Augmented Inverse Probability Weighting Research Articles

Impact of the COVID-19 vaccinations on economic outcomes and mental health services in the U.S

The development of vaccines has long been viewed as a critical public health tool to raise immunity against the COVID-19 virus and to reopen economic activities globally. Against this background, this study examines the impact of COVID-19 vaccinations on economic outcomes and mental health services in the U.S. We employed the Household Pulse Survey covering 549, 950 and 57, 892 vaccinated and unvaccinated individuals, respectively. For the causal analysis, we control the differences between the vaccinated and unvaccinated groups using propensity score matching (PSM) and augmented inverse probability weighting (AIPW) methods. Economic outcomes include whether individuals work on-site, telework or work from home, in-store shopping, job loss, or food sufficient. We also consider whether individuals experience mental health distress and receive mental health services as a potential outcome. The empirical results show that the probability of working on-site, in-store shopping, food sufficiency, and using mental health services are significantly higher among the recipients of the COVID-19 vaccines than non-recipients. We also find that the likelihood of teleworking and job loss decreased significantly among the recipients of the COVID-19 vaccine compared to non-recipients. The magnitude of the estimated impact across race and ethnic groups is mixed, which shows that vaccination effects are heterogeneous across the races/ethnic groups in the sample.

The impact of family residence structure on adolescents' non-cognitive abilities: evidence from China.

The family residence structure serves as a crucial pathway through which the family environment influences adolescents' development. Drawing on nationally representative data, this study employs multiple linear regression models and propensity score matching to examine the impact of various family residence structures on adolescents' non-cognitive abilities. Causal identification is achieved through propensity score matching, while robustness is assessed using methods such as augmented inverse probability weighting and placebo tests. Heterogeneity analysis is conducted based on gender and household registration, aiming to explore the mechanisms by which family residence structure affects adolescents' non-cognitive abilities. The findings indicate that compared to two-parent co-residence households, three-generation co-residence families have significantly positive effects on emotional stability, conscientiousness, and agreeableness among adolescents. In contrast, skip-generation coresidence families exhibit significant negative effects on emotional stability and agreeableness in adolescents. Further investigation into the underlying mechanisms reveals that parental involvement and family socioeconomic status within three-generation co-residence families positively influence adolescents' non-cognitive abilities. This study highlights the importance of considering grandparents' role in adolescent growth and advocates for policy recommendations focusing on enhancing non-cognitive abilities in adolescents from skip-generation co-residence families.

Clinicians Who Practice Primarily in Nursing Homes and the Quality of End-of-Life Care Among Residents

Clinician specialization in the care of nursing home (NH) residents or patients in skilled nursing facilities (SNFs) has become increasingly common. It is not known whether clinicians focused on NH care, often referred to as SNFists (ie, physicians, nurse practitioners, and physician assistants concentrating their practice in the NH or SNF setting), are associated with a reduced likelihood of burdensome transitions in the last 90 days of life for residents, which are a marker of poor-quality end-of-life (EOL) care. To quantify the association between receipt of care from an SNFist and quality of EOL care for NH residents. This cohort study analyzed Medicare fee-for-service claims for a nationally representative 20% sample of beneficiaries to examine burdensome transitions among NH decedents at the EOL from January 1, 2013, through December 31, 2019. Statistical analyses were conducted from December 2022 to June 2023. Receipt of care from an SNFist, defined as physicians and advanced practitioners who provided 80% or more of their evaluation and management visits in NHs annually. This study used augmented inverse probability weighting in analyses of Medicare fee-for-service claims for a nationally representative 20% sample of beneficiaries. Main outcomes included 4 measures of burdensome transitions: (1) hospital transfer in the last 3 days of life; (2) lack of continuity in NHs after hospitalization in the last 90 days of life; (3) multiple hospitalizations in the last 90 days of life for any reason or any hospitalization for pneumonia, urinary tract infection, dehydration, or sepsis; and (4) any hospitalization in the last 90 days of life for an ambulatory care-sensitive condition. Of the 2 091 954 NH decedents studied (mean [SD] age, 85.4 [8.5] years; 1 470 724 women [70.3%]), 953 722 (45.6%) received care from SNFists and 1 138 232 (54.4%) received care from non-SNFists; 422 575 of all decedents (20.2%) experienced a burdensome transition at the EOL. Receipt of care by an SNFist was associated with a reduced risk of (1) hospital transfer in the last 3 days of life (-1.6% [95% CI, -2.5% to -0.8%]), (2) lack of continuity in NHs after hospitalization (-4.8% [95% CI, -6.7% to -3.0%]), and (3) decedents experiencing multiple hospitalizations for any reason or any hospitalization for pneumonia, urinary tract infection, dehydration, or sepsis (-5.8% [95% CI, -10.1% to -1.7%]). There was not a statistically significant association with the risk of hospitalization for an ambulatory care-sensitive condition in the last 90 days of life (0.0% [95% CI, -14.7% to 131.7%]). This study suggests that SNFists may be an important resource to improve the quality of EOL care for NH residents.

