Analiza czynników patogenetycznych
nieprawidłowej adaptacji psychospołecznej
u pacjentów z uzależnieniem od alkoholu

Liliya V. Zhyvotovska

Higher State Educational Establishment of Ukraine, Ukrainian Medical Stomatological Academy, Poltava, Ukraine

АBSTRACT

Introduction: The search for early diagnostic markers of the psychosocial maladaptation formation in alcohol dependence to optimize the treatment, rehabilitation and preventive measures in this cohort of patients is one of the urgent tasks of the contemporary narcology to date.

The aim: The purpose of the paper was to reveal the significant pathogenetic factors for the psychosocial maladaptation formation in patients with alcohol dependence.

Materials and methods: 290 male patients with alcohol dependence, aged 23 to 59 years have been involved into the comprehensive study that has been carried out using the clinicopsychopathological, psychodiagnostic, neuropsychological, biochemical and statistical methods. To determine the characterological features the Leonhard-Schmieschek questionnaire has been used; neuropsychological study has been conducted using the method, developed by O.R. Luria; the level of neuropsychological deficit has been assessed using the І. F. Roschina’s rating scale; the research on social indicators to determine the level of maladaptation has been made using the questionnaire of N.K. Liphardt, V.P. Radchenko; the diagnostics of the states of hormonal regulation of carbohydrate metabolism has been made according to the criteria, developed by Ya. I. Tomashevskii, O.Ya. Tomashevska; statistical data processing has been done using the factor and discriminant analyses.

Results: Multicentric study has been carried out to identify the common peculiarities of the pathogenic mechanisms of the psychosocial maladaptation formation in patients with alcohol dependence, which permitted to distinguish six main factors, i.e., factors of neurocognitive deficit, the state of carbohydrate metabolism, the level of maladaptation, physico-typological features, the clinical manifestations and hereditary load. The findings of the discriminant analysis have defined a list of variables that have the most significant impact on the patient classification according to the groups depending on the stage and physico-typological features, confirming the findings of the multicentric study.

Conclusion: The findings of the research have presented the groups of indices that elucidated the main pathogenetic mechanisms of the maladaptation formation in patients with alcohol dependence. The resulting data complement the existing views on the common pathogenetic mechanisms of the development of alcohol dependence.

 

Wiad Lek 2018, 71, 6, -1192

 

INTRODUCTION

Chronic ethanol intoxication induces the extensive suppression of different structures of the central nervous system, causing the disorganization and impairment of highly integrated processes, including those related to the maintenance of homeostasis, leading to the progression of the disease and adverse health and social outcomes [1-3]. While treating the alcohol dependence in terms of the triad of adaptive reactions, there is an opinion that there are common immanent factors that are ultimately responsible for psychosomatic transformation of negative emotional-and-personal experiences and the formation of the addictive mechanisms of behavior that lead to the pathological addiction to alcohol [4].

At the current stage of the clinical and experimental study of the mechanisms of the alcohol dependence formation it has been found that disorders of the higher forms of adaptive activity, i.e., psychoemotional and psychophysiological adaptation, as well as the dysfunction of the adaptive mechanisms that are localized in the limbic system to determine the functional state of the sympathetic, parasympathetic and neuroendocrine system, are of significant importance [5-7]. The processes of disintegration of the endocrine systems lead to the formation of the human maladaptive states, intensifying the symptomatology of alcohol motivation. With the loss of sociocultural traditions and spiritual values the transition from one psychoemotional state to another can be one of the key mechanisms in the process of the alcohol dependence formation [8, 9]. The search for early diagnostic markers of maladaptation formation in alcohol dependence to optimize the treatment, rehabilitation and preventive measures in this cohort of patients is one of the urgent tasks of the contemporary narcology.

THE AIM

The purpose of the paper was to reveal the significant pathogenetic factors for the development of psychosocial maladaptation in patients with alcohol-related mental and behavioral disorders.

MATERIALS AND METHODS

290 male patients with alcohol dependence, aged 23 to 59 years have been involved into the comprehensive study that has been carried out using the clinicopsychopathological, psychodiagnostic, neuropsychological, biochemical and statistical methods.

