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ORIGINAL ARTICLE |
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Year : 2016 | Volume
: 37
| Issue : 3 | Page : 174-179 |
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A study of opioid dependence among Mansoura University students
Rehab M Mahgoub MBBCh, MSc 1, Mohamed A El-Hadidy2, Mohamed F Abo El Hoda2, Mohamed H Atrouny2
1 Psychiatry Department, Mansoura University Student’ Hospital, Faculty of Medicine, Mansoura University, Mansoura, Egypt 2 Psychiatry Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt
Date of Submission | 29-Aug-2016 |
Date of Acceptance | 19-Sep-2016 |
Date of Web Publication | 13-Dec-2016 |
Correspondence Address: Rehab M Mahgoub Psychiatry Department, Mansoura University Student’ Hospital, Faculty of Medicine, Mansoura University, Mansoura, 35511 Egypt
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/1110-1105.195548
Background The prevalence of opioid dependence is increasing in the world and in Egypt among university students, which because of many false concepts being adopted. Objectives This study was conducted to detect the prevalence and the effects of opioid dependence among a sample of Mansoura University students. Participants and methods The study was carried out on 700 male students, aged 18–25 years. All students were assessed using semistructured interview and urine drug screening. Students were divided into three groups: the first group comprised 300 students who were not drug users, the second group comprised 300 polysubstance users, and the third group comprised 100 solitary opioid users. The first and third groups were subjected to psychometric assessment using Mini Neuropsychiatric Interview for substance dependence, Arabic version. Psychometric assessment was performed with the following tools: Wisconsin Card Sorting Test, Hamilton rating scale for depression, and PANSS positive and negative symptom scale; laboratory investigations included liver function tests and kidney function test. Results We found that out of 100 students who were opioid users, 88 students used tramadol and 12 used heroin. Liver and renal functions were nearly normal in cases, with a high statistically significant difference between cases and controls regarding serum glutamic oxaloacetic transaminase (SGOT), serum glutamic-pyruvic transaminase (SGPT), and creatinine. Higher scores for Hamilton scale for depression and trail A and B mean values were found in cases compared with controls. Conclusion The prevalence of tramadol dependence among Mansoura University students is higher than heroin dependence. In addition, opioid dependence has a negative biological and psychiatric sequelae, which is contrast to the false concepts of opioid dependence.
Keywords: Cognitive function, creatinine, depression, false concepts, liver function, opioids
How to cite this article: Mahgoub RM, El-Hadidy MA, Abo El Hoda MF, Atrouny MH. A study of opioid dependence among Mansoura University students. Egypt J Psychiatr 2016;37:174-9 |
How to cite this URL: Mahgoub RM, El-Hadidy MA, Abo El Hoda MF, Atrouny MH. A study of opioid dependence among Mansoura University students. Egypt J Psychiatr [serial online] 2016 [cited 2023 Dec 10];37:174-9. Available from: https://new.ejpsy.eg.net//text.asp?2016/37/3/174/195548 |
Introduction | |  |
Substance dependence is a social international problem. In Egypt, since the 1970s there has been a great increase of substance dependence (Hamdi et al., 2016). According to the WHO (WHO, 2010), the prevalence of drug dependence in individuals between 15 and 64 years of age in Egypt was 0.8%. In recent studies, opioids were the substances of major problem in 44% of the substance dependence cases (tramadol tablets were the main dependence substances in 30% of the sample, heroin in 12%, and nalbuphine in 2%) (Mohamed et al., 2013; Mohamed et al., 2015).
In the Middle East region, tramadol dependence has increased, particularly in Iran (Nazarzadeh et al., 2014) and Egypt (Abolmaged et al., 2013). The prevalence of lifetime tramadol misuse among Iranian adolescents was 4.8% (Nazarzadeh et al., 2014). In Egypt, it was found that 20% of Egyptian male students have used drugs (Soueif et al., 1986): 5% hashish dependence, 1% opiate dependence, 2.5% tranquilizer dependence, 1.5% stimulant dependence, and 2.15% hypnotics dependence (Soueif et al., 1990). The last Egyptian National Survey report shows that 8.6% of Egyptians used drugs at least once during their lives (Hamdi et al., 2013). Tramadol dependence has markedly increased in Egypt since 2008 (Abolmaged et al., 2013). The mean age of the heroin addicts’ first-time use of heroin was 19.67 years. Kumar et al. (1996) reported that 7% of the heroin users started heroin at an age younger than 17 years, and about 83% of them began to use heroin between the ages of 16 and 24.