Quantifying bias due to missing data in quality of life surveys of advanced-stage cancer patients.

Many studies on cancer patients investigate the impact of treatment on health-related quality of life (QoL). Typically, QoL is measured longitudinally, at baseline and at predefined timepoints thereafter. The question is whether, at a given timepoint, patients who return their questionnaire (available cases, AC) have a different QoL than those who do not return their questionnaire (non-AC). We employed augmented inverse probability weighting (AIPW) to estimate the average QoL of non-AC in two studies on advanced-stage cancer patients. The AIPW estimator assumed data to be missing at random (MAR) and used machine learning (ML)-based methods to estimate answering probabilities of individuals at given timepoints as well as their reported QoL, as a function of auxiliary variables. These auxiliary variables were selected by medical oncologists based on domain expertise. We aggregated results both by timepoint and by time until death and compared AIPW estimates to the AC averages. Additionally, we used a pattern mixture model (PMM) to check sensitivity of our AIPW estimates against violation of the MAR assumption. Our study included 1927 patients with advanced pancreatic and 797 patients with advanced breast cancer. The AIPW estimate for average QoL of non-AC was below the average QoL of AC when aggregated by timepoint. The difference vanished when aggregated by time until death. PMM estimates were below AIPW estimates. Our results indicate that non-AC have a lower average QoL than AC. However, estimates for QoL of non-AC are subject to unverifiable assumptions about the missingness mechanism.

Association of Stressful Life Events With Oral Health Among Japanese Workers.

Psychological stress can cause various mental and physical health problems. The previous results on stress and oral health are inconsistent, possibly because of the narrow stress measurements. We aimed to examine the association between a broader range of stressful life events and oral health among workers. This cross-sectional study analyzed anonymous individual data from a national survey in Japan. Data on stressful life events, oral health problems which are one or more of tooth pain, gum swelling/bleeding, and difficulty chewing, and covariates were obtained using a self-reported questionnaire. Covariates used included gender, age group, and disease under treatment. Logistic regression analysis was used to estimate the association between stressful life events and oral health problems. We then estimated the causal treatment effects of stress using the augmented inverse-probability weighting (AIPW) method. Among the 274,881 subjects, 152,850 men (55.6%) and 122,031 women (44.4%) with a mean age of 47.0 (standard deviation, 14.4) years, 4.0% reported oral health problems, with a prevalence of 2.1% among those without any stress. The prevalence increased with stress score, reaching 15.4% for those with the maximum stress score. The adjusted odds ratio of this group compared to those without any stress was 9.2 (95% confidence interval [CI], 8.2-10.3). The estimated prevalence of oral health problems by the AIPW analysis was 2.2% (95% CI, 2.1-2.3%) for those without any stress and 14.4% (95% CI, 12.1-16.7%) for those with the maximum stress scores. There was a clear dose-response association between stressful life events and oral health problems.

Occupational feminization, gender, and wages: evidence from Thailand

This study examines the relationship between occupational feminization and wages in Thailand using the Thailand Labor Force Survey data (LFS) (2008-2017). Employing the Augmented Inverse Probability Weighting (AIPW) and the Inverse Probability Weighted Regression Adjustment (IPWRA) double robust matching techniques, this study investigates the effects of occupational feminization and the interaction effect of occupational feminization and gender on wages. The findings indicate that occupational feminization decreased wages in Thailand, and the negative effect weakened over time. While the gender wage gap persisted in feminized occupations over the years, there was a reduction in the gender wage gap in non-feminized occupations. The wage gap between females in feminized occupations and males in non-feminized occupations decreased over time, even though it remained larger than the overall gender wage gap. Male workers continued to take advantage and ride the “glass escalator” in both feminized and non-feminized occupations.