The basic clinicopsychopathological method of examination has been applied for the evaluation of patients and identification of features of clinical presentation and progression of pathological process. Nosological diagnostics, i.e., mental and behavioral disorders caused by alcohol use (MBDA), was based on the ICD-10 (F10) criteria. The assessment of the severity of the disease (phase, stage) was based on the classification, developed by F.F. Portnov, І.N.Piatnitska (1971) and M.M. Ivanets [10], in which a traditional clinico-dynamic approach is preserved that reflects a common pathologic model of the progression of chronic diseases. The analysis of social indicators to determine the level of maladaptation using a tailored questionnaire, which contains a description of occupational attitudes (OA), interpersonal relations (IR), the range of interests (RI), measured by the 4-score scale (N.K. Liphardt, V.P. Radchenko, 1982). According to the degree of expressiveness, three alternates for psychosocial maladaptation have been considered: minor (Level I), moderate (Level II) and severe maladaptation (Level III). To determine the characterological features of the subjects the Leonhard-Schmieschek questionnaire (1970) has been used. Neuropsychological study has been conducted using the method, developed by O.R. Luria [11], and the level of neuropsychological deficit has been assessed using the І. F. Roschina’s 5-score rating scale [12].

The study of the carbohydrate metabolism disorders on the model of the functional state of the pyruvate dehydrogenase complex (PDC) has been conducted using the following techniques: determination of the total content of α-keto acids in the night portion of urine; determination of the total content of α-keto acids in the 2-hour portion of urine following a carbohydrate breakfast; the analysis of the pyruvate concentration and PDC activity of the capillary blood within 2 hours after carbohydrate breakfast; determination of the level of blood glucose within 2 hours after carbohydrate breakfast. The diagnostics of the states of hormonal regulation of carbohydrate metabolism has been made according to the criteria, developed by Ya. I. Tomashevskii, O.Ya. Tomashevska [13].

According to ICD-10 criteria, among all examined patients 80 individuals (27.6%) were diagnosed with MBDA and alcohol dependence (F 10.20); 102 individuals (35.2%) were diagnosed with withdrawal state with delirium (F 10.40 – 64, F 10.41-38); 11 individuals (3.7%) were diagnosed with hallucinatory disorder (F 10.52); 14 individuals (4.8%) were diagnosed with delusional disorder (F 10.51); 28 individuals (9.7%) were diagnosed with withdrawal state with convulsions (F 10.31); 23 individuals (7.9%) were diagnosed with withdrawal state without convulsions (F 10.30); 15 individuals (5.2%) were diagnosed with sustained cognitive disorder (F 10.74); 9 individuals (3.1%) were diagnosed with the amnestic syndrome (F 10.6); 8 individuals (2.7%) were diagnosed with dementia (F 10.73). According to the stage of the disease all patients were classified as follows: Stage 1 (initial) – 34 patients (11.7%) and Stage1-2 (transitional) – 46 patients (15.9%); Stage 2 (median) – 125 patients (43.1%); Stage 2-3 (transitional) – 53 patients (18.3%); Stage 3 (terminal) – 32 patients (11.0%). Among the examined patients the Level I of psychosocial maladaptation has been registered in 75 individuals (25.9%) with the following mean indices of the social factors: the OA index was rated with the score of 2.4 and the RI index was rated with the score of 1.8; the Level II has been registered in 147 individuals (50.7%) with the following indices: the OA index was rated with the score of 2.9, the IR index was rated with the score of 2.1, and the RI index was rated with the score of 2.5; the Level III has been registered in 68 individuals (23.4%), where OA index was rated with the score of 3.6, the IR index was rated with the score of 2.9, and the RI index was rated with the score of 3.2. Taking into account the physico-typological features all patients have been assigned into 4 groups: Group I involved 86 individuals (29.7%) with syntonic characterological features; Group II involved 92 individuals (31.7%) with characterological features of the excitable type; Group III involved 59 (20.3%) individuals with asthenic characterological features; Group IV involved 53 (18.3%) individuals with dysthymic characterological features. The groups were representative by the age and socio-demographic indicies.

RESULTS AND DISSCUSION

The multicentric study has been conducted to identify the common features of the pathogenic mechanisms of the maladaptation formation in patients with alcohol dependence. For this purpose the graph of the eigenvalues of the factors (the “scree” graph) (Fig. 1) has been made. The figure shows that 6 factors, which explain over 72% of the population variance, are enough to describe the subject.

