Global analysis of an age-structured tuberculosis model with an application to Jiangsu, China.

Diagnostic delay for TB infected individuals and the lack of TB vaccines for adults are the main challenges to achieve the goals of WHO by 2050. In order to evaluate the impacts of diagnostic delay and vaccination for adults on prevalence of TB, we propose an age-structured model with latent age and infection age, and we incorporate Mycobacterium TB in the environment and vaccination into the model. Diagnostic delay is indicated by the age of infection before receiving treatment. The threshold dynamics are established in terms of the basic reproduction number R 0 . When R 0 < 1 , the disease-free equilibrium is globally asymptotically stable, which means that TB epidemic will die out; When R 0 = 1 , the disease-free equilibrium is globally attractive; there exists a unique endemic equilibrium and the endemic equilibrium is globally attractive when R 0 > 1 . We estimate that the basic reproduction number R 0 = 0.5320 (95% CI (0.3060, 0.7556)) in Jiangsu Province, which means that TB epidemic will die out. However, we find that the annual number of new TB cases by 2050 is 1,151 (95%CI: (138, 8,014)), which means that it is challenging to achieve the goal of WHO by 2050. To this end, we evaluate the possibility of achieving the goals of WHO if we start vaccinating adults and reduce diagnostic delay in 2025. Our results demonstrate that when the diagnostic delay is reduced from longer than four months to four months, or 20% adults are vaccinated, the goal of WHO in 2050 can be achieved, and 73,137 (95%CI: (23,906, 234,086)) and 54,828 (95%CI: (15,811, 206,468)) individuals will be prevented from being infected from 2025 to 2050, respectively. The modeling approaches and simulation results used in this work can help policymakers design control measures to reduce the prevalence of TB.

Exploring the seasonality and optimal control strategy of HIV/AIDS epidemic in China: The impact of seasonal testing.

In this work, we investigate how the seasonal variation in the number of individuals who are tested for an HIV antibody in outpatient clinics affects the HIV transmission patterns in China, which has not been well studied. Based on the characteristics of outpatient testing data and reported cases, we establish a periodic infectious disease model to study the impact of seasonal testing on HIV transmission. The results indicate that the seasonal testing is a driving factor for the seasonality of new cases. We demonstrate the feasibility of ending the HIV/AIDS epidemic. We find that the diagnostic rates related to testing play a crucial role in controlling the size of the epidemic. Specifically, when considering minimizing both infected individuals and diagnostic rates, the level of attention paid to undiagnosed infected individuals is always positively correlated with the optimal diagnostic rates, while the optimal diagnostic rates are negatively correlated with the size of the epidemic at the terminal time.

High Cytomegalovirus Viral Load Is Associated With 182-Day All-Cause Mortality in Hospitalized People With Human Immunodeficiency Virus.

BACKGROUND: Cytomegalovirus (CMV) infection is associated with increased mortality in persons with HIV (PWH). It is less clear whether CMV infection is still associated with mortality when routinely screened and adequately treated. METHODS: This retrospective cohort study recruited 1003 hospitalized adults with HIV with CD4 cell counts <200 cells/µL from May 2017 to June 2021. Blood CMV DNA was routinely measured and CMV DNAemia was treated if end-organ disease occurred. CMV viral load was categorized into below the limit of quantification (BLQ; <500 IU/mL), low viral load (LVL; 500-10 000 IU/mL), and high viral load (HVL; ≥10 000 IU/mL) groups. We compared the 182-day all-cause mortality among different groups. RESULTS: The median (IQR) CD4 cell count of patients was 33 (13-84) cells/µL. The prevalence of CMV DNAemia was 39.8% (95% CI: 36.7-42.9%) and was significantly associated with CD4 cell count. The 182-day all-cause mortality was 9.9% (95% CI: 8.0-11.7%). Univariable analysis showed that, compared with BLQ, LVL and HVL were associated with 1.73-fold and 3.81-fold increased risks of mortality, respectively (P = .032 and P < .001). After adjustment for predefined confounding factors, HVL but not LVL was still associated with increased risk of mortality (adjusted hazard ratio: 2.63; 95% CI: 1.61-4.29; P < .001). However, for patients on effective antiretroviral therapy, the impact of HVL on 182-day mortality was not significant (P = .713). CONCLUSIONS: High CMV viral load in hospitalized PWH was associated with higher mortality, even when identified early by screening. Optimalization of the management for those patients needs to be explored in future studies.

