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PREDICTORS FOR THE FORMATION OF DYSTHYMIC DISORDERS

Authors: Sultanov Sh.; Talimbekov, O.; Khodjaeva, N.; Abdullaeva, V.;

PREDICTORS FOR THE FORMATION OF DYSTHYMIC DISORDERS

Abstract

References: 1. Abdullaeva V.K., Abbasova D.S., Sultonova K.B. et al. Predict depressive disorders at the earliest stages of its formation in adolescents // Annali d/ Italia - 2020. - VOL 1, № 7; pp 15-18. 2. Andrews G. et al. Why does the burden of disease persist. Relating the burden of anxiety and depression to effectiveness of treatment // Bull. WHO. - 2000. - Vol. 78, № 4. - P. 446–454. 3. Abdullaeva V.K, Nurkhodjaev S.N. Optimization of Therapy of Treatment Resistant Depressions in patients taking into account Personal Characterestics. Jornal of Research in health science, 67-72,2019. 4. Ballenger J. Risk factors for chronic depression - A systematic review. Year Book of Psychiatry & Applied Mental Health. 2012;2012:277–278. 5. Cassano G. B., Maggini C., Akiskal H. S.: Short-term subchronic and chronic sequelae of affective disorders. Psychiatric Clinics North America 2017. Vol. 6. P. 55-68. 6. Helmhen H. Diagnostic dilemmas and difficulties in elderly depressed patients / H. Helmhen // The elderly person as a patient / Ed. P. Kielcholz, C. Adams. Koln : Deutsch Arte-Verlag, 1986. - P. 100-105. 7. Hölzel L, Härter M, Reese C, Kriston L. Risk factors for chronic depression - a systematic review. Journal of affective disorders. 2011;129(1–3):1–13. 8. Ivanets N.N., Kinkulkina M.A., Tikhonova Y.G., Izyumina T.A. Venlafaxine in the treatment of moderate and severe depression: approaches to increasing treatment efficacy. Neuroscience and Behavioral Physiology. 2016. Т. 46. № 5. С. 529-533. 9. Keller M. B., Sessa F. Dysthymia: development and clinical course. In: Burton S., Akiskal H. (eds.): Dysthymic Disorder. Gaskell, Royal College of Psychiatrists- 2015.- P. 13-23. 10. Köhler S., Chrysanthou S., Guhn A., Sterzer P. Differences between chronic and nonchronic depression: Systematic review and implications for treatment. Depression and anxiety. 2019;36(1):18–30. 11. Melrose S. Persistent Depressive Disorder or Dysthymia: An Overview of Assessment and Treatment Approaches Open Journal of Depression. 2017;(6)1–13. 12. Nurkhodjaev S., Babarakhimova S., Abdullaeva V. Early Detection and Prevention of Suicidal Behavior in Adolescents – Indian Jornal of Forensic medicine & Toxicology. VOL 14, № 3(2020) pp.7258-7263 13. Sultanov Sh.H., Tursunkhodzhaeva L.A., Khodzhaeva N.I., Abdullaeva V.K., Nurkhodjaev S.N. Diagnostics of Dysthymic Disorders and Therapy of Patients with Opium Addiction with Anxiety-Depressive Variant of Post-Withdrawal Syndrome // International Journal of Current Research and Review, Vol 12, Issue 23, 142-147, 2020. 14. Thapar A., Collishaw S., Pine D.S., Thapar A.K. Depression in adolescence. The Lancet. 2012;379(9820):1056–1067. 15. Vasila K. Abdullaeva, Botir T. Daminov, Abdulaziz A. Nasirov, Janna T. Rustamova, Yen., 2020. Features of affective disorders and compliance of patients with chronic renal failure receiving replacement therapy by hemodialysis. International Journal of Pharmaceutical Research No. 4(12). - P.531-535. 16. Visentini C, Cassidy M, Bird VJ, Priebe S. Social networks of patients with chronic depression: A systematic review. Journal of affective disorders. 2018;241:571–578.

Abstract The article analyzes the premorbid factors in the formation of dysthymic disorders, the clinical polymorphism of which is determined by mild manifestations of depressive disorders, the conditions for its formation and genesis, in which the leading role belongs to the combined influence of constitutional-biological and psychogenic factors.

Keywords

affective pathology, dysthymia, depression, premorbid factors

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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