Covariate Balancing Propensity Score Research Articles

Household size and depressive symptoms during the COVID-19 pandemic: A gendered analysis

ABSTRACT The study explores the nature of the relationship between household size and depressive symptoms under COVID-19 strict lockdown conditions, when a surge in large-size households observed in South Africa. The study used nationally representative data to implement covariate balancing propensity scores within a multivalued treatment framework (by varying household size) to control for observables. While the study found that both solo living and large-sized households are positively associated with depressive symptoms for males, the depressive symptoms for females are not found to be strongly associated with household size. Further, the analysis indicates that the higher average depressive symptoms observed for males compared to females under the COVID-19 pandemic are largely driven by males in large-size households. The gendered effect points to the different roles that men and women continue to play within the household. The need for policy interventions to consider living arrangements is highlighted through this study.

Voluntary sustainability standards and technical efficiency of Honduran smallholder coffee producers

Sustainable coffee production promises to improve production techniques and enhance the socioeconomic conditions of smallholder farmers. Using primary survey data from 659 coffee producers in Honduras, this study assesses the impact of voluntary sustainability standards (VSS) on the technical efficiency of smallholder coffee production. The article uses the Stochastic Production Frontier Analysis model to analyze and compare the technical efficiency (TE) of certified and non-certified coffee producers. To provide reliable comparability between groups, the dataset was balanced using Covariate Balancing Propensity Score (CBPS). The results show that the mean technical efficiency was 52.86% for pooled certified farmers and 55.56% for non-certified smallholder coffee producers. Specifically, the technical efficiency of 4C farmers was 51.58%, 53.82% for the Fairtrade group, 60.56% for RA farmers, and 60.15% for the UTZ group, indicating substantial inefficiencies in the coffee production of the different certified groups. Results from Tobit’s model for the determinants of TE indicated that variables such as the age of the household head, access to credit, and training attendance are among the main factors that significantly drive the technical efficiency of certified and non-certified farmers. Based on the findings, enhancing education opportunities, improving infrastructure for better market access and farm management, and expanding credit access are recommended to improve efficiency in the study area. Honduran smallholder coffee producers have considerable potential to increase output with existing technology by improving their technical efficiency. Therefore, stakeholders’ efforts should focus on enhancing efficiency levels and capitalizing on potential gains for both certified and non-certified farmers, to ultimately improve the farmers’ livelihoods.

Communication‐Efficient Distributed Estimation of Causal Effects With High‐Dimensional Data

ABSTRACTWe propose a communication‐efficient algorithm to estimate the average treatment effect (ATE), when the data are distributed across multiple sites and the number of covariates is possibly much larger than the sample size in each site. Our main idea is to calibrate the estimates of the propensity score and outcome models using some proper surrogate loss functions to approximately attain the desired covariate balancing property. We show that under possible model misspecification, our distributed covariate balancing propensity score estimator (disthdCBPS) can approximate the global estimator, obtained by pooling together the data from multiple sites, at a fast rate. Thus, our estimator remains consistent and asymptotically normal. In addition, when both the propensity score and the outcome models are correctly specified, the proposed estimator attains the semi‐parametric efficiency bound. We illustrate the empirical performance of the proposed method in both simulation and empirical studies.

Robust Covariate-Balancing Method in Learning Optimal Individualized Treatment Regimes

Summary One of the most important problems in precision medicine is to find the optimal individualized treatment rule, which is designed to recommend treatment decisions and maximize overall clinical benefit to patients based on their individual characteristics. Typically, the expected clinical outcome is required to be estimated first, in which an outcome regression model or a propensity score model usually needs to be assumed for most of the existing statistical methods. However, if either model assumption is invalid, the estimated treatment regime is not reliable. In this article, we first define a contrast value function, which is the basis of the study for individualized treatment regimes. Then we construct a hybrid estimator of the contrast value function, by combining two types of estimation methods. We further propose a robust covariate-balancing estimator of the contrast value function by combining the inverse probability weighted method and matching method, which is based on the covariate balancing propensity score proposed by Imai and Ratkovic (2014). Theoretical results show that the proposed estimator is doubly robust, that is, it is consistent if either the propensity score model or the matching is correct. Based on a large number of simulation studies, we demonstrate that the proposed estimator outperforms existing methods. Lastly, the proposed method is illustrated through analysis of the SUPPORT study.

