The Influence of Cold Forming and Heat Treatment Processes on the Mechanical and Fracture Properties of AA6016 Aluminum Sheets.

In order to ascertain the mechanical properties and fracture performance of AA6016 aluminum sheets after cold forming and heat treatment processes, uniaxial tensile tests and fracture tests were conducted under various pre-strain conditions and heat treatment parameters. The experimental outcomes demonstrated that pre-strain and heat treatment had significant impacts on both stress-strain curves and fracture properties. Pre-strain plays a predominant role in influencing the mechanical and fracture properties. The behavior of precipitation hardening under different pre-strains was investigated using Differential Scanning Calorimetry (DSC). The results indicated that pre-strain accelerates the precipitation of the ß″ strengthening phase, but excessive pre-strain can inhibit the heat treatment strengthening effect. To consider the influences of pre-strain and heat treatment, a constitutive model, as well as a predictive model for load-displacement curves, was established using a backpropagation (BP) neural network. An analysis of the number of hidden layers and neuron nodes in the network revealed that the accuracy of the model does not necessarily improve with an increase in the number of hidden layers and neuron nodes, and an excessive number might actually decrease the efficiency of the machine learning process.

Optimization of Diagnosis-Related Groups for 14,246 Patients with Uterine Leiomyoma in a Single Center in Western China Using a Machine Learning Model.

Background: Uterine leiomyoma (UL) is one of the most common benign tumors in women, and its incidence is gradually increasing in China. The clinical complications of UL have a negative impact on women's health, and the cost of treatment poses a significant burden on patients. Diagnosis-related groups (DRG) are internationally recognized as advanced healthcare payment management methods that can effectively reduce costs. However, there are variations in the design and grouping rules of DRG policies across different regions. Therefore, this study aims to analyze the factors influencing the hospitalization costs of patients with UL and optimize the design of DRG grouping schemes to provide insights for the development of localized DRG grouping policies. Methods: The Mann-Whitney U-test or the Kruskal-Wallis H-test was employed for univariate analysis, and multiple stepwise linear regression analysis was utilized to identify the primary influencing factors of hospitalization costs for UL. Case combination classification was conducted using the exhaustive chi-square automatic interactive detection (E-CHAID) algorithm within a decision tree framework. Results: Age, occupation, number of hospitalizations, type of medical insurance, Transfer to other departments, length of stay (LOS), type of UL, admission condition, comorbidities and complications, type of primary procedure, other types of surgical procedures, and discharge method had a significant impact on hospitalization costs (P<0.05). Among them, the type of primary procedure, other types of surgical procedures, and LOS were the main factors influencing hospitalization costs. By incorporating the type of primary procedure, other types of surgical procedures, and LOS into the decision tree model, patients were divided into 11 DRG combinations. Conclusion: Hospitalization costs for UL are mainly related to the type of primary procedure, other types of surgical procedures, and LOS. The DRG case combinations of UL based on E-CHAID algorithm are scientific and reasonable.

Investigation of statistical methods used in prognostic prediction models for obstetric care: A 10 year-span cross-sectional study.

INTRODUCTION: Obstetric care is a highly active area in the development and application of prognostic prediction models. The development and validation of these models often require the utilization of advanced statistical techniques. However, failure to adhere to rigorous methodological standards could greatly undermine the reliability and trustworthiness of the resultant models. Consequently, the aim of our study was to examine the current statistical practices employed in obstetric care and offer recommendations to enhance the utilization of statistical methods in the development of prognostic prediction models. MATERIAL AND METHODS: We conducted a cross-sectional survey using a sample of studies developing or validating prognostic prediction models for obstetric care published in a 10-year span (2011-2020). A structured questionnaire was developed to investigate the statistical issues in five domains, including model derivation (predictor selection and algorithm development), model validation (internal and external), model performance, model presentation, and risk threshold setting. On the ground of survey results and existing guidelines, a list of recommendations for statistical methods in prognostic models was developed. RESULTS: A total of 112 eligible studies were included, with 107 reporting model development and five exclusively reporting external validation. During model development, 58.9% of the studies did not include any form of validation. Of these, 46.4% used stepwise regression in a crude manner for predictor selection, while two-thirds made decisions on retaining or dropping candidate predictors solely based on p-values. Additionally, 26.2% transformed continuous predictors into categorical variables, and 80.4% did not consider nonlinear relationships between predictors and outcomes. Surprisingly, 94.4% of the studies did not examine the correlation between predictors. Moreover, 47.1% of the studies did not compare population characteristics between the development and external validation datasets, and only one-fifth evaluated both discrimination and calibration. Furthermore, 53.6% of the studies did not clearly present the model, and less than half established a risk threshold to define risk categories. In light of these findings, 10 recommendations were formulated to promote the appropriate use of statistical methods. CONCLUSIONS: The use of statistical methods is not yet optimal. Ten recommendations were offered to assist the statistical methods of prognostic prediction models in obstetric care.