Factor loading matrix of the multifactor model is presented in Table I. The Table shows that the factor of neurocognitive deficit explains 25% of the population variance and is associated with the age of beginning and duration of the alcohol abuse, the stage, cognitive impairments and indices of carbohydrate metabolism. Over 17% of the population variance is caused by the factor that characterizes the state of carbohydrate metabolism. It is associated with the duration of the disease, the age of the beginning of the alcohol abuse, the presence of cognitive impairments and delirious states in both the history and during the physical examination, the integral index of the neurocognitive disorders. Over 11% of the population variance is caused by the factor that characterizes the level of maladaptation which closely correlates with the age of the beginning of alcohol abuse, duration of the disease, the presence of cognitive impairments, integral index of neurocognitive disorders, duration of remission, hereditary load of narcological diseases. Over 7% of the population variance is caused by the factor of the physico-typological features, associated with the integral index of the neurocognitive disorders and indices of carbohydrate metabolism. Clinical factor causes 6% of the population variance and demonstrates the close relationship of the acute psychoses and convulsions with cognitive impairments. Factor of the hereditary load explains more than 5% of the population variance and determines the differences in the formation of the physico-typological features of the patients.

The Statistica 8.0 discriminant analysis of the patient classification according to the stages of the disease made by the method of incremental inclusion of the variables permitted to distinguish 8 signs that provide 95% accuracy of the patient classification. The classification matrix is presented in Table II.

In our study the key indices were the age of the beginning of alcohol abuse, duration of the diseases, convulsions and psychoses in the history, including delirium, the state of carbohydrate metabolism, attention impairments, the integral index of the neurocognitive disorders. Close to zero the Wilk’s value (λ = 0.08) and great F = 41.9 (p < 0.0001) statistic value give the evidence of the high capacity of the discriminative functions to identify the groups of classification. The results of discriminant analysis of the patient classification according to the stages of the disease are shown in Table III, and placement of groups of classification in the space of the canonical variables is presented in Fig. 2.

The discriminant analysis of the patient classification according to the groups depending on the physico-typological features made by the method of incremental inclusion of the variables permitted to distinguish 13 signs, providing 76,5% accuracy of the classification of patients. The classification matrix is presented in Table IV.

The results of discriminant analysis of the classification of patients according to the groups depending on the physico-typological features are shown in Table V, and placement of groups of classification in the space of the canonical variables is presented in Fig. 3.

In our study the major indices were the integral index of the neurocognitive disorders, reduced ability of focus, sustains, or shift attention, indices of the working, long-range auditory-and-speech and optospatial memory, the level of pyruvate, the age of beginning of alcohol abuse, the level of maladaptation, cognitive impairments, psychoses and delirious states in both the history and during examination. Close to zero the Wilk’s value (λ=0,15) and F=8,77 (р<0,0001) statistic value give the evidence of the rather high capacity of the discriminative functions to identify the groups of classification.

The list of variables that have the most significant impact on the patient classification according to the groups depending on the stage and physico-typological features also confirms the findings of the multicentric study.

In the summary, it should be noted that findings of the study have revealed the diverse interactions of the investigated indices and their contribution to the maladaptation formation in patients with alcohol dependence. This shows the complexity and multilayered impairments of the processes of psychosocial adaptation under the influence of numerous biological, clinical and social factors.

CONCLUSIONS

Thus, the results of the factor and discriminant analyses permitted to form the groups of indices that elucidated the main pathogenetic mechanisms of the maladaptation formation in patients with alcohol dependence. Such factors are neurocognitive deficit, the state of carbohydrate metabolism, the level of maladaptation, physico-typological features, clinical manifestations and hereditary load. The resulting data complement the existing views on the common pathogenetic mechanisms of the development of alcohol dependence.

REFERENCES

1. Tabachnikov S. I., Haponov K. D. Psykhosotsialni, klinichni ta terapevtychni aspekty suchasnoho patomorfozu alkoholnoi zalezhnosti. Arkhiv psykhiatrii. 2012; T.18,1(68):53-60.

2. Narkolohiia: natsionalnyi pidruchnyk za red. I. K. Sosina, Yu. F. Chuieva. Kharkiv: Kolehium, 2014:33-69.

3. Sanchez R. S., Stephens D. N., Duka D. T. Heightened Impulsivity: Associated with Family History of Alcohol Misuse, and a Consequence of Alcohol Intake. Alcoholism: Clinical and Experimental Research. 2016;30,4: 450-461.

