PA-MSHA improves prognosis of patients undergoing radical cystectomy: a retrospective cohort study using inverse probability of treatment weighting.

Objective: To observe the effect of Pseudomonas aeruginosa mannose-sensitive hemagglutinin (PA-MSHA) on the prognosis and the incidence of lymphatic leakage in patients undergoing radical cystectomy (RC). Method: A total of 129 patients who underwent RC in Lanzhou University Second Hospital from 2013 to 2022 were enrolled in this study. They were divided into 43 patients treated with PA-MSHA and 86 patients in the control group. Inverse probability of treatment weighting (IPTW) was applied to reduce potential selection bias. Kaplan-Meier method and Cox regression analysis were used to analyze the effect of PA-MSHA on the survival of patients and the incidence of postoperative lymphatic leakage. Results: The PA-MSHA group exhibited improved overall survival (OS) and cancer-specific survival (CSS) rates compared to the control group. The 3-year and 5-year overall survival (OS) rates for the PA-MSHA group were 69.1% and 53.2%, respectively, compared to 55.6% and 45.3% for the control group (Log-rank=3.218, P=0.072). The 3-year and 5-year cancer-specific survival (CSS) rates for the PA-MSHA group were 73.3% and 56.5%, respectively, compared to 58.0% and 47.3% for the control group (Log-rank=3.218, P=0.072). Additionally, the 3-year and 5-year progression-free survival (PFS) rates for the PA-MSHA group were 74.4% and 56.8%, respectively, compared to 57.1% and 52.2% for the control group (Log-rank=2.016, P=0.156). Multivariate Cox regression analysis indicates that lymph node metastasis and distant metastasis are poor prognostic factors for patients, while the use of PA-MSHA can improve patients' OS (HR: 0.547, 95%CI: 0.304-0.983, P=0.044), PFS (HR: 0.469, 95%CI: 0.229-0.959, P=0.038) and CSS (HR: 0.484, 95%CI: 0.257-0.908, P=0.024). The same trend was observed in the cohort After IPTW adjustment. Although there was no significant difference in the incidence of postoperative lymphatic leakage [18.6% (8/35) vs. 15.1% (84.9%), P=0.613] and pelvic drainage volume [470 (440) ml vs. 462.5 (430) ml, P=0.814] between PA-MSHA group and control group, PA-MSHA could shorten the median retention time of drainage tube (7.0 d vs 9.0 d) (P=0.021). Conclusion: PA-MSHA may improve radical cystectomy in patients with OS, PFS, and CSS, shorten the pelvic drainage tube retention time.

Reduction in the need for surgery and mortality after early administration of fibrinolytics following empyema drainage.

OBJECTIVES: Although intrapleural administration of fibrinolytics is an important treatment option for the management of empyema, the addition of fibrinolytics failed to reduce the need for surgery and mortality in previous randomized controlled trials. This study aimed to investigate the effect of administrating fibrinolytics in the early phase (within 3 days of chest tube insertion) of empyema compared with late administration or no administration. METHODS: We used the Japanese Diagnosis Procedure Combination inpatient database to identify patients aged ≥ 16 years who were hospitalized and underwent chest tube drainage for empyema. A 1:2 propensity score matching and stabilized inverse probability of treatment weighting were conducted. RESULTS: Among the 16,265 eligible patients, 3,082 and 13,183 patients were categorized into the early and control group, respectively. The proportion of patients who underwent surgery was significantly lower in the early fibrinolytics group than in the control group; the odds ratio (95% confidence interval) was 0.69 (0.54-0.88) in the propensity score matching (P = 0.003) and 0.64 (0.50-0.80) in the stabilized inverse probability of treatment weighting analysis (P < 0.001). All-cause 30-day in-hospital mortality, length of hospital stay, duration of chest tube drainage, and total hospitalization costs were also more favorable in the early fibrinolytic group. CONCLUSIONS: The early administration of fibrinolytics may reduce the need for surgery and death in adult patients with empyema.

Trajectory of medical expenditure and regional disparities in hypertensive patients in South Korea.