Dermal repeated dose toxicity study of the anti-breast cancer drug Formestane cream in Bama minipig.

Formestane (4-OHA) has been proven to be highly effective with high systemic tolerability in treating ER+ breast cancer. However, its intramuscular administration and associated side effects make it unsuitable for adjuvant treatment, leading to its withdrawal from the market. In contrast, Formestane cream may offer a solution by providing a more convenient route of administration and retaining its tumor-shrinking effects. This suggests that 4-OHA cream could have promising clinical applications. However, before clinical application, it is necessary to evaluate the potential toxicity of the cream in animals. This study evaluated the toxicity of 4-OHA cream on female Bama minipigs in vivo by analyzing hematology, biochemistry, and histopathology. The results showed that there was no significant difference between the cream-treated group and the control normal group for each parameter analyzed, indicating that 4-OHA cream was non-dermal toxic to minipigs. This finding provides a basis for the safe clinical use of the cream.

Effect of Strain Rate on Tensile Properties of Carbon Fiber-Reinforced Epoxy Laminates with Different Stacking Sequences and Ply Orientations.

In practical application situations, a carbon fiber-reinforced polymer (CFRP) is often subjected to complex dynamic loadings. The effect of the strain rate on mechanical properties is very important for the CFRP design and product development. In this work, static and dynamic tensile properties of CFRP with different stacking sequences and ply orientations were investigated. The results showed that the tensile strengths of CFRP laminates were sensitive to the strain rate, while Young's modulus was independent of the strain rate. Moreover, the strain rate effect was related to the stacking sequences and ply orientations. The experimental results showed that the strain rate effects of the cross-ply laminates and quasi-isotropic-ply laminates were lower than that of the unidirectional-ply laminates. Finally, the failure modes of CFRP laminates were investigated. Failure morphology demonstrated that the differences in strain rate effects among cross-ply laminates, quasi-isotropic-ply laminates, and unidirectional-ply laminates were caused by the mismatch between the fiber and the matrix when the strain rate increased.

Mechanical Properties of Weld Lines in Injection-Molded Carbon Fiber-Reinforced Nylon (PA-CF) Composites.

Weld lines are a common defect generated in injection molding, which apparently affects the performance of final products, but the available reports on carbon fiber-reinforced thermoplastics are still rather few. In this study, the effects of injection temperature, injection pressure, and fiber content on the mechanical properties of weld lines were studied for carbon fiber-reinforced nylon (PA-CF) composites. The weld line coefficient was also calculated by comparing specimens with and without weld lines. The tensile and flexural properties of PA-CF composites significantly increased with the rise of fiber content for specimens without weld lines, while injection temperature and pressure demonstrated slight influences on mechanical properties. However, the existence of weld lines had negative influences on the mechanical properties of PA-CF composites due to poor fiber orientation in weld line regions. The weld line coefficient of PA-CF composites decreased as fiber content increased, indicating that the damage of weld lines to mechanical properties increased. The microstructure analysis showed that there were a large number of fibers distributed vertically to flow direction in weld lines regions, which could not play a reinforcing role. In addition, increasing injection temperature and pressure facilitated fiber orientation, which improved the mechanical properties of composites with low fiber content, while weakening composites with high fiber content instead. This article provides practical information for product design containing weld lines, which helps to optimize the forming process and formula design of PA-CF composites with weld lines.

Impact of maternal hepatitis B carrier status on congenital abnormalities: a systematic review and meta-analysis.