4. Kashirskaya E. I. Mehanizmyi i faktoryi riska formirovaniya narkoticheskoy i alkogolnoy zavisimosti u detey i podrostkov. Narkologiya. 2010;2:75-80.

5. Maruta N. O., Minko O. I. Emotsiini porushennia pry pohranychnykh psykhichnykh rozladakh ta alkoholnii zalezhnosti (diahnostyka ta pryntsypy likuvannia): metodychni rekomendatsii. Kharkiv, 2003. 20.

6. Paykova L. N. Trevozhno-depressivnyie i psihofiziologicheskie pokazateli emotsionalnyih i kognitivnyih narusheniy u bolnyih s addiktivnyim povedeniem. Psihicheskoe zdorove. 2009;2:49-51.

7. Kotov A. V. K prirode fenomena addiktsii v mehanizmah tselenapravlennoy aktivnosti. Psihicheskoe zdorove. 2008;4:57-67.

8. Chernobrovkina T. V., Kershengolts B. M., Artemchuk A. F. Sinergeticheskaya meditsina: teoreticheskie i prikladnyie aspektyi v addiktologii. Harkov: «Pleyada», 2007.240.

9. I. V. Linskyi, M. Yu. Ihnatov. Narkopatolohiia yak «dzerkalo» psykhichnoho zdorovia i hromadskoho blahopoluchchia ukrainskoho suspilstva. Mizhnarodnyi psykhiatrychnyi, psykhoterapevtychnyi ta psykhoanalitychnyi zhurnal. 2007; 1,1:76-84.

10. Ivanets N. N., Vinnikova M. A. Voprosyi klassifikatsii narkologicheskih zabolevaniy. V kn. Rukovodstvo po narkologii; pod red. N. N. Ivantsa. M.: «Medpraktika-M», 2002. T.1: 189-197.

11. Luriya A. R. Vyisshie korkovyie funktsii cheloveka. M.: Akademicheskiy prospekt, 2000. 506.

12. Roschina I. F., Zharikov G. A. Neyropsihologicheskiy metod v diagnostike myagkoy dementsii u lits pozhilogo i starcheskogo vozrasta. Zhurn. nevropatologii i psihiatrii im. S.S.Korsakova. 1998; 98,2: 34-39.

13. Tomashevska O. Ya. Novi metodolohichni pidkhody stosovno vyvchennia porushen vuhlevodnoho obminu u zahalnii populiatsii. Osnovy diahnostyky, profilaktyky ta likuvannia endokrynnykh zakhvoriuvan. Lviv: NTSh, 1999. 32-44.

The study was carried out in accordance with the plan of scientific research of the National Medical University named after A.A. Bogomolets MoH Ukraine and is part of the research topic “Depression in the main forms of mental and somato-neurological pathology” (state registration number 0106U004079).

Conflict of interest:

The Author declare no conflict of interest

CORRESPONDING AUTHOR

Liliya V. Zhyvotovska

Medychna St., 1, 36013, Poltava, Ukraine

tel: +380677531590

e-mail: lzhyvotovska@gmail.com

Received: 16.04.2018

Accepted: 10.08.2018

Table І. Factor loading matrix of the multifactor model in patients with alcohol dependence (n=290)