The aim of this study is to understand how different regions influence the management and financial burden of hypertension, and to identify regional disparities in hypertension management and medical expenditure. The study utilized data from the Korean Health Panel Survey conducted between 2014 and 2018, focusing on individuals with hypertension. Medical expenditures were classified into three trajectory groups: "Persistent Low," "Expenditure Increasing," and "Persistent High" over a five-year period using trajectory analysis. Inverse Probability Weighting (IPW) analysis was then employed to identify the association between regions and medical expenditure trajectories. The results indicate that individuals residing in metropolitan cities (Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan) and rural areas were more likely to belong to the "Expenditure Increasing" group compared to the "Persistent Low Expenditure" group (OR = 1.07; 95% CI; p < 0.001), as opposed to those in the capital city (Seoul) (OR = 1.07; 95% CI; p < 0.001). Additionally, residents of rural areas were more likely to be in the "High Expenditure" group compared to the "Persistent Low Expenditure" group than those residing in the capital city (OR = 1.05; 95% CI; p = 0.001). These findings suggest that individuals in rural areas may be receiving relatively inadequate management for hypertension, leading to higher medical expenditures compared to those in the capital region. These disparities signify health inequality and highlight the need for policy efforts to address regional imbalances in social structures and healthcare resource distribution to ensure equitable chronic disease management across different regions.

Absolute risk from double nested case-control designs: cause-specific proportional hazards models with and without augmented estimating equations.

We estimate relative hazards and absolute risks (or cumulative incidence or crude risk) under cause-specific proportional hazards models for competing risks from double nested case-control (DNCC) data. In the DNCC design, controls are time-matched not only to cases from the cause of primary interest, but also to cases from competing risks (the phase-two sample). Complete covariate data are available in the phase-two sample, but other cohort members only have information on survival outcomes and some covariates. Design-weighted estimators use inverse sampling probabilities computed from Samuelsen-type calculations for DNCC. To take advantage of additional information available on all cohort members, we augment the estimating equations with a term that is unbiased for zero but improves the efficiency of estimates from the cause-specific proportional hazards model. We establish the asymptotic properties of the proposed estimators, including the estimator of absolute risk, and derive consistent variance estimators. We show that augmented design-weighted estimators are more efficient than design-weighted estimators. Through simulations, we show that the proposed asymptotic methods yield nominal operating characteristics in practical sample sizes. We illustrate the methods using prostate cancer mortality data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Study of the National Cancer Institute.

Making Sense of Censored Covariates: Statistical Methods for Studies of Huntington's Disease.

The landscape of survival analysis is constantly being revolutionized to answer biomedical challenges, most recently the statistical challenge of censored covariates rather than outcomes. There are many promising strategies to tackle censored covariates, including weighting, imputation, maximum likelihood, and Bayesian methods. Still, this is a relatively fresh area of research, different from the areas of censored outcomes (i.e., survival analysis) or missing covariates. In this review, we discuss the unique statistical challenges encountered when handling censored covariates and provide an in-depth review of existing methods designed to address those challenges. We emphasize each method's relative strengths and weaknesses, providing recommendations to help investigators pinpoint the best approach to handling censored covariates in their data.

Comparative effectiveness of antihypertensive monotherapies in primary prevention of cardiovascular events-a real-world longitudinal inception cohort study.

Introduction: Antihypertensive drugs are used preventatively to lower the risk of cardiovascular disease events. Comparative effectiveness studies on angiotensin-converting enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs), beta-blockers (BBs), calcium channel blockers (CCBs), and thiazides have yielded inconsistent results and given little consideration to patient adherence. Using a longitudinal cohort and considering time-varying adherence and confounding factors, we aimed to estimate the real-world effectiveness of five major antihypertensive drug monotherapies in the primary prevention of cardiovascular events. Methods: Eligible patients for a retrospective inception cohort study were selected using information obtained from the University of Groningen IADB.nl pharmacy prescription database. Cohort 1 comprised adherent patients with a follow-up time exceeding 1 year, and cohort 2 comprised all patients independent of adherence. The exposures were ACEIs, ARBs, BBs, CCBs, and thiazides. The primary outcome was the time to the first prescription for an acute cardiac drug therapy (CDT) measured using valid drug proxies to identify the first major cardiovascular event. A per-protocol analytical approach was adopted with inverse probability of treatment weighted (IPTW), time-varying Cox regression analysis to obtain the hazard ratios (HRs) and 95% confidence intervals (CIs). Results: In cohort 1 (n = 22,441), 1,294 patients (5.8%) were prescribed an acute CDT with an average follow-up time of 4.2 ± 2.8 years. Following IPTW, the hazard measures of ARBs and thiazides were lower than those of BBs (HRs: 0.79 and 0.80, respectively; 95% CIs: 0.64-0.97 and 0.69-0.94, respectively). Among drug-treated diabetic patients, the hazard measures were even lower, with HR point estimates of 0.43 (CI: 0.19-0.98) for ARBs and 0.32 (CI: 0.13-0.82) for thiazides. In cohort 2 (n = 33,427) and sensitivity analysis, the comparative effectiveness results for thiazides and BBs were similar to those for cohort 1. Conclusion: The findings of this real-world analysis suggest that the incidence of CDT associated with long-term thiazide or ARB monotherapy is lower than the incidence of CDT with BBs, notably among high-risk patients. Incidences of CDT associated with ACEIs and CCBs were comparable relative to those associated with BBs.