OBJECTIVES: This study aims to explore whether maternal hepatitis B carrier status is associated with an increased risk of congenital abnormalities. DESIGN: A systematic review and meta-analysis of observational studies. DATA SOURCES: PubMed, Embase (Ovid), Scopus, the China National Knowledge Infrastructure (CNKI) and the Wanfang databases. STUDY SELECTION: Five databases were searched systematically from inception to 7 September 2021. Cohort and case-control studies that investigated the association between maternal hepatitis B virus (HBV) infection and congenital abnormalities were included. This study was conducted according to MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently collected data, as well as assessed risk of bias by using Newcastle-Ottawa Scale. We pooled crude relative risk (cRR) and adjusted OR (aOR) by DerSimonian-Laird random-effects model. Heterogeneity was explored by I 2 statistics, Cochran's Q test. Several subgroup analyses and sensitivity analyses were performed. RESULTS: In total, 14 studies involving 16 205 pregnant women exposed to HBV were included. The pooled cRR of 1.15 (95% CI: 0.92 to 1.45; 14 studies included) showed a marginal but not significant association between maternal HBV-carrier status and congenital abnormalities. However, the pooled aOR of 1.40 (95% CI: 1.01 to 1.93; 8 studies included) indicated that pregnant women with HBV infection might be associated with a higher risk of congenital abnormalities. Subgroup analyses of adjusted data showed a higher pooling cRR or aOR on high prevalence HBV infection populations, as well as studies from Asia and Oceania. CONCLUSIONS: Maternal hepatitis B carrier status might be at potential risk for congenital abnormalities. The existing evidence was not sufficient to draw a firm conclusion. Additional studies may be warranted to confirm the association. PROSPERO REGISTRATION NUMBER: CRD42020205459.

The allocation and fairness of health human resources in Chinese maternal and child health care institutions: a nationwide longitudinal study.

BACKGROUND: In response to an aging population, the Chinese government implemented the three-child policy in 2021 based on the comprehensive two-child policy. With the implementation of the new birth policy, people's maternal and child health (MCH) needs will also increase. The allocation and fairness of MCH human resources directly affect people's access to MCH services. The purpose of this study is to analyze the allocation of health human resources in Chinese maternal and child health care institutions, evaluate the fairness of the allocation, to provide a reference for the rational allocation of MCH human resources. METHODS: The data of health technicians, licensed (assistant) physicians, and registered nurses in maternal and child health care institutions nationwide from 2016 to 2020 were included. The health resource density index (HRDI) is used to evaluate the allocation level of MCH human resources. The Gini coefficient (G) and Theil index (T) are used to evaluate the fairness of the allocation of MCH human resources from the perspectives of population and geographic area. RESULTS: From 2016 to 2020, the average annual growth rate of the number of health technicians, licensed (assistant) physicians, and registered nurses in Chinese maternal and child health care institutions was 7.53, 6.88, and 9.12%, respectively. The Gini coefficient (G) of the three types of MCH human resources allocated by population were all below 0.23, and the Gini coefficient (G) allocated by geographical area were all above 0.65. The Theil index (T) of the three types of MCH human resources allocated by population was all lower than 0.06, and the Theil index (T) allocated by geographical area was all higher than 0.53. In addition, the three types of MCH human resources allocated by population and geographic area contributed more than 84% of the Theil index within the group (Tintra) to the Theil index (T). CONCLUSIONS: China's MCH human resources were fair in terms of population allocation, but unfair in terms of geographical area allocation. In the future, more attention should be paid to the geographical accessibility of MCH human resources, and the allocation of resources should comprehensively consider the two factors of serving the population and geographical area.

The reporting of prognostic prediction models for obstetric care was poor: a cross-sectional survey of 10-year publications.