Drug dependence was significantly higher among individuals between 18 and 25 years of age (44%) than among those between 26 and 40 years of age (EL-Sherbiny, 2015). An Egyptian study shows that tramadol dependence starts as follows: 21% of the patients started tramadol dependence for its pleasurable effect (to improve mood), 20% of the patients for sexual purpose (prolongation of the time of intercourse), 14.1% to get more power for hard work (to delay feeling fatigue), 13% for pain relief, 12% as self-medication to relieve depression, 11% as self-medication to relive anxiety, 9.5% because of peer pressure, and 4.5% for other purposes (Mohamed et al., 2015).
Chronic use of opioids leads to impairment in learning and memory because of their effect on the frontal cortex (Yang et al., 2009) and the hippocampus (Lu et al., 2010). Havard et al. (2006) reported that the prevalence of depression among opiate addicts, depending on the population, setting, and recall period, ranges between 15 and 45%.
Ilic et al. (2010) had reported that heroin dependence induces vesicular and fatty changes in the liver tissue. Another study showed that tramadol was found to significantly increase SGOT and SGPT among its users, and serum aminotransferase levels can be elevated in a small proportion of patients receiving tramadol at high doses (Loughrey et al., 2003).
Rationale of the study
We hypothesize that opioid dependence has negative effects on psychological functions (cognitive, mood, and psychosis) and liver and/or renal functions among university students.
Participants and methods | |  |
Study design
This is a cross-sectional study and a control study.
Site of the study
This study was conducted in Mansoura University Students’ Hospital.
Participants
All students (n=700) who came to the psychiatric clinic of Mansoura University Students’ Hospital in 6 months duration were subjected to urine screening for drugs. Out of 700 screened students, 43% (n=301) were negative for drug use, 42.8% (n=299) were multidrug addicts, 12.2% (n=86) were tramadoladdicts, and 2% (n=14) were heroin addicts. A total of 100 students fulfilling the criteria for diagnosis of solitary opioid dependence matched with 100 healthy control individuals as regards age and sex. Informed written consent was obtained from all subjects after explanation of the procedures.
Inclusion criteria for the patient group
Patients were recruited from the outpatient clinic of Psychiatry Department at Mansoura University Students’ Hospital, according to the criteria of opioid dependence of DSM-IV-TR. Male individuals were aged from 18 to 25 years old.
Exclusion criteria
Exclusion criteria included other drug use or polysubstance use, cases that have any hepatic or renal illness before the use of drugs or because of any other causes (viral hepatitis), or cases taking any other drugs that affect renal or hepatic function.
Inclusion criteria for controls: Controls were recruited from the attendants coming to medicine clinics at Mansoura University Students’ Hospital (for medical fitness before they could join certain sports or gym). Cases with no history of psychiatric or neurological diseases and those who do not have any hepatic or renal diseases were included in the study. Controls included people of both sexes and same age range between 18 and 25 years. All were subjected to the same scales and tools of the case group.
Assessment tools
- Clinical assessment of the patients: A semistructured interview was conducted, which included the following − detailed history taking and thorough clinical examination using Mansoura University Hospital psychiatric sheet and Mini Neuropsychiatric Interview for substance dependence Arabic version (Sheehan et al., 1998), and complete thorough physical and neurological examinations.
- Psychometric assessment: This included Wisconsin Card Sorting Test (WCST) (Heaton et al., 1993), trail making cognitive test (Reitan, 1958), Hamilton rating scale for depression (Hamilton, 1960), and PANSS positive and negative syndrome scale (Kay et al., 1987).
- Laboratory: Laboratory investigations included liver function tests (SGOT) and (SGPT) levels, as well as renal function test.
All data were collected, tabulated, and statistically analyzed using SPSS 20.0 for Windows (SPSS Inc., Chicago, Illinois, USA).
