Machine learning-based prognostic prediction for hospitalized HIV/AIDS patients with cryptococcus infection in Guangxi, China.

OBJECTIVE: To develop and validate a machine learning model for predicting mortality-associated prognostic factors in order to reduce in-hospital mortality rates among HIV/AIDS patients with Cryptococcus infection in Guangxi, China. METHODS: This retrospective prognostic study included HIV/AIDS patients with cryptococcosis in the Fourth People's Hospital of Nanning from October 2011 to June 2019. Clinical features were extracted and used to train ten machine learning models, including Logistic Regression, KNN, DT, RF, Adaboost, Xgboost, LightGBM, Catboost, SVM, and NBM, to predict the outcome of HIV patients with cryptococcosis infection. The sensitivity, specificity, AUC, and F1 value were applied to assess model performance in both the testing and training sets. The optimal model was selected and interpreted. RESULTS: A total of 396 patients were included in the study. The average in-hospital mortality of HIV/AIDS patients with cryptococcosis was 12.9% from 2012 to 2019. After feature screening, 20 clinical features were selected for model construction, accounting for 93.8%, including ART, Electrolyte disorder, Anemia, and 17 laboratory tests. The RF model (AUC 0.9787, Sensitivity 0.9535, Specificity 0.8889, F1 0.7455) and the SVM model (AUC 0.9286, Sensitivity 0.7907, Specificity 0.9786, F1 0.8293) had excellent performance. The SHAP analysis showed that the primary risk factors for prognosis prediction were identified as BUN/CREA, Electrolyte disorder, NEUT%, Urea, and IBIL. CONCLUSIONS: RF and SVM machine learning models have shown promising predictive abilities for the prognosis of hospitalized HIV/AIDS patients with cryptococcosis, which can aid clinical assessment and treatment decisions for patient prognosis.

Spectrum and mortality of opportunistic infections among HIV/AIDS patients in southwestern China.

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.

HLA-mismatched allogeneic adoptive immune therapy in patients with severely immunosuppressed AIDS: a multicenter, open-label, controlled, phase 2a study.

Recurrent opportunistic infections (OIs) in patients with severely immunosuppressed AIDS remain an unresolved medical challenge despite advancements in antiretroviral therapy (ART). To address this gap, we developed an HLA-mismatched allogeneic adoptive immune therapy (AAIT) specifically targeting this patient population. The safety and efficacy of this novel therapeutic approach were preliminarily confirmed in our phase 1 trial. Subsequently, a multicenter, open-label, controlled, phase 2a trial was conducted to evaluate the efficacy of AAIT in combination with ART compared with the conventional ART-only regimen. No difference in the incidence of adverse events (AEs) was observed between the two groups at the 96-week follow-up. AAIT treatment improved CD4+ T cell recovery at weeks 72 (P = 0.048) and 96 (P = 0.024) compared to the Control Group. Additionally, stratified analysis of patients in the AAIT Group showed that donor/recipient sex mismatch was significantly associated with the likelihood of patients achieving an immunological response (OR = 8.667; 95% CI, 2.010-37.377; P = 0.004). These findings suggest that AAIT serves as a promising adjunct therapy for improving the outcomes of patients with severely immunosuppressed AIDS. Further studies are needed to elucidate the immunological mechanisms underlying AAIT and identify the subpopulations that respond optimally to this therapeutic approach. This trial is registered at www.clinicaltrials.gov (NCT04098770).Trial registration: ClinicalTrials.gov identifier: NCT04098770.Trial registration: ClinicalTrials.gov identifier: NCT02651376.

Characteristics and risk factors for readmission in HIV-infected patients with Talaromyces marneffei infection.

