Economic evaluation of GnRH-agonist long protocol and GnRH-antagonist protocol in IVT/ICSI among the Chinese population: using pharmacoeconomic models.

OBJECTIVE: This paper uses health economics methods to discuss the cost-effectiveness value of long protocol and antagonist protocol for in vitro fertilisation and embryo transfer (ET) in the Chinese population. DESIGN: Health economic evaluation study. SETTING: The data needed to construct the model for this study were derived from published studies and other secondary sources in China. PARTICIPANTS: No patients participated in the study. MEASURES: The main outcomes were live birth rate (LBR) and cost. From the societal perspective, we considered the direct and indirect costs over the course of the treatment cycles. A cost-effectiveness was measured using the incremental cost-effectiveness ratio and the probability that a protocol has higher net monetary benefit. Sensitivity analysis was carried out to verify the reliability of the simulation results. RESULTS: For the Chinese population, the long protocol resulted in a higher LBR than the antagonist protocol (29.33% vs 20.39%), but at the same time, it was more expensive (ï¿¥29 146.26 (US$4333.17) vs ï¿¥23 343.70 (US$3470.51)), in the case of considering only one fresh ET cycle. It was the same when considering subsequent frozen ET (FET) cycles (51.78% vs 42.81%; ï¿¥30 703.02 (US$4564.62) vs ï¿¥24 740.95 (US$3678.24)). The results of most subgroups were consistent with the results of the basic analysis. However, for certain populations, the long protocol was the inferior protocol (less effective and more expensive). CONCLUSION: For the Chinese population, when the monetary value per live birth was greater than ï¿¥65 420 (US$9726) and ï¿¥66 400 (US$9872), respectively, considering only one fresh cycle and considering subsequent frozen cycles, the long protocol is the preferred protocol. This threshold also varies for women of different ages and ovarian response capacities. For women in POSEIDON (Patient-Oriented Strategies Encompassing IndividualizeD Oocyte Number) group 2, group 3 and group 4, antagonist protocol is recommended as the preferred protocol. The results of this study need to be verified by further large-scale randomised controlled trials.

Systematic review of the economic evaluation model of assisted reproductive technology.

BACKGROUND: With the increasing demand for fertility services, it is urgent to select the most cost-effective assisted reproductive technology (ART) treatment plan and include it in medical insurance. Economic evaluation reports are an important reference for medical insurance negotiation. The aim of this study is to systematically evaluate the economic evaluation research of ART, analyze the existing shortcomings, and provide a reference for the economic evaluation of ART. METHODS: PubMed, EMbase, Web of Science, Cochrane Library and ScienceDirect databases were searched for relevant articles on the economic evaluation of ART. These articles were screened, and their quality was evaluated based on the Comprehensive Health Economics Evaluation Report Standard (CHEERS 2022), and the data on the basic characteristics, model characteristics and other aspects of the included studies were summarized. RESULTS: One hundred and two related articles were obtained in the preliminary search, but based on the inclusion criteria, 12 studies were used for the analysis, of which nine used the decision tree model. The model parameters were mainly derived from published literature and included retrospective clinical data of patients. Only two studies included direct non-medical and indirect costs in the cost measurement. Live birth rate was used as an outcome indicator in half of the studies. CONCLUSION: Suggesting the setting of the threshold range in the field of fertility should be actively discussed, and the monetary value of each live birth is assumed to be in a certain range when the WTP threshold for fertility is uncertain. The range of the parameter sources should be expanded. Direct non-medical and indirect costs should be included in the calculation of costs, and the analysis should be carried out from the perspective of the whole society. In the evaluation of clinical effect, the effectiveness and safety indexes should be selected for a comprehensive evaluation, thereby making the evaluation more comprehensive and reliable. At least subgroup analysis based on age stratification should be considered in the relevant economic evaluation.

Effect of GnRH agonist trigger with or without low-dose hCG on reproductive outcomes for PCOS women with freeze-all strategy: a propensity score matching study.

