Talaromyces marneffei infection is commonly found in hospitalized HIV/AIDS patients in southern China and was associated with a higher mortality rate than most HIV-associated complications. These results highlight the need for improved diagnosis, treatment and prevention of infection by this neglected fungal pathogen in southern China.

Rural-to-urban migrants are at high risk of HIV infection. The goal of this survey was to explore the commercial sexual behavior and condom use among male rural-to-urban migrants in western China. A cross-sectional survey on male rural-to-urban migrants in western China was conducted. Among all the subjects surveyed, 140 (7.4%) had commercial sexual behavior, which is associated with being aged older than 24 years, being of Han or other ethnic minorities, being divorced, separated, or widowed, having experienced drug abuse, having had heterosexual behavior, having had casual sexual partners, having had sex with a homosexual, and being from Xinjiang. A total of 31.4% of them never use condoms when buying sex. Not using condoms is associated with being from Chongqing, having a high school or above education, and having commercial sex monthly. Commercial sexual behavior and not using condoms are common among male rural-to-urban migrants in western China. Strategies and appropriate education should be developed to prevent HIV transmission due to high-risk sexual behaviors.

Previous studies investigating HIV-infected patients suggested a direct link between underweight and the mortality rate of AIDS. However, there was a lack of evidence showing the optimal range of initial body mass index (BMI) patients maintain during antiretroviral therapy (ART). We aimed to evaluate associations of the BMI values pre-ART and during the entire ART duration with mortality among HIV-positive individuals. In total, 5101 HIV/AIDS patients, including 1439 (28.2%) underweight, 3047 (59.7%) normal-weight, 548 (10.7%) overweight and 67 (1.3%) obese patients, were included in this cohort. The cumulative mortality of underweight, normal-weight, and overweight were 2.4/100 person-years (95% CI 1.9–2.9), 1.1/100 person-years (95% CI 0.9–1.3), and 0.5/100 person-years (95% CI 0.1–0.9), respectively. Cumulative mortality was lower in both the normal-weight and overweight populations than in the underweight population, with an adjusted hazard ratio ( AHR ) of 0.5 (95% CI 0.4–0.7, p < 0.001) and 0.3 (95% CI 0.1–0.6, p = 0.002), respectively. Additionally, in the 1176 patients with available viral load data, there was significant difference between the underweight and normal-weight groups after adjustment for all factors, including viral load ( p = 0.031). This result suggests that HIV-infected patients in Guangxi maintaining a BMI of 19–28 kg/m 2 , especially 24–28 kg/m 2 , have a reduced risk of death.

The aim of this study was to develop and externally validate a simple-to-use nomogram for predicting the survival of hospitalised human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) patients (hospitalised person living with HIV/AIDS (PLWHAs)). Hospitalised PLWHAs (n = 3724) between January 2012 and December 2014 were enrolled in the training cohort. HIV-infected inpatients (n = 1987) admitted in 2015 were included as the external-validation cohort. The least absolute shrinkage and selection operator method was used to perform data dimension reduction and select the optimal predictors. The nomogram incorporated 11 independent predictors, including occupation, antiretroviral therapy, pneumonia, tuberculosis, Talaromyces marneffei, hypertension, septicemia, anaemia, respiratory failure, hypoproteinemia and electrolyte disturbances. The Likelihood χ2 statistic of the model was 516.30 (P = 0.000). Integrated Brier Score was 0.076 and Brier scores of the nomogram at the 10-day and 20-day time points were 0.046 and 0.071, respectively. The area under the curves for receiver operating characteristic were 0.819 and 0.828, and precision-recall curves were 0.242 and 0.378 at two time points. Calibration plots and decision curve analysis in the two sets showed good performance and a high net benefit of nomogram. In conclusion, the nomogram developed in the current study has relatively high calibration and is clinically useful. It provides a convenient and useful tool for timely clinical decision-making and the risk management of hospitalised PLWHAs.

