Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19.

Methodological biases are common in observational studies evaluating treatment effectiveness. The objective of this study is to emulate a target trial in a competing risks setting using hospital-based observational data. We extend established methodology accounting for immortal time bias and time-fixed confounding biases to a setting where no survival information beyond hospital discharge is available: a condition common to coronavirus disease 2019 (COVID-19) research data.

The population-attributable fraction for time-to-event data.

Background: Even though the population-attributable fraction (PAF) is a well-established metric, it is often incorrectly estimated or interpreted not only in clinical application, but also in statistical research articles. The risk of bias is especially high in more complex time-to-event data settings.

Methods: We explain how the PAF can be defined, identified and estimated in time-to-event settings with competing risks and time-dependent exposures.

Impact of adherence to individual quality-of-care indicators on the prognosis of bloodstream infection due to Staphylococcus aureus: a prospective observational multicentre cohort.

Objectives: To analyse the adherence and impact of quality-of-care indicators (QCIs) in the management of Staphylococcus aureus bloodstream infection in a prospective and multicentre cohort.

Methods: Analysis of the prospective, multicentre international S. Aureus Collaboration cohort of S.

Inverse Probability Weighting Enhances Absolute Risk Estimation in Three Common Study Designs of Nosocomial Infections.

Purpose: When studying nosocomial infections, resource-efficient sampling designs such as nested case-control, case-cohort, and point prevalence studies are preferred. However, standard analyses of these study designs can introduce selection bias, especially when interested in absolute rates and risks. Moreover, nosocomial infection studies are often subject to competing risks.

Translation and Psychometric Evaluation of the German Version of the Thirst Distress Scale for Patients With Heart Failure.

Background: In patients with chronic heart failure, thirst can be perceived as an intensive and burdensome symptom, which may have a negative impact on patients' quality of life. To initiate thirst-relieving interventions, assessment of thirst and its related distress is essential. At the time of this study, no instrument was available to evaluate thirst distress in patients with heart failure in Germany.

Association of osteopontin with kidney function and kidney failure in chronic kidney disease patients: the GCKD study.

Background: Osteopontin (OPN), synthesized in the thick ascending limb of Henle's loop and in the distal tubule, is involved in the pathogenesis of kidney fibrosis, a hallmark of kidney failure (KF). In a cohort of chronic kidney disease (CKD) patients, we evaluated OPN's association with kidney markers and KF.

Methods: OPN was measured from baseline serum samples of German Chronic Kidney Disease study participants.

Quantifying and communicating the burden of COVID-19.

Background: An essential aspect of preventing further COVID-19 outbreaks and to learn for future pandemics is the evaluation of different political strategies, which aim at reducing transmission of and mortality due to COVID-19. One important aspect in this context is the comparison of attributable mortality.

Methods: We give a comprehensive overview of six epidemiological measures that are used to quantify COVID-19 attributable mortality (p-score, standardized mortality ratio, absolute number of excess deaths, per capita rate, z-score and the population attributable fraction).

Predicting Potential Prevention Effects on Hospital Burden of Nosocomial Infections: A Multistate Modeling Approach.

Objectives: Hospital-acquired infections (HAIs) place a substantial burden on health systems. Tools are required to quantify the change in this burden as a result of a preventive intervention. We aim to estimate how much a reduction in the rate of hospital-acquired infections translates into a change in hospital mortality and length of stay.

Self-management for patients on ventricular assist device support: a national, multicentre study: protocol for a 3-phase study.

Introduction: Self-management (SM) may facilitate patient participation and involvement to become active and knowledgeable partners in the care of complex chronic conditions such as ventricular assist device (VAD) therapy. The 'SM model for patients on VAD support' will serve to distinguish between SM components, and will guide the development, implementation and evaluation of an evidence-based curriculum.

Methods And Analysis: This is a 3-phase, multicentre study.

Methodological evaluation of bias in observational coronavirus disease 2019 studies on drug effectiveness.

Background And Objective: Observational studies may provide valuable evidence on real-world causal effects of drug effectiveness in patients with coronavirus disease 2019 (COVID-19). As patients are usually observed from hospital admission to discharge and drug initiation starts during hospitalization, advanced statistical methods are needed to account for time-dependent drug exposure, confounding and competing events. Our objective is to evaluate the observational studies on the three common methodological pitfalls in time-to-event analyses: immortal time bias, confounding bias and competing risk bias.