Balancing versus modelling in weighted analysis of non-randomised studies with survival outcomes: A simulation study.

Weighting methods are widely used for causal effect estimation in non-randomised studies. In general, these methods use the propensity score (PS), the probability of receiving the treatment given the covariates, to arrive at the respective weights. All of these "modelling" methods actually optimize prediction of the respective outcome, which is, in the PS model, treatment assignment. However, this does not match with the actual aim of weighting, which is eliminating the association between covariates and treatment assignment. In the "balancing" approach, covariates are thus balanced directly by solving systems of numerical equations, explicitly without fitting a PS model. To compare modelling, balancing and hybrid approaches to weighting we performed a large simulation study for a binary treatment and a survival outcome. For maximal practical relevance all simulation parameters were selected after a systematic review of medical studies that used PS methods for analysis. We also introduce a new hybrid method that uses the idea of the covariate balancing propensity score and matching weights, thus avoiding extreme weights. In addition, we present a corrected robust variance estimator for some of the methods. Overall, our simulations results indicate that balancing approach methods work worse than expected. However, among the considered balancing methods, entropy balancing consistently outperforms the variance balancing approach. All methods estimating the average treatment effect in the overlap population perform well with very little bias and small standard errors even in settings with misspecified propensity score models. Finally, the coverage using the standard robust variance estimator was too high for all methods, with the proposed corrected robust variance estimator improving coverage in a variety of settings.

Abstract PO5-06-03: Impact of curative-intent treatment on survival for metastatic breast cancer limited to distant lymph nodes

Abstract BACKGROUND: Metastatic breast cancer limited to distant lymph nodes is classified as stage IV but potentially represents an anatomically distinct entity amenable to curative treatment. Its optimal management is unclear, with existing studies limited by small sample sizes and short follow-up durations. We sought to investigate the impact of curative-intent treatment on breast cancer-specific survival (BCSS) and overall survival (OS) for patients with this diagnosis. METHODS: Three cohorts of patients diagnosed with breast cancer from 2010 to 2019 were identified from the Surveillance, Epidemiology, and End Results 17 registries database. The curative cohort consisted of patients with metastatic breast cancer involving only distant lymph nodes who received a combination of chemotherapy, surgery to the primary site, and radiotherapy (curative-intent treatment). The palliative cohort included patients who underwent chemotherapy but not curative-intent treatment. The N3c cohort was comprised of patients with ipsilateral supraclavicular lymph node metastases but no distant metastases who received curative-intent treatment. Weighting based on covariate balancing propensity scores was performed to balance age, sex, race, median household income, year of diagnosis, T stage, histology, pathological grade, and ER/PR/HER2 status between the cohorts. Weight-adjusted multivariable Cox regression models with the same covariates were then used to compare the BCSS and OS of the three cohorts. RESULTS: A total of 2,089 patients with a median follow-up of 37 months were eligible for analysis, of whom 577 (27.6%) were in the curative cohort, 905 (43.3%) were in the palliative cohort, and 607 (29.1%) were in the N3c cohort. After propensity score weighting, the maximal standardized mean difference for all covariates was less than 0.1. Five-year BCSS for patients in the weight-adjusted curative, palliative, and N3c cohorts were 63.0% (95% CI 58.1-68.3), 46.7% (42.4-51.4), and 66.4% (61.4-71.8), respectively; and five-year OS were 57.9% (53.0-63.2), 41.2% (37.2-45.7), and 62.2% (57.3-67.6), respectively. Compared to the palliative cohort, the curative cohort exhibited better BCSS (HR 0.47, 95% CI 0.38-0.57; P< 0.001) and OS (HR 0.48, 95% CI 0.40-0.58; P< 0.001). In contrast, the N3c cohort had similar BCSS (HR 0.93, 95% CI 0.73-1.17; P=0.53) and OS (HR 0.96, 95% CI 0.77-1.19; P=0.68) to the curative cohort. CONCLUSIONS: Patients treated curatively for metastatic breast cancer limited to distant lymph nodes had higher BCSS and OS than those receiving palliative chemotherapy and similar BCSS and OS to patients receiving curative-intent treatment for ipsilateral supraclavicular lymph node metastases. These results support the use of aggressive multimodal therapy for select stage IV breast cancer patients with only distant nodal metastases and, if confirmed, suggest that a substantial portion of such patients may be undertreated. Citation Format: Yang Xu. Impact of curative-intent treatment on survival for metastatic breast cancer limited to distant lymph nodes [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-06-03.

