摘要
目的分析云南省HIV感染者病程长期不进展的影响因素。方法采用1：1匹配的病例对照研究方法，以云南省病程长期（10年）不进展的HIV感染者为病例组，病程进展的感染者为对照组，从中国疾病预防控制信息系统下载病例资料，并对感染者进行面对面访谈。使用Epidata3．1建立数据库，并使用SPSS19．0进行数据处理和统计分析。结果病程长期不进展组和病程进展组病例数均为143例。条件Logistic回归分析显示，首次CD4＋T淋巴细胞计数〉700个／μL（OR=5．101，95％CI：1．004～13．819）、随访次数≥20次（OR=26．501，95％CI：2．149—326．847）是HIV感染者病程长期不进展的促进因素；注射吸毒感染（OR=0．152，95％CI：0．020—0．381）、未接受社区美沙酮维持治疗（OR=0．005。95％CI：0．001—0．109）是HIV感染者病程进展的促进因素。结论H1V感染者早发现并保持良好的随访依从性能延缓病程发展，注射吸毒感染且未接受社区美沙酮维持治疗会促进病程发展。
Objective To analyze the influencing factors of HIV infection with long term non-progression in Yunnan Province. Methods The research methods was case-control study. The HIV patients with long-term stable course （ 10 years） were as case group, and patients in progressive course were as the control group. The cases data were downloaded from China information system for disease control and prevention, and the HIV in- fected were interviewed face to face. The database was established by EpiData3. 1, and the SPSS19. 0 soft- ware was used to process and analyze data. Results The number of the case group and the control group were 143. Conditional Logistic regression analysis showed that the first count of CD4＋ T lymphocyte more than 700/μL （ OR = 5. 101, 95 % CI： 1. 004 - 13. 819 ）, the follow-up times ≥ 20 times （ OR =. 26. 501, 95 % CI： 2. 149- 326. 847） were the promoting factors of HIV infection in long-term stable course. Infected by injecting drug （ OR = 0. 152, 95% CI： 0. 020 - 0. 381 ）, not receiving methadone maintenance treatment （ OR = 0.005, 95% CI： 0. 001 - 0. 109） were promoting factors in disease progression. Conclusion HIV infected found early and maintain higher follow-up compliance could delay the progression of the disease. Injecting drug users and not accepting methadone maintenance treatment could promote the development of disease.
出处
《中国皮肤性病学杂志》
CAS
CSCD
北大核心
2015年第9期927-929,983,共4页
The Chinese Journal of Dermatovenereology
基金
国家"十二五"科技重大专项:艾滋病和病毒性肝炎等重大传染病防治(2013ZX10004-906)
关键词
HIV感染者
病程
长期不进展
影响因素
条件LOGISTIC回归
HIV infected
Course of disease
Long term non-progressors
Influencing factors
Conditional logistic regression