[Estimation of soil moisture and organic matter content in saline alkali farmland by using CARS algorithm combined with covariates]. / 利用CARS算法联合协变量估算盐碱农田土壤水分和有机质含量.

Rapid acquisition of the data of soil moisture content (SMC) and soil organic matter (SOM) content is crucial for the improvement and utilization of saline alkali farmland soil. Based on field measurements of hyperspectral reflectance and soil properties of farmland soil in the Hetao Plain, we used a competitive adaptive reweighted sampling algorithm (CARS) to screen sensitive bands after transforming the original spectral reflectance (Ref) into a standard normal variable (SNV). Strategies Ⅰ, Ⅱ, and Ⅲ were used to model the input variables of Ref, Ref SNV, Ref-SNV+ soil covariate (SC), and digital elevation model (DEM). We constructed SMC and SOM estimation models based on random forest (RF) and light gradient boosting machine (LightGBM), and then verified and compared the accuracy of the models. The results showed that after CARS screening, the sensitive bands of SMC and SOM were compressed to below 3.3% of the entire band, which effectively optimized band selection and reduced redundant spectral information. Compared with the LightGBM model, the RF model had higher accuracy in SMC and SOM estimation, and the input variable strategy Ⅲ was better than Ⅱ and Ⅰ. The introduction of auxiliary variables effectively improved the estimation ability of the model. Based on comprehensive analysis, the coefficient of determination (Rp2), root mean square error (RMSE), and relative analysis error (RPD) of the SMC estimation model validation based on strategy Ⅲ-RF were 0.63, 3.16, and 2.01, respectively. The SOM estimation models based on strategy Ⅲ-RF had Rp2, RMSE, and RPD of 0.93, 1.15, and 3.52, respectively. The strategy Ⅲ-RF model was an effective method for estimating SMC and SOM. Our results could provide a new method for the rapid estimation of soil moisture and organic matter content in saline alkali farmland.

Child meal support program, food and nutrition insecurity, and health among Korean children.

BACKGROUND: Korea's child meal support program (CMSP) aims to reduce food and nutrition insecurity (FNI) and improve health among children from low-income households. AIM: We examined the impact of different types of CMSP on children's FNI and health in Korea, analyzing meal frequency and healthful food consumption (FNI), and general health and depression (health) among child meal card (CMC) and facility meal service (FMS) participants compared with nonparticipants. METHODS: The 2018 Comprehensive Survey on Korean Children data were analyzed. Precisely, 847 children from low-income households aged 9-17 were categorized into CMC (n = 331), FMS (n = 209), and income-eligible nonparticipants (n = 307). Propensity score-weighted generalized linear models assessed CMSP's impact on FNI and health. Stratified generalized linear models examined heterogeneity in FNI-health associations by CMSP status. RESULTS: CMC participants reported more frequent breakfast consumption (odds ratio [OR] = 0.662, p < 0.05) but poorer self-rated general health (OR = 1.890, p < 0.05); FMS participants were less likely to have three meals (OR = 1.814, p < 0.05), fruits and vegetables (OR = 2.194, p < 0.001), and protein-rich foods daily (OR = 1.695, p < 0.05) than nonparticipants. Health risks associated with healthful food consumption and meal frequency were more pronounced among CMC and FMS/nonparticipants, respectively. CONCLUSION: CMSP had a limited impact on reducing FNI and improving health among children from low-income households. CMC appeared more effective than FMS in alleviating FNI, notwithstanding potential health concerns. Food assistance programs should seek comprehensive enhancements in children's food and nutrition security and health.