Association of Endocrine-Disrupting Chemicals with All-Cause and Cause-Specific Mortality in the U.S.: A Prospective Cohort Study.

Wide exposure to endocrine-disrupting chemicals (EDCs) poses a great risk on human health. However, few large-scale cohort studies have comprehensively estimated the association between EDCs exposure and mortality risk. This study aimed to investigate the association of urinary EDCs exposure with mortality risk and quantify attributable mortality and economic loss. Multivariable Cox proportional hazards regression models were performed to investigate the association of 38 representative EDCs exposure with mortality risk in the National Health and Nutrition Examination Survey (NHANES). During a median follow-up of 7.7 years, 47,279 individuals were enrolled. All-cause mortality was positively associated with 1-hydroxynaphthalene, 2-hydroxynaphthalene, cadmium, antimony, cobalt, and monobenzyl phthalate. Cancer mortality was positively associated with cadmium. Cardiovascular disease (CVD) mortality was positively associated with 1-hydroxynaphthalene, 2-hydroxynaphthalene, and 2-hydroxyfluorene. Nonlinear U-shaped relationships were found between all-cause mortality and cadmium and cobalt, which was also identified between 2-hydroxyfluorene and CVD mortality. J-shaped association of cadmium exposure with cancer mortality was also determined. EDCs exposure may cause 56.52% of total deaths (1,528,500 deaths) and around 1,897 billion USD in economic costs. Exposure to certain phthalates, polycyclic aromatic hydrocarbons, phytoestrogens, or toxic metals, even at substantially low levels, is significantly associated with mortality and induces high economic costs.

Impact of inactivated COVID-19 vaccines on lung injury in B.1.617.2 (Delta) variant-infected patients.

BACKGROUND: Chest computerized tomography (CT) scan is an important strategy that quantifies the severity of COVID-19 pneumonia. To what extent inactivated COVID-19 vaccines could impact the COVID-19 pneumonia on chest CT is not clear. METHODS: This study recruited 357 SARS-COV-2 B.1.617.2 (Delta) variant-infected patients admitted to the Second Hospital of Nanjing from July to August 2021. An artificial intelligence-assisted CT imaging system was used to quantify the severity of COVID-19 pneumonia. We compared the volume of infection (VOI), percentage of infection (POI) and chest CT scores among patients with different vaccination statuses. RESULTS: Of the 357 Delta variant-infected patients included for analysis, 105 were unvaccinated, 72 were partially vaccinated and 180 were fully vaccinated. Fully vaccination had the least lung injuries when quantified by VOI (median VOI of 222.4 cm3, 126.6 cm3 and 39.9 cm3 in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001), POI (median POI of 7.60%, 3.55% and 1.20% in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001) and chest CT scores (median CT score of 8.00, 6.00 and 4.00 in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001). After adjustment for age, sex, comorbidity, time from illness onset to hospitalization and viral load, fully vaccination but not partial vaccination was significantly associated with less lung injuries quantified by VOI {adjust coefficient[95%CI] for "full vaccination": - 106.10(- 167.30,44.89); p < 0.001}, POI {adjust coefficient[95%CI] for "full vaccination": - 3.88(- 5.96, - 1.79); p = 0.001} and chest CT scores {adjust coefficient[95%CI] for "full vaccination": - 1.81(- 2.72, - 0.91); p < 0.001}. The extent of reduction of pulmonary injuries was more profound in fully vaccinated patients with older age, having underlying diseases, and being female sex, as demonstrated by relatively larger absolute values of adjusted coefficients. Finally, even within the non-severe COVID-19 population, fully vaccinated patients were found to have less lung injuries. CONCLUSION: Fully vaccination but not partially vaccination could significantly protect lung injury manifested on chest CT. Our study provides additional evidence to encourage a full course of vaccination.

