Predictors of relapse in the early stages of the treatment among inpatients with opioid use disorder: A single-center, prospective cohort study


Gica Sakir, Donmez Zeliha, Unubol Basak, Iyisoy M. Sinan, Gulec Huseyin



Abstract

Background: Relapse rates in patients with opioid use disorder (OUD) seem to be higher compared with relapse rates in other substance use disorders. In this regard, it is important to deal with the treatment process after discharge and to determine the factors affecting relapse in the early stages of the treatment of the disease. The present study aimed to investigate the factors that may be related to relapse in the first 3 months of treatment, such as sociodemographics, substance use characteristics, attention-deficit, and hyperactivity symptomatology and cognitive functions in detail.

Method: A total of 100 inpatients with OUD who consented to participate were included in the research. CANTAB Rapid Visual Information Processing (RVP), CANTAB Emotion Recognition Task (ERT), the CANTAB Cambridge Gambling Test (CGT), Addiction Profile Index (API), Barratt Impulsiveness Scale (BIS), and Adult Attention-Deficit and Hyperactivity Disorder Self-Reporting Scale (ASRS) were administered to the patients. After discharge, the patients were followed up by phone calls, polyclinic follow-ups, and urine analysis for 2 months. Relapse was evaluated both in the interview and the results of the urine analysis.

Results: Two months after discharge, there were 16 (16%) patients who reported no substance use. The patients were divided into three groups; 1) those who could not complete hospitalization, 2) those who experienced a shift on the first day after discharge, and 3) those who experienced a shift after discharge or those in remission. When the sociodemographic data, substance use characteristics, API, ASRS scores, and cognitive functions of the three groups were compared, only the mean RVP – the ability to determine target scores and RVP – total correct rejection scores in patients who were in remission or experienced relapse in the later stages of discharge were significantly higher than the mean score of patients who were discharged before completing the hospitalization protocol (p= 0.011 and p=0.008, respectively). Age, education level, ASRS attention-deficit and impulsivity scores, recognition of happiness scores, and ability to determine to target scores had a significant effect on relapse. After the patients were divided into two groups according to the RVP median value, the abstinence probabilities of the patients were examined using Kaplan-Meier survival analysis.

Conclusion: Interrogating and treating patients with attention-deficit and hyperactivity disease and symptomatology, as well as interventions with new treatment methods (such as computerized cognitive training and cognitive rehabilitation programs) for patients with sustained attention and social cognition impairment are needed to prevent relapse in the early stages of the treatment in patients with OUD.

Keywords: cognition; attention, opioid addiction, attention-deficit hyperactivity disorder, relapse prevention

FULL TEXT XML

Predictors of relapse in the early stages of the treatment among inpatients with opioid use disorder: A single-center, prospective cohort study

 

Gica Sakira, Donmez Zelihab, Unubol Basakc, Iyisoy M. Sinanc, Gulec Huseyind

 

a Necmettin Erbakan University, Meram Medical Faculty, Department of Psychiatry, Konya; 

b University of Health Sciences Turkey Umraniye Training and Research Hospital, Department of Psychiatry, Istanbul; 

c Necmettin Erbakan University, Meram Medical Faculty, Department of Medical Education and Informatics, Konya; 

d University of Health Sciences Turkey Erenkoy Psychiatric and Neurological Diseases Training and Research Hospital, Department of Psychiatry, Istanbul, Turkey

 

 

Abstract

Background: Relapse rates in patients with opioid use disorder (OUD) seem to be higher compared with relapse rates in other substance use disorders. In this regard, it is important to deal with the treatment process after discharge and to determine the factors affecting relapse in the early stages of the treatment of the disease. The present study aimed to investigate the factors that may be related to relapse in the first 3 months of treatment, such as sociodemographics, substance use characteristics, attention-deficit, and hyperactivity symptomatology and cognitive functions in detail.