This study was approved by Ethical Committee at Mansoura University, Faculty of Medicine.
Results | |  |
[Table 1] shows that the studied groups were matched regarding age and sex, with a mean age of 22.29 and 22 years, respectively, for cases and control. All participants were male. Opioid dependence was more frequent in rural areas than in urban areas.
[Table 2] shows that there was a high statistically significant difference between cases and controls regarding SGOT, SGPT, and creatinine, with higher mean values in cases than in controls (38.8, 38.03, and 0.79 for cases vs. 36.8, 37.4, and 0.65 for controls). In spite of this difference, very few cases showed an abnormal level of SGOT and SGPT without a statistically significant difference between cases and controls.
[Table 3] shows that there was a high statistically significant difference between cases and controls regarding mean Hamilton scale for depression score and its grouping, with higher mean score in cases than in controls (11.92 and 8.32, respectively). Mild depression was higher among controls, whereas moderate depression presented in cases.
[Table 4] shows a statistically significant weak positive correlation between trail making test, PANSS scores, and Hamilton scale for depression score in cases, whereas Wisconsin card sorting score shows a statistically significant weak negative correlation with Hamilton scale for depression score in the control group. | Table 4 Correlation of Hamilton score with age, PANSS, trail making test, and Wisconsin Card Sorting Test scores
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[Table 5] shows that the Hamilton scale for depression score, PANSS test positive and negative symptom scores, trail A, trail B, and preservative response were statistically significant predictors for cases, with the total percentage predicted to be 99.5%.
Discussion | |  |
As the international society is striving to increase the social awareness about dependence − especially opioid dependence − this study was conducted to highlight the problem of opioid dependence being a great social and international concern in an alarming phenomenon, especially the use of tramadol with a lot of wrong concepts about its effects. In our search, we focused on the effects of opioid dependence (tramadol and heroin), as they have great social, physical, and neuropsychological consequences (Gruber Staci et al., 2007). Therefore, this study was conducted to reveal the effects of opioid dependence on the cognitive functions, psychiatric effects, and physical effects (liver and renal functions), as well as to know about the prevalence of opioid dependence among university students and to have a comparison between tramadol and heroin dependence in a sample of university students.
We found that 43% of cases were positive for multidrug and other drug use, 12% were positive for tramadol use, and 2% were positive for heroin use. This result is in agreement with another study, which reported that about 43.94% (n=145) of the patients were under polysubstance use, whereas the percentages of patients who used one substance were as follows: tramadol, 30.30% (n=100); and heroin, 11.52% (n=38) (Mohamed et al., 2015). In contrast to our study (Bassiony et al., 2015), another study stated that tramadol dependence is more prevalent than other drugs, and this may be because of the different age range. From these results, we found that tramadol is more addictive than heroin, and these results were supported by the study by Fawzy (2010) who reported that tramadol is associated with an increased probability of being addicted, as it is more accessible and cheaper than heroin, its price is lower, its availability without prescription makes it easy to obtain, and also because of the false concept about tramadol as they consider it as a treatment for premature ejaculation and to increase sexual orgasm, and as it lowers depressive criteria in relation to stresses, such as headaches and relieve back aches to increase the productivity. It was stated by epidemiological reports that tramadol dependence has increased in the USA, and recently in (Dare et al., 2011) Iran (Nazarzadeh et al., 2014) and Egypt (Abolmaged et al., 2013).
The sociodemographic data of the two groups (opioid dependences and control) showed that the studied groups were matched regarding age and sex, with a mean age of 22 years. Other studies are in harmony with our results showing that the mean age of the heroin addicts’ first-time use of heroin was 22±4 years old (Mohamed Mosad Salama et al., 2015).
In agreement with our study, a study reported the highest prevalence of substance abuse among persons to be between 18 and 25 years of age (Hamdi et al., 2013).
Cases were more frequent in rural areas than in urban areas, without a statistically significant difference between cases and controls. In contrast, one study suggested (Hamdi et al., 2013) that opioid abuse is less prevalent in rural areas. This difference may be because the university students attending to the psychiatric clinic in university student’s hospital are from rural areas and cannot go to private clinics, and the urban students prefer going to private clinics.