Comparison of resumption of ovulation after cessation of oral contraceptives and medroxyprogesterone acetate in women with polycystic ovary syndrome

Objective Both oral contraceptive pills (OCPs) and cyclic medroxyprogesterone acetate (MPA) are widely used to control menstrual abnormalities in women with polycystic ovary syndrome (PCOS). We aimed to evaluate the chance of ovulation resumption after cessation of OCPs and MPA in women with PCOS. Methods A retrospective study was conducted of women with PCOS who were treated with OCPs or cyclic MPA from September 2015 to March 2019. After cessation of medication, ovulation was assessed using basal body temperature and/or measurement of serum progesterone. The odds ratio for ovulation resumption was assessed with multivariable logistic regression. Additionally, doubly robust analysis was performed with inverse-probability-weighted analysis and regression adjustment based on the covariate balancing propensity score to adjust for the effect of covariates on the treatment assignment. Results Among 272 women with PCOS, 136 were prescribed OCPs and 136 were prescribed cyclic MPA. Ovulation resumed in 18.4% of women (n = 25) after cessation of MPA and in 24.3% of women (n = 33) after cessation of OCPs. The odds of ovulation resumption in MPA users were comparable with those in OCP users (adjusted odds ratio (aOR) 1.00, 95% confidence interval (CI) 0.89–1.12). After multiple imputation due to missing values, the results did not change substantially (aOR 0.99, 95% CI 0.89–1.10). Conclusions Among women with PCOS, MPA users have a similar chance of ovulation resumption as OCP users after cessation of medication. Cyclic MPA can be a good alternative to OCPs in women for whom OCPs are contraindicated or who decline to take OCPs.

Mechanical ventilation as a major driver of COVID-19 hospitalization costs: a costing study in a German setting

BackgroundWhile COVID-19 hospitalization costs are essential for policymakers to make informed health care resource decisions, little is known about these costs in western Europe. The aim of the current study is to analyze these costs for a German setting, track the development of these costs over time and analyze the daily costs.MethodsAdministrative costing data was analyzed for 598 non-Intensive Care Unit (ICU) patients and 510 ICU patients diagnosed with COVID-19 at the Frankfurt University hospital. Descriptive statistics of total per patient hospitalization costs were obtained and assessed over time. Propensity scores were estimated for length of stay (LOS) at the general ward and mechanical ventilation (MV) duration, using covariate balancing propensity score for continuous treatment. Costs for each additional day in the general ward and each additional day in the ICU with and without MV were estimated by regressing the total hospitalization costs on the LOS and the presence or absence of several treatments using generalized linear models, while controlling for patient characteristics, comorbidities, and complications.ResultsMedian total per patient hospitalization costs were €3,010 (Q1 – Q3: €2,224—€5,273), €5,887 (Q1 – Q3: €3,054—€10,879) and €21,536 (Q1 – Q3: €7,504—€43,480), respectively, for non-ICU patients, non-MV and MV ICU patients. Total per patient hospitalization costs for non-ICU patients showed a slight increase over time, while total per patient hospitalization costs for ICU patients decreased over time. Each additional day in the general ward for non-ICU COVID-19 patients costed €463.66 (SE: 15.89). Costs for each additional day in the general ward and ICU without and with mechanical ventilation for ICU patients were estimated at €414.20 (SE: 22.17), €927.45 (SE: 45.52) and €2,224.84 (SE: 70.24).ConclusionsThis is, to our knowledge, the first study examining the costs of COVID-19 hospitalizations in Germany. Estimated costs were overall in agreement with costs found in literature for non-COVID-19 patients, except for higher estimated costs for mechanical ventilation. These estimated costs can potentially improve the precision of COVID-19 cost effectiveness studies in Germany and will thereby allow health care policymakers to provide better informed health care resource decisions in the future.