Causal inference in the absence of positivity: The role of overlap weights.

How to analyze data when there is violation of the positivity assumption? Several possible solutions exist in the literature. In this paper, we consider propensity score (PS) methods that are commonly used in observational studies to assess causal treatment effects in the context where the positivity assumption is violated. We focus on and examine four specific alternative solutions to the inverse probability weighting (IPW) trimming and truncation: matching weight (MW), Shannon's entropy weight (EW), overlap weight (OW), and beta weight (BW) estimators. We first specify their target population, the population of patients for whom clinical equipoise, that is, where we have sufficient PS overlap. Then, we establish the nexus among the different corresponding weights (and estimators); this allows us to highlight the shared properties and theoretical implications of these estimators. Finally, we introduce their augmented estimators that take advantage of estimating both the propensity score and outcome regression models to enhance the treatment effect estimators in terms of bias and efficiency. We also elucidate the role of the OW estimator as the flagship of all these methods that target the overlap population. Our analytic results demonstrate that OW, MW, and EW are preferable to IPW and some cases of BW when there is a moderate or extreme (stochastic or structural) violation of the positivity assumption. We then evaluate, compare, and confirm the finite-sample performance of the aforementioned estimators via Monte Carlo simulations. Finally, we illustrate these methods using two real-world data examples marked by violations of the positivity assumption.

High-dimensional mediation analysis for continuous outcome with confounders using overlap weighting method in observational epigenetic study.

BACKGROUND: Mediation analysis is a powerful tool to identify factors mediating the causal pathway of exposure to health outcomes. Mediation analysis has been extended to study a large number of potential mediators in high-dimensional data settings. The presence of confounding in observational studies is inevitable. Hence, it's an essential part of high-dimensional mediation analysis (HDMA) to adjust for the potential confounders. Although the propensity score (PS) related method such as propensity score regression adjustment (PSR) and inverse probability weighting (IPW) has been proposed to tackle this problem, the characteristics with extreme propensity score distribution of the PS-based method would result in the biased estimation. METHODS: In this article, we integrated the overlapping weighting (OW) technique into HDMA workflow and proposed a concise and powerful high-dimensional mediation analysis procedure consisting of OW confounding adjustment, sure independence screening (SIS), de-biased Lasso penalization, and joint-significance testing underlying the mixture null distribution. We compared the proposed method with the existing method consisting of PS-based confounding adjustment, SIS, minimax concave penalty (MCP) variable selection, and classical joint-significance testing. RESULTS: Simulation studies demonstrate the proposed procedure has the best performance in mediator selection and estimation. The proposed procedure yielded the highest true positive rate, acceptable false discovery proportion level, and lower mean square error. In the empirical study based on the GSE117859 dataset in the Gene Expression Omnibus database using the proposed method, we found that smoking history may lead to the estimated natural killer (NK) cell level reduction through the mediation effect of some methylation markers, mainly including methylation sites cg13917614 in CNP gene and cg16893868 in LILRA2 gene. CONCLUSIONS: The proposed method has higher power, sufficient false discovery rate control, and precise mediation effect estimation. Meanwhile, it is feasible to be implemented with the presence of confounders. Hence, our method is worth considering in HDMA studies.

Comparison of two propensity score-based methods for balancing covariates: the overlap weighting and fine stratification methods in real-world claims data.