Non-invasive embryo selection strategy for clinical IVF to avoid wastage of potentially competent embryos.

RESEARCH QUESTION: Can a non-invasive embryo transfer strategy provide a reference for embryo selection to be established? DESIGN: Chromosome sequencing of 345 paired blastocyst culture medium and whole blastocyst samples was carried out and a non-invasive embryo grading system was developed based on the random forest machine learning algorithm to predict blastocyst ploidy. The system was validated in 266 patients, and a blinded prospective observational study was conducted to investigate clinical outcomes between machine learning-guided and traditional non-invasive preimplantation genetic testing for aneuploidy (niPGT-A) analyses. Embryos were graded as A, B or C according to their euploidy probability levels predicted by non-invasive chromosomal screening (NICS). RESULTS: Higher live birth rate was observed in A- versus C-grade embryos (50.4% versus 27.1%, P = 0.006) and B- versus C-grade embryos (45.3% versus 27.1%, P = 0.022) and lower miscarriage rate in A- versus C-grade embryos (15.9% versus 33.3%, P = 0.026) and B- versus C-grade embryos (14.3% versus 33.3%, P = 0.021). The embryo utilization rate was significantly higher through the machine learning strategy than the conventional dichotomic judgment of euploidy or aneuploidy in the niPGT-A analysis (78.8% versus 57.9%, P < 0.001). Better outcomes were observed in A- and B-grade embryos versus C-grade embryos and higher embryo utilization rates through the machine learning strategy compared with traditional niPGT-A analysis. CONCLUSION: A machine learning guided embryo grading system can be used to optimize embryo selection and avoid wastage of potential embryos.

Vaccine failure, seasonality and demographic changes associate with mumps outbreaks in Jiangsu Province, China: Age-structured mathematical modelling study.

Measles, mumps and rubella (MMR) vaccine program was introduced in Jiangsu province of China in May 2008 and has been greatly contributed to decreasing of mumps cases. However, mumps has been resurging since May 2015. A number of studies have put forward that the resurgence of mumps is due to vaccine failure. In this paper, we investigated the other reasons for the resurging of mumps, such as the changes in seasonal transmission patterns and demographic structures, by using an age-structured mathematical model. We divided the history (January 2005 to May 2019) of mumps epidemics of Jiangsu province into three different stages: No vaccine stage (January 2005 to December 2008), effectively controlled stage (January 2009 to December 2014) and resurgence stage (January 2015 to May 2019). The features of mumps epidemics in three stages are compared under different demographic structures with same physical contact rate. The mumps transmission rate was increased in summer and dropped in November in stage III compared with that in stage I. The changes in demographic structures give a good explanation why the mumps outbreaked among children around 10 years old in stage I and around 5 years old in stage III. We have a conclusion that the vaccine failure, changes in seasonality and demographic structures were associated with the mumps outbreaks in recent years in Jiangsu province, China. We give the patterns of mumps dynamics considering age, vaccine, seasonality and demographic structures, which can help health program planners to implement more preventive interventions in mumps control during the period of higher risk of infection.

The impact of supplementary immunization activities on measles transmission dynamics and implications for measles elimination goals: A mathematical modelling study.

