The effect of citalopram on the psychophysiological parameters of patients with nonpsychotic depressive disorders

Background. There is no systematic data on the effect of antidepressant therapy on the indicators of the psychophysiological state of patients with nonpsychotic depressive disorders. The role of emotional changes in the regulation of mental and physiological processes and adaptive behavior has not been sufficiently studied. Consideration of psychophysiological parameters during the course of antidepressant therapy, based on the example of an analysis of the effect of citalopram, allows us to refine a personalized treatment plan for patients.
Objective. To establish the clinical, psychophysiological and therapeutic interdependence of the characteristics of manifestations of stressfrustration reactions, aggression and aggressiveness in patients with non-psychotic depressive disorders on the background of course therapy with citalopram, which is one of the most effective "model" antidepressants from the group of selective serotonin reuptake inhibitors.
Materials and methods. A two-fold comprehensive systemic clinical and psychophysiological study of the condition of 107 patients with nonpsychotic depressive disorders with a predominance of anxiety, asthenic and hysterical clinical variants was conducted before the start of treatment (background) and upon the onset of a pronounced clinical effect (after 6-8 weeks of therapy). The traditional clinical and psychopathological analysis was used, supplemented by the method of multivector analysis (Yu. A. Alexandrovsky). The psychophysiological status of the patients was assessed using the automated diagnostic system "Multipsychometer" (MPM-05), taking into account the standardized population indicators of each of the methods. The battery of tests included: a set of methods for evaluating thinking, tests of verbal and nonverbal intelligence, nonverbal and mathematical intelligence, frustration, the Bass – Darkey aggression and aggression questionnaire, and the MMPI clinical and typological personality test.
Conclusion. Course therapy with citalopram in the studied group of patients with nonpsychotic depressive disorders leads to a positive transformation of psychophysiological indicators of aggression and aggressiveness with its positive therapeutic effect on clinical, pathopsychological and pathological symptom complexes of depressive disorders of the neurotic level. During citalopram therapy, a group of patients with negative therapeutic dynamics of psychopathological manifestations and an increase in stress-frustration reactions of an impunitive nature were identified. There is no systematic data on the effect of antidepressant therapy on the indicators of the psychophysiological state of patients with nonpsychotic depressive disorders. Their violations of perception and evaluation of incoming information, the role of emotions in the regulation of mental and physiological processes and adaptive behavior have not been sufficiently studied. Consideration of psychophysiological parameters during the course of antidepressant therapy, based on the example of an analysis of the effect of citalopram, allows us to justify a personalized treatment plan for patients.

1. Aleksandrovskii Yu. A. States of mental maladaptation and their compensation. M.: Nauka; 1976:272. EDN YMGED. (InRuss.).(In Russ.)

2. Mosolov S. N., Avedisova А. S., Nemkova E. S. Use of original and generic fluvoxamine in clinical psychiatric and neurological practice for the treatment of depression. Sovremennaya terapiya psikhicheskih rasstroistv. 2025; 2: 38-45. DOI: 10.48612/psyph/zph4-2e1n-8h9r. (In Russ.)

3. Ma S.-N., Liu X.-H., & Cai W.-S. Preventive noninvasive vagal nerve stimulation reduces insufficient sleep-induced depression by improving the autonomic nervous system. Biomedicine & Pharmacotherapy. 2024; 173, 116344. https:// doi.org/10.1016/j.biopha.2024.116344.

4. Valenza G. Depression as a cardiovascular disorder: central-autonomic network, brain-heart axis, and vagal perspectives of low mood. Front. Netw. Physiol. 3:1125495. doi:10.3389/fnetp.2023.1125495.

5. Yanushko M. G., Shamanina M. V. Factors and Cognitive Deficits in Recurrent Depression: The Search for Pathogenetic and Therapeutic Targets. Sovremennaya terapiya psikhicheskih rasstroistv. 2024; DOI: 10.21265/PSYPH.2024.61.34.003 (In Russ.)

6. Nelson J. Cю, Gandelman J. A., Mackin R. S. A Systematic Review of Antidepressants and Psychotherapy Commonly Used in the Treatment of Late Life Depression for Their Effects on Cognition. J Geriatr Psychiatry. 2025; 33 (3): 287-304. DOI: 10.1016/j.jagp.2024.08.015. Epub 2024 Sep 6.

7. Serretti A., Kasper S., Bartova L., et al. Clinical predictors of treatment resistant depression. European Neuropsychopharmacology. 2025; 98: 26-34.

8. Yafei Wu, Chongtao Wei, Yaheng Zhang, Chenming Gu, Ya Fang. Investigating intrinsic and situational predictors of depression among older adults: An analysis of the CHARLS database. Asian Journal of Psychiatry. 2024; 102: 5-11. https://doi.org/10.1016/j.ajp.2024.104279.

9. Lapin I. A., Rogacheva T. A., Mitrofanov A. A., Mosolov S. N. Biotyping of Depressions Based on Electroencephalographic Parameters of Imaginary Coherence. Sovremennaya terapiya psikhicheskih rasstroistv. 2022; 2: 11-26. DOI: 10.21265/PSYPH.2022.45.34.002. (In Russ.)

10. Mendelevich V. D., Koroleva P. V., Nesterina M. K. Suicide and Selfharm Resulting from Antidepressants: Facts and Interpretations. Sovremennaya terapiya psikhicheskih rasstroistv. 2024; 3: 70-76. DOI:10.21265/PSYPH.2024.87.39.00. (In Russ.)

11. Taşci G., Kaya Ş., Korkmaz S., Atmaca M. Peripheral Inflammatory Parameters in Patients with Antisocial Personality Disorder. Arch Neuropsychiatry 2022; 59: 38-43. https://doi.org/10.29399/npa.22739.

12. Mikheenkova N. M., Ryvkin P. V., Mosolov S. N. Serotonin Syndrome: Clinical Aspects, Pathophysiology and Treatment. Sovremennaya terapiya psikhicheskih rasstroistv. 2022; 2: 53-63. DOI: 10.21265/PSYPH.2022.90.61.006. (In Russ.)

13. Khasanova A. K., Mosolov S. N. Antidepressant Withdrawal Syndrome (Algorithm for the Prevention and Management). Sovremennaya terapiya psikhicheskih rasstroistv. 2023; 2: 37-47. DOI: 10.21265/PSYPH.2023.15.79.005. (In Russ.)

14. Qi Wang, Li Li, Hongyan Zhao, Wenwen Cheng, Gang Cui, Lin Fan, Xiaomei Dong, Tianchao Xu, Zhongli Geng. Predictors of response to accelerated rTMS in the treatment of treatment-resistant depression. European Archives of Psychiatry and Clinical Neuroscience. 2025; 275: 1725-1736. https://doi.org/10.1007/s00406-024-01903-y