Triple challenges - Small sample size in both exposure and control groups to scan rare maternal outcomes in a signal identification approach: A simulation study.

There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS' ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with "true" expected incidence proportions and compared these to imprecise incidence proportions derived from sparse control samples. We varied parameters impacting Type I error and statistical power (exposure group size, outcome's incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of Type I error, and removal of very rare outcomes for TBSS analysis due to "zero" background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts.

Layering and capillary waves in the structure factor of liquid surfaces.

Within the extended Capillary Wave Theory (ECWT), to extract the bending modulus of a liquid surface from the total structure factor of the interfacial region requires to separate the capillary waves (CW) signal from a non-CW background. Some years ago, Höfling and Dietrich (HD), working in the strict grazing incidence limit qz = 0, proposed a background that combines the liquid and vapor bulk structure factors in the amounts set by Gibbs's plane. We contrast that proposal with Molecular Dynamics (MD) simulations of the Lennard-Jones model analyzed with the Intrinsic Sampling Method (ISM). The study is extended to qz ≠ 0, to test the stronger consistency requirements of the ECWT and the experimental conditions; it shows a good MD-ECWT matching although we need some fine tuning over HD proposal. Then, the agreement with the ISM result for the surface bending modulus is good and that provides an interpretation, in terms of the molecular layering at the liquid edge, for the fluctuating surface represented by the CW signal in the surface structure factor, both for MD simulations and surface diffraction experiments.

Tip Charge Dependence of Three-Dimensional AFM Mapping of Concentrated Ionic Solutions.

A molecular scale understanding of the organization and structure of a liquid near a solid surface is currently a major challenge in surface science. It has implications across different fields from electrochemistry and energy storage to molecular biology. Three-dimensional AFM generates atomically resolved maps of solid-liquid interfaces. The imaging mechanism behind those maps is under debate, in particular, for concentrated ionic solutions. Theory predicts that the observed contrast should depend on the tip's charged state. Here, by using neutrally, negatively, and positively charged tips, we demonstrate that the 3D maps depend on the tip's polarization. A neutral tip will explore the total particle density distribution (water and ions) while a charged tip will reveal the charge density distribution. The experimental data reproduce the key findings of the theory.

Travel to Mexico and uropathogen-antibiotic susceptibility mismatch in the emergency department.

INTRODUCTION: International travel results in an increased risk of colonization and infection with multidrug-resistant organisms. This study aimed to determine if recent travel to Mexico affects the rate of uropathogen-antibiotic susceptibility mismatch (UASM) in outpatients treated for urinary tract infection (UTI) in a South Texas emergency department (ED). METHODS: A retrospective cohort of adult patients presenting to the ED and treated outpatient for UTI from October 1, 2014, to February 25, 2020, was conducted at a community hospital located within approximately 15 miles of the United States-Mexico border. Rates of UASM were compared between patients with a history of recent travel to Mexico and those who have not recently traveled. RESULTS: A total of 192 patients were included, with 64 in the travel to Mexico group and 128 in the no travel group. UASM was significantly higher in the recent travel to Mexico group when compared to the no travel group (RR 1.49, 95% CI 1.03-2.13). Antibiotics most commonly associated with UASM included fluoroquinolones, cephalexin, and sulfamethoxazole-trimethoprim. There was no significant difference between the rates of resistance to first-line agents for the treatment of UTI among the two groups. CONCLUSION: In addition to known antibiotic resistance risk factors, recent travel to Mexico may increase the risk of UASM for ED patients with UTI. Considering the potential consequences of UTI treatment failure, antimicrobial stewardship services in the ED should include screening for antibiotic resistance risk factors and urine culture follow-up to ensure appropriate outpatient antibiotic therapy, especially among patients with recent international travel.

Density functional analysis of atomic force microscopy in a dense fluid.

We present a density functional (DF) analysis for the entropic force in Atomic Force Microscopy (AFM) across the layers of a dense fluid. Previous theoretical analysis, based on the ideal gas entropy, was apparently supported by the similarity in the oscillatory decay for the force and density profile. We point out that such similarity is a generic DF result, which carries no information on the interface, since the decaying mode is characteristic of the bulk fluid correlation. The truly interfacial information, from the layering measured by AFM, comes in its amplitude and not in the decay mode. With our rigorous study of a simple hard sphere model, we find semiempirical clues to disentangle the role of the tip radius and to relate the amplitude of the molecular layering to the oscillatory force on the AFM tip.

Knowledge and beliefs, behaviors, and adherence among Latino parents or legal guardians related to antibiotic use for upper respiratory tract infections in children under 6 years of age.