BACKGROUND: To investigate the reporting of prognostic prediction model studies in obstetric care through a cross-sectional survey design. METHODS: PubMed was searched to identify prognostic prediction model studies in obstetric care published from January 2011 to December 2020. The quality of reporting was assessed by the TRIPOD checklist. The overall adherence by study and the adherence by item were calculated separately, and linear regression analysis was conducted to explore the association between overall adherence and prespecified study characteristics. RESULTS: A total of 121 studies were included, while no study completely adhered to the TRIPOD. The results showed that the overall adherence was poor (median 46.4%), and no significant improvement was observed after the release of the TRIPOD (43.9 to 46.7%). Studies including both model development and external validation had higher reporting quality versus those including model development only (68.1% vs. 44.8%). Among the 37 items required by the TRIPOD, 10 items were reported adequately with an adherence rate over of 80%, and the remaining 27 items had an adherence rate ranging from 2.5 to 79.3%. In addition, 11 items had a report rate lower than 25.0% and even covered key methodological aspects, including blinding assessment of predictors (2.5%), methods for model-building procedures (4.5%) and predictor handling (13.5%), how to use the model (13.5%), and presentation of model performance (14.4%). CONCLUSIONS: In a 10-year span, prognostic prediction studies in obstetric care continued to be poorly reported and did not improve even after the release of the TRIPOD checklist. Substantial efforts are warranted to improve the reporting of obstetric prognostic prediction models, particularly those that adhere to the TRIPOD checklist are highly desirable.

[Relevant thoughts on development of traditional Chinese medicine industry in new era].

Since the 18th National Congress of the Communist Party of China(CPC), the CPC and the government have highligh-ted the development of traditional Chinese Medicine(TCM) and issued a series of policies, such as the Plan for Protection and Deve-lopment of Chinese Medicinal Materials(2015-2020) forwarded by the General Office of the State Council in 2015, the Plan for Healthy Development of Traditional Chinese Medicine(2015-2020) released by the General Office of the State Council in the same year, the Healthy China 2030 Plan published by the CPC Central Committee and the State Council in 2016, the Law of the People's Republic of China on Traditional Chinese Medicine which took effect on July 2017, On the Preservation and Innovative Development of Traditional Chinese Medicine promulgated by CPC Central Committee and the State Council in 2019, and Plan for the Development of Traditional Chinese Medicine during the 14th Five-Year Plan Period of China released by the General Office of the State Council in March 2022, to promote the development of the TCM industry, which have brought historical opportunities to the TCM industry. However, TCM industry faces various challenges in the development. In terms of drug development in TCM, the current studies mainly focused on the chemical research and technical requests, which neglected TCM characteristics and cased in conformity between new drug transformation of TCM and clinical practice. Therefore, a more considerable and profound authoritative guideline is needed, and innovative thought and research are necessary for academics and the industry. Through the investigation of the development TCM industry in recent years, this study summarized the policies on and trends of Chinese medicinal materials, new drug development in TCM, catalogue of national basic drugs, and national basic health insurance, and proposed suggestions for further development of TCM industry.

The impact of biparental hepatitis B virus infection on pregnancy outcomes in patients undergoing assisted reproductive technology treatment: a systematic review and meta-analysis.

PURPOSE: To evaluate the association between biparental hepatitis B virus (HBV) infection (hepatitis B surface antigen [HBsAg] seropositivity) and pregnancy outcomes in patients undergoing assisted reproductive technology (ART) treatment, including clinical pregnancy rate (CPR) and live birth rate (LBR). METHODS: We searched various literature databases from the earliest date available until May 20, 2021, including PubMed, Embase, Medline, Web of Science, Scopus, CNKI, and Wangfang. Four patterns of biparental HBV infection for pregnancy outcomes following ART were synthesized separately by using random-effects model. We also performed subgroup analyses (matched or unmatched) and two forms of sensitivity analysis. RESULTS: A total of 25 retrospective cohort studies, involving more than 19,269 couples, were included. Maternal and paternal HBV co-infection (crude relative risk [cRR]: 0.58, 95% confidence interval: 0.28-1.23), either maternal or paternal infection (cRR: 1.05, 0.88-1.24), maternal HBV infection alone (cRR: 0.96, 0.79-1.16), or paternal HBV infection alone (cRR: 1.02, 0.91-1.13) were not associated with significant reductions in CPR at per woman level. These patterns of infection were also not significantly associated with decreased LBR at per woman level. However, paternal HBV infection alone reduced CPR (adjusted odds ratio: 0.54, 0.33-0.86) and LBR (cRR: 0.52, 0.28-0.99) at per cycle level. Subgroup analyses and sensitivity analyses were mostly consistent with the primary results. CONCLUSIONS: Paternal HBV infection alone probably decrease CPR after ART at per cycle level. However, maternal HBV infection was not associated with reductions in CPR and LBR in women undergoing ART at per woman level.

