychiatry, Uppsala, Sweden Aim: To analyze prescription rate of drugs to subjects with adolescent depression followed over 15 years. Method: In 1991–1992, 2 465 adolescents in Uppsala, Sweden, were screened for the presence of depressive disorders. After screening and interview, 362 individuals were identified as depressed, 261 with major depressive disorders and 101 with dysthymia or subsyndromal depressive disorders, and 250 were selected as controls. Fifteen years later the prescription of drug use has been evaluated by means of a national register kept by the National Health and Welfare Board. Results: The former depressed female adolescents had significantly higher numbers of prescriptions for prescription drugs compared to the controls (z = 3.34; p < 0.001). There were statistical differences between controls for mood drug prescriptions like antidepressants (c2 = 6.16; p < 0.01), anticonvulsants (c2 = 6.29; p < 0.01) and thyroid therapy (c2 = 5.58; p < 0.02) Also, there were other drug prescriptions that make statistical difference like antibacterial (c2 = 6.17; p < 0.01), antimycotics (c2 = 4.44; p < 0.05) for systemic use corticosteroids for dermatological preparations (c2 = 4.93; p < 0.02) and mineral supplements (c2 = 5.58; p < 0.02). Former depressed men did not differ in the use of prescription drugs as compared to the controls. In addition the former depressed men had significantly lower number of recipes for prescription drugs as compared to the former depressed women. Discussion: Different hypotheses and possible courses discuss why depressed females have a higher numbers prescription of drugs like augmentation, co-morbid disorders and side effects. Augmentation strategies are widely practiced in order to optimize antidepressant response. In our study we found statistically more prescriptions of different drugs like anticonvulsants (mood stabilizes) and
thyroid hormone, that clinician could use for treatment depression in female group. An alternative hypothesis is that subjects with depression presenting more co-morbid disorders, are more likely to use antidepressants and other drugs. It has also been shown that people with allergy, hay fever, asthma, ulcers, elevated blood pressure and coronary heart disease as well as sub-clinical hypothyroidism and inflammation have been linked to increased risk of depression. Antidepressants have been prescribed in support for pain treatment and chronic stress. An another alternative hypotheses is that antidepressants use presents some side effects like increase the risk of falls and subsequent fractures because of cardiovascular, anticholinergic and antihistaminergic side effects. But there is evidence that antidepressants increase risk of fracture as well as another mechanism than falling. The use of antidepressants was associated with a low bone mineral density and sometimes it needs medical correction with mineral supplements. Conclusion: The results indicate that females with adolescent depression have more mental and somatic illnesses 15 years later, as determined from their use of prescription drugs. Males with adolescent depression on the other hand do not use more prescription drugs 15 years later. It may be due to the fact that alcohol, drug abuse and behavioral disturbances are more common in males, which might lead to treatment outside of the health care system. It is also possible that the illnesses in the males are under diagnosed and under-treated. Reference(s) [1] Olsson G.I., von Knorring A-L.1999 May. Acta Psychiatr Scand. Adolescent depression: prevalence in Swedish high-school students. 99(5):324−31. [2] Weisler R.H., Cutler A.J., Ballenger J.C., Post R.M. 2006 CNS Spectr. The use of antiepileptic drugs in bipolar disorders: a review based on evidence from controlled trials. 11: 788–799. [3] Danese A., Moffitt T.E., Pariante C.M., Ambler A. 2008 Arch Gen Psychiatry. Elevated inflammation levels in depressed adults with a history of childhood maltreatment. 65 (4): 409–416.
P.3.015 Community treatment orders, ethnicity, conditions and psychotropic medication: the first six months (N = 126) M.X. Patel1 ° , J. Matonhodze2 , J. Gilleen1 , J. Boydell1 , D. Taylor2 , G. Szmukler1 , T.J. Lambert3 , A.S. David1 . 1 Institute of Psychiatry King’s College London, Division of Psychological Medicine, London, United Kingdom; 2 South London and Maudsley NHS Foundation Trust,