Unhealthy alcohol use, HIV infection and risk of liver fibrosis in drug users with hepatitis C

Aim To analyze alcohol use, clinical data and laboratory parameters that may affect FIB-4, an index for measuring liver fibrosis, in HCV-monoinfected and HCV/HIV-coinfected drug users. Patients and Methods Patients admitted for substance abuse treatment between 1994 and 2006 were studied. Socio-demographic data, alcohol and drug use characteristics and clinical variables were obtained through hospital records. Blood samples for biochemistry, liver function tests, CD4 cell count, and serology of HIV and HCV infection were collected at admission. Multivariate linear regression was used to analyze the predictors of FIB-4 increase. Results A total of 472 (83% M, 17% F) patients were eligible. The median age at admission was 31 years (Interquartile range (IQR) 27–35 years), and the median duration of drug use was 10 years (IQR 5.5–15 years). Unhealthy drinking (>50 grams/day) was reported in 32% of the patients. The FIB-4 scores were significantly greater in the HCV/HIV-coinfected patients (1.14, IQR 0.76–1.87) than in the HCV-monoinfected patients (0.75, IQR 0.56–1.11) (p<0.001). In the multivariate analysis, unhealthy drinking (p = 0.034), lower total cholesterol (p = 0.042), serum albumin (p<0.001), higher GGT (p<0.001) and a longer duration of addiction (p = 0.005) were independently associated with higher FIB-4 scores in the HCV-monoinfected drug users. The effect of unhealthy drinking on FIB-4 scores disappeared in the HCV/HIV-coinfected patients, whereas lower serum albumin (p<0.001), a lower CD4 cell count (p = 0.006), higher total bilirubin (p<0.001) and a longer drug addiction duration (p<0.001) were significantly associated with higher FIB-4 values. Conclusions Unhealthy alcohol use in the HCV-monoinfected patients and HIV-related immunodeficiency in the HCV/HIV-coinfected patients are important risk factors associated with liver fibrosis in the respective populations.

Was bietet die Spezialklinik den Suchtpatienten?

Der stationäre Klinikaufenthalt von Patienten mit Abhängigkeitserkrankungen ist häufig ein unverzichtbarer Teil in der Behandlungskette von Suchterkrankungen. Es werden die verschiedenen Phasen der Behandlung, deren Therapieelemente sowie Vor- und Nachteile eines stationären Aufenthalts diskutiert. Anhand der Klinik Südhang, welche Patienten und Patientinnen mit einer Alkohol- und/oder Medikamentenabhängigkeit stationär behandelt, zeigt sich die Bedeutung eines individualisierten Therapieangebots je nach Entzugs- und Entwöhnungsphase. Um Patienten mit einer Abhängigkeitserkrankung einen erfolgreichen Entzug, bzw. Entwöhnung zu gewährleisten, ist eine interdisziplinäre Betreuung und Nachsorge essentiell.

Opioid maintenance therapy in Switzerland: an overview of the Swiss IMPROVE study

BACKGROUND/AIMS: Switzerland’s drug policy model has always been unique and progressive, but there is a Need to reassess this system in a rapidly changing world. The IMPROVE study was conducted to gain understanding of the attitudes and beliefs towards opioid maintenance therapy (OMT) in Switzerland with regards to quality and Access to treatment. To obtain a “real-world” view on OMT, the study approached its goals from two different angles: from the perspectives of the OMT patients and of the physicians who treat patients with maintenance therapy. The IMPROVE study collected a large body of data on OMT in Switzerland. This paper presents a small subset of the dataset, focusing on the research design and methodology, the profile of the participants and the responses to several key questions addressed by the questionnaires. METHODS: IMPROVE was an observational, questionnaire-based cross-sectional study on OMT conducted in Switzerland. Respondents consisted of OMT patients and treating physicians from various regions of the country. Data were collected using questionnaires in German and French. Physicians were interviewed by phone with a computer-based questionnaire. Patients self-completed a paper-based questionnaire at the physicians’ Offices or OMT treatment centres. RESULTS: A total of 200 physicians and 207 patients participated in the study. Liquid methadone and methadone tablets or capsules were the medications most commonly prescribed by physicians (60% and 20% of patient load, respectively) whereas buprenorphine use was less frequent. Patients (88%) and physicians (83%) were generally satisfied with the OMT currently offered. The current political framework and lack of training or information were cited as determining factors that deter physicians from engaging in OMT. About 31% of OMT physicians interviewed were ≥60 years old, indicating an ageing population. Diversion and misuse were considered a significant problem in Switzerland by 45% of the physicians. CONCLUSION: The subset of IMPROVE data presented gives a present-day, real-life overview of the OMT landscape in Switzerland. It represents a valuable resource for policy makers, key opinion leaders and drug addiction researchers and will be a useful basis for improving the current Swiss OMT model.

Tabulation of multiple responses

Although multiple-response questions are quite common in survey research, Stata’s official release does not provide much capability for an effective analysis of multiple-response variables. For example, in a study on drug addiction an interview question might be, “Which substances did you consume during the last four weeks?” The respondents just list all the drugs they took, if any; e.g., an answer could be “cannabis, cocaine, heroin” or “ecstasy, cannabis” or “none”, etc. Usually, the responses to such questions are stored as a set of variables and, therefore, cannot be easily tabulated. I will address this issue here and present a new module to compute one- and two-way tables of multiple responses. The module supports several types of data structure, provides significance tests, and offers various options to control the computation and display of the results. In addition, tools to create graphs of multiple-response distributions are presented.

Tabulation of multiple responses

Although multiple response questions are quite common in survey research, Stata's official release does not provide much possibility for an effective analysis of multiple response variables. For example, in a study on drug addiction an interview question might be, "Which substances did you consume during the last four weeks?" The respondents just list all the drugs they took if any, e.g., an answer could be "cannabis, cocaine, heroin" or "ecstasy, cannabis" or "none", etc. Usually, the responses to such questions are held as a set of variables and, therefore, cannot be easily tabulated. I will address this issue and present a new module to compute one- and two-way tables of multiple responses. The module supports several types of data structure, provides significance tests, and offers various options to control the computation and display of the results.