Prevalence and Influencing Factors of Thyroid Dysfunction in HIV-Infected Patients.
Shujing JiChangzhong JinStefan HöxtermannWolfgang FuchsTiansheng XieXiangyun LuHaibo WuLinfang ChengAdriane Skaletz-RorowskiNorbert H BrockmeyerNanping WuPublished in: BioMed research international (2016)
Thyroid dysfunction is more common in human immunodeficiency virus (HIV) patients. But the effects of highly active antiretroviral therapy (HAART) and hepatitis B/C virus (HBV/HCV) coinfection on thyroid function is unclear. We retrospectively reviewed the data of 178 HIV patients and determined the prevalence of thyroid dysfunction and the relationship between thyroid hormone levels, CD4 cell count, HIV-1 duration, HAART duration/regimens, and HBV/HCV coinfection. Of the 178 patients, 59 (33.1%) had thyroid dysfunction, mostly hypothyroidism. Thyroid dysfunction was significantly more frequent in the HAART group (41/104, 39.4%) than in the HAART-naïve group (18/74, 24.3%; P < 0.05). The mean CD4 cell count was significantly lower in patients with hypothyroidism (372 ± 331/μL) than in the other patients (P < 0.05). The FT4 level was significantly lower in the HAART group than in the HAART-naïve group (1.09 ± 0.23 versus 1.20 ± 0.29 pg/mL, P < 0.05). FT3/FT4 levels were negatively related to HIV duration and FT3 levels were positively related to CD4 cell (P < 0.05). HBV patients had lower FT3 levels, while HCV patients had higher FT3 and FT4 levels (P < 0.05). Thyroid dysfunction is more common in HIV patients on HAART, mainly manifested as hypothyroidism. FT3/FT4 levels are correlated with HIV progression. HBV/HCV coinfection increases the probability of thyroid dysfunction.
Keyphrases
- antiretroviral therapy
- human immunodeficiency virus
- hiv infected patients
- end stage renal disease
- hepatitis c virus
- hiv infected
- ejection fraction
- newly diagnosed
- hiv positive
- chronic kidney disease
- hiv aids
- peritoneal dialysis
- prognostic factors
- hepatitis b virus
- machine learning
- cell therapy
- bone marrow
- single cell
- risk factors
- artificial intelligence
- electronic health record
- peripheral blood
- big data