Sociodemographic and clinical characteristics of patients with long-term remission with buprenorphine / naloxone in opiate use disorder

Introduction

Buprenorphine/Naloxone (BP/NLX) is an effective drug combination used in long-term maintenance therapy in opiate use disorder (OUD). In some studies, abstinence over 180 days was defined as long-term remission (1).

Objectives

The aim of this study is to determine the sociodemographic and clinical characteristics of patients in long-term remission with BP/NLX.

Methods

In this study, 30 patients who were followed up with OUD at Akdeniz University Addiction Center and were in remission with BP/NLX for at least 180 days were evaluated retrospectively.

Results

Sociodemographic and clinical characteristics are summarized in table 1.

Conclusions

OUD is associated with lower quality of life and employment rate (2). In our study, the rate of working in a regular job is high. It can be concluded that prolonged remission improves functionality in patients. Although patients are in remission for a long time in terms of opiate use, 20% of patients continue to use cannabis and 10% continue to use cocaine. In a study, there was no difference in productivity and quality of life between BP users with and without current cannabis use. Continued use of cannabis by patients may be related to this condition. However, cannabis use increases many mental illnesses, especially psychosis (4). In patients in remission with BP/NLX, studies should also be carried out to avoid other substances than opiates. In our study, in accordance with the literature (5), no negative effects on kidney and liver functions were observed with long-term BP/NLX treatment. BP/NLX appears to be safe in prolonged use.

Disclosure

No significant relationships.

Modeling of pulmonary crackles using wavelet networks

In this study, wavelet networks are used to model pulmonary crackles with a view to extract features for the classification analysis of crackles obtained from subjects with a wide spectrum of pulmonary disorders. Crackles are very common adventitious sounds which are transient in character and whose characteristics, such as type, number of occurrence and pitch, convey information regarding the type and severity of the pulmonary disease. Crackles generally start with a sharp deflection and continue with a damped and progressively wider sinusoidal wave. In this study, due to the capability of time-frequency representation of wavelet functions, wavelet network (WN) is employed to characterize crackles, and the parameters acquired from wavelet nodes are used to distinguish them into two clinical classes, i.e. fine and coarse. For this purpose, a wavelet function (complex Morlet) in the first node is trained to fit the crackles and the second wavelet node is tuned to represent the error of the first node. Both of the nodes are, then, trained to minimize the total representative error. The five parameters of the WN node, i.e. scaling, time-shifting, frequency and two weight factors of sinus and cosines components are used as features in the classification analysis of crackles. The crackle information is strongly represented by the first wavelet node, therefore, the parameters belonging to the first node are used in the classification of crackles.