BACKGROUND: Two propensity score (PS) based balancing covariate methods, the overlap weighting method (OW) and the fine stratification method (FS), produce superb covariate balance. OW has been compared with various weighting methods while FS has been compared with the traditional stratification method and various matching methods. However, no study has yet compared OW and FS. In addition, OW has not yet been evaluated in large claims data with low prevalence exposure and with low frequency outcomes, a context in which optimal use of balancing methods is critical. In the study, we aimed to compare OW and FS using real-world data and simulations with low prevalence exposure and with low frequency outcomes. METHODS: We used the Texas State Medicaid claims data on adult beneficiaries with diabetes in 2012 as an empirical example (N = 42,628). Based on its real-world research question, we estimated an average treatment effect of health center vs. non-health center attendance in the total population. We also performed simulations to evaluate their relative performance. To preserve associations between covariates, we used the plasmode approach to simulate outcomes and/or exposures with N = 4,000. We simulated both homogeneous and heterogeneous treatment effects with various outcome risks (1-30% or observed: 27.75%) and/or exposure prevalence (2.5-30% or observed:10.55%). We used a weighted generalized linear model to estimate the exposure effect and the cluster-robust standard error (SE) method to estimate its SE. RESULTS: In the empirical example, we found that OW had smaller standardized mean differences in all covariates (range: OW: 0.0-0.02 vs. FS: 0.22-3.26) and Mahalanobis balance distance (MB) (< 0.001 vs. > 0.049) than FS. In simulations, OW also achieved smaller MB (homogeneity: <0.04 vs. > 0.04; heterogeneity: 0.0-0.11 vs. 0.07-0.29), relative bias (homogeneity: 4.04-56.20 vs. 20-61.63; heterogeneity: 7.85-57.6 vs. 15.0-60.4), square root of mean squared error (homogeneity: 0.332-1.308 vs. 0.385-1.365; heterogeneity: 0.263-0.526 vs 0.313-0.620), and coverage probability (homogeneity: 0.0-80.4% vs. 0.0-69.8%; heterogeneity: 0.0-97.6% vs. 0.0-92.8%), than FS, in most cases. CONCLUSIONS: These findings suggest that OW can yield nearly perfect covariate balance and therefore enhance the accuracy of average treatment effect estimation in the total population.

Optimal weighting factor design based on entropy technique in finite control set model predictive torque control for electric drive applications.

In the conventional finite control set model predictive torque control, the cost function consists of different control objectives with varying units of measurements. Due to presence of diverse variables in cost function, weighting factors are used to set the relative importance of these objectives. However, selection of these weighting factors in predictive control of electric drives and power converters still remains an open research challenge. Improper selection of weighting factors can lead to deterioration of the controller performance. This work proposes a novel weighting factor tuning method based on the Multi-Criteria-Decision-Making (MCDM) technique called the Entropy method. This technique has several advantages for multi-objective problem optimization. It provides a quantitive approach and incorporates uncertainties and adaptability to assess the relative importance of different criteria or objectives. This technique performs the online tuning of the weighting factor by forming a data set of the control objectives, i.e., electromagnetic torque and stator flux magnitude. After obtaining the error set of control variables, the objective matrix is normalized, and the entropy technique is applied to design the corresponding weights. An experimental setup based on the dSpace dS1104 controller is used to validate the effectiveness of the proposed method for a two-level, three-phase voltage source inverter (2L-3P) fed induction motor drive. The dynamic response of the proposed technique is compared with the previously proposed MCDM-based weighting factor tuning technique and conventional MPTC. The results reveal that the proposed method provides an improved dynamic response of the drive under changing operating conditions with a reduction of 28% in computational burden and 38% in total harmonic distortion, respectively.

Association of waist circumference and BMI with premature death in young and middle-aged population.

Introduction: Premature death is a global health indicator, significantly impacted by obesity, especially in young and middle-aged population. Both body mass index (BMI) and waist circumference (WC) assess obesity, with WC specifically indicating central obesity and showing a stronger relationship with mortality. However, despite known associations between BMI and premature death, as well as the well-recognized correlation between WC and adverse health outcomes, the specific relationship between WC and premature death remains unclear. Therefore, focusing on young and middle-aged individuals, this study aimed to reliably estimate independent and combined associations between WC, BMI and premature death, thereby providing causal evidence to support strategies for obesity management. Methods: This study involved 49,217 subjects aged 18-50 years in the United States from 1999 to 2018 National Health and Nutrition Examination Survey (NHANES). Independent and combined associations between WC and BMI with premature death across sex and age stratum were examined by Cox regression. Survey weighting and inverse probability weighting (IPW) were further considered to control selection and confounding bias. Robustness assessment has been conducted on both NHANES and China Health and Retirement Longitudinal Study (CHARLS) data. Results: A linear and positive relationship between WC and all-cause premature death was found in both males and females, with adjusted HRs of 1.019 (95%CI = 1.004-1.034) and 1.065 (95%CI = 1.039-1.091), respectively. Nonlinear relationships were found with respect to BMI and all-cause premature death. For females aged 36-50 with a BMI below 28.6 kg/m2, the risk of premature death decreased as BMI increased, indicated by adjusted HRs of 0.856 (95%CI = 0.790-0.927). Joint analysis showed among people living with obesity, a larger WC increased premature death risk (HR = 1.924, 95%CI = 1.444-2.564). Discussion: WC and BMI exhibited prominent associations with premature death in young and middle-aged population. Maintaining an appropriate WC and BMI bears significant implications for preventing premature death.