COVID-19 in-hospital mortality and mode of death in a dynamic and non-restricted tertiary care model in Germany.

Background: Reported mortality of hospitalised Coronavirus Disease-2019 (COVID-19) patients varies substantially, particularly in critically ill patients. So far COVID-19 in-hospital mortality and modes of death under state of the art care have not been systematically studied.

Methods: This retrospective observational monocenter cohort study was performed after implementation of a non-restricted, dynamic tertiary care model at the University Medical Center Freiburg, an experienced acute respiratory distress syndrome (ARDS) and extracorporeal membrane-oxygenation (ECMO) referral center.

Harmonizing Heterogeneous Endpoints in Coronavirus Disease 2019 Trials Without Loss of Information.

Objectives: Many trials investigate potential effects of treatments for coronavirus disease 2019. To provide sufficient information for all involveddecision-makers (clinicians, public health authorities, and drug regulatory agencies), a multiplicity of endpoints must be considered. The objectives are to provide hands-on statistical guidelines for harmonizing heterogeneous endpoints in coronavirus disease 2019 clinical trials.

Statistical Analysis of Clinical COVID-19 Data: A Concise Overview of Lessons Learned, Common Errors and How to Avoid Them.

By definition, in-hospital patient data are restricted to the time between hospital admission and discharge (alive or dead). For hospitalised cases of COVID-19, a number of events during hospitalization are of interest regarding the influence of risk factors on the likelihood of experiencing these events. The same is true for predicting times from hospital admission of COVID-19 patients to intensive care or from start of ventilation (invasive or non-invasive) to extubation.

Quantification and interpretation of attributable mortality in core clinical infectious disease journals.

Attributable mortality is an important metric that mirrors the public health effect of a potentially harmful infection by accounting not only for the effect of infection on mortality, but also for its prevalence within the target population. We did a systematic literature review to identify how attributable deaths were quantified and interpreted in core clinical infectious diseases journals between Jan 1, 2013, and April 6, 2020. Of the 1591 abstracts screened, 234 entered the primary analysis.

Joint analysis of duration of ventilation, length of intensive care, and mortality of COVID-19 patients: a multistate approach.

Background: The clinical progress of patients hospitalized due to COVID-19 is often associated with severe pneumonia which may require intensive care, invasive ventilation, or extracorporeal membrane oxygenation (ECMO). The length of intensive care and the duration of these supportive therapies are clinically relevant outcomes. From the statistical perspective, these quantities are challenging to estimate due to episodes being time-dependent and potentially multiple, as well as being determined by the competing, terminal events of discharge alive and death.

Donepezil, a cholinesterase inhibitor used in Alzheimer's disease therapy, is actively exported out of the brain by abcb1ab p-glycoproteins in mice.

Polymorphisms in the drug transporter gene ABCB1 predict the treatment response of selected antidepressants and limit anticonvulsive medication's effectiveness. The ABCB1 locus encodes the energy-dependent transporter P-glycoprotein (P-gp) of the blood brain barrier (BBB), which serves as an efflux pump of its substrates in the expressing tissues of vertebrates. One experimental setup to determine a posteriori the P-gp substrate status is the use of the double abcb1ab knock-out (KO) mice model.

The population-attributable fraction for time-dependent exposures using dynamic prediction and landmarking.

The public health impact of a harmful exposure can be quantified by the population-attributable fraction (PAF). The PAF describes the attributable risk due to an exposure and is often interpreted as the proportion of preventable cases if the exposure was extinct. Difficulties in the definition and interpretation of the PAF arise when the exposure of interest depends on time.

The population-attributable fraction for time-dependent exposures and competing risks-A discussion on estimands.

The population-attributable fraction (PAF) quantifies the public health impact of a harmful exposure. Despite being a measure of significant importance, an estimand accommodating complicated time-to-event data is not clearly defined. We discuss current estimands of the PAF used to quantify the public health impact of an internal time-dependent exposure for data subject to competing outcomes.