PURPOSE: This study aimed to compare the effect of gonadotropin-releasing hormone agonist (GnRHa) trigger alone versus dual trigger comprising GnRHa and low-dose human chorionic gonadotropin (hCG) on reproductive outcomes in patients with polycystic ovary syndrome (PCOS) who received the freeze-all strategy. METHODS: A total of 615 cycles were included in this retrospective cohort study. Propensity score matching (PSM) was performed to control potential confounding factors between GnRHa-trigger group (0.2 mg GnRHa) and dual-trigger group (0.2 mg GnRHa plus 1000/2000 IU hCG) in a 1:1 ratio. Multivariate logistic regression was applied to estimate the association between trigger methods and reproductive outcomes. RESULTS: After PSM, patients with dual trigger (n = 176) had more oocytes retrieved, mature oocytes, and 2PN embryos compared to that with GnRHa trigger alone. However, the oocytes maturation rate, normal fertilization rate, and frozen embryos between the two groups were not statistically different. The incidence of ovarian hyperstimulation syndrome (OHSS) (14.8% vs. 2.8%, P < 0.001) and moderate/severe OHSS (11.4% vs. 1.7%, P < 0.001) were significantly higher in dual-trigger group than in GnRHa-alone group. Logistic regression analysis showed the adjusted odds ratio of dual trigger was 5.971 (95% confidence interval 2.201-16.198, P < 0.001) for OHSS. The pregnancy and single neonatal outcomes were comparable between the two groups (P > 0.05). CONCLUSION: For PCOS women with freeze-all strategy, GnRHa trigger alone decreased the risk of OHSS without damaging oocyte maturation and achieved satisfactory pregnancy outcomes.

The Association Between Air Pollutants and Daily Outpatient Visits for Allergic Rhinitis: A Time-Series Analysis Based on Distribution Lag Nonlinear Model in Chongqing, China.

Background: Allergic rhinitis (AR) is a severe and the most common chronic allergic disease, affecting 10-40% of the world population. The effect of air pollutants on AR has been confirmed in clinical experiments. Purpose: This study aimed to quantify the association between air pollutants and daily outpatient visits for AR in Chongqing, China. Methods: Based on the data of AR outpatients in the primary urban area of Chongqing from 2016 to 2017, along with the atmospheric pollutants and meteorological data in the same period, the distributed lag nonlinear model (DLNM) and generalized additive model (GAM) were used to analyze the time-series. We examined the effects of the single and double pollutant models with a maximum lag day of 30 days. Effect estimates were described as relative risk (RR) and 95% confidence intervals (CIs) in daily outpatient visits for AR per 10 µg/m3 increases in PM2.5, PM10, SO2, NO2, O3, and per 1 mg/m3 increase in CO. Results: A single pollutant's O3 level had an immediate positive effect on AR within two days, the relative risks (RR, 95% CI) were 1.066 (1.008-1.127), 1.057 (1.005-1.112) and 1.048 (1.002-1.097). PM2.5 had a lag effect within 11-18 days, the max relative risks (RR, 95% CI) were 1.083 (1.010-1.160). Moreover, O3, PM2.5, PM10, SO2 and NO2 had significant effects on AR in the two-pollutant model. The RR cumulative effect of PM2.5 became more pronounced as the concentration increased. The cumulative effect of NO2 was lesser than PM2.5. Conclusion: Air pollutants were associated with the daily outpatient visits for AR, which may have considerable implications for developing tailored health policies and services to prevent AR in Chongqing and even all over the world.

Diagnosis System of Microscopic Hyperspectral Image of Hepatobiliary Tumors Based on Convolutional Neural Network.

Hepatobiliary tumor is one of the common tumors and cancers in medicine, which seriously affects people's lives, so how to accurately diagnose it is a very serious problem. This article mainly studies a diagnostic method of microscopic images of liver and gallbladder tumors. Under this research direction, this article proposes to use convolutional neural network to learn and use hyperspectral images to diagnose it. It is found that the addition of the convolutional neural network can greatly improve the actual map classification and the accuracy of the map, and effectively improve the success rate of the treatment. At the same time, the article designs related experiments to compare its feature extraction performance and classification situation. The experimental results in this article show that the improved diagnostic method based on convolutional neural network has an accuracy rate of 85%-90%, which is as high as 6%-8% compared with the traditional accuracy rate, and thus it effectively improves the clinical problem of hepatobiliary tumor treatment.

Genetic polymorphisms of chemokine (C-X-C motif) ligand 10 gene associated with hepatitis B virus infection in a Chinese Han population.