BACKGROUND: Measles has re-emerged globally due to the accumulation of susceptible individuals and immunity gap, which causes challenges in eliminating measles. Routine vaccination and supplementary immunization activities (SIAs) have greatly improved measles control, but the impact of SIAs on the measles transmission dynamics remains unclear as the vaccine-induced immunity wanes. METHODS: We developed a comprehensive measles transmission dynamics model by taking into account population demographics, age-specific contact patterns, seasonality, routine vaccination, SIAs, and the waning vaccine-induced immunity. The model was calibrated by the monthly age-specific cases data from 2005 to 2018 in Jiangsu Province, China, and validated by the dynamic sero-prevalence data. We aimed to investigate the short-term and long-term impact of three-time SIAs during 2009-2012 (9.68 million and 4.25 million children aged 8 months-14 years in March 2009 and September 2010, respectively, and 140,000 children aged 8 months-6 years in March 2012) on the measles disease burden and explored whether additional SIAs could accelerate the measles elimination. RESULTS: We estimated that the cumulative numbers of measles cases from March 2009 to December 2012 (in the short run) and to December 2018 (in the long run) after three-time SIAs (base case) were 6,699 (95% confidence interval [CI]: 2,928-10,469), and 22,411 (15,146-29,675), which averted 45.0% (42.9%-47.0%) and 34.3% (30.7%-37.9%) of 12,226 (4,916-19,537) and 34,274 (21,350-47,199) cases without SIAs, respectively. The fraction of susceptibles for children aged 8-23 months and 2-14 years decreased from 8.3% and 10.8% in March 2009 to 5.8% and 5.8% in April 2012, respectively. However, the fraction of susceptibles aged 15-49 years and above 50 years increased gradually to about 15% in 2018 irrespective of SIAs due to the waning immunity. The measles elimination goal would be reached in 2028, and administrating additional one-off SIAs in September 2022 to children aged 8-23 months, or young adolescents aged 15-19 years could accelerate the elimination one year earlier. CONCLUSIONS: SIAs have greatly reduced the measles incidence and the fraction of susceptibles, but the benefit may wane over time. Under the current interventions, Jiangsu province would reach the measles elimination goal in 2028. Additional SIAs may accelerate the measles elimination one year earlier.

Construction and validation of a prognostic nomogram for predicting the survival of HIV/AIDS adults who received antiretroviral therapy: a cohort between 2003 and 2019 in Nanjing.

BACKGROUND: Great achievements have been achieved by free antiretroviral therapy (ART). A rapid and accurate prediction of survival in people living with HIV/AIDS (PLHIV) is needed for effective management. We aimed to establish an effective prognostic model to forecast the survival of PLHIV after ART. METHODS: The participants were enrolled from a follow-up cohort over 2003-2019 in Nanjing AIDS Prevention and Control Information System. A nested case-control study was employed with HIV-related death, and a propensity-score matching (PSM) approach was applied in a ratio of 1:4 to allocate the patients. Univariable and multivariable Cox proportional hazards analyses were performed based on the training set to determine the risk factors. The discrimination was qualified using the area under the curve (AUC) and concordance index (C-Index). The nomogram was calibrated using the calibration curve. The clinical benefit of prognostic nomogram was assessed by decision curve analysis (DCA). RESULTS: Predictive factors including CD4 cell count (CD4), body mass index (BMI) and hemoglobin (HB) were determined and incorporated into the nomogram. In the training set, AUC and C-index (95% CI) were 0.831 and 0.798 (0.758, 0.839), respectively. The validation set revealed a good discrimination with an AUC of 0.802 and a C-index (95% CI) of 0.786 (0.681, 0.892). The calibration curve also exhibited a high consistency in the predictive power (especially in the first 3 years after ART initiation) of the nomogram. Moreover, DCA demonstrated that the nomogram was clinically beneficial. CONCLUSION: The nomogram is effective and accurate in forecasting the survival of PLHIV, and beneficial for medical workers in health administration.

Immunity and coagulation and fibrinolytic processes may reduce the risk of severe illness in pregnant women with coronavirus disease 2019.