Objective Talaromycosis is a serious regional disease endemic in Southeast Asia. In China, Talaromyces marneffei (T. marneffei) infections is mainly concentrated in the southern region, especially in Guangxi, and cause considerable in-hospital mortality in HIV-infected individuals. Currently, the factors that influence in-hospital death of HIV/AIDS patients with T. marneffei infection are not completely clear. Existing machine learning techniques can be used to develop a predictive model to identify relevant prognostic factors to predict death and appears to be essential to reducing in-hospital mortality. Methods We prospectively enrolled HIV/AIDS patients with talaromycosis in the Fourth People’s Hospital of Nanning, Guangxi, from January 2012 to June 2019. Clinical features were selected and used to train four different machine learning models (logistic regression, XGBoost, KNN, and SVM) to predict the treatment outcome of hospitalized patients, and 30% internal validation was used to evaluate the performance of models. Machine learning model performance was assessed according to a range of learning metrics, including area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) tool was used to explain the model. Results A total of 1927 HIV/AIDS patients with T. marneffei infection were included. The average in-hospital mortality rate was 13.3% (256/1927) from 2012 to 2019. The most common complications/coinfections were pneumonia (68.9%), followed by oral candida (47.5%), and tuberculosis (40.6%). Deceased patients showed higher CD4/CD8 ratios, aspartate aminotransferase (AST) levels, creatinine levels, urea levels, uric acid (UA) levels, lactate dehydrogenase (LDH) levels, total bilirubin levels, creatine kinase levels, white blood-cell counts (WBC) counts, neutrophil counts, procaicltonin levels and C-reactive protein (CRP) levels and lower CD3+ T-cell count, CD8+ T-cell count, and lymphocyte counts, platelet (PLT), high-density lipoprotein cholesterol (HDL), hemoglobin (Hb) levels than those of surviving patients. The predictive XGBoost model exhibited 0.71 sensitivity, 0.99 specificity, and 0.97 AUC in the training dataset, and our outcome prediction model provided robust discrimination in the testing dataset, showing an AUC of 0.90 with 0.69 sensitivity and 0.96 specificity. The other three models were ruled out due to poor performance. Septic shock and respiratory failure were the most important predictive features, followed by uric acid, urea, platelets, and the AST/ALT ratios. Conclusion The XGBoost machine learning model is a good predictor in the hospitalization outcome of HIV/AIDS patients with T. marneffei infection. The model may have potential application in mortality prediction and high-risk factor identification in the talaromycosis population.

The dimorphic fungus Talaromyces marneffei (TM) is a common cause of HIV-associated opportunistic infections in Southeast Asia. Cotrimoxazole (CTX) inhibits folic acid synthesis which is important for the survival of many bacteria, protozoa, and fungi and has been used to prevent several opportunistic infections among HIV/AIDS patients. We question whether CTX is effective in preventing TM infection. To investigate this question, we conducted an 11-year (2005–2016) retrospective observational cohort study of all patients on the Chinese national antiretroviral therapy (ART) programme in Guangxi, a province with high HIV and TM burden in China. Survival analysis was conducted to investigate TM cumulative incidence, and Cox regression and propensity score matching (PSM) were used to evaluate the effect of CTX on TM incidence. Of the 3359 eligible individuals contributing 10,504.66 person-years of follow-up, 81.81% received CTX within 6 months after ART initiation, and 4.73% developed TM infection, contributing 15.14/1,000 person-year TM incidence rate. CTX patients had a significantly lower incidence of TM infection than non-CTX patients (4.11% vs. 7.53%; adjusted hazard ratio (aHR) = 0.50, 95% CI 0.35–0.73). CTX reduced TM incidence in all CD4 + cell subgroups (<50 cells/μL, 50–99 cells/μL, 100–199 cells/μL), with the highest reduction observed in patients with a baseline CD4 + cell count <50 cells/μL in both Cox regression and the PSM analyses. In conclusion, in addition to preventing other HIV-associated opportunistic infections, CTX prophylaxis has the potential to prevent TM infection in HIV/AIDS patients receiving ART.

We describe the opportunistic infections (OIs) of HIV/AIDS to understand the spectrum, mortality, and frequency of multiple coinfected OIs among HIV/AIDS patients in southern China, where OIs are severe. We carried out a retrospective cohort study of hospitalized HIV-infected individuals at the Fourth People’s Hospital of Nanning, Guangxi, China, from Jan. 2011 to May. 2019. The chi-square test was used to analyze cross-infection; the Kaplan‒Meier analysis was used to compare mortality. A total of 12,612 HIV-infected patients were admitted to this cohort study. Among them, 8982 (71.2%) developed one or more OIs. The overall in-hospital mortality rate was 9.0%. Among the patients, 35.6% coinfected one OI, and 64.4% coinfected more than two OIs simultaneously. Almost half of the patients (60.6%) had CD4 + T-cell counts < 200 cells/μL. Pneumonia (39.8%), tuberculosis (35.3%), and candidiasis (28.8%) were the most common OIs. Coinfected cryptococcal meningitis and dermatitis are the most common combined OIs. The rate of anaemia (17.0%) was highest among those common HIV-associated complications. Multiple OIs are commonly found in hospitalized HIV/AIDS patients in southwestern China, which highlights the need for improved diagnosis and treatment.