Sampling Importance Resampling Algorithm with Nonignorable Missing Response Variable Based on Smoothed Quantile Regression

The presence of nonignorable missing response variables often leads to complex conditional distribution patterns that cannot be effectively captured through mean regression. In contrast, quantile regression offers valuable insights into the conditional distribution. Consequently, this article places emphasis on the quantile regression approach to address nonrandom missing data. Taking inspiration from fractional imputation, this paper proposes a novel smoothed quantile regression estimation equation based on a sampling importance resampling (SIR) algorithm instead of nonparametric kernel regression methods. Additionally, we present an augmented inverse probability weighting (AIPW) smoothed quantile regression estimation equation to reduce the influence of potential misspecification in a working model. The consistency and asymptotic normality of the empirical likelihood estimators corresponding to the above estimating equations are proven under the assumption of a correctly specified parameter working model. Furthermore, we demonstrate that the AIPW estimation equation converges to an IPW estimation equation when a parameter working model is misspecified, thus illustrating the robustness of the AIPW estimation approach. Through numerical simulations, we examine the finite sample properties of the proposed method when the working models are both correctly specified and misspecified. Furthermore, we apply the proposed method to analyze HIV—CD4 data, thereby exploring variations in treatment effects and the influence of other covariates across different quantiles.

Estimation in optimal treatment regimes based on mean residual lifetimes with right-censored data.

An optimal individualized treatment regime (ITR) is a decision rule in allocating the best treatment to each patient and, hence, maximizing overall benefits. In this paper, we propose a novel framework based on nonparametric inverse probability weighting (IPW) and augmented inverse probability weighting (AIPW) estimators of the value function when the data are subject to right censoring. In contrast to most existing approaches that are designed to maximize the expected survival time under a binary treatment framework, the proposed method targets maximizing the mean residual lifetime of patients. Specifically, the proposed IPW method searches the optimal ITR by maximizing an estimator for the overall population outcome directly, without specifying the regression model for the conditional mean residual lifetime, whereas the AIPW method integrates the model information of the mean residual lifetime to improve the robustness. Furthermore, to overcome the computational difficulty in a nonsmooth value estimator, smoothed IPW and AIPW estimators are constructed. In theory, we establish the asymptotic properties of the proposed method under suitable regularity conditions. The empirical performances of the proposed IPW and AIPW estimators are evaluated using simulation studies and are further illustrated with an application to the real-world data set from the Acquired Immunodeficiency Syndrome Clinical Trial Group Protocol 175 (ACTG175).

An efficient doubly-robust imputation framework for longitudinal dropout, with an application to an Alzheimer’s clinical trial

We develop a novel doubly-robust (DR) imputation framework for longitudinal studies with monotone dropout, motivated by the informative dropout that is common in FDA-regulated trials for Alzheimer's disease. In this approach, the missing data are first imputed using a doubly-robust augmented inverse probability weighting (AIPW) estimator, then the imputed completed data are substituted into a full-data estimating equation, and the estimate is obtained using standard software. The imputed completed data may be inspected and compared to the observed data, and standard model diagnostics are available. The same imputed completed data can be used for several different estimands, such as subgroup analyses in a clinical trial, allowing for reduced computation and increased consistency across analyses. We present two specific DR imputation estimators, AIPW-I and AIPW-S, study their theoretical properties, and investigate their performance by simulation. AIPW-S has substantially reduced computational burden compared to many other DR estimators, at the cost of some loss of efficiency and the requirement of stronger assumptions. Simulation studies support the theoretical properties and good performance of the DR imputation framework. Importantly, we demonstrate their ability to address time-varying covariates, such as a time by treatment interaction. We illustrate using data from a large randomized Phase III trial investigating the effect of donepezil in Alzheimer's disease, from the Alzheimer's Disease Cooperative Study (ADCS) group.