OBJECTIVE: Evaluate parents or legal guardians' knowledge and beliefs, behaviors, and adherence regarding antibiotic use for upper respiratory tract infection (URTI) in their children who are younger than 6 years. DESIGN: A cross-sectional study from September 2016 to February 2017. SETTING: Emergency department with a pediatric unit. PARTICIPANTS: One hundred and one parents or legal guardians who visited one of the selected emergency departments during the study period. INTERVENTION: Administration of a validated questionnaire to assess knowledge and beliefs, behaviors, and adherence regarding antibiotic use for URTI. MAIN OUTCOME MEASURES: Knowledge and beliefs, behaviors, and adherence regarding antibiotic use for URTI. RESULTS: Items with the least desired scores were seen in the "knowledge and beliefs" domain. Higher number of antibiotics used for URTI during the last year (P < 0.01) and lower education level (P = 0.03) were associated with least desired knowledge and beliefs scores. The "behaviors" domain contained the items with the best scores: higher education level (P = 0.05), fewer antibiotics used for URTI during the last year (P = 0.05), and older age (P = 0.02) were the only variables associated with better behaviors. For the "adherence" domain, lower education level (P < 0.01) was associated with poor indicators of adherence. The Cronbach alpha for the "knowledge and beliefs" items was 0.875, the "behaviors" items 0.569, and the "adherence" items 0.798. CONCLUSION: Findings of our study support the need for proper antibiotic education among parents, especially in those with an increased risk of antibiotic misuse and overuse. Pharmacists and physicians need to establish a dialogue with parents or legal guardians to discuss how antibiotics work, what types of infection they treat, and how to prevent antibiotic resistance. Sociodemographic variables can be used to identify at-risk groups and to develop successful interventions.

A MOF@COF Composite with Enhanced Uptake through Interfacial Pore Generation.

Herein, we describe a new class of porous composites comprising metal-organic framework (MOF) crystals confined in single spherical matrices made of packed covalent-organic framework (COF) nanocrystals. These MOF@COF composites are synthesized through a two-step method of spray-drying and subsequent amorphous (imine-based polymer)-to-crystalline (imine-based COF) transformation. This transformation around the MOF crystals generates micro- and mesopores at the MOF/COF interface that provide far superior porosity compared to that of the constituent MOF and COF components added together. We report that water sorption in these new pores occurs within the same pressure window as in the COF pores. Our new MOF@COF composites, with their additional pores at the MOF/COF interface, should have implications for the development of new composites.

Capillary waves as eigenmodes of the density correlation at liquid surfaces.

We analyze the density correlations in a liquid-vapor surface to establish a quantitative connection between the Density Functional (DF) formalism, Molecular Dynamic (MD) simulations, and the Capillary Wave (CW) theory. Instead of the integrated structure factor, we identify the CW fluctuations as eigenmodes of the correlation function. The square-gradient DF approximation appears as fully consistent with the use of the thermodynamic surface tension to describe the surface fluctuations for any wavevector because it misses the upper cutoff in the surface Hamiltonian from the merging of the CW mode with the non-CW band. This mesoscopic cutoff may be accurately predicted from the main peak in the structure factor of the bulk liquid. We explore the difference between the full density-density correlation mode and the bare CW that represents the correlation between the corrugation of the intrinsic surface and the density at the interfacial region. The non-local decay of the CW effects, predicted from DF analysis and observed in MD simulations with the intrinsic sampling method, is found to characterize the bare CW fluctuations, which also require a wavevector-dependent surface tension.

Density correlation in liquid surfaces: Bedeaux-Weeks high order terms and non capillary wave background.

We present Molecular Dynamics (MD) simulations of liquid-vapor surfaces, and their Intrinsic Sampling Method analysis, to get a quantitative test for the theoretical prediction of the capillary wave (CW) effects on density correlation done by Bedeaux and Weeks (BW) in 1985. The results are contrasted with Wertheim's proposal which is the first term in BW series and are complemented with a (formally defined and computational accessible) proposal for the background of non-CW fluctuations. Our conclusion is that BW theory is both accurate and needed since it may differ significantly from Wertheim's proposal. We discuss the implications for the analysis of experimental X-ray surface diffraction data and MD simulations.

Knowledge and Perceptions of E-cigarettes and the Motivations for their Use: Talking to Smokers (E-cigarettes and/or Conventional Cigarettes) and Non-smokers in Puerto Rico.

