OBJECTIVE: To explore the change and impact factors of craving for heroin in patients after 6 month methadone maintenance treatment (MMT). METHODS: The questionnaire of craving for heroin was used to measure the level of craving for heroin when patients just entered the study and were treated for 6 months. The influence of MMT on craving in patients were analyzed. RESULTS: The total score and score for other factors decreased except the factor "self-control" after MMT. The craving for high dose patients decreased significantly after 6 month treatment (P<0.05). The degree of craving for heroin in males and females all decreased after MMT, but no significant difference was shown (P>0.05). The craving degree for heroin in patients with long drug use was higher than that of patients with short drug use. After the treatment, the improvement of craving was more significant for the long drug users. CONCLUSION MMT can decline the craving for heroin in drug users. Dosage for methadone and gender may be the risk factors of craving change.
Adult ; China ; Female ; Heroin Dependence ; drug therapy ; psychology ; rehabilitation ; Humans ; Male ; Methadone ; therapeutic use ; Substance Withdrawal Syndrome ; drug therapy ; psychology ; Surveys and Questionnaires ; Young Adult

Spinal vascular disease is rare in clinic, especially in cases of spinal cord embolism caused by abnormal embolism. It is rare in clinic and has not been reported in China. We report a case of pulmonary embolism complicated with abnormal spinal cord embolism due to lack of protein S activity and analyze its clinical data in order to improve clinical understanding of the disease.

As an important branch of artificial intelligence, machine learning is widely used in various fields. Machine learning has similarity to classical statistical methods, but can solve many problems which are difficult for traditional statistics, so it is one of the important tools in epidemiological research. This paper introduced 9 common algorithms of machine learning and summarized their characteristics and applications in epidemiological research. Readers could choose appropriate machine learning method according to the research purpose for the better application of machine learning in epidemiological research.