Bias-corrected and doubly robust inference for the three-level longitudinal cluster-randomized trials with missing continuous outcomes and small number of clusters: Simulation study and application to a study for adults with serious mental illnesses

Longitudinal cluster-randomized designs have been popular tools for comparative effective research in clinical trials. The methodologies for the three-level hierarchical design with longitudinal outcomes need to be better understood under more pragmatic settings; that is, with a small number of clusters, heterogeneous cluster sizes, and missing outcomes. Generalized estimating equations (GEEs) have been frequently used when the distribution of data and the correlation model are unknown. Standard GEEs lead to bias and an inflated type I error rate due to the small number of available clinics and non-completely random missing data in longitudinal outcomes. We evaluate the performance of inverse probability weighted (IPW) estimating equations, with and without augmentation, for two types of missing data in continuous outcomes and individual-level treatment allocation mechanisms combined with two bias-corrected variance estimators. Our intensive simulation results suggest that the proposed augmented IPW method with bias-corrected variance estimation successfully prevents the inflation of false positive findings and improves efficiency when the number of clinics is small, with moderate to severe missing outcomes. Our findings are expected to aid researchers in choosing appropriate analysis methods for three-level longitudinal cluster-randomized designs. The proposed approaches were applied to analyze data from a longitudinal cluster-randomized clinical trial involving adults with serious mental illnesses.

Labeling effects of initial juvenile justice system processing decision on youth interpersonal ties*

AbstractThe juvenile justice system can process youth in myriad ways. Youth who are formally processed, relative to being informally processed, may experience more public and harsh sanctions that label youth more negatively as “deviant.” Drawing on labeling theory, the current study evaluates the relative effect of formal justice system processing on the interpersonal dynamics of youth peer networks. Using data from the Crossroads Study, a multisite longitudinal sample of first‐time adolescent offenders, the current study applies augmented inverse probability weighting and generalized mixed‐effects models to estimate the effects of formal processing on friendship selection processes of homophily and withdrawal and considers whether these effects vary by race and ethnicity. Consistent with expectations of homophily, formally processed youth acquire more new deviant peers and fewer nondeviant peers during the 3 years after their initial processing decision compared with informally processed youth. The findings suggest no differences exist across processing types in withdrawal from friends. These effects were consistent across racial and ethnic groups. Ultimately, this study explores the dynamic interpersonal mechanisms associated with labeling theory and offers additional insight into the negative effects of formal processing.

Do patients with prediabetes managed with metformin achieve better glycaemic control? A national study using primary care medical records.

To estimate the effectiveness of metformin on glycaemic parameters among participants with incident prediabetes attending Australian general practices. This retrospective cohort study used electronic health records of regular participants (3+ visits in two consecutive years) attending 383 Australian general practices (MedicineInsight). Participants with 'incident' prediabetes (newly recorded diagnosis between 2012 and 2017) and their glycaemic parameters (haemoglobin A1c [HbA1c] or fasting blood glucose [FBG]) at 6-, 12-, and 18-24 months post diagnosis (unexposed) or post-management with metformin (treatment) were identified from the database. We estimated the average treatment effect (ATE) of metformin management on glycaemic parameters using both linear regression and augmented inverse probability weighting. Of the 4770 investigated participants with 'incident' prediabetes, 10.2% were managed with metformin. Participants on metformin had higher HbA1c levels at the baseline than those unexposed (mean 45 mmol/mol [6.2%] and 41 mmol/mol [5.9%], respectively), but no differences were observed at 6-12 months (mmol/mol ATE 0.0, 95% CI -0.4; 0.7) or 12-18 months (ATE -0.3, 95% CI -1.2; 0.3). However, participants on metformin had lower mean HbA1c mmol/mol at 18-24 months (ATE -1.1, 95% CI -2.0; 0.1) than those unexposed. Consistent results were observed for FBG (ATE at 6-12 months -0.14 [95% CI -0.25; -0.04], 12-18 months 0.02 [95% CI -0.08; 0.13] and 18-24 months -0.07 [95% CI -0.25; 0.12]). The higher HbA1c and FBG baseline levels among participants with 'incident' prediabetes managed with metformin improved after 6-12 months of starting pharmacological management, and the effect persisted for up to 24 months. Management with metformin could prevent further deterioration of glycaemic levels.

Effect of colorectal cancer screening on 1-year mortality and medical costs: Real-world evidence from the largest commercial medical claims database in the US.