Weighted expectile average estimation based on CBPS with responses missing at random

<p>An improved weighted expectile average estimator for the regression coefficient has been obtained based on the covariate balancing propensity score (CBPS), when the responses of linear models are missing at random. The asymptotic normality of the proposed method has been proved, and the estimation effect of the method is further illustrated by numerical simulation.</p>

Early absolute lymphocyte count was associated with one-year mortality in critically ill surgical patients: A propensity score-matching and weighting study.

Absolute lymphocyte count (ALC) is a crucial indicator of immunity in critical illness, but studies focusing on long-term outcomes in critically ill patients, particularly surgical patients, are still lacking. We sought to explore the association between week-one ALC and long-term mortality in critically ill surgical patients. We used the 2015-2020 critical care database of Taichung Veterans General Hospital (TCVGH), a referral hospital in central Taiwan, and the primary outcome was one-year all-cause mortality. We assessed the association between ALC and long-term mortality by measuring hazard ratios (HRs) with 95% confidence intervals (CIs). Furthermore, we used propensity score-matching and -weighting analyses, consisting of propensity score matching (PSM), inverse probability of treatment weighting (IPTW), and covariate balancing propensity score (CBPS), to validate the association. A total of 8052 patients were enrolled, with their one-year mortality being 24.2%. Cox regression showed that low ALC was independently associated with mortality (adjHR 1.140, 95% CI 1.091-1.192). Moreover, this association tended to be stronger among younger patients, patients with fewer comorbidities and lower severity. The association between low ALC and mortality in original, PSM, IPTW, and CBPS populations were 1.497 (95% CI 1.320-1.697), 1.391 (95% CI 1.169-1.654), 1.512 (95% CI 1.310-1.744), and 1.511 (95% CI 1.310-1.744), respectively. Additionally, the association appears to be consistent, using distinct cutoff levels to define the low ALC. We identified that early low ALC was associated with increased one-year mortality in critically ill surgical patients, and prospective studies are warranted to confirm the finding.

Segmental ischemia and indocyanine green navigation: impact on perioperative parameters in laparoscopic vs. open partial nephrectomy

The aim of this study is to compare perioperative parameters of laparoscopic partial nephrectomy and open partial nephrectomy in renal tumor management, and to evaluate the effect of using novel method of indocyanine green navigation in segmental ischemia on these parameters. The prospective study included 455 patients (89 laparoscopic partial nephrectomies, 366 open partial nephrectomies). Sub-groups (n=39, 32, 18) in Laparoscopic partial nephrectomy employed diverse ischemia techniques, including full warm ischemia, segmental ischemia with indocyanine green navigation and segmental ischemia without navigation. Parameters assessed encompassed estimated blood loss, ope­rative time, warm ischemia time, and changes in estimated glomerular filtration rate. Covariate-balancing propensity scores ensured homogeneity. Statistical analysis included the Wilcoxon signed-rank test, for two matched groups. Two-sided p-values were reported for all statistical tests, a p-value <0.05 was considered to be statistically significant. The findings of the conducted research indicate that open partial nephrectomy has revealed significant differences in estimated blood loss, operative time, and warm ischemia time, in favor of open partial nephrectomy. Laparoscopic partial nephrectomy offers advantages in preserving renal function and minimizing estimated Glomerular Filtration Rate decline compared to open partial nephrectomy. The utilization indocyanine green navigation, facilitates precise and limited ischemia, contributing to enhanced preservation of renal function. Surgeons must weigh these considerations for optimal renal tumor management.