Effects of Motherwort Injection Versus Intramuscular Oxytocin for Preventing Postpartum Hemorrhage Among Women Who Underwent Cesarean Section.

Objectives: Subject to ethical constraints, real-world data are an important resource for evaluating treatment effects of medication use during pregnancy and the postpartum period. This study investigated whether motherwort injection, a traditional Chinese medicine preparation, was more effective than intramuscular (IM) oxytocin for preventing postpartum hemorrhage (PPH) in a real-world setting when intravenous (IV) oxytocin is administered. Methods: We conducted an active-controlled, propensity-score matched cohort study using an established pregnancy registry database. Women who underwent cesarean section and received IV oxytocin at the third stage of labor were included. We used an active-comparator design to minimize indication bias, in which we compared IM motherwort injection in the uterus versus IM oxytocin, both on top of IV oxytocin use. We applied 1:1 propensity-score matching (PSM) to balance patient baseline characteristics and used a logistic regression model to estimate treatment effect (i.e., risk difference (RD) and odds ratio (OR)) by using the counterfactual framework. The outcomes of interest were blood loss over 500 ml within 2 h after delivery (PPH, primary) and blood loss over 1,000 ml (severe PPH, secondary). We conducted four sensitivity analyses to examine the robustness of the results. Results: A total of 22,519 pregnant women underwent cesarean sections, among which 4,081 (18.12%) PPH and 480 (2.13%) severe PPH occurred. Among included women, 586 (2.60%) were administrated with IM motherwort injection, and 21,933 (97.40%) used IM oxytocin. After PSM, patient baseline characteristics were well balanced. Compared with IM oxytocin, the use of IM motherwort injection was associated with significantly lower risk of PPH (RD -25.26%, 95% CI -30.04% to -20.47%, p < 0.001; OR 0.25, 95% CI 0.18 to 0.32, p < 0.001) and severe PPH (RD -3.58%, 95% CI -5.87% to -1.30%, p < 0.001; OR 0.39, 95% CI 0.20 to 0.71, p < 0.002). Sensitivity analyses showed that the results were similar. Conclusion: With the use of data from a real-world setting, the findings consistently showed that among women undergoing cesarean section who had received IV oxytocin, the additional use of IM motherwort injection could achieve a lower risk of PPH as compared to the additional use of IM oxytocin. Our study suggested a paradigm for investigating the treatment effect of Chinese herbal medicine in the real-world practice setting.

[Thoughts on path of R&D and registration of innovative traditional Chinese medicine with synchronous transformation of "series prescriptions"].

Since the implementation of drug registration in China, the classification of Chinese medicine has greatly met the needs of public health and effectively guided the transformation, inheritance, and innovation of research achievements on traditional Chinese medicine(TCM). In the past 30 years, the development of new Chinese medicine has followed the registration transformation model of " one prescription for single drug". This model refers to the R&D and registration system of modern drugs, and approximates to the " law-abiding" medication method in TCM clinic, while it rarely reflects the sequential therapy of syndrome differentiation and comprehensive treatment with multiple measures. In 2017, Opinions on Deepening the Reform of Review and Approval System and Encouraging the Innovation of Drugs and Medical Devices released by the General Office of the CPC Central Committee and the General Office of the State Council pointed out that it is necessary to " establish and improve the registration and technical evaluation system in line with the characteristics of Chinese medicine, and handle the relationship between the traditional advantages of Chinese medicine and the requirements of modern drug research". Therefore, based on the development law and characteristics of TCM, clinical thinking should be highlighted in the current technical requirements and registration system of research and development of Chinese medicine. Based on the current situation of registration supervision of Chinese medicine and the modern drug research in China, the present study analyzed limitations and deficiency of " one prescription for single drug" in the research and development of Chinese medicine. Additionally, a new type of " series prescriptions" was proposed, which was consistent with clinical thinking and clinical reality. This study is expected to contribute to the independent innovation and high-quality development of the TCM industry.

A methodological framework for tackling confounding by indication when assessing the treatment effects of Chinese herbal injections in the real world.