Method: A total of 100 inpatients with OUD who consented to participate were included in the research. CANTAB Rapid Visual Information Processing (RVP), CANTAB Emotion Recognition Task (ERT), the CANTAB Cambridge Gambling Test (CGT), Addiction Profile Index (API), Barratt Impulsiveness Scale (BIS), and Adult Attention-Deficit and Hyperactivity Disorder Self-Reporting Scale (ASRS) were administered to the patients. After discharge, the patients were followed up by phone calls, polyclinic follow-ups, and urine analysis for 2 months. Relapse was evaluated both in the interview and the results of the urine analysis.

Results: Two months after discharge, there were 16 (16%) patients who reported no substance use. The patients were divided into three groups; 1) those who could not complete hospitalization, 2) those who experienced a shift on the first day after discharge, and 3) those who experienced a shift after discharge or those in remission. When the sociodemographic data, substance use characteristics, API, ASRS scores, and cognitive functions of the three groups were compared, only the mean RVP - the ability to determine target scores and RVP - total correct rejection scores in patients who were in remission or experienced relapse in the later stages of discharge were significantly higher than the mean score of patients who were discharged before completing the hospitalization protocol (p= 0.011 and p=0.008, respectively). Age, education level, ASRS attention-deficit and impulsivity scores, recognition of happiness scores, and ability to determine to target scores had a significant effect on relapse. After the patients were divided into two groups according to the RVP median value, the abstinence probabilities of the patients were examined using Kaplan-Meier survival analysis.

Conclusion: Interrogating and treating patients with attention-deficit and hyperactivity disease and symptomatology, as well as interventions with new treatment methods (such as computerized cognitive training and cognitive rehabilitation programs) for patients with sustained attention and social cognition impairment are needed to prevent relapse in the early stages of the treatment in patients with OUD.

Keywords: cognition; attention, opioid addiction, attention-deficit hyperactivity disorder, relapse prevention

 

Introduction

Opioid use disorder (OUD) is an important public health problem that is highly associated with mortality and morbidity (1, 2). Nevertheless, the prevalence of OUD is rising worldwide (3). In the 2016 Global Burden of Disease study, 26.8 million people worldwide were estimated to be living with OUD (4). In this context, it is essential to reduce high relapse rates, one of the major challenges in the treatment of OUD (5, 6). Only one-third of patients with OUD continue their maintenance for 6 months (7). Studies have found that the majority of patients lapse within one month of discharge (8-10). Improvement in these rates can be achieved through a better understanding of risk factors, including patient characteristics associated with relapse after inpatient detoxification. Studies examining relapse in substance use generally focus on three areas: (1) characteristics related to substance use, (2) presence of attention-deficit/ hyperactivity disorder (ADHD) comorbidity, and (3) cognitive functions.

Relapse after inpatient detoxification is significantly predicted by younger age, greater opioid use prior to treatment, history of injecting, failure to complete treatment, and failure to enter aftercare (9, 11). Another study found that age, sex, and marital and employment status were important predictors of survival rates of patients with substance use disorder (SUD) (12).

The frequent co-occurrence of SUDs and ADHD has received increased attention (13, 14). Comparing SUD with/without ADHD, it was reported that those with ADHD had a younger onset of substance abuse, SUDs were more severe, and they frequently displayed more risk-taking behaviors (15).

Recent developments in cognitive neuroscience point to neurocognitive measures (i.e., brain-imaging measures during a cognitive-task performance) as potential predictors of relapse. Even more, it is reported that neurocognitive measures can provide more valuable data in order to predict relapse than information obtained from self-report measures such as craving (16). Many clinical studies have shown that chronic opioid use is associated with cognitive dysfunctions such as attention, working memory, decision-making, learning and memory deficits, and functional disorders such as impulsivity and distractibility (17-21). Early functional magnetic resonance imaging (fMRI) studies in patients with OUD showed reduced activity in a broad network of brain regions involved in regulating behavioral inhibition/impulsivity (17, 19, 22), and in cognitive control (23), suggesting a greater likelihood of relapse (24). Dysfunction of prefrontal cortex regions may contribute to the development of craving, compulsive use, and losing control of drug use (24).