10579 Background: Colorectal cancer (CRC) is the third leading cause of cancer-related deaths in the United States with increasing trends in both mortality and incidence in individuals under age 50. Whether CRC screening reduces mortality recently becomes controversial in some observational studies due to a lack of data and a possibility of screenings confounded with social determinants of health (SDoH) and patient characteristics that were not properly addressed. Methods: We used the Optum’s de-identified Clinformatics Data Mart Database that provides information of healthcare plan, major SDoH, the CRC diagnosis, treatments, medical service and prescription charges, and survival data since 2007 for over 75 million patients to re-examine benefits of CRC screenings. Our CRC study cohort (N=99,704) included persons first diagnosed with CRC between 2010 – 2020, with 3-year pre-diagnosis continuing insurance coverage to identify pre-diagnosis screening, and 1-year follow-up to identify death and associated costs. Primary outcomes are 1-year mortality, the post-diagnosis medical and prescription cost increments, and health plan change after CRC diagnosis. Augmented inverse probability weighting (AIPW) models were employed to estimate the benefits of CRC screening, adjusting the probabilities of pre-diagnosis screenings due to insurance cover types (commercial/employer, Medicare advantage, and dual Medicare-Medicaid or low-income subsidy (LIS) covers), and healthcare plans (pre-paid, only-in-network, pay-less in-network, and fee-for-service plans), ages, sex, race, residential states, and calendar year. Results: In the study cohort, 37.8% have pre-diagnosis screening records, 18% died within 1 year. Women, persons under age 45, and persons with dual covers were more present in the non-screening group than the screening one. CRC screening was associated with a significant reduction of one-year mortality after adjusting for age, sex, race, health plans, and other factors (death rates in the non-screening group vs the screening one were 23% vs 12%, adjusted OR = 0.57, 95%CI = 0.55 - 0.59). Persons with no screening records experienced higher one-year medical cost increases than those who had pre-diagnosis screenings (17.8% vs 14.8%). No significant difference in health plan changes and/or disruption among the two groups was obvious for persons having either dual- or commercial-cover beneficiaries, yet the screenings slightly induced more these plan changes in the Medicare advantage beneficiaries (OR = 1.06, 95%CI = 1.01 - 1.11). Conclusions: The real-world evidence from the US largest medical claims database suggested that, after adjusting for the screening probability due to healthcare plans and other confounders, CRC screening dramatically reduced one-year death risk, and slightly eased the 1-year financial burdens after CRC diagnosis.

Can we estimate the causal effects of diet and sedentary behavior on schoolchildren’s overweight/obesity from observational studies?

Aim: To investigate the causal impact of diet and sedentary behavior on Brazilian schoolchildren’s overweight/obesity using the data from observational studies. Methods: Annual cross-sectional nutritional surveys over the 2013–2015 period, with 26,712 children old 7–12 years in Florianópolis, Brazil, provided the data for this analysis. The surveys applied an online previous-day recall questionnaire on food intake and physical/sedentary activities. Outcome measures were overweight/obesity, whereas exposure variables were daily frequencies of consuming sugary drinks and ultra-processed foods, the total number of dietary items consumed and the total number of sedentary activities per day, and consuming breakfast, mid-morning snacks, lunch, afternoon snack, dinner, and evening snack. Control variables included child age, sex, family income, school shift, survey year, day of the week the questionnaire refers to, metabolic equivalents (METs) of physical activities (PAs), and the quality of dietary and PA reports. Causal effects were estimated by augmented inverse probability weighting. Results: Daily consumption of sugary drinks, eating ten or more foods, and engaging in three or more sedentary behaviors per day significantly increased the odds ratios (ORs) of being overweight/obese in the range of 3–24% compared to the reference, with 95% confidence intervals in the range of 1–32%. Among 19 ORs with P-value ≤ 0.05, only 3 exceeded 10%. Conclusions: Under certain conditions, not uncommon in large-scale monitoring and surveillance studies, it is possible to evaluate the causal effects of diet and sedentary activities on overweight/obesity. Daily consumption of sugar-sweetened beverages, eating ten or more foods, skipping breakfast, and engaging in three or more sedentary behaviors per day significantly increased the odds of being overweight/obese.

Impactof long-term management with sleep medications on blood pressure: An Australian national study.