AIM: In the context of integrative medicine, whether Chinese herbal injections are effective in routine practice has become a question of broad interest. However, confounding by indication (i.e., indication bias) is a prevalent and highly challenging methodological issue when using routinely collected health care data to assess the real-world effectiveness of Chinese herbal injections. METHODS AND RESULTS: We proposed a methodological approach to tackling confounding by indication in assessing the real-world effectiveness of Chinese herbal injections, incorporating empirical experiences, a literature review and interactive discussions, and a panel of external experts to finally achieve a consensus. This approach consisted of three cohesive steps, including a full understanding of treatment patterns, construction of fair comparisons by identifying appropriate combination treatments and comparators, and using statistical methods to further control for confounding. In the investigation of treatment patterns, we proposed five domains to identify treatment patterns with Chinese herbal injections, and we offered five patterns of combination treatments to characterize how Chinese herbal injections are used in conjunction with other treatments. In constructing fair comparisons, we suggested the use of both nonuse and active comparators; given the diverse combination treatments, we developed six scenarios that may form fair comparisons. In the statistical analysis, we discussed five statistical models for controlling confounding by indication, including their pros and cons. We also included a practical example to illustrate the usefulness of the methodological approach. CONCLUSION: The proposed approach may serve as an effective tool to guide researchers to reliably assess the effectiveness of Chinese herbal injections in the context of integrative medicine.

Quantifying the impacts of human mobility restriction on the spread of coronavirus disease 2019: an empirical analysis from 344 cities of China.

BACKGROUND: Since the outbreak of coronavirus disease 2019 (COVID-19), human mobility restriction measures have raised controversies, partly because of the inconsistent findings. An empirical study is promptly needed to reliably assess the causal effects of the mobility restriction. The purpose of this study was to quantify the causal effects of human mobility restriction on the spread of COVID-19. METHODS: Our study applied the difference-in-difference (DID) model to assess the declines of population mobility at the city level, and used the log-log regression model to examine the effects of population mobility declines on the disease spread measured by cumulative or new cases of COVID-19 over time after adjusting for confounders. RESULTS: The DID model showed that a continual expansion of the relative declines over time in 2020. After 4 weeks, population mobility declined by -54.81% (interquartile range, -65.50% to -43.56%). The accrued population mobility declines were associated with the significant reduction of cumulative COVID-19 cases throughout 6 weeks (ie, 1% decline of population mobility was associated with 0.72% [95% CI: 0.50%-0.93%] reduction of cumulative cases for 1 week, 1.42% 2 weeks, 1.69% 3 weeks, 1.72% 4 weeks, 1.64% 5 weeks, and 1.52% 6 weeks). The impact on the weekly new cases seemed greater in the first 4 weeks but faded thereafter. The effects on cumulative cases differed by cities of different population sizes, with greater effects seen in larger cities. CONCLUSIONS: Persistent population mobility restrictions are well deserved. Implementation of mobility restrictions in major cities with large population sizes may be even more important.

Texture Recognition Based on Perception Data from a Bionic Tactile Sensor.

Texture recognition is important for robots to discern the characteristics of the object surface and adjust grasping and manipulation strategies accordingly. It is still challenging to develop texture classification approaches that are accurate and do not require high computational costs. In this work, we adopt a bionic tactile sensor to collect vibration data while sliding against materials of interest. Under a fixed contact pressure and speed, a total of 1000 sets of vibration data from ten different materials were collected. With the tactile perception data, four types of texture recognition algorithms are proposed. Three machine learning algorithms, including support vector machine, random forest, and K-nearest neighbor, are established for texture recognition. The test accuracy of those three methods are 95%, 94%, 94%, respectively. In the detection process of machine learning algorithms, the asamoto and polyester are easy to be confused with each other. A convolutional neural network is established to further increase the test accuracy to 98.5%. The three machine learning models and convolutional neural network demonstrate high accuracy and excellent robustness.

Prognostic factors and prediction models for acute aortic dissection: a systematic review.

