Estimating incidence of venous thromboembolism in COVID-19:Methodological considerations

Background Coagulation abnormalities and coagulopathy are recognized as consequences of severe acute respiratory syndrome coronavirus 2 infection and the resulting coronavirus disease 2019 (COVID-19). Specifically, venous thromboembolism (VTE) has been reported as a frequent complication. By May 27, 2021, at least 93 original studies and 25 meta-analyses investigating VTE incidence in patients with COVID-19 had been published, showing large heterogeneity in reported VTE incidence ranging from 0% to 85%. This large variation complicates interpretation of individual study results as well as comparisons across studies, for example, to investigate changes in incidence over time, compare subgroups, and perform meta-analyses. Objectives This study sets out to provide an overview of sources of heterogeneity in VTE incidence studies in patients with COVID-19, illustrated using examples. Methods The original studies of three meta-analyses were screened and a list of sources of heterogeneity that may explain observed heterogeneity across studies was composed. Results The sources of heterogeneity in VTE incidence were classified as clinical sources and methodologic sources. Clinical sources of heterogeneity include differences between studies regarding patient characteristics that affect baseline VTE risk and protocols used for VTE testing. Methodologic sources of heterogeneity include differences in VTE inclusion types, data quality, and the methods used for data analysis. Conclusions To appreciate reported estimates of VTE incidence in patients with COVID-19 in relation to its etiology, prevention, and treatment, researchers should unambiguously report about possible clinical and methodological sources of heterogeneity in those estimates. This article provides suggestions for that.Thrombosis and Hemostasi

Quantum-Classical Correspondence of Dynamical Observables, Quantization and the Time of Arrival Correspondence Problem

We raise the problem of constructing quantum observables that have classical counterparts without quantization. Specifically we seek to define and motivate a solution to the quantum-classical correspondence problem independent from quantization and discuss the general insufficiency of prescriptive quantization, particularly the Weyl quantization. We demonstrate our points by constructing time of arrival operators without quantization and from these recover their classical counterparts

Drug exposure misclassification in pharmacoepidemiology: sources and relative impact

Background Drug exposure assessment based on dispensing data can be misclassified when patients do not adhere to their therapy or when information about over-the-counter drugs is not captured in the study database. Previous research has considered hypothetical sensitivity and specificity values, whereas this study aims to assess the impact of literature-based real values of exposure misclassification. Methods A synthetic cohort study was constructed based on the proportion of exposure theoretically captured in a database (range 0.5-1.0) and the level of adherence (0.5-1.0). Three scenarios were explored: nondifferential misclassification, differential misclassification (misclassifications dependent on an unmeasured risk factor doubling the outcome risk), and nondifferential misclassification in a comparative effectiveness study (RRA and RRB both 2.0 compared to nonuse, RRA-B 1.0). Results For the scenarios with nondifferential misclassification, 25% nonadherence or 25% uncaptured exposure changed the RR from 2.0 to 1.75, and 1.95, respectively. Applying different proportions of nonadherence or uncaptured use (20% vs. 40%) for subgroups with and without the risk factor, an RR of 0.95 was observed in the absence of a true effect (i.e., true RR = 1). In the comparative effectiveness study, no effect on RR was seen for different proportions of uncaptured exposure; however, different levels of nonadherence for the drugs (20% vs. 40%) led to an underestimation of RRA-B (0.89). Discussion All scenarios led to biased estimates, but the magnitude of the bias differed across scenarios. When testing the robustness of findings of pharmacoepidemiologic studies, we recommend using realistic values of nonadherence and uncaptured exposure based on real-world data.Clinical epidemiolog

Gradient-only approaches to avoid spurious local minima in unconstrained optimization

We reflect on some theoretical aspects of gradient-only optimization for the unconstrained optimization of objective functions containing non-physical step or jump discontinuities. This kind of discontinuity arises when the optimization problem is based on the solutions of systems of partial differential equations, in combination with variable discretization techniques (e.g. remeshing in spatial domains, and/or variable time stepping in temporal domains). These discontinuities, which may cause local minima, are artifacts of the numerical strategies used and should not influence the solution to the optimization problem. Although the discontinuities imply that the gradient field is not defined everywhere, the gradient field associated with the computational scheme can nevertheless be computed everywhere; this field is denoted the associated gradient field. We demonstrate that it is possible to overcome attraction to the local minima if only associated gradient information is used. Various gradient-only algorithmic options are discussed. A salient feature of our approach is that variable discretization strategies, so important in the numerical solution of partial differential equations, can be combined with efficient local optimization algorithms.National Research Foundation (NRF)http://link.springer.com/journal/11081hb201