Manifestations

Factors

F1

F2

F 3

F 4

F 5

F 6

Group

0,007

0,129

0,231

0,894

0,166

0,538

Stage

0,845

0,209

0,179

-0,007

0,168

-0,062

Integral index of the findings of neuropsychological study

0,875

0,300

0,397

0,415

0,158

0,145

Integral index of the memory

-0,801

-0,231

0,247

0,168

-0,014

-0,241

Attention

-0,793

-0,197

0,110

0,009

0,056

-0,046

State of carbohydrate metabolism

0,489

0,573

0,143

0,291

0,146

0,054

Pyruvate

0,253

0,864

0,136

0,174

0,020

0,045

PDC

-0,355

-0,260

-0,206

-0,272

0,028

-0,086

Glucose

0,261

0,863

0,010

0,121

0,066

0,028

The age of the beginning of alcohol abuse

0,853

0,284

-0,511

0,059

0,145

-0,001

Duration of the disease

0,740

0,418

0,389

0,018

0,117

-0,008

Delirium

0,198

0,350

0,185

0,063

0,765

-0,075

Convulsions

0,094

-0,158

0,243

0,067

0,520

0,096

Cognitive impairments

0,799

-0,276

0,454

0,082

-0,474

-0,030

Recurrent delirium

0,177

0,351

0,216

0,001

0,699

-0,140

Duration of remission

0,061

0,182

-0,317

0,213

0,159

0,047

Level of maladaptation

0,174

0,052

0,649

0,078

0,097

0,239

Hereditary load of narcological diseases

0,076

0,021

0,364

0,053

-0,085

-0,668

Hereditary load of mental diseases

0,042

0,123

0,215

0,084

-0,134

0,718

Corrected dispersion

9,136

5,865

3,004

1,955

1,589

1,431

Stage of factorization

0,246

0,177

0,111

0,072

0,059

0,053

Note. Indices that are major ones in the formation of the corresponding factor are marked in bold.

Fig. 1. The graph of the eigenvalues of the factors of the subject (n=290)

Table ІІ. Matrix of patient classification according to the stages of the disease

Stage

% of correctness

G_1:1

G_2:2

G_3:3

G_1:1

100,0

51

0

0

G_2:2

91,2

5

83

3

G_3:3

96,6

0

2

56

Total

95,0

56

85

59

Table ІІІ. The results of discriminant analysis of the patient classification according to the stages of the disease

Parameters

Analysis of discriminant function
Number of the variables in the model: 8

the Wilks’ Lambda: 0,08331, F (22,374)=41,899, p<0,0000

Wilks’ Lambda

Partial lambda

F-extraction (2,187)

p-level

Tolerance

R2

Age of the beginning of alcohol abuse

0,104

0,798

23,642

0,000

0,588

0,412

Convulsions

0,104

0,800

23,344

0,000

0,880

0,120

Psychoses

0,103

0,806

22,513

0,000

0,752

0,248

Delirium

0,091

0,916

8,596

0,000

0,756

0,244

Duration of the diseases

0,093

0,896

10,897

0,000

0,582

0,418

State of carbohydrate metabolism

0,090

0,924

7,668

0,001

0,495

0,505

Attention

0,110

0,758

29,829

0,000

0,704

0,296

Integral index of the findings of neuropsychological study

0,090

0,927

7,310

0,001

0,702

0,298

Table IV. Matrix of patient classification according to the physico-typological features

Group

% of correctness

G_1:1

G_2:2

G_3:3

G_4:4

G_1:1

85,5

47

6

2

0

G_2:2

81,7

5

49

3

3

G_3:3

61,7

5

8

29

5

G_4:4

73,7

1

4

5

28

Total

76,5

58

67

39

36

Fig. 2. Placement of groups of patient classification according to the stages of the disease in the space of the canonical variables

Fig. 3. Placement of groups of patient classification according to the physico-typological features in the space of the canonical variables.

Table V. The results of discriminant analysis of the patient classification according to the physico-typological features

Parameters

Analysis of discriminant function

Number of the variables in the model: 13

the Wilks’ Lambda: 0,15097 F (54,534)=8,7659 p<0,0001

Wilks’ Lambda

Partial lambda

F-extraction (3,179)

p-level

Tolerance

R2

Integral index of the findings of neuropsychological study

0,285

0,529

53,069

0,000

0,103

0,897

Attention

0,173

0,871

8,800

0,000

0,131

0,869

Long-range auditory-and-speech memory

0,168

0,899

6,667

0,000

0,155

0,845

Integral index of memory

0,165

0,913

5,690

0,001

0,045

0,955

Optospatial memory

0,163

0,929

4,595

0,004

0,120

0,880

Working memory

0,159

0,951

3,096

0,028

0,204

0,796

Pyruvate

0,179

0,844

11,038

0,000

0,429

0,571

The age of beginning of alcohol abuse

0,170

0,887

7,564

0,000

0,141

0,859

The level of maladaptation

0,161

0,939

3,854

0,011

0,805

0,195

Delirium

0,161

0,935

4,128

0,007

0,216

0,784

Recurrent delirium

0,162

0,930

4,516

0,004

0,421

0,579

Psychoses

0,160

0,945

3,439

0,018

0,606

0,394

Cognitive impairments

0,157

0,962

2,338

0,075

0,179

0,821