BACKGROUND: There are specific physiological features regarding the immunity and coagulation among pregnant women, which may play important roles in the development of coronavirus disease 2019. OBJECTIVE: This study aimed to determine the key factors associated with the deterioration of patients with coronavirus disease 2019 and the differentiating clinical characteristics of pregnant women with coronavirus disease 2019 to interfere with the progression of coronavirus disease 2019. STUDY DESIGN: A retrospective study of 539 Chinese Han adult patients with coronavirus disease 2019 was conducted, of which 36 cases were pregnant women. In addition, 36 pregnant women without coronavirus disease 2019 were recruited as the control. The characteristics of severe and critical illnesses, which were differentiated from mild and moderate illnesses in patients with coronavirus disease 2019, were analyzed using a machine learning algorithm. In addition, major differences between pregnant women with coronavirus disease 2019 and age-matched nonpregnant women with severe or critical coronavirus disease 2019, paired with pregnant women without coronavirus disease 2019, were explored to identify specific physiological features of pregnant women with coronavirus disease 2019. RESULTS: For the total patient population, the lymphocyte, CD3+, CD4+, CD8+, CD19+, and CD16+CD56+ cell counts were significantly lower, and white blood cell count, neutrophil count, and neutrophil-to-lymphocyte ratio were higher in those with severe or critical illness than those with mild or moderate illness (P<.001). The plasma levels of interleukin-6, interleukin-10, and interleukin-6-to-interleukin-10 ratio were significantly increased in patients with critical illness compared with patients with mild, moderate, and severe illnesses (P<.001). The above immunologic coclusters achieved an area under the receiver operating characteristic curve of 0.801 (95% confidence interval, 0.764-0.838), and its combined model with the coagulation and fibrinolysis indices (prothrombin time, D-dimer) achieved an area under the receiver operating characteristic curve of 0.815 (95% confidence interval, 0.779-0.851) using the random forest regression model to predict severe or critical illness. For pregnant women with coronavirus disease 2019, none had preexisting diseases. Compared with nonpregnant women with mild or moderate coronavirus disease 2019, pregnant women with coronavirus disease 2019 displayed increased white blood cell count, neutrophil count, neutrophil-to-lymphocyte ratio, and levels of D-dimer and fibrinogen, along with decreased lymphocyte and interleukin-4 levels (P<.05). Although they presented similar changes of immunologic markers of lymphocyte; white blood cell count; neutrophil-to-lymphocyte ratio; CD3+, CD4+, CD8+, and CD16+CD56+ cell counts; and interleukin-6-to-interleukin-10 ratio, compared with nonpregnant women with severe or critical coronavirus disease 2019, none of the pregnant women with coronavirus disease 2019 deteriorated into severe or critical illness. There was no significant difference in white blood cell count, lymphocyte count, neutrophil count, neutrophil-to-lymphocyte ratio, immunologic markers, or coagulation and fibrinolysis markers between pregnant women with coronavirus disease 2019 and pregnant women without coronavirus disease 2019. As for the discrepancy of pathophysiological features between pregnant women with coronavirus disease 2019 and nonpregnant women with severe or critical coronavirus disease 2019, the immunologic markers achieved an area under the receiver operating characteristic curve of 0.875 (95% confidence interval, 0.773-0.977), and its combined model with coagulation and fibrinolysis indices achieved an area under the receiver operating characteristic curve of 0.931 (95% confidence interval, 0.850-1.000). CONCLUSION: Immune dysregulation was identified as a crucial feature of patients with coronavirus disease 2019, which developed severe or critical illness, and pregnant women with coronavirus disease 2019 presented with similar immune responses but rarer incidences of severe or critical illness. Immune dysregulation is related to the risks of deterioration into severe or critical illness. The specific coagulation and fibrinolysis systems of pregnancy may reduce the risk of pregnant women with coronavirus disease 2019 without preexisting disease from developing severe illness.

Modelling the effects of the contaminated environments on tuberculosis in Jiangsu, China.

Tuberculosis (TB) is still an important public health issue in Jiangsu province, China. In this study, based on the TB transmission routes and the statistical data of TB cases, we formulate a novel TB epidemic model accounting for the effects of the contaminated environments on TB transmission dynamics. The value of this study lies in two aspects. Mathematically, we define the basic reproduction number, R0, and prove that R0 can be used to govern the threshold dynamics of the model. Epidemiologically, we find that the annual average R0 is 1.13,>1 and TB in Jiangsu is an endemic disease. Therefore, in order to control the TB in Jiangsu efficiently, we must decrease the virus shedding rate or increase the recovery rates, and increase the environmental clearance rate.

Inferencing superspreading potential using zero-truncated negative binomial model: exemplification with COVID-19.

