Algorithms of diagnosis and therapy of a primary depressive episode

Abstract

Depressive disorders are among the most widespread forms of mental pathology with significant medical and social consequences and require adequate and timely medical assistance. It is known that algorithms are effective methods of optimizing the provision of psychiatric care in order to prevent the development of therapy-resistant forms of mental pathology and reduce their treatment costs, which is particularly relevant in the case of a primary depressive episode (PDE). The aim of the work is to develop algorithms for rapid diagnosis and therapy of the PDE. Materials and methods. During 2018–2021, 131 patients (49 men and 82 women) with the PDE who sought outpatient psychiatric help were clinically examined. All subjects were tested to determine the level of depressive disorder, according to the unified clinical protocol of highly specialized medical care, according to the Hamilton Rating Scale for Depression, Hamilton Anxiety Rating Scale, and the Clinical Global Impressions Scale. The clinical-ethological description consisted of three stages: at the first stage, at a patients’ first visit, a general description within the framework of a clinical and psychopathological examinations; at the second stage, the clinical-ethological characteristics of non-verbal behavior were studied; at the last, third stage, non-verbal behavior was recoded into ethological elements according to A. A. Korobov’s glossary (1991). Statistical analysis was performed using the Statistica 10 license package of application programs. Results. An algorithm for the PDE diagnosis has been developed based upon four stages: the first one – the symptomatic state diagnosis; the second – clinical-ethological analysis of depressive phenomenon signs and a neurophysiological electroencephalographic (EEG) examination; the third – psycho-experimental examinations using appropriate tools; the fourth – structuring of the obtained diagnostic data, diagnosis verification and development of therapeutic intervention tactics. A therapeutic algorithm for the PDE treatment was also developed and proposed: at the first stage – use of existing antidepressants with proven clinical effectiveness; at the second – switching from a drug in case of its ineffectiveness within 3–4 weeks to another drug with a different mechanism of action; at the third – in case of the previous stage ineffectiveness, using a combination antidepressant therapy (combining drugs of different groups); at the fourth – application of therapeutic schemes using diuretics, pathogenetic psychotherapy and electroconvulsive therapy. Conclusions. The proposed diagnostic and treatment algorithms are reliable enough to detect and treat such a category as the primary depressive episode. The effectiveness of personalized comprehensive diagnostic and treatment methods for these conditions should be based on the principles of phasing, comprehensiveness, using integrated approaches, combining therapies aimed at developing an adequate attitude to a disease state, mitigating the intensity of negative emotions, restoring internal and external resources of patients.