2314. Association Between Behavior and Risk of COVID-19 in a Cohort of Healthcare Personnel

Abstract Background Social behaviors are associated with COVID-19 infection. Most studies assessing exposure risk from daily activities were performed in the general population. Less is known about the impact of social behavior on the risk of COVID-19 among healthcare personnel (HCP), who have a higher risk of exposure at work and more awareness of prevention measures than the general population. Methods We conducted a prospective cohort study, with monthly surveys from Dec 2021 to June 2022 of HCP at an academic healthcare system. Each survey asked HCP if they had been tested for SARS-CoV-2, their results, and if they had engaged in any of 9 common social activities outside of work (see figure). A composite social activities exposure measure was defined as the count of “Yes” to the social activities at the previous survey, with a possible range from 0-9. Similarity of current overall social behavior compared to pre-pandemic was also reported on a scale of 0-10, with 10 reflecting the same level as pre-pandemic. We employed mixed effect logistic regression, weighted for dropout using covariate balancing propensity scores, to estimate the association between previously reported social behavior and activities and testing positive for SARS-CoV-2 after adjusting for covariates (see table). Results Recruitment emails were sent to 10,321 HCP, with 1,802 (17.5%) consenting to participate and 1,302 (72.3%) completing 2 or more surveys. 981 HCP reported being tested for SARS-CoV-2 with at least one positive test reported by 277 HCP (28.2%). Engaging in overall social behavior more similar to pre-pandemic levels was found to be statistically significantly associated with an increased likelihood of testing positive for SARS-CoV-2 (OR 1.32, 95% CI 1.11-1.56). However, while there was a trend to testing positive with an increased number of social activities reported at the previous survey, it was not significant (OR 1.06, 95% CI 0.95-1.18). Temporal Trends of Social Activities in Healthcare Workers Reported social activities of healthcare workers at an academic healthcare system from late November 2021 to May 2022. Association Between Social Activity Measures and Positive COVID-19 Test 1. Similarity of social behavior at the previous survey with pre-pandemic behavior reported on a scale of 0-10, with 10 reflecting the same level of activity as pre-pandemic. 2. Count of “Yes” to the social activities at the previous survey, with a possible range from 0-9. 3. Covariates adjusted: calendar month, age, gender, clinic role, working location, general health, comorbidities, household status, illnesses reported at the previous survey, time since last vaccine, and time since the previous survey. Conclusion This study, which included the Omicron surge, saw HCP participation in a range of social activities. Reporting levels of social activity similar to pre-pandemic levels was associated with an increased risk of subsequent COVID-19. This feedback is important for HCP consideration of exposures outside of work. Disclosures Jeanmarie Mayer, MD, GlaxoSmithKline: Stocks/Bonds Andrew T. Pavia, MD, GlaxoSmith Kline: Advisor/Consultant|Sanofi: Advisor/Consultant

Early transthoracic echocardiography and long-term mortality in moderate- to-severe acute respiratory distress syndrome: An analysis of the Medical Information Mart for Intensive Care database.