There is mixed evidence about the impact of long-term management with hypnotic medications on blood pressure (BP). To estimate the effect of short- and long-term management with benzodiazepine and z-drugs (BZD) on BP. Open cohort study using deidentified electronic health records of 523,486 adult regular patients (42.3% males; mean age 59.0±17.0 years) annually attending 402 Australian general practices between 2016 to 2018 (MedicineInsight database). Average treatment effects (ATE) of recorded incident BZD prescriptions in 2017 on systolic (SBP) and diastolic (DBP) BP after starting these prescriptions were computed using augmented inverse probability weighting (AIPW). In 2017, 16,623 new cases of short-term management with BZD and 2532 cases of long-term management with BZD were identified (incidence 3.2% and 0.5%, respectively). The mean BP among those not treated with BZD (reference group) was 130.9/77.3mmHg. Patients prescribed short-term BZD showed a slightly higher SBP (ATE 0.4; 95% CI 0.1, 0.7) and DBP (ATE 0.5; 95% CI 0.3, 0.7), while those on long-term BZD prescriptions showed lower SBP (ATE -1.1; 95% CI -2.0, -0.2), but no effect on DBP (ATE -0.1; 95% CI -0.8, 0.5). However, long-term BZD prescriptions showed a stronger BP-lowering effect among patients aged 65+ years (SBP ATE -2.5 [95% CI -3.8, -1.3]; DBP ATE -1.0 [95% CI -1.7, -0.2]), but almost no effect was observed among younger patients. Long-term management with BZD had a BP-lowering effect among older patients. These findings add new evidence to current recommendations on limiting long-term BZD management in the elderly.

Non-Asymptotic Bounds of AIPW Estimators for Means with Missingness at Random

The augmented inverse probability weighting is well known for its double robustness in missing data and causal inference. If either the propensity score model or the outcome regression model is correctly specified, the estimator is guaranteed to be consistent. Another important property of the augmented inverse probability weighting is that it can achieve first-order equivalence to the oracle estimator in which all nuisance parameters are known, even if the fitted models do not converge at the parametric root-n rate. We explore the non-asymptotic properties of the augmented inverse probability weighting estimator to infer the population mean with missingness at random. We also consider inferences of the mean outcomes on the observed group and on the unobserved group.

Vein Graft Use and Long-Term Survival Following Coronary Bypass Grafting

BackgroundAlthough placement of at least 1 arterial graft during coronary artery bypass grafting (CABG) has a proven survival benefit, it is unknown what degree of revascularization with saphenous vein grafting (SVG) is associated with improved survival. ObjectivesThe authors sought to determine whether undergoing surgery performed by a surgeon who is liberal with vein graft utilization is associated with improved survival in patients undergoing single arterial graft CABG (SAG-CABG). MethodsThis was a retrospective, observational study of SAG-CABG performed in Medicare beneficiaries from 2001 to 2015. Surgeons were stratified by number of SVG utilized per SAG-CABG into conservative (≥1 SD below mean), average (within 1 SD of mean), and liberal (≥1 SD above mean). Long-term survival was estimated using Kaplan-Meier analysis and compared among surgeon groups before and after augmented inverse-probability weighting. ResultsThere were 1,028,264 Medicare beneficiaries undergoing SAG-CABG from 2001 to 2015 (mean age 72.0 ± 7.9 years, 68.3% male). Over time, 1-vein and 2-vein SAG-CABG utilization increased, whereas 3-vein and ≥4-vein SAG-CABG utilization decreased (P < 0.001). Surgeons who were conservative vein graft users performed a mean 1.7 ± 0.2 vein grafts per SAG-CABG, whereas those who were liberal vein graft users performed a mean 2.9 ± 0.2 vein grafts per SAG-CABG. Weighted analysis demonstrated no difference in median survival among patients undergoing SAG-CABG by liberal vs conservative vein graft users (adjusted median survival difference 27 days). ConclusionsAmong Medicare beneficiaries undergoing SAG-CABG, there is no association between surgeon proclivity for vein graft utilization and long-term survival, suggesting that a conservative approach to vein graft utilization is reasonable.

The Combination of Daptomycin with Fosfomycin is More Effective than Daptomycin Alone in Reducing Mortality of Vancomycin-Resistant Enterococcal Bloodstream Infections: A Retrospective, Comparative Cohort Study.