It is noteworthy that studies on OUD are fewer than those related to other substances. Moreover, the findings cannot be confirmed in every study. The feature that distinguishes the current study from other previous studies is the detailed examination of the post-discharge process, the handling of all factors in a totalitarian fashion, and the use of standardized, widely used computerized batteries for the evaluation of cognitive functions. In the design of the current study, inpatients with OUD were closely followed in the early stages of post-discharge treatment and classified according to their relapse status. We think that this study design allows a more detailed examination of the factors related to relapse in the early stage of the treatment. However, addressing both ADHD symptoms and ADHD-related cognitive functions together is an important feature of the research.  In this study, we aimed to measure the rates of relapse in patients with OUD undergoing inpatient detoxification treatment in the addiction clinic and to examine patient-related factors such as sociodemographics, substance use characteristics, attention-deficit, and hyperactivity symptomatology, and the cognitive functions that might be associated with relapse in the first 3 months of treatment. We hypothesized that in the group that could not complete hospitalization, the impulsivity and addiction profile scores would be higher, in particular, sustained attention and decision-making scores would be lower. We also expected that deficits in sustained attention and decision-making, severe symptomatology of ADHD, and an addiction profile could predict relapse in the early stages of the treatment.

Methods

Our study is a prospective comparative case series study. Patients who were hospitalized in the AMATEM (alcohol, substance, treatment center) addiction clinic were included in the study. This addiction clinic is for the detoxification of addicts who use alcohol, opioids, cannabis, cocaine, psychostimulants, inhalants, or other substances. This addiction clinic has a capacity of 36 beds; detoxification is provided with pharmacologic treatments. In addition to pharmacologic treatment, psychosocial support is provided at the center, and the mean duration of hospitalization is 3 weeks. The treatment costs of patients are covered by state health insurance, and no additional funding was used in the study. The inclusion/exclusion criteria, materials used in the research, and the flow chart of the study are shown in Figure 1.

The therapeutic agents used by the patients were regulated by the treatment team at the clinic and not decided by the researchers. However, all patients were receiving suboxone at the time of the initial psychiatric interview and cognitive tests in order to exclude a medication effect.  At the same time, all patients were also receiving quetiapine (mean dosage: 50-200 mg/day) and mirtazapine (mean dosage: 15 mg/day).

Evaluation interviews lasted approximately one hour for each patient. Cognitive tests were always performed by the same practitioner (UZ). All tests were performed in one session in the morning, and when the patients were full.

Patients who did not complete the standard inpatient treatment protocol for 21 days were presumed to have relapsed on the day of discharge because they declared that they wanted to be discharged for substance use.

Necessary consents for this research were obtained from HSU Turkey Erenkoy Psychiatric and Neurological Diseases Training and Research Hospital Clinical Research Ethics Committee (IRB date/number: 03.04.2017/5).

Materials:

CANTAB (The Cambridge Neuropsychological Test Automated Battery)

Rapid Visual Information Processing (RVP): In this test, sustained attention is assessed using outcome values such as response accuracy, target sensitivity, and response time.

Emotion Recognition Task (ERT): In this test, the ability to recognize emotional facial expressions such as anger, disgust, fear, surprise, happiness, and sadness are evaluated. Some facial expressions are easier to understand, whereas some facial expressions are more difficult. The test consists of two blocks. There are 90 facial expressions in each block.

Cambridge Gambling Test (CGT): This test evaluates decision-making and risk-taking behavior by excluding learning status. 

Adult Attention-Deficit Hyperactivity Disorder Self-Report Scale (ASRS): The World Health Organization's (WHO) ASRS consists of two sub-scales: “attention deficit” and “hyperactivity/impulsivity” sub-scales, each consisting of 9 items. The validity and reliability study of the Turkish version of the scale has been conducted (25).