The clinical use of transthoracic echocardiography (TTE) in patients with acute respiratory distress syndrome (ARDS) in the intensive care unit (ICU) has dramatically increased, its impact on long-term prognosis in these patients has not been studied. This study aimed to explore the effect of early-TTE on long-term mortality in patients with moderate-to-severe ARDS in ICU. A total of 2833 patients with moderate-to-severe ARDS who had or had not received early-TTE were obtained from the Medical Information Mart for Intensive Care (MIMIC-III) database after imputing missing values by a random forest model, patients were divided into early-TTE group and non-early-TTE group according to whether they received TTE examination in ICU. A variety of statistical methods were used to balance 41 covariates and increase the reliability of this study, including propensity score matching, inverse probability of treatment weight, covariate balancing propensity score, multivariable regression, and doubly robust estimation. Chi-Square test and t-tests were used to examine the differences between groups for categorical and continuous data, respectively. There was a significant improvement in 90-day mortality in the early-TTE group compared to non-early-TTE group (odds ratio = 0.79, 95% CI: 0.64-0.98, p-value = 0.036), revealing a beneficial effect of early-TTE. Net-input was significantly decreased in the early-TTE group on the third day of ICU admission and throughout the ICU stay, compared with non-early-TTE group (838.57 vs. 1181.89 mL, p-value = 0.014; 4542.54 vs. 8025.25 mL, p-value = 0.05). There was a significant difference in the reduction of serum lactate between the two groups, revealing the beneficial effect of early-TTE (0.59 vs. 0.83, p-value = 0.009). Furthermore, the reduction in the proportion of acute kidney injury demonstrated a correlation between early-TTE and kidney protection (33% vs. 40%, p-value < 0.001). Early application of TTE is beneficial to improve the long-term mortality of patients with moderate-to-severe ARDS.

Evaluating the impact of sickle cell disease on COVID-19 susceptibility and severity: a retrospective cohort study based on electronic health record.

Sickle cell trait/disease (SCT/SCD) are enriched among Black people and associated with various comorbidities. The overrepresentation of these characteristics prevents traditional regression approach obtaining convincing evidence for the independent effect of SCT/SCD on other health outcomes. This study aims to investigate the association between SCT/SCD and COVID-19-related outcomes using causal inference approaches that balance the covariate. We leveraged electronic health record (EHR) data from the University of Chicago Medicine between March 2020 and December 2021. Demographic characteristics were retrieved. Medical conditions were identified using ICD-10 codes. Five approaches, including two traditional regression approaches (unadjusted and adjusted) and three causal inference approaches [covariate balancing propensity score (CBPS) matching, CBPS weighting, and CBPS adjustment], were employed. A total of 112,334 patients were included in the study, among which 504 had SCT and 388 SCD. Patients with SCT/SCD were more likely to be non-Hispanic Black people, younger, female, non-smokers, and had a diagnosis of diabetes, heart failure, asthma, and cerebral infarction. Causal inference approaches achieved a balanced distribution of these covariates while traditional approaches failed. Across these approaches, SCD was consistently associated with COVID-19-related pneumonia (odds ratios (OR) estimates, 3.23 (95% CI: 2.13-4.89) to 2.57 (95% CI: 1.10-6.00)) and pain (OR estimates, 6.51 (95% CI: 4.68-9.06) to 2.47 (95% CI: 1.35-4.49)). While CBPS matching suggested an association between SCD and COVID-19-related acute respiratory distress syndrome (OR = 2.01, 95% CI: 0.97-4.17), this association was significant in other approaches (OR estimates, 2.96 (95% CI: 1.69-5.18) to 2.50 (95% CI: 1.43-4.37)). No association was observed between SCT and COVID-19-related outcomes in causal inference approaches. Using causal inference approaches, we provide comprehensive evidence for the link between SCT/SCD and COVID-19-related outcomes.

Sarcopenia Is a Prognostic Factor in Patients Undergoing Percutaneous Endoscopic Gastrostomy.