BACKGROUND: In infectious disease transmission dynamics, the high heterogeneity in individual infectiousness indicates that few index cases generate large numbers of secondary cases, which is commonly known as superspreading events. The heterogeneity in transmission can be measured by describing the distribution of the number of secondary cases as a negative binomial (NB) distribution with dispersion parameter, k. However, such inference framework usually neglects the under-ascertainment of sporadic cases, which are those without known epidemiological link and considered as independent clusters of size one, and this may potentially bias the estimates. METHODS: In this study, we adopt a zero-truncated likelihood-based framework to estimate k. We evaluate the estimation performance by using stochastic simulations, and compare it with the baseline non-truncated version. We exemplify the analytical framework with three contact tracing datasets of COVID-19. RESULTS: We demonstrate that the estimation bias exists when the under-ascertainment of index cases with 0 secondary case occurs, and the zero-truncated inference overcomes this problem and yields a less biased estimator of k. We find that the k of COVID-19 is inferred at 0.32 (95%CI: 0.15, 0.64), which appears slightly smaller than many previous estimates. We provide the simulation codes applying the inference framework in this study. CONCLUSIONS: The zero-truncated framework is recommended for less biased transmission heterogeneity estimates. These findings highlight the importance of individual-specific case management strategies to mitigate COVID-19 pandemic by lowering the transmission risks of potential super-spreaders with priority.

Epidemiology of 631 Cases of COVID-19 Identified in Jiangsu Province Between January 1st and March 20th 2020: Factors Associated with Disease Severity and Analysis of Zero Mortality.

BACKGROUND This retrospective study aimed to investigate the factors associated with disease severity and patient outcomes in 631 patients with COVID-19 who were reported to the Jiangsu Commission of Health between January 1 and March 20, 2020. MATERIAL AND METHODS We conducted an epidemiological investigation enrolling 631 patients with laboratory-confirmed COVID-19 from our clinic from January to March 2020. Patients' information was collected through a standard questionnaire. Then, we described the patients' epidemiological characteristics, analyzed risk factors associated with disease severity, and assessed causes of zero mortality. Additionally, some key technologies for epidemic prevention and control were identified. RESULTS Of the 631 patients, 8.46% (n=53) were severe cases, and no deaths were recorded (n=0). The epidemic of COVID-19 has gone through 4 stages: a sporadic phase, an exponential growth phase, a peak plateau phase, and a declining phase. The proportion of severe cases was significantly different among the 4 stages and 13 municipal prefectures (P<0.001). Factors including age >65 years old, underlying medical conditions, highest fever >39.0°C, dyspnea, and lymphocytopenia (<1.0×109/L) were early warning signs of disease severity (P<0.05). In contrast, earlier clinic visits were associated with better patient outcomes (P=0.029). Further, the viral load was a potentially useful marker associated with COVID-19 infection severity. CONCLUSIONS The study findings from the beginning of the COVID-19 epidemic in Jiangsu Province, China showed that patients who were more than 65 years of age and with comorbidities and presented with a fever of more than 39.0°C developed more severe disease. However, mortality was prevented in this initial patient population by early supportive clinical management.

Analysis on the trend of AIDS incidence in Zhejiang, China based on the age-period-cohort model (2004-2018).

OBJECTIVE: To predict the trend of AIDS in specific age groups and to determine the objective population for AIDS screening, this study explored the three transmission routes and characterized each patient group using the APC model based on the whole, local, and immigrant populations in Zhejiang, China. METHODS: The data recruited in this paper was obtained from the national Comprehensive AIDS Prevention and Control Information System - Antiviral Therapy Management database and the Chinese Disease Prevention and Control Information System and the Statistical Yearbook of Zhejiang, China. An APC model was used to estimate the impact of age, period, and cohort on the incidence of AIDS, as well as to predict the AIDS incidence in specific age groups based on different sexes with different transmission routes. RESULTS: The AIDS incidence peaked in males aged 20-35 years; the incidence of males was higher than that of females due to the impact of period; obvious cohort effect was observed among the immigrants. In the whole and local populations, the incidences of males in all age groups and females in both the 35-year-old group and the whole age group were predicted to increase sharply in 5 years. In the immigrant population, the AIDS incidences in both sexes in all age groups were expected to increase significantly in 5 years. Under the influence of period, the incidence of AIDS via homosexual transmission in the whole population and the local population increased and remained stable after 2015. At the same time, the incidence of AIDS transmitted by homosexual and heterosexual routes in the immigrants also showed an increasing trend. CONCLUSIONS: The results elucidate that there are sex differences in AIDS incidence, and the incidence of AIDS through various transmission routes in all groups is predicted to exhibit an upward trend in the 5 years to come. Effective intervention strategies should be developed and implemented by the public health departments in Zhejiang to control the epidemic of AIDS.