The renal and liver functions were within normal ranges in the two groups but significantly higher in cases than in controls (high normal). These results were supported by a recent study in rats, which reported a significant increase in the levels of liver functions enzymes and creatinine as a result of chronic use of opioids, and these findings suggest the possible hepatotoxic effects of opioids (morphine and tramadol) in the long term (Atici et al., 2005). A more recent study by El-Hadidy and Helaly (2015) in humans documented that the liver function enzymes were within normal limits; however, a slight nonsignificant rise in liver enzymes was reported in some cases.
The current study showed that a higher mean score of Hamilton scale of depression was found in cases than in the control group, with a high statistically significant difference. Moderate depression was more frequent among heroin addicts and mild depression was more frequent among tramadol addicts. This is in agreement with that found by El-Hadidy and Helaly (2015), who reported that depression scores were higher with a statistically significant difference after stopping tramadol use than before the treatment, as tramadol has a mechanism of action by which it increases serotonin, norepinephrine, and 5/HT2-C antagonist receptors and this results in improvement in the depressive symptoms. Another study supports our results, reporting that depression is more prevalent in heroin users and is higher than in the general population (Havard et al., 2006).
Moreover, in this study, the severity of depressive symptoms assessed with the Hamilton scale of depression was one of the predictors of opioid dependence. This result is consistent with another study (Boscarino et al., 2010). The other important predictor for opioid dependence was PANSS scores (positive and negative symptoms scores). Many contradictory studies have been established related to this issue. For example, one study (Dervaux et al., 2001) reported no relationships between the severity of symptoms and substance dependence, whereas Pencer and Addington (2003) reported that substance use was associated with more severe positive symptoms. After that Talamo et al. (2006) adopted the hypothesis that cases with comorbid disorders had more positive versus negative symptoms than cases with no comorbidity, and both studies are in agreement with our current study.
A great number of models were proven to explain the association between substance dependence and psychotic symptoms, and the most agreed one is self-medication hypothesis (Khantzian, 1997), which states that substance abuse disorder is an extension of psychotic disorder to decrease their symptoms, especially opioids, as opioids have an antipsychotic effect. Besides, there are models that suggest that schizophrenia (Gottesman and Shields, 1976) and substance use disorder (Rhee et al., 2003) stem from the same genetic load.
In the current study, we found group differences regarding neurocognitive assessments by using WCST and trail test. The psychometric properties of WCST were examined using factor analytic techniques by several studies. By applying these factors to our results, we found that there was poor performance across the parameters of factors 1 and 3 in cases (indicating deficits in concept formation, flexibility, memory, and attention). Better performance was found in factor 2, which represents problem-solving. This comes with what was reported by another study (Soyka et al., 2011), which states that chronic opiate abuse, such as heroin and morphine, is found to harm cognitive function. Other studies suggested that chronic opiate dependence has effects on brain points related to learning and memory, such as the frontal cortex (Yang et al., 2009) and the hippocampus (Lu et al., 2010). On the contrary, other studies (Guerra et al., 1987) found that there was no difference between heroin dependences and controls with regard to neuropsychological measures. This may be explained by the dose and duration of the opioid dependence in this study and different methodological tools. Some studies have found that the performance in heroin dependence was the same as the control group (Rohlinga et al., 2002), or that some areas of cognitive function are spared relative to others.
This study also reveals that the cognitive function is negatively correlated with depressive symptoms and age, and this was in agreement with many studies, one of which was the study by Gould Thomas (2010), who stated that depressed mood was associated with decreased performance on measures of memory. Moreover, this study found that cognitive function is a good predictor for substance dependence in general, and opioid dependence. We found that there was a positive correlation between trail making test part A and B scores and opioid dependence, which means that cognitive dysfunction predicts opioid dependence, and this is in agreement with the study by Gould Thomas (2010).