(1) Background: Percutaneous endoscopic gastrostomy (PEG) is a widely used long-term enteral nutrition method, but little is known about the associated prognostic factors in patients with PEG. Sarcopenia, a condition characterized by a loss of skeletal muscle mass, increases the risk of developing various gastrointestinal disorders. Yet, the relationship between sarcopenia and the prognosis after PEG remains unclear. (2) Methods: We conducted a retrospective study of patients who underwent PEG consecutively from March 2008 to April 2020. We analyzed preoperative sarcopenia and the prognosis of patients after PEG. We defined sarcopenia as a skeletal muscle index at the level of the third lumbar vertebra of ≤29.6 cm2/m2 for women and ≤36.2 cm2/m2 for men. Cross-sectional computed tomography images of skeletal muscle at the level of the third lumbar vertebra were evaluated using DICOM image analysis software (OsiriX). The primary outcome was the difference in overall survival after PEG based on the status of sarcopenia. We also performed a covariate balancing propensity score matching analysis. (3) Results: Of 127 patients (99 men, 28 women), 71 (56%) were diagnosed with sarcopenia, and 64 patients died during the observation period. The median follow-up period did not differ between patients with and without sarcopenia (p = 0.5). The median survival time after PEG was 273 days in patients with sarcopenia and 1133 days in those without (p < 0.001). Cox proportional hazard model analyses identified three factors that were significantly associated with overall survival: sarcopenia (adjusted hazard ratio [HR]: 2.9, 95% confidence interval [CI]: 1.6-5.4, p < 0.001), serum albumin level (adjusted HR: 0.34, 95% CI: 0.21-0.55, p < 0.001) and male sex (adjusted HR: 2.0, 95% CI: 1.1-3.7, p = 0.03). Propensity score-matched analysis (n = 37 vs. 37) showed that the survival rate was lower in the sarcopenia group than in the non-sarcopenia group (at 90 days: 77% (95% CI, 59-88) vs. 92% (76-97), at 180 days: 56% (38-71) vs. 92% (76-97), and at one year: 35% (19-51) vs. 81% (63-91), p = 0.0014). (4) Conclusions: Sarcopenia was associated with poor prognosis in patients having undergone PEG.

Primary care services and emergency department visits in blended fee-for-service and blended capitation models: evidence from Ontario, Canada.

It is well-known that the way physicians are remunerated can affect delivery of health care services to the population. Fee-for-service (FFS) generally leads to oversupply of services, while capitation leads to undersupply of services. However, little evidence exists on the link between remuneration and emergency department (ED) visits. We fill this gap using two popular blended models introduced in Ontario, Canada: the Family Health Group (FHG), an enhanced/blended FFS model, and Family Health Organization (FHO), a blended capitation model. We compare primary care services and rates of emergency department ED visits between these two models. We also evaluate whether these outcomes vary by regular- and after-hours, and patient morbidity status. Physicians practicing in an FHG or FHO between April 2012 and March 2017 and their enrolled adult patients were included for analyses. The covariate-balancing propensity score weighting method was used to remove the influence of observable confounding and negative-binomial and linear regression models were used to evaluate the rates of primary care services, ED visits, and the dollar value of primary care services delivered between FHGs and FHOs. Visits were stratified as regular- and after-hours. Patients were stratified into three morbidity groups: non-morbid, single-morbid, and multimorbid (two or more chronic conditions). 6184 physicians and their patients were available for analysis. Compared to FHG physicians, FHO physicians delivered 14% (95% CI 13%, 15%) fewer primary care services per patient per year, with 27% fewer services during after-hours (95% CI 25%, 29%). Patients enrolled to FHO physicians made 27% more less-urgent (95% CI 23%, 31%) and 10% more urgent (95% CI 7%, 13%) ED visits per patient per year, with no difference in very-urgent ED visits. Differences in the pattern of ED visits were similar during regular- and after-hours. Although FHO physicians provided fewer services, multimorbid patients in FHOs made fewer very-urgent and urgent ED visits, with no difference in less-urgent ED visits. Primary care physicians practicing in Ontario's blended capitation model provide fewer primary care services compared to those practicing in a blended FFS model. Although the overall rate of ED visits was higher among patients enrolled to FHO physicians, multimorbid patients of FHO physicians make fewer urgent and very-urgent ED visits.