A recalibrated prediction model can identify level-1 trauma patients at risk of nosocomial pneumonia

Introduction: Nosocomial pneumonia has poor prognosis in hospitalized trauma patients. Croce et al. published a model to predict post-traumatic ventilator-associated pneumonia, which achieved high discrimination and reasonable sensitivity. We aimed to externally validate Croce’s model to predict nosocomial pneumonia in patients admitted to a Dutch level-1 trauma center. Materials and methods: This retrospective study included all trauma patients (≥ 16y) admitted for &gt; 24 h to our level-1 trauma center in 2017. Exclusion criteria were pneumonia or antibiotic treatment upon hospital admission, treatment elsewhere &gt; 24 h, or death &lt; 48 h. Croce’s model used eight clinical variables—on trauma severity and treatment, available in the emergency department—to predict nosocomial pneumonia risk. The model’s predictive performance was assessed through discrimination and calibration before and after re-estimating the model’s coefficients. In sensitivity analysis, the model was updated using Ridge regression. Results: 809 Patients were included (median age 51y, 67% male, 97% blunt trauma), of whom 86 (11%) developed nosocomial pneumonia. Pneumonia patients were older, more severely injured, and underwent more emergent interventions. Croce’s model showed good discrimination (AUC 0.83, 95% CI 0.79–0.87), yet predicted probabilities were too low (mean predicted risk 6.4%), and calibration was suboptimal (calibration slope 0.63). After full model recalibration, discrimination (AUC 0.84, 95% CI 0.80–0.88) and calibration improved. Adding age to the model increased the AUC to 0.87 (95% CI 0.84–0.91). Prediction parameters were similar after the models were updated using Ridge regression. Conclusion: The externally validated and intercept-recalibrated models show good discrimination and have the potential to predict nosocomial pneumonia. At this time, clinicians could apply these models to identify high-risk patients, increase patient monitoring, and initiate preventative measures. Recalibration of Croce’s model improved the predictive performance (discrimination and calibration). The recalibrated model provides a further basis for nosocomial pneumonia prediction in level-1 trauma patients. Several models are accessible via an online tool. Level of evidence: Level III, Prognostic/Epidemiological Study.</p

Effectiveness and toxicity of lenvatinib in refractory thyroid cancer:Dutch real-life data

Objective: The SELECT trial showed progression-free survival (PFS) benefit for lenvatinib for advanced radioiodine-refractory differentiated thyroid cancer (RAI-refractory or RR-DTC) patients, on which current clinical practice is based. We assessed whether the effectiveness and toxicity of lenvatinib in real-life clinical practice in the Netherlands were comparable to the pivotal SELECT trial. Methods: From three Dutch centres Electronic Health Records (EHRs) of patients treated in the lenvatinib compassionate use program or as standard of care were reviewed and checked for SELECT eligibility criteria. Baseline characteristics, safety, and efficacy measures were compared and PFS and overall survival (OS) were calculated. Furthermore, PFS was compared to estimates of PFS reported in other studies. Results: A total of 39 DTC patients with a median age of 62 years were analysed. Of these, 27 patients (69%) did not fulfil the SELECT eligibility criteria. The most common grade >= 3 toxicities were hypertension (n = 11, 28%), diarrhoea (n = 7, 18%), vomiting (n = 4, 10%), and gallbladder disease (n = 3, 8%). Median PFS and median OS were 9.7 (95% confidence interval (CI): 4.0-15.5) and 18.3 (95% CI: 4.9-31.7) months, respectively, response rate was 38% (95% CI: 23-54%). PFS in the Dutch real-life situation was comparable to previous real-life studies, but inferior to PFS as shown in the SELECT trial (P = 0.04). Conclusions: PFS in our non-trial population was significantly shorter than in the SELECT trial population. In the interpretation of results, differences in the real-life population and the SELECT study population regarding patient characteristics should be taken into account