Conclusion | |  |
We found that polysubstance dependence is more prevalent in university students. Tramadol dependence is more prevalent among students than heroin dependence. Opiate dependence was associated with severe depression and deterioration of cognitive function. Depressive symptoms and cognitive dysfunction can predict opioid dependence.[39]
Limitations of the study | |  |
This study is limited by the small sample size. Consequently, the participants might not be representative of Mansoura University students. In addition, the denial of students in this study decreases our chances of detecting the prevalence of dependences. Besides, the young age of the case group decreased our chance to detect sexual effects of opioid dependence, as they are not married.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References | |  |
1. | Abolmaged S, Kodera A, Okasha T, Gawad T, Rawson R (2013). Tramadol use in Egypt: emergence of a major new public health problem. Can J Addict Med 4:5. |
2. | Atici S, Cinel I, Cinel L, Doruk N, Eskandari G, Oral U (2005). Liver and kidney toxicity in chronic use of opioids: an experimental long-term treatment model. J Biosci 30:245–252. |
3. | Bassiony MM, Salah El-Deen GM, Yousef U, Raya Y, Abdel-Ghani MM, El-Gohari H, Atwa SA (2015). Adolescent tramadol use and abuse in Egypt. Am J Drug Alcohol Abuse 41:206–211. |
4. | Boscarino JA, Rukstalis M, Hoffman SN, Han JJ, Erlich PM, Gerhard GS, Stewart WF (2010). Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system. Addiction 105:1776–1782. |
5. | Dare RC, Dasgupta N, Bailey JE, Spiller HA (2011). Interpreting poison center call volume associated with tramadol. Ann Pharmacother 45:424. |
6. | Dervaux A, Baylé FJ, Laqueille X, Bourdel M, Le Borgne M, Olié J et al. (2001). Is substance abuse in schizophrenia related to impulsivity, sensation seeking, or anhedonia? Am J Psychiatry158:492–494. |
7. | Elmorsy E, Salama MM, Abdelsalam M, Nwidu LL, Zaki MES, El-Bendary M et al. (2015). Liver functions derangement among substances abusers. Int J Med Phar Sci 6(3):19. |
8. | EL-Sherbiny AAM (2015). Drug abuse among patients of Tanta university hospital outpatient clinic, Gharbia governorate, Egypt. Tanta Med J 43:82–88. |
9. | El-Hadidy MA, Helaly AMN (2015). Medical and psychiatric effects of long-term dependence on high dose of tramadol. Substance use & misuse, 50(5):582–589. |
10. | Fawzy MM (2010). Some medicolegal aspects concerning tramadol abuse: the new Middle East youth plague . Egypt J Forensic Sci 1:99–102. |
11. | Gottesman II, Shields JA (1976). A critical review of recent adoption, twin and family studies of schizophrenia: behavioural genetics perspectives. Schizophr Bull 2:360–401. |
12. | Gould Thomas J (2010). Addiction and cognition. Addict Sci Clin Pract 5:4–14. |
13. | Gruber Staci A, Silveri Marisa M, Yurgelun-Todd DA (2007). Neuropsychological consequences of opiate use. Neuropsychol Rev 17:299–315. |
14. | Guerra D, Sole A, Cami J, Tobena A (1987). Neuropsychological performance in opiate addicts after rapid detoxification. Drug Alcohol Depend 20:261–270. |
15. | Hamdi E, Gawad T, Khoweiled A, Sidrak AE, Amer D, Mamdouh R et al. (2013). Lifetime prevalence of alcohol and substance abuse in Egypt: a community survey. Subst Abuse 34:97–114. |
16. | Hamdi E, Sabry N, Sedrak A, Khowailed A, Rabie LN, Ramy H (2016). Addiction. J Addict Prev 4:1. |
17. | Hamilton M (1960). A rating scale for depression. J Neurol Neurosurg Psychiatry 23:56–62. |
18. | Havard A, Teesson M, Darke S, Ross J (2006). Depression among heroin users: 12-month outcomes from the Australian Treatment Outcome Study (ATOS). J Subst Abuse Treat 30:355–362. |
19. | Heaton RK, Chelune GJ, Talley JL, Kay GG, Curtiss G (1993). Wisconsin Card Sorting Test manual: revised and expanded. Odessa, FL: Psychological Assessment Resources. |