The effects of acupuncture on pregnancy outcomes of in vitro fertilization: a systematic review and meta-analysis.

BACKGROUND: The effects of acupuncture on in vitro fertilization (IVF) outcomes remain controversial. And the variation in participant, interventions, outcomes studied, and trial design may relate to the efficacy of adjuvant acupuncture. METHODS: We searched digital databases for relevant studies, including Embase, PubMed, Cochrane Library and some Chinese databases up to December 2018, for randomized controlled trials (RCTs) evaluating the effects of acupuncture on women undergoing IVF. We included studies with intervention groups using needling, and control groups consisting of no acupuncture or sham (placebo) acupuncture. Primary outcomes were clinical pregnancy rate (CPR) and live birth rate (LBR). Meta-regression and subgroup analysis were conducted on the basis of eight pre-specified covariates to investigate the variances of the effects of adjuvant acupuncture on pregnancy rates and the sources of heterogeneity. RESULTS: Twenty-seven studies with 6116 participants were included. The pooled clinical pregnancy rate (CPR) from all of acupuncture groups was significantly greater than that of control groups (RR 1.21, 95% CI: 1.07-1.38), whereas the pooled live birth rate (LBR) was not. Meta-regression subgroup analysis showed a more significant benefit of acupuncture for repeated IVF cycle proportion (number of women with a history of prior unsuccessful IVF attempt divided by number of women included in each trial) ≥ 50% group (CPR: RR 1.60, 95% CI: 1.28-2.00; LBR: RR 1.42, 95% CI: 1.05-1.92), and this covariate explained most of the heterogeneity (CPR and LBR: adjusted R2 = 100 and 87.90%). Similar results were found between CPR and number of acupuncture treatments (CPR: p = 0.002, adjusted R2 = 51.90%), but not LBR. CONCLUSIONS: Our analysis finds a benefit of acupuncture for IVF outcomes in women with a history of unsuccessful IVF attempt, and number of acupuncture treatments is a potential influential factor. Given the poor reporting and methodological flaws of existing studies, studies with larger scales and better methodologies are needed to verify these findings.

Assessment of the cancerization risk for oral potentially malignant disorders by clinical risk model combined with autofluorescence and brush biopsy with DNA-image cytometry.

PURPOSE: To explore the feasibility of assessing the cancerization risk of oral potentially malignant disorders (OPMD) through a clinical risk model combined with autofluorescence and brush biopsy with DNA-image cytometry. METHODS: We collected the baseline clinical data of 269 patients; then, performed autofluorescence, brush biopsy with DNA-image cytometry and histopathological examination. Then, we obtained the significant factors by univariate logistic analysis, constructed the clinical risk model by multiple logistic regression and selected the optimal cutoff value according to the maximum Youden index. Finally, we calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the clinical risk score ≥ cutoff value, autofluorescence and brush biopsy with DNA-image cytometry, and plotted the receiver-operating characteristic (ROC) curves and decision curve analysis (DCA). RESULTS: The clinical risk model is represented by the formula: 1 × gender + 1.6 × age group + 1 × lesion site + 1.4 × local stimulus + 1.5 × drink. The area under the curve (AUC) was 0.83, and the optimal cutoff score was 3. The AUC indicated that the clinical risk score ≥ 3 (0.74) and autofluorescence (0.77) had a certain diagnostic values, while brush biopsy with DNA-image cytometry (0.92) displayed a good value. Besides, the DCA showed that all three tests had clinical significance. CONCLUSIONS: The cancerization risk of patients can be assessed by the clinical risk model combined with sequence application of autofluorescence and brush biopsy with DNA-image cytometry, to decide whether histopathological examination or other intervention measures should be selected.

Personalized life expectancy and treatment benefit index of antiretroviral therapy.