Addiction Profile Index (API): The API-Soft determines the risks and requirements of alcohol and drug users, and contributes to the creation of an individualized treatment plan. The scale was developed by Ögel et al. (26).

Statistical evaluation:

Statistical analyses were performed using the SPSS version 20 software and SAS University Edition 9.4. The suitability of the variables to normal distribution was examined using visual (histogram and probability graphs) and analytical (Kolmogorov-Smirnov and Shapiro-Wilk) tests. The Kruskal-Wallis test was used for the comparison of non-normally distributed numerical data between groups of patients who did not complete hospitalization, who experienced a relapse on the first day after discharge, and patients who experienced a relapse later. One-way analysis of variance (ANOVA) was used for the comparison of normally distributed numerical data between groups of patients. The Chi-square test was used to compare categorical variables between the groups. In a post-hoc analysis, homogeneous distributions of parameters were examined using the Levene test. The Tukey test was used for post hoc analysis of homogenously distributed data. The Mann-Whitney U test was used for post hoc analysis of the Kruskal-Wallis test (p=0.017 with Bonferroni correction). In comparing cognitive parameters between groups, multivariate analysis of variance (MANOVA), and follow-up, ANOVA was used to reduce Type 1 error. Logistic regression analysis was used to evaluate the clinical and cognitive functions affecting relapse. Kaplan-Meier survival analysis was used to estimate remission probability, and the log-rank test was used to compare survival curves. For statistical significance, the total type-1 error level was used as 5%.

Results

Thirty patients with OUD were discharged without completing the 21-day standard inpatient procedure. Thirty-five patients with OUD reported that they had a shift on the 21st day, the first day of discharge, although they completed the inpatient treatment protocol. Two months after discharge, 16 patients reported no substance use, and no substances were detected in urine tests. In this context, patients were divided into 3 groups: (1) those who could not complete hospitalization; (2) those who experienced a shift on the first day after discharge; and (3) those who experienced a shift after discharge or those in remission. The comparison of sociodemographic and clinical data of the patients is shown in Table 1.

According to the responses of the patients in the API evaluation scale, a total of 30 patients reported use of another substance with opioids more than once per week. Six (6%) of the patients used cannabis more than once per week, 8 (8%) patients used ecstasy more than once per week, 13 (13%) patients used cocaine more than once per week, and two (2%) patients used flunitrazepam (Rohypnol) more than once per week. No patients abused solvents or medical drugs.

The comparison of API and ASRS scores between the groups is shown in Table 2. There were no statistically significant differences in API and ASRS scores between the groups.

The comparison of cognitive functions between the groups is shown in Table 3. When MANOVA was used to compare cognitive parameters between the groups, no significant difference was found according to Pillai's trace test (Pillai’s trace=0.319, F=1.501, df=22, error df=174, at p = 0.078). In follow-up ANOVA, the mean RVP - ability to determine target scores and RVP- total correct rejection scores in patients who were in remission or experienced relapse in the later stages of discharge were significantly higher than those of patients who discharged before completing the hospitalization protocol (F=4.758, p=0.011 and F=4.191, p=0.018, respectively). Furthermore, the group that experiencing relapse on the first day after discharge had significantly lower recognition of anger and surprise scores than the group that was in remission or experienced relapse in the later stages of discharge (F=3.145, p=0.048 and F=4.383 0.015, respectively).

Sociodemographic and clinical/cognitive factors that can predict relapse were examined by creating a logistic regression model (See Table 4). Age, education level, ASRS attention- deficit and impulsivity scores, recognition of happiness scores, and ability to determine to target scores had a significant effect on relapse. After the patients were divided into two groups according to the median RVP value, the abstinence probabilities of the patients were examined using Kaplan-Meier survival analysis (See Figure 2). As a result of the log-rank test, the abstinence curves of these two groups were found to be different (p<0.001).