20. | Ilic G, Karadzic R, Kostic-Banovic L, Stojanovic J, Antovic A (2010). Ultrastructural changes in the liver of intravenous heroin addicts. Bosnian J Basic Med Sci 10:38–43. |
21. | Kay SR, Abraham F, Opfer LA (1987). The Positive and Negative Syndrome Scale (PANSS) for schizophrenia. Schizophr Bull 13:261–276. |
22. | Khantzian EJ (1997). The self-medication hypothesis of substance use disorders: a reconsideration and recent applications. Harv Rev Psychiatry 4:231–244. |
23. | Kumar S, Wairagkar NS, Mahanta J, Satyanarayana K, Chetial M, Phukan RK, Goswami SK (1996). Profile of heroin addicts in Nagaland, India. Southeast Asian J Trop Med Public Health 27:768–771. |
24. | Loughrey MB, Loughrey CM, Johnston S, O’Rourke D (2003). Fatal hepatic failure following accidental tramadol overdose. Forensic Sci Int 134:232–233 |
25. | Lu G, Zhou QX, Kang S, Li QL, Zhao LC, Chen JD et al. (2010). Chronic morphine treatment impaired hippocampal long-term potentiation and spatial memory via accumulation of extracellular adenosine acting on adenosine A1 receptors. J Neurosci 30:5058–5070. |
26. | Mohamed NR, Hammad SA, El Hamrawy LG, Rajab AZ, El Bahy MS, Soltan MR (2013). Dual diagnosis and psychosocial correlates in substance abuse in Menoufia. Egypt Menoufia Med J 26:114–121. |
27. | Mohamed NlR, El Hamrawya LG, Shalabya AS, El Bahya MS, Abd Allahb MM (2015). An epidemiological study of tramadol HCl dependence in an outpatient addiction clinic at Heliopolis Psychiatric Hospital. MMJ 28:591–596. |
28. | Nazarzadeh M, Bidel Z, Carson KV (2014). The association between tramadol hydrochloride misuse and other substances use in adolescent population: phase I of a prospective survey. Addict Behav 39:333–337. |
29. | Pencer A, Addington J (2003). Substance use and cognition in early psychosis. J Psychiatry Neurosci 28:48–54. |
30. | Reitan RM (1958). The validity of the Trail Making Test as an indicator of organic brain damage. Percept Mot Skills 8:271–276. |
31. | Rhee SH, Hewitt JK, Young SE, Corley RP, Crowley TJ, Stallings MC (2003). Genetic and environmental influences on substance initiation, use, and problem use in adolescents. Arch Gen Psychiatry 60:1256–1264. |
32. | Rohlinga ML, Greenb P, III L, Iversond GL (2002). Depressive symptoms and neurocognitive test scores in patients passing symptom validity tests. Arch Clin Neuropsychol 17:205–222. |
33. | Sheehan DV, Lecrubier Y, Harnett-Sheehan K, Amorim P, Janavs J, Weiller E et al. (1998). The Mini International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview. J Clin Psychiatry 59(Suppl 20):22–33. |
34. | Soueif MI, Yunis FA, Taha HS (1986). Extent and patterns of drug abuse and its associated factors in Egypt. Bull Narc 38:113–120. |
35. | Soueif MI, Youssuf GS, Taha HS, Moneim HA, Sree OA, Badr KA et al. (1990). Use of psychoactive substances among secondary school students in Egypt: a study on a nationwide representative sample. Drug Alcohol Depend 26:63–79. |
36. | Soyka M, Limmer C, Lehnert R, Koller G, Martin G, Küfner H et al. (2011). A comparison of cognitive function in patients under maintenance treatment with heroin, methadone, or buprenorphine and healthy controls: an open pilot study. Am J Drug Alcohol Abuse 37:497–508. |
37. | Talamo A, Centorrino F, Tondo L, Dimitri A, Hennen J, Baldessarini RJ (2006). Comorbid substance-use in schizophrenia: relation to positive and negative symptoms. Schizophr Res 86:251–255. |
38. | |
39. | Yang Z, Xie J, Shao YC, Xie CM, Fu LP, Li DJ et al. (2009). Dynamic neural responses to cue-reactivity paradigms in heroin-dependent users: an fMRI study. Hum Brain Mapp 30:766–775. |
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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