BACKGROUND: The progression of Human Immunodeficiency Virus (HIV) within host includes typical stages and the Antiretroviral Therapy (ART) is shown to be effective in slowing down this progression. There are great challenges in describing the entire HIV disease progression and evaluating comprehensive effects of ART on life expectancy for HIV infected individuals on ART. METHODS: We develop a novel summative treatment benefit index (TBI), based on an HIV viral dynamics model and linking the infection and viral production rates to the Weibull function. This index summarizes the integrated effect of ART on the life expectancy (LE) of a patient, and more importantly, can be reconstructed from the individual clinic data. RESULTS: The proposed model, faithfully mimicking the entire HIV disease progression, enables us to predict life expectancy and trace back the timing of infection. We fit the model to the longitudinal data in a cohort study in China to reconstruct the treatment benefit index, and we describe the dependence of individual life expectancy on key ART treatment specifics including the timing of ART initiation, timing of emergence of drug resistant virus variants and ART adherence. CONCLUSIONS: We show that combining model predictions with monitored CD4 counts and viral loads can provide critical information about the disease progression, to assist the design of ART regimen for maximizing the treatment benefits.

A novel polymorphism near HLA class II region is associated with spontaneous clearance of HCV and response to interferon treatment in Chinese patients.

A recent genome-wide association study (GWAS) has identified the single-nucleotide polymorphism (SNP) rs4273729 in a 100-kbp region comprising human leukocyte antigens (HLAs) class II genes as an important predictor of hepatitis C virus (HCV) clearance in European and African populations. This study was to determine whether this polymorphism is also associated with spontaneous HCV clearance as well as response to interferon treatment in Chinese patients. Thus, 686 chronic HCV carriers, 432 individuals with spontaneous viral clearance and 243 patients with pegylated interferon-α and ribavirin (PEG IFN-α/RBV) treatment were genotyped. The rs4273729 GG genotype was strongly associated with spontaneous HCV clearance as well as better IFN/RBV treatment response compared with the GC/CC genotypes in Chinese Han population (additive model: odds ratio (OR)=0.62, 95% confidence interval (95% CI)=0.51-0.76; OR=0.58, 95% CI=0.38-0.88, respectively). Rs4273729, rs12980275, baseline HCV RNA and platelet level were independent predictors for sustained virological response (SVR). The area under the receiver-operating characteristic curve (AUC) was 0.578 when including rs4273729 alone, but the prediction value was improved significantly (AUC=0.733) when further including rs12980275, baseline viral load and baseline platelet level. In conclusion, the genetic variation of rs4273729 is associated with clearance of HCV in both the natural course and the treatment process in Chinese Han population.

Genetic variations in vitamin D receptor were associated with the outcomes of hepatitis C virus infection among Chinese population.

Vitamin D has been considered as an immune modulator, and exerted the effect through the vitamin D receptor (VDR). This study investigated the associations of single-nucleotide polymorphisms (SNPs) of VDR with the outcomes of Hepatitis C virus (HCV) infection. Three SNPs (rs2228570, rs757343 and rs739837) were genotyped by TaqMan assay among Chinese population, including 538 HCV spontaneous clearance subjects, 834 persistent infection subjects and 1030 uninfected subjects. Binary logistic analyses were used to control the effects of confounding factors. The results showed that subjects with the rs757343 A allele and rs739837 A allele had the significantly reduced risk of HCV susceptibility (all PBonferroni<0.05 in dominant/additive model). In the stratified analysis, the protection of rs757343 A allele and rs739837 A allele against HCV infection remained effective in some subgroups. In addition, patients carrying rs739837 CA genotype were less prone to develop persistent infection (PBonferroni=0.033) and such effect still work in several subgroups in the stratified analysis. Furthermore, haplotype analysis indicated that when compared with the most frequent GC haplotype, the haplotype carrying AA (odds ratio (OR)=0.66, 95% confidence interval (CI)=0.56-0.78) and GA (OR=0.64, 95% CI=0.47-0.85) suggested a protective effect. Our findings indicated that the polymorphisms of VDR are associated with the outcomes of HCV infection among Chinese population.