Anaemia in the first week may be associated with long-term mortality among critically ill patients: propensity score-based analyses

BackgroundAnaemia is highly prevalent in critically ill patients; however, the long-term effect on mortality remains unclear.MethodsWe retrospectively included patients admitted to the medical intensive care units (ICUs) during 2015–2020 at the Taichung Veterans General Hospital. The primary outcome of interest was one-year mortality, and hazard ratios (HRs) with 95% confidence intervals (CIs) were determined to assess the association. We used propensity score matching (PSM) and propensity score matching methods, including inverse probability of treatment weighting (IPTW) as well as covariate balancing propensity score (CBPS), in the present study.ResultsA total of 7,089 patients were eligible for analyses, and 45.0% (3,189/7,089) of them had anaemia, defined by mean levels of haemoglobin being less than 10 g/dL. The standardised difference of covariates in this study were lower than 0.20 after matching and weighting. The application of CBPS further reduced the imbalance among covariates. We demonstrated a similar association, and adjusted HRs in original, PSM, IPTW and CBPS populations were 1.345 (95% CI 1.227–1.474), 1.265 (95% CI 1.145–1.397), 1.276 (95% CI 1.142–1.427) and 1.260 (95% CI 1.125–1.411), respectively.ConclusionsWe used propensity score-based analyses to identify that anaemia within the first week was associated with increased one-year mortality in critically ill patients.

Assessing the Effect of Abortion Restrictions: Improving Methodology and Expanding Outcomes.

Assessing the Effect of Abortion Restrictions: Improving Methodology and Expanding Outcomes.

The Association Between Absolute Lymphocyte Count and Long-Term Mortality in Critically Ill Medical Patients: Propensity Score-Based Analyses.

Absolute lymphocyte count (ALC) has been implicated with short-term outcomes in a number of diseases, and we aimed to investigate the association between week-one ALC and long-term mortality in patients who were admitted to the medical intensive care units (ICUs). We enrolled patients who were admitted to the medical ICUs at the Taichung Veterans General Hospital, a referral centre located in central Taiwan, between 2015 and 2020 to conduct this retrospective cohort study. The outcome of interest was long-term all-cause mortality, and hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to determine the association. Furthermore, we employed propensity score-matching (PSM) and weighting techniques, consisting of inverse probability of treatment weighting (IPTW) and covariate balancing propensity score (CBPS), to confirm the association between ALC and mortality. A total of 5722 critically ill patients were enrolled, and the one-year mortality was 44.8%. The non-survivor group had a lower ALC (1549, 1027-2388 vs 1948, 1373-2743 counts/μL, p<0.01) compared with those in the survivor group. Cox regression showed that low ALC was independently associated with mortality (adjHR 1.091, 95% CI 1.050-1.134). Propensity score-based analyses demonstrated the robust association, with adjHRs in the original, PSM, IPTW, and CBPS populations of 1.327 (95% CI 1.224-1.438), 1.301 (95% CI 1.188-1.424), 1.292 (95% CI 1.186-1.407), and 1.297 (95% CI 1.191-1.412), respectively. Sensitivity analyses further showed that the association between low ALC and mortality existed in a dose-response manner. We found that low ALC was associated with long-term mortality in critically ill patients; further studies are warranted to validate and translate these findings into clinical utility.

Rbw: An R Package for Constructing Residual Balancing Weights

We describe the R package [rbw](https://CRAN.R-project.org/package=rbw), which implements the method of residual balancing weights (RBW) for estimating marginal structural models. In contrast to other methods such as inverse probability weighting (IPW) and covariate balancing propensity scores (CBPS), RBW involves modeling the conditional means of post-treatment confounders instead of the conditional distributions of the treatment to construct the weights. RBW is thus easier to use with continuous treatments, and the method is less susceptible to model misspecification issues that often arise when modeling the conditional distributions of treatments. RBW is also advantageous from a computational perspective. As its weighting procedure involves a convex optimization problem, RBW typically locates a solution considerably faster than other methods whose optimization relies on nonconvex loss functions --- such as the recently proposed nonparametric version of CBPS. We explain the rationale behind RBW, describe the functions in [rbw](https://CRAN.R-project.org/package=rbw), and then use real-world data to illustrate their applications in three scenarios: effect estimation for point treatments, causal mediation analysis, and effect estimation for time-varying treatments with time-varying confounders.