High-dose daptomycin-based combinations are recommended for vancomycin-resistant Enterococcus (VRE) bloodstream infection (BSI). Preclinical data have shown a synergistic effect of daptomycin/fosfomycin combinations against VRE. However, clinical studies comparing daptomycin monotherapy with daptomycin/fosfomycin combinations are unavailable. An observational study of VRE-BSI was performed between 2010-2021 on patients receiving daptomycin monotherapy (≥ 8mg/kg) or daptomycin combined with intravenous fosfomycin. Patients treated with concomitant β-lactam combinations were excluded. The primary outcome was in-hospital mortality. Outcomes were analyzed using multivariable logistic regression and augmented inverse probability weighting (AIPW) analyses. Among 224 patients, 176 received daptomycin monotherapy, and 48 received fosfomycin combinations. The median daptomycin and fosfomycin doses were 9.8mg/kg and 12g/day, respectively. In-hospital mortality was 77.3% and 47.9% in the daptomycin monotherapy and fosfomycin combination groups (P < 0.001), respectively. Multivariable logistic regression analysis predicted lower mortality with fosfomycin combination treatment (adjusted odds ratio, 0.35; 95% confidence interval (CI), 0.17-0.73; P = 0.005). AIPW demonstrated a 17.8% reduced mortality with fosfomycin combinations (95% CI, - 30.6- - 4.9%; P = 0.007). The survival benefit was significant, especially among patients with a lower Pitt bacteremia score or fosfomycin minimum inhibitory concentration (MIC) ≤ 64mg/l. Fosfomycin combination resulted in higher hypernatremia (10.4% vs. 2.8%, P = 0.04) and hypokalemia (33.3% vs. 15.3%, P = 0.009) compared to daptomycin monotherapy. The combination of high-dose daptomycin with fosfomycin improved the survival rate of patients with VRE-BSI compared to daptomycin alone. The benefit of the combination was most pronounced for VRE with fosfomycin MIC ≤ 64mg/l and for patients with a low Pitt bacteremia score.

Addressing Disparities in the Propensity Score Distributions for Treatment Comparisons from Observational Studies

Propensity score (PS) based methods, such as matching, stratification, regression adjustment, simple and augmented inverse probability weighting, are popular for controlling for observed confounders in observational studies of causal effects. More recently, we proposed penalized spline of propensity prediction (PENCOMP), which multiply-imputes outcomes for unassigned treatments using a regression model that includes a penalized spline of the estimated selection probability and other covariates. For PS methods to work reliably, there should be sufficient overlap in the propensity score distributions between treatment groups. Limited overlap can result in fewer subjects being matched or in extreme weights causing numerical instability and bias in causal estimation. The problem of limited overlap suggests (a) defining alternative estimands that restrict inferences to subpopulations where all treatments have the potential to be assigned, and (b) excluding or down-weighting sample cases where the propensity to receive one of the compared treatments is close to zero. We compared PENCOMP and other PS methods for estimation of alternative causal estimands when limited overlap occurs. Simulations suggest that, when there are extreme weights, PENCOMP tends to outperform the weighted estimators for ATE and performs similarly to the weighted estimators for alternative estimands. We illustrate PENCOMP in two applications: the effect of antiretroviral treatments on CD4 counts using the Multicenter AIDS cohort study (MACS) and whether right heart catheterization (RHC) is a beneficial treatment in treating critically ill patients.

Impact of a heart failure nurse practitioner service on rehospitalizations, emergency presentations, and survival in patients hospitalized with acute heart failure.

Heart failure nurse practitioners (HF NPs) are an emerging component of the heart failure (HF) specialist workforce but their impact in an inpatient setting is untested. The aim of this paper is to explore the impact of an inpatient HF NP service on 12-month all-cause rehospitalizations, emergency department (ED) presentations, and mortality in patients hospitalized with HF compared with usual hospital care. Retrospective, two-group comparative design involving patients (n = 408) admitted via ED with acute HF to a metropolitan quaternary hospital between January 2013 and August 2017. Doubly robust estimation with augmented inverse probability weighting (DR-AIPW) was used to account for the non-random allocation of patients to usual hospital care or the HF NP service in addition to usual in-hospital care. Among 408 patients (186 usual care and 222 HF NP service) admitted with acute HF, the mean age was 76.5 [standard deviation (SD) 12.0] years and 56.4% (n = 230) were male. After IPW adjustment, patients seen by the HF NP service had a lower risk of 12-month rehospitalization (61.3 vs. 78.3% usual care; difference -16.9%, 95% CI: -26.4%, -6.6%) and ED presentations (12.6 vs. 22.0%; difference -9.4%, 95% CI: -17.3%, -1.4%) with no difference in 6- or 12-month mortality. The HF NP service improved referrals to a home visiting programme that was available to HF patients (64.4 vs. 45.4%; difference 19%, 95% CI: 8.8%, 28.8%). Additional support by an inpatient HF NP service has the potential to significantly reduce rehospitalizations and ED presentations over 12 months. Further evidence from a multicentre randomized control trial is warranted.