OBJECTIVES: Talaromyces marneffei (T. marneffei) is an opportunistic fungal infection (talaromycosis), which is common in subtropical regions and is a leading cause of death in HIV-1-infected patients. This study aimed to determine the characteristics and risk factors associated with hospital readmissions in HIV patients with T. marneffei infection in order to reduce readmissions. METHODS: We conducted a retrospective study of admitted HIV-infected individuals at the Fourth People's Hospital of Nanning, Guangxi, China, from 2012 to 2019. Kaplan-Meier analyses and Principal component analysis (PCA) were used to evaluate the effects of T. marneffei infection on patient readmissions. Additionally, univariate and multifactorial analyses, as well as Propensity score matching (PSM) were used to analyze the factors associated with patient readmissions. RESULTS: HIV/AIDS patients with T. marneffei-infected had shorter intervals between admissions and longer lengths of stay than non-T. marneffei-infected patients, despite lower readmission rates. Compared with non-T. marneffei-infected patients, the mortality rate for talaromycosis patients was higher at the first admission. Among HIV/AIDS patients with opportunistic infections, the mortality rate was highest for T. marneffei at 16.2%, followed by cryptococcus at 12.5%. However, the readmission rate was highest for cryptococcus infection (37.5%) and lowest for T. marneffei (10.8%). PSM and Logistic regression analysis identified leukopenia and elevated low-density lipoprotein (LDL) as key factors in T.marneffei-infected patients hospital readmissions. CONCLUSIONS: The first admission represents a critical window to intervene in the prognosis of patients with T. marneffei infection. Leukopenia and elevated LDL may be potential risk factors impacting readmissions. Our findings provide scientific evidence to improve the long-term outcomes of HIV patients with T. marneffei infection.

Elevated glutamate impedes anti-HIV-1 CD8 + T cell responses in HIV-1-infected individuals on antiretroviral therapy.

CD8 + T cells are essential for long-lasting HIV-1 control and have been harnessed to develop therapeutic and preventive approaches for people living with HIV-1 (PLWH). HIV-1 infection induces marked metabolic alterations. However, it is unclear whether these changes affect the anti-HIV function of CD8 + T cells. Here, we show that PLWH exhibit higher levels of plasma glutamate than healthy controls. In PLWH, glutamate levels positively correlate with HIV-1 reservoir and negatively correlate with the anti-HIV function of CD8 + T cells. Single-cell metabolic modeling reveals glutamate metabolism is surprisingly robust in virtual memory CD8 + T cells (TVM). We further confirmed that glutamate inhibits TVM cells function via the mTORC1 pathway in vitro. Our findings reveal an association between metabolic plasticity and CD8 + T cell-mediated HIV control, suggesting that glutamate metabolism can be exploited as a therapeutic target for the reversion of anti-HIV CD8 + T cell function in PLWH.

Machine learning-based in-hospital mortality prediction of HIV/AIDS patients with Talaromyces marneffei infection in Guangxi, China.

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.

CCL5-Secreting Virtual Memory CD8+ T Cells Inversely Associate With Viral Reservoir Size in HIV-1-Infected Individuals on Antiretroviral Therapy.

Recent studies highlighted that CD8+ T cells are necessary for restraining reservoir in HIV-1-infected individuals who undergo antiretroviral therapy (ART), whereas the underlying cellular and molecular mechanisms remain largely unknown. Here, we enrolled 60 virologically suppressed HIV-1-infected individuals, to assess the correlations of the effector molecules and phenotypic subsets of CD8+ T cells with HIV-1 DNA and cell-associated unspliced RNA (CA usRNA). We found that the levels of HIV-1 DNA and usRNA correlated positively with the percentage of CCL4+CCL5- CD8+ central memory cells (TCM) while negatively with CCL4-CCL5+ CD8+ terminally differentiated effector memory cells (TEMRA). Moreover, a virtual memory CD8+ T cell (TVM) subset was enriched in CCL4-CCL5+ TEMRA cells and phenotypically distinctive from CCL4+ TCM subset, supported by single-cell RNA-Seq data. Specifically, TVM cells showed superior cytotoxicity potentially driven by T-bet and RUNX3, while CCL4+ TCM subset displayed a suppressive phenotype dominated by JUNB and CREM. In viral inhibition assays, TVM cells inhibited HIV-1 reactivation more effectively than non-TVM CD8+ T cells, which was dependent on CCL5 secretion. Our study highlights CCL5-secreting TVM cells subset as a potential determinant of HIV-1 reservoir size. This might be helpful to design CD8+ T cell-based therapeutic strategies for cure of the disease.

An optimal BMI range associated with a lower risk of mortality among HIV-infected adults initiating antiretroviral therapy in Guangxi, China.

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/m2, especially 24-28 kg/m2, have a reduced risk of death.

Effects of cotrimoxazole prophylaxis on Talaromyces marneffei infection in HIV/AIDS patients receiving antiretroviral therapy: a retrospective cohort study.

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.

Commercial Sexual Behaviors Among Male Rural-to-Urban Migrants in Western China: Implications for HIV Prevention.

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.