Effects of non-specific low back pain on static balance in emerging adults.

BACKGROUND: Postural control impairments in middle-aged or older people with chronic low back pain (CLBP) have been extensively documented. However, little is known about changes in postural control early in the disease process which may underlie compensatory movement strategies. OBJECTIVE: Our purpose was to quantify postural sway and sensory weighting in emerging adults with and without CLBP. METHODS: Nineteen emerging adults with CLBP (age = 18-26 years (21.11 ± 1.73)) and 19 matched peers without CLBP (18-27 years (22.20 ± 1.97)) participated in a cross-sectional study. Displacement of the center of mass during Quiet stance (QS), Tandem stance (TS), and Unilateral stance (US) on 2 surfaces (stable, unstable) were used to assess postural sway. Sensory Organization Test (SOT) was used to assess sensory weighting. RESULTS: Emerging adults with CLBP showed large, significant increases in postural sway during unstable TS (p ≤ .020). Participants with CLBP relied more on somatosensory input, as evidenced by lower equilibrium scores during conditions favoring visual (p = .020) or vestibular (p < .001) input during the SOT. CONCLUSION: Emerging adults with CLBP showed postural control impairments related to altered sensory weighting. These findings provide insights into the development of CLBP and its effects on postural control. This information may aid early identification, monitoring, and treatment of individuals in the initial stages of disease development who may have unrecognized postural impairments.

Limited Memory-Based Random-Weighted Kalman Filter.

The Kalman filter is an important technique for system state estimation. It requires the exact knowledge of system noise statistics to achieve optimal state estimation. However, in practice, this knowledge is often unknown or inaccurate due to uncertainties and disturbances involved in the dynamic environment, leading to degraded or even divergent filtering solutions. To address this issue, this paper presents a new method by combining the random weighting concept with the limited memory technique to accurately estimate system noise statistics. To avoid the influence of excessive historical information on state estimation, random weighting theories are established based on the limited memory technique to estimate both process noise and measurement noise statistics within a limited memory. Subsequently, the estimated system noise statistics are fed back into the Kalman filtering process for system state estimation. The proposed method improves the Kalman filtering accuracy by adaptively adjusting the weights of system noise statistics within a limited memory to suppress the interference of system noise on system state estimation. Simulations and experiments as well as comparison analysis were conducted, demonstrating that the proposed method can overcome the disadvantage of the traditional limited memory filter, leading to im-proved accuracy for system state estimation.

Incorporating Adaptive Survey Design in a Two-Stage National Web or Mail Mixed-Mode Survey: An Experiment in the American Family Health Study.

This article presents the results of an adaptive design experiment in the recruitment of households and individuals for a two-stage national probability web or mail mixed-mode survey, the American Family Health Study (AFHS). In the screening stage, we based the adaptive design's subgroup differentiation on Esri Tapestry segmentation. We used tailored invitation materials for a subsample where a high proportion of the population was Hispanic and added a paper questionnaire to the initial mailing for a subsample with rural and older families. In the main-survey stage, the adaptive design targeted the households where a member other than the screening respondent was selected for the survey. The adaptations included emailing and/or texting, an additional prepaid incentive, and seeking screening respondents' help to remind the selected individuals. The main research questions are (i) whether the adaptive design improved survey production outcomes and (ii) whether combining adaptive design and postsurvey weighting adjustments improved survey estimates compared to performing postsurvey adjustments alone. Unfortunately, the adaptive designs did not improve the survey production outcomes. We found that the weighted AFHS estimates closely resemble those of a benchmark national face-to-face survey, the National Survey of Family Growth, although the adaptive design did not additionally change survey estimates beyond the weighting adjustments. Nonetheless, our experiment yields useful insights about the implementation of adaptive design in a self-administered mail-recruit web or mail survey. We were able to identify subgroups with potentially lower response rates and distinctive characteristics, but it was challenging to develop effective protocol adaptations for these subgroups under the constraints of the two primary survey modes and the operational budget of the AFHS. In addition, for self-administered within-household selection, it was difficult to obtain contact information from, reach, and recruit selected household members that did not respond to the screening interview.