BACKGROUND AND AIMS: Chemokine (C-X-C motif) ligand 10 (CXCL10) has been recently shown to be associated with inflammatory diseases. However, the association between the genetic variation of this gene and the susceptibility to hepatitis B virus (HBV) infection remains unclear, especially in children. This study aimed to investigate the relationship between CXCL10 polymorphisms and the risk of chronic HBV infection in a Chinese Han population. METHODS: A two-stage case-control study of 1048 adults and 627 children was performed. A total of 5 tagging SNPs in CXCL10 were genotyped. Dual-Luciferase Reporter Assay was used to assess the effect of the rs4508917 polymorphism on transcriptional activity of CXCL10. RESULTS: CXCL10 rs4508917 and rs4256246 polymorphisms were significantly associated with an increased risk of chronic HBV infection in Chinese Han adults (p = 0.036 and p = 0.033), of which rs4508917 AA genotype could increase the serum CXCL10 level (p = 0.014). In addition, the rs4508917 AA genotype was identified to facilitate HBV persistent infection (p = 0.017) and breakthrough infection (p = 0.013) in children. Subsequent functional analysis indicated that rs4508917 A allele could promote the transcriptional activity of CXCL10. Additionally, we observed that the rs4508917 A allele carriers (AA and AG genotypes) had a limited HBV viral load suppression in patients treated with nucleos(t)ide analogues (NAs). CONCLUSION: The A allele of the CXCL10 rs4508917 may be a risk factor of the persistent HBV infection both in adults and children, which may influence the response to NAs treatment.

Application of Machine Learning for the Prediction of Etiological Types of Classic Fever of Unknown Origin.

Background: The etiology of fever of unknown origin (FUO) is complex and remains a major challenge for clinicians. This study aims to investigate the distribution of the etiology of classic FUO and the differences in clinical indicators in patients with different etiologies of classic FUO and to establish a machine learning (ML) model based on clinical data. Methods: The clinical data and final diagnosis results of 527 patients with classic FUO admitted to 7 medical institutions in Chongqing from January 2012 to August 2021 and who met the classic FUO diagnostic criteria were collected. Three hundred seventy-three patients with final diagnosis were divided into 4 groups according to 4 different etiological types of classical FUO, and statistical analysis was carried out to screen out the indicators with statistical differences under different etiological types. On the basis of these indicators, five kinds of ML models, i.e., random forest (RF), support vector machine (SVM), Light Gradient Boosting Machine (LightGBM), artificial neural network (ANN), and naive Bayes (NB) models, were used to evaluate all datasets using 5-fold cross-validation, and the performance of the models were evaluated using micro-F1 scores. Results: The 373 patients were divided into the infectious disease group (n = 277), non-infectious inflammatory disease group (n = 51), neoplastic disease group (n = 31), and other diseases group (n = 14) according to 4 different etiological types. Another 154 patients were classified as undetermined group because the cause of fever was still unclear at discharge. There were significant differences in gender, age, and 18 other indicators among the four groups of patients with classic FUO with different etiological types (P < 0.05). The micro-F1 score for LightGBM was 75.8%, which was higher than that for the other four ML models, and the LightGBM prediction model had the best performance. Conclusions: Infectious diseases are still the main etiological type of classic FUO. Based on 18 statistically significant clinical indicators such as gender and age, we constructed and evaluated five ML models. LightGBM model has a good effect on predicting the etiological type of classic FUO, which will play a good auxiliary decision-making function.

Ambient Air Pollution and Hospitalizations for Ischemic Stroke: A Time Series Analysis Using a Distributed Lag Nonlinear Model in Chongqing, China.

Short-term exposure to air pollution has been associated with ischemic stroke (IS) hospitalizations, but the evidence of its effects on IS in low- and middle-income countries is limited and inconsistent. We aimed to quantitatively estimate the association between air pollution and hospitalizations for IS in Chongqing, China. This time series study included 2,299 inpatients with IS from three hospitals in Chongqing from January 2015 to December 2016. Generalized linear regression models combined with a distributed lag nonlinear model (DLNM) were used to investigate the impact of air pollution on IS hospitalizations. Stratification analysis was further implemented by sex, age, and season. The maximum lag-specific and cumulative percentage changes of IS were 1.2% (95% CI: 0.4-2.1%, lag 3 day) and 3.6% (95% CI: 0.5-6.7%, lag 05 day) for each 10 µg/m3 increase in PM2.5; 1.0% (95% CI: 0.3-1.7%, lag 3 day) and 2.9% (95% CI: 0.6-5.2%, lag 05 day) for each 10 µg/m3 increase in PM10; 4.8% (95% CI: 0.1-9.7%, lag 4 day) for each 10 µg/m3 increase in SO2; 2.5% (95% CI: 0.3-4.7%, lag 3 day) and 8.2% (95% CI: 0.9-16.0%, lag 05 day) for each 10 µg/m3 increase in NO2; 0.7% (95% CI: 0.0-1.5%, lag 6 day) for each 10 µg/m3 increase in O3. No effect modifications were detected for sex, age, and season. Our findings suggest that short-term exposure to PM2.5, PM10, SO2, NO2, and O3 contributes to more IS hospitalizations, which warrant the government to take effective actions in addressing air pollution issues.