OBJECTIVE: The awareness and use of e-cigarettes have been increasing in recent years. The World Health Organization recently reported that regulations are needed to impede the promotion of e-cigarettes to young people, prohibit unproven health claims about them (including those regarding smoking-cessation efficacy), minimize potential health risks to e-cigarette users and non-users, and protect existing tobacco controls. The study described herein explored e-cigarette knowledge, perceptions, and usage motivations among a group of adults in Puerto Rico. METHODS: This research study used a validated questionnaire with closed-ended questions to gather data. Non-inferential and inferential statistics were used to characterize smokers (of e-cigarettes, of conventional cigarettes, and of both) and non-smokers. RESULTS: A total of 415 respondents took part; they were evenly distributed by gender, age, and socioeconomic status; all were residents of Puerto Rico at the time of the survey. The overall awareness of e-cigarettes was high, but knowledge of nicotine content and regulations was limited. Asked whether e-cigarettes contain nicotine (they do not), approximately two thirds stated either that they do or that they didn't know; asked whether e-cigarettes are regulated as a tobacco product (they are in Puerto Rico), 84% stated either that they are not or that they didn't know. Common perceptions of e-cigarettes are that they are harmful to health and that they are no less harmful than cigarettes are. However, a significant portion of the respondents perceived e-cigarettes to be less addictive than conventional cigarettes are. Overall, the respondents were divided on the efficacy of e-cigarettes for smoking cessation. Nonetheless, the most common motivation for their use, according to both current users and potential future users, is to aid in smoking cessation or reduction. CONCLUSION: The majority of individuals surveyed were aware of e-cigarettes but had limited knowledge of their contents or regulation. As an aid in smoking cessation was the most commonly mentioned motivation for e-cigarette use.

Prevalence of Concurrent Prescribing of ACE-Is and ARBs among Beneficiaries of Puerto Rico's Government-Sponsored Health Care Plan During 2012 and 2013.

OBJECTIVE: Cardiovascular conditions are the second cause of death in Puerto Rico. The individual use of angiotensin-converting enzyme inhibitors (ACE-Is) or angiotensin receptor blockers (ARBs) is considered the first-line therapy for the treatment of several cardiovascular-related medical conditions. However, the concurrent use of these 2 therapeutic classes of drugs is not supported by treatment guidelines. Studies have shown that their concurrent use represents a potential health risk. The research described in this paper aimed to determine the prevalence of the concurrent prescription of ACE-Is and ARBs, either separately or as a combination product, in a group of beneficiaries of the Puerto Rico Health Services Administration (ASES, by its initials in Spanish). METHODS: A 2-year cross sectional study was conducted. All pharmacy claims from the years 2012 and 2013 were provided by ASES and subsequently evaluated by the investigators to identify those involving the prescription of an ACE-I, an ARB, or a combination of drugs belonging to both therapeutic classes. Each pharmacy claim was complemented with sociodemographic and clinical data. The final dataset was analyzed at the person-month level using frequency, cumulative frequency, percentage, and cumulative percentage. RESULTS: The final sample consisted of 361,841 beneficiaries. A total of 23,598 beneficiaries were excluded because of incomplete diagnostic information. Of the beneficiaries with complete information, 36,202 out of 338,243 (10.7%) had concurrent prescriptions for ACE-Is and ARBs during the study period. We excluded 1,124 beneficiaries who had a primary diagnosis of HF, resulting in a final pool of 35,078 beneficiaries (10.4%) who had prescriptions for combination products. CONCLUSION: An unacceptable pattern of ACE-I and ARB co-prescribing during the years 2012 and 2013 was observed in patients with diagnoses for which the combination is not clinically indicated.

Cost-Utility Study of Warfarin Genotyping in the VACHS Affiliated Anticoagulation Clinic of Puerto Rico.

OBJECTIVE: To evaluate the cost-utility of the pharmacogenetic-guided dosing of warfarin (PGx), when compared to the current dosing strategy. METHODS: A Markov model was developed to assess the impact of the genotypingguided warfarin dosing in a hypothetical cohort of patients. The model was based on the percentage of time patients spent within the therapeutic international normalized ratio (INR) range (PTTR). PTTR estimates and genotype distribution were derived from a cohort of patients (n = 206) treated in the Veteran Affairs Caribbean Healthcare System (VACHS) and from results of other research study. Costs, utilities and event probability data were obtained from the literature. Probabilistic and one-way sensitivity analyses were performed to explore the range of plausible results. Willingness to pay was established at $50,000 per Quality Adjusted Life Year (QALY) gained. RESULTS: According to our model, the PGx strategy showed a QALY increase of 0.0021, with an increase in total cost of $272. This corresponds to an incremental cost-utility ratio (ICUR) of $127,501, ranging from $95,690 to $148,611. One-way sensitivity analysis revealed that the ICURs were more sensitive to the cost of genotyping and the effect of genotyping on the PTTR. CONCLUSION: Our model suggests that the warfarin PGx was not superior to the standard of care dosing strategy in terms of cost-utility.

smdi: an R package to perform structural missing data investigations on partially observed confounders in real-world evidence studies.