An Adaptive Sampling Algorithm with Dynamic Iterative Probability Adjustment Incorporating Positional Information.

Physics-informed neural networks (PINNs) have garnered widespread use for solving a variety of complex partial differential equations (PDEs). Nevertheless, when addressing certain specific problem types, traditional sampling algorithms still reveal deficiencies in efficiency and precision. In response, this paper builds upon the progress of adaptive sampling techniques, addressing the inadequacy of existing algorithms to fully leverage the spatial location information of sample points, and introduces an innovative adaptive sampling method. This approach incorporates the Dual Inverse Distance Weighting (DIDW) algorithm, embedding the spatial characteristics of sampling points within the probability sampling process. Furthermore, it introduces reward factors derived from reinforcement learning principles to dynamically refine the probability sampling formula. This strategy more effectively captures the essential characteristics of PDEs with each iteration. We utilize sparsely connected networks and have adjusted the sampling process, which has proven to effectively reduce the training time. In numerical experiments on fluid mechanics problems, such as the two-dimensional Burgers' equation with sharp solutions, pipe flow, flow around a circular cylinder, lid-driven cavity flow, and Kovasznay flow, our proposed adaptive sampling algorithm markedly enhances accuracy over conventional PINN methods, validating the algorithm's efficacy.

Inequality of opportunity in the double burden of malnutrition in Mexico.

This paper proposes a pseudo-birth-cohort approach to deal with a lack of longitudinal data to measure health inequities over time. Using Roemer's framework for inequality of opportunity, this study measures ex-ante and ex-post inequalities in malnutrition, a concept that spans both sides of the nutrition continuum. The total contribution of observed circumstances and the direct contribution of observed efforts to the variation of malnutrition are disentangled for people born between 1983 and 1988 in Mexico. Results indicate that inequality of opportunity has been persistent across this 30-year lifespan for that cohort. Some evidence suggests that a lack of opportunities has been transmitted from parents to children and that people's circumstances account for most of the explained variation in the double burden of malnutrition. However, stratifying the analysis by sex shows that efforts account for more of the explained variation of inequality of opportunity for women in their middle adulthood than for men in most of the outcomes analyzed.

Evaluating the Effectiveness of Systemic Heparin During Arteriovenous Fistula Creation by Emulating a Target Trial.

Most of the 800,000 people living with end-stage kidney disease in the United States rely on a functioning vascular access to provide life-sustaining hemodialysis, yet one-third of arteriovenous fistulas experience early failures. Determining the safety and effectiveness of systemic heparin during fistula creation could improve the quality and quantity of life for these vulnerable patients. In this paper, a pragmatic randomized trial was emulated to assess the effect of systemic heparin administration (vs. none) during radiocephalic arteriovenous fistula creation on early bleeding and thrombosis using data from two international multicenter randomized trials performed between 2014 and 2019. Marginal risks were estimated using inverse probability weighted parametric survival analysis and confidence intervals were generated with bootstrapping. A total of 914 patients were enrolled and 61% received systemic heparin; median (IQR) age was 58 (49, 67) years and 45% were on hemodialysis at enrollment. No difference in the risk of bleeding events was observed, with a risk difference (95% CI) at 14 days of -0.1% (-1.6, 1.4). The risk of access thrombosis was lower in the heparin group, with a risk of 3.7% (2.6, 4.8) after heparin and 5.3% (3.4, 7.4) without heparin at 14 days (risk ratio 0.72, 95% CI 0.50, 0.98).