Discussion

In the current study, patients with OUD who were receiving inpatient treatment protocol were evaluated in detail regarding their relapse experiences during hospitalization and 2 months after discharge. In our study, the factors that might be related to relapse in the first 3 months of treatment, such as sociodemographics, substance use characteristics, attention-deficit, and hyperactivity symptomatology, and cognitive functions were examined in detail. It was found that patients who had a relapse during the inpatient treatment procedure had poorer sustained attention than patients who had relapse relatively later or who were in remission after 2 months. There was an inability to recognize emotions (anger and surprise) in patients with relapse shortly after discharge. At the same time, age, education level, attention-deficit, and hyperactivity symptomatology, sustained attention, and the ability to recognize happiness had a significant effect on relapse. Furthermore, patients with OUD who had deficits in sustained attention appeared to have lower abstinence probabilities from the first day of treatment.

It was determined that 65 of the 100 patients included in our study experienced a relapse during inpatient treatment or on the first day of discharge, and only 16 were in remission after 2 months. This finding is similar to the results of studies investigating relapse rates in inpatients with OUD in the literature. In a study conducted by Smyth et al. with 109 patients, it was found that the relapse rate was 59% (64 patients) within one week after discharge, and 71% at the end of the first month (27). Other studies are supporting the vast majority of patients with OUD relapse within a short time after discharge (9, 10).

Although the patients included in our study had used the long-release naltrexone injection form or buprenorphine/naloxone, which is approved by the United States Food and Drug Administration (FDA) for the treatment of OUD, it seems that the studies that examined these drugs and opioid abstinence rates separately had similar rates (20% and 36%, respectively) (28, 29). However, when all SUDs are considered in general, remission rates are reported as 46% (30).  In other words, relapse rates in patients with OUD seem to be higher compared with those in other substance use disorders. In this regard, it is important to deal with the treatment process after discharge and to determine the factors affecting relapse in the early stages of the treatment of the disease.

When the current literature is examined, there are many studies on the presence of SUDs and ADHD as comorbidity. The addition of ADHD symptoms to SUD has been reported to exacerbate the clinical appearance, worsen existing symptoms, and lead to a worse course, more difficult treatment, and poor treatment compliance (31,32). However, studies on OUD with ADHD as comorbidity are limited. In addition, it is still unclear as to which cognitive areas comorbid ADHD affect and makes changes in the severity of dependence in OUD. The reason for the small number of studies is probably that the medicines used in the treatment of OUD and other comorbid psychiatric disorders confuse the manifestation of ADHD (33). However, studies investigating the effect of ADHD as a comorbidity in patients with alcohol, cocaine, and cannabis use disorder have shown that the presence of ADHD symptoms worsens clinical features, there are more frequent relapses with longer substance exposure (31-35). Also, there is no clear consensus on when to start ADHD treatment in patients with comorbid SUD and ADHD. Some authors report that SUD should be treated first so that both ADHD treatment efficacy and the possibility of retention in treatment may increase (36). However, some authors state that starting earlier comorbid ADHD pharmacologic treatment may reduce the risk of relapse (37). Findings obtained from the current study support that ADHD symptomatology is effective on relapse in the early stages of the treatment. It is stated in studies that patients who cannot control themselves use drugs extensively when they are exposed to a substance due to impaired executive function in ADHD (38,39). In addition, impairment in the reward system in the brain has been shown to predispose patients to use substances as stimulants and to develop substance dependency (38,39).

The main focus of the current study was to examine the effects of cognitive functions, one of the current issues in addiction, on relapse in the early stages of the treatment in detail. Evidence from recent studies supports the central role of cognition in SUD symptomology, clinical prognosis, and potential therapeutic targets (40). Substance addiction can be evaluated as a pathologic behavior model that includes compulsive and chronic substance use, loss of control regarding limiting substance use, continued substance use despite negative results, craving, tolerance, and withdrawal (41, 42).