Objectives: Partially observed confounder data pose a major challenge in statistical analyses aimed to inform causal inference using electronic health records (EHRs). While analytic approaches such as imputation are available, assumptions on underlying missingness patterns and mechanisms must be verified. We aimed to develop a toolkit to streamline missing data diagnostics to guide choice of analytic approaches based on meeting necessary assumptions. Materials and methods: We developed the smdi (structural missing data investigations) R package based on results of a previous simulation study which considered structural assumptions of common missing data mechanisms in EHR. Results: smdi enables users to run principled missing data investigations on partially observed confounders and implement functions to visualize, describe, and infer potential missingness patterns and mechanisms based on observed data. Conclusions: The smdi R package is freely available on CRAN and can provide valuable insights into underlying missingness patterns and mechanisms and thereby help improve the robustness of real-world evidence studies.

A Principled Approach to Characterize and Analyze Partially Observed Confounder Data from Electronic Health Records.

Objective: Partially observed confounder data pose challenges to the statistical analysis of electronic health records (EHR) and systematic assessments of potentially underlying missingness mechanisms are lacking. We aimed to provide a principled approach to empirically characterize missing data processes and investigate performance of analytic methods. Methods: Three empirical sub-cohorts of diabetic SGLT2 or DPP4-inhibitor initiators with complete information on HbA1c, BMI and smoking as confounders of interest (COI) formed the basis of data simulation under a plasmode framework. A true null treatment effect, including the COI in the outcome generation model, and four missingness mechanisms for the COI were simulated: completely at random (MCAR), at random (MAR), and two not at random (MNAR) mechanisms, where missingness was dependent on an unmeasured confounder and on the value of the COI itself. We evaluated the ability of three groups of diagnostics to differentiate between mechanisms: 1)-differences in characteristics between patients with or without the observed COI (using averaged standardized mean differences [ASMD]), 2)-predictive ability of the missingness indicator based on observed covariates, and 3)-association of the missingness indicator with the outcome. We then compared analytic methods including "complete case", inverse probability weighting, single and multiple imputation in their ability to recover true treatment effects. Results: The diagnostics successfully identified characteristic patterns of simulated missingness mechanisms. For MAR, but not MCAR, the patient characteristics showed substantial differences (median ASMD 0.20 vs 0.05) and consequently, discrimination of the prediction models for missingness was also higher (0.59 vs 0.50). For MNAR, but not MAR or MCAR, missingness was significantly associated with the outcome even in models adjusting for other observed covariates. Comparing analytic methods, multiple imputation using a random forest algorithm resulted in the lowest root-mean-squared-error. Conclusion: Principled diagnostics provided reliable insights into missingness mechanisms. When assumptions allow, multiple imputation with nonparametric models could help reduce bias.

Use of the Sentinel System to Examine Medical Product Use and Outcomes During Pregnancy.

While many pregnant individuals use prescription medications, evidence supporting product safety during pregnancy is often inadequate. Existing electronic healthcare data sources provide large, diverse samples of health plan members to allow for the study of medical product utilization during pregnancy, as well as pregnancy, maternal, and infant outcomes. The Sentinel System is a national medical product surveillance system that includes administrative claims and electronic health record databases from large national and regional health insurers. In addition to these data sources, Sentinel develops and maintains a sizeable selection of analytic tools to facilitate epidemiologic analyses in a way that protects patient privacy and health system autonomy. In this article, we provide an overview of Sentinel System infrastructure, including the Mother-Infant Linkage Table, parameterizable analytic tools, and algorithms to estimate gestational age and identify pregnancy outcomes. We also describe past and future Sentinel work that contributes to our understanding of the way medical products are used and the safety of these products during pregnancy.

Risk of Arterial and Venous Thrombotic Events Among Patients with COVID-19: A Multi-National Collaboration of Regulatory Agencies from Canada, Europe, and United States.

Purpose: Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability. Patients and Methods: We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE. Results: The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US. Conclusion: There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability.

Improving data capture of race and ethnicity for the Food and Drug Administration Sentinel database: a narrative review.