OBJECTIVE: Our study aimed to systematically review the methodological characteristics of studies that identified prognostic factors or developed or validated models for predicting mortalities among patients with acute aortic dissection (AAD), which would inform future work. DESIGN/SETTING: A methodological review of published studies. METHODS: We searched PubMed and EMBASE from inception to June 2020 for studies about prognostic factors or prediction models on mortality among patients with AAD. Two reviewers independently collected the information about methodological characteristics. We also documented the information about the performance of the prognostic factors or prediction models. RESULTS: Thirty-two studies were included, of which 18 evaluated the performance of prognostic factors, and 14 developed or validated prediction models. Of the 32 studies, 23 (72%) were single-centre studies, 22 (69%) used data from electronic medical records, 19 (59%) chose retrospective cohort study design, 26 (81%) did not report missing predictor data and 5 (16%) that reported missing predictor data used complete-case analysis. Among the 14 prediction model studies, only 3 (21%) had the event per variable over 20, and only 5 (36%) reported both discrimination and calibration statistics. Among model development studies, 3 (27%) did not report statistical methods, 3 (27%) exclusively used statistical significance threshold for selecting predictors and 7 (64%) did not report the methods for handling continuous predictors. Most prediction models were considered at high risk of bias. The performance of prognostic factors showed varying discrimination (AUC 0.58 to 0.95), and the performance of prediction models also varied substantially (AUC 0.49 to 0.91). Only six studies reported calibration statistic. CONCLUSIONS: The methods used for prognostic studies on mortality among patients with AAD-including prediction models or prognostic factor studies-were suboptimal, and the model performance highly varied. Substantial efforts are warranted to improve the use of the methods in this population.

Association between maternal prepregnancy body mass index and pregnancy outcomes following assisted reproductive technology: A systematic review and dose-response meta-analysis.

This systematic review investigated dose-response relationship between maternal prepregnancy body mass index (BMI) and pregnancy outcomes following assisted reproductive technology, including clinical pregnancy rate (CPR), miscarriage rate (MR), and live birth rate (LBR). We searched four major databases and finally included 105 studies involving more than 271,632 pregnant women. We performed linear or nonlinear dose-response meta-analyses using random effects models. At per-woman level, pooling of unadjusted estimates shown an inverted J-shaped relationship between maternal BMI and CPR; pooling of adjusted estimates showed a linear association, suggesting statistical association between higher maternal BMI and lower CPR (adjusted OR [aOR] for 5-unit increase in BMI: 0.96, 95%CI: 0.94-0.98). At per-cycle level, linear dose-response relationship was found between maternal BMI and CPR (crude relative risk, RR, [cRR] for 5-unit increase in BMI 0.97, 0.96-0.98; aOR 0.96, 0.94-0.99). Linear dose-response relationship was established between maternal BMI and the outcomes of MR or LBR (higher BMI associated with higher MR [cRR 1.15, 1.08-1.22] and lower LBR [cRR 0.91, 0.88-0.94] at per-woman level). Sensitivity analyses showed no significant changes. In conclusion, there is dose-response relationship between maternal BMI and pregnancy outcomes following assisted reproductive technology. Higher BMI values may suggest suboptimal pregnancy outcomes.

The impact of smoking on annual healthcare cost: an econometric model analysis in China, 2015.

BACKGROUND: Smoking exerts substantial medical burdens on society. Precise estimation of the smoking-attributable medical expenditures (SAME) helps to inform tobacco control policy makers. Based on the epidemiological approach, prior studies in China only focused on a few smoking-related diseases to estimate SAME. In contrast, this study used the econometric approach, which is capable of capturing all of the potential costs. METHODS: Three waves of panel data from the 2011-2015 national China Health and Retirement Longitudinal Study (CHARLS) were used. A total of 34,503 observations aged 45 and above were identified. Estimates from econometric models were combined to predict the smoking-attributable fraction (SAF) and medical expenditures attributable to smoking by sex, registered residency and healthcare service categories. All monetary amounts were adjusted to 2015 dollars. RESULTS: In 2015, the overall smoking-attributable fraction (SAF) of China was 10.97%, ranging from 5.77% for self-medication to 16.87% for inpatient visits. The smoking-attributable medical expenditure (SAME) was about $45.28 billion, accounting for 7.24% of the total health expenditure. The SAME was $226.77 per smoker aged 45 and above. The regression results suggest that being a former smoker has the greatest impact, which decreases over time after quitting however, on the value of medical expenditures. CONCLUSIONS: Smoking-attributable medical expenditures was substantial and placed a heavy burden on Chinese society. Comprehensive tobacco control policies and regulations are still needed to promote progress toward curbing the tobacco related losses.