Cognitive domains that contribute to this understanding of dependency are response inhibition, working memory, and attention (43, 44). The reaction time is prolonged in the Stroop test in studies about sustained attention in OUD (45-47). Speed and attention are required to perform complex executive tasks, such as action selection and response inhibition (48). It is understood that procedures related to attention processes have a push (avoidance) or pull (approach) effect when giving explicit or implicit responses to a person's substance-related clues (49). A prospective systemic review showed that speed/accuracy during attention and reasoning tasks (MicroCog) was the only consistent predictor of treatment retention (50). The findings of our study support the fact that insufficiency in maintaining attention towards healthy internal and external stimuli that will continue to motivate substance abstinence may be effective in relapse. In addition, computerized cognitive training and cognitive rehabilitation programs have been designed to help patients retain impulsive behavior, use caution to align their sources of attention with their own goals (e.g., deprivation), and select behaviors that comply with these objectives (51, 52).

A recent meta-analysis about substance use disorders has shown that there are important deficits related to emotion recognition and the Theory of Mind, which are critical components of social cognition (53). Studies on emotional recognition in alcohol and SUDs show conflicting findings (54). In some studies conducted with various kind of substances, it is reported that emotion recognition abilities are related to duration, amount of substance use, and severity of dependency (55-59), and some studies showed no significant change in facial emotion recognition ability compared with healthy controls (60, 61). These contradictory findings are thought to result from differences in age, sex, and substances used. However, especially in studies on alcohol use disorder, it is reported that defects in emotion recognition cause difficulties in interpersonal relations (62). By acting in this way, it has been shown that substance and alcohol use may be associated with relapse in the early stages of the treatment (63). The findings of our study also support the information in the literature.

The limitations of our study are that some of the patients had a history of additional substance use, and medicines such as buprenorphine, naltrexone, mirtazapine, and quetiapine used for the treatment have the potential to be effective on both attention-deficit and hyperactivity symptoms and cognitive functions. In addition, the absence of an IQ test and lack of questioning additional psychiatric diseases other than ADHD is among the limitations of our study. Another limitation of our study is that our sample size is relatively small. Although previous studies have found that gender differences also affect survival rate in substance abuse, statistical analysis has not been performed in the current study since the number of female inpatients with OUD included in our study was very small (n=7).

In conclusion, a considerable number of patients with OUDs experience relapse in the early stages of discharge. Therefore, it is important to take precautions to prevent patients from relapse in this period. In this context, additional applications such as extending the length of hospitalization periods, inviting patients for psychiatric interviews, making motivational interventions, and taking urine samples more frequently in the early period after discharge may be appropriate. Symptoms of ADHD and cognitive functions such as sustained attention and social cognition have an impact on relapse. In addition, it was concluded that interrogating and treating patients with ADHD symptomatology, as well as interventions with new treatment methods (such as computerized cognitive training and cognitive rehabilitation programs) for patients with sustained attention and social cognition impairment are needed to prevent relapse in the early stages of the treatment in patients with OUD.

Acknowledgment

We would like to thank the staff working at the Substance Abuse Center for their important contributions during data collection.

Statement of Ethics

Subjects (or their parents or guardians) have given their written informed consent. The research institute’s committee has approved the study protocol on human research (IRB date/number: 03.04.2017/5).

Disclosure Statement

The authors have no conflicts of interest to declare.

Author Contributions

G.S. contributed to analysis and interpretation; drafted manuscript; critically revised manuscript; gave final approval; agreed to be accountable for all aspects of work ensuring integrity and accuracy. D.Z. Contributed to analysis and interpretation; critically revised manuscript; gave final approval; agreed to be accountable for all aspects of work, ensuring integrity and accuracy. U.B. contributed to interpretation; critically revised manuscript; gave final approval; agreed to be accountable for all aspects of work ensuring completeness and accuracy. I.M.S. contributed to analysis and interpretation; agreed to be accountable for all aspects of work, ensuring integrity and accuracy. G.H. contributed to interpretation; critically revised manuscript; gave final approval; agreed to be accountable for all aspects of work, ensuring integrity and accuracy.

 

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