PURPOSE: The U.S. Food and Drug Administration's Sentinel System is a national medical product safety surveillance system consisting of a large multisite distributed database of administrative claims supplemented by electronic health-care record data. The program seeks to improve data capture of race and ethnicity for pharmacoepidemiology studies. METHODS: We conducted a narrative literature review of published research on data augmentation and imputation methods to improve race and ethnicity capture in U.S. health-care systems databases. We focused on methods with limited (five-digit ZIP codes only) or full patient identifiers available to link to external sources of self-reported data. We organized the literature by themes: (1) variation in data capture of self-reported data, (2) data augmentation from external sources of self-reported data, and (3) imputation methods, including Bayesian analysis and multiple regression. RESULTS: Researchers reduced data missingness with high validity for Asian, Black, White, and Pacific Islander racial groups and Hispanic ethnicity. Native American and multiracial groups were difficult to validate due to relatively small sample sizes. CONCLUSIONS: Limitations on accessible self-reported data for validation will dictate methods to improve race and ethnicity data capture. We recommend methods leveraging multiple sources that account for variations in geography, age, and sex.

Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.

INTRODUCTION: Pharmacovigilance programs protect patient health and safety by identifying adverse event signals through postmarketing surveillance of claims data and spontaneous reports. Electronic health records (EHRs) provide new opportunities to address limitations of traditional approaches and promote discovery-oriented pharmacovigilance. METHODS: To evaluate the current state of EHR-based medication safety signal identification, we conducted a scoping literature review of studies aimed at identifying safety signals from routinely collected patient-level EHR data. We extracted information on study design, EHR data elements utilized, analytic methods employed, drugs and outcomes evaluated, and key statistical and data analysis choices. RESULTS: We identified 81 eligible studies. Disproportionality methods were the predominant analytic approach, followed by data mining and regression. Variability in study design makes direct comparisons difficult. Studies varied widely in terms of data, confounding adjustment, and statistical considerations. CONCLUSION: Despite broad interest in utilizing EHRs for safety signal identification, current efforts fail to leverage the full breadth and depth of available data or to rigorously control for confounding. The development of best practices and application of common data models would promote the expansion of EHR-based pharmacovigilance.

Perceived value of self-monitoring blood glucose by primary care physicians and endocrinologists.

The value of self-monitoring blood glucose (SMBG) in patients with non-insulin-treated type 2 diabetes (NITT2DM) has been debated; however, the practice remains common. Patient perception of SMBG has been documented in several qualitative studies. However, the literature is lacking on the perceived value of SMBG by providers. This study used a structured questionnaire to evaluate and compare the perceived value, recommended frequency, and utility of SMBG in patients with NITT2DM by primary care providers (PCPs) and endocrinologists. A total of 70 PCPs and 14 endocrinologists completed the questionnaire. The results suggest that PCPs and endocrinologists find the practice of SMBG valuable in NITT2DM and believe it promotes behavioral changes in their patients. However, endocrinologists tend to recommend more frequent SMBG and find SMBG values more useful in making medication decisions. Conversely, PCPs tend to find the hemoglobin A1c more valuable than SMBG in making medication adjustments.

Bending Modulus of Lipid Membranes from Density Correlation Functions.

The bending modulus κ quantifies the elasticity of biological membranes in terms of the free energy cost of increasing the membrane corrugation. Molecular dynamics (MD) simulations provide a powerful approach to quantify κ by analyzing the thermal fluctuations of the lipid bilayer. However, existing methods require the identification and filtering of non-mesoscopic fluctuation modes. State of the art methods rely on identifying a smooth surface to describe the membrane shape. These methods introduce uncertainties in calculating κ since they rely on different criteria to select the relevant fluctuation modes. Here, we present a method to compute κ using molecular simulations. Our approach circumvents the need to define a mesoscopic surface or an orientation field for the lipid tails explicitly. The bending and tilt moduli can be extracted from the analysis of the density correlation function (DCF). The method introduced here builds on the Bedeaux and Weeks (BW) theory for the DCF of fluctuating interfaces and on the coupled undulatory (CU) mode introduced by us in previous work. We test the BW-DCF method by computing the elastic properties of lipid membranes with different system sizes (from 500 to 6000 lipid molecules) and using coarse-grained (for POPC and DPPC lipids) and fully atomistic models (for DPPC). Further, we quantify the impact of cholesterol on the bending modulus of DPPC bilayers. We compare our results with bending moduli obtained with X-ray diffraction data and different computer simulation methods.