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This paper presents a comprehensive review on the sources of model inaccuracy and parameter uncertainty in metal laser powder bed fusion (L-PBF) process. Metal additive manufacturing (AM) involves multiple physical phenomena and parameters that potentially affect the quality of the final part. To capture the dynamics and complexity of heat and phase transformations that exist in the metal L-PBF process, computational models and simulations ranging from low to high fidelity have been developed. Since it is difficult to incorporate all the physical phenomena encountered in the L-PBF process, computational models rely on assumptions that may neglect or simplify some physics of the process. Modeling assumptions and uncertainty play significant role in the predictive accuracy of such L-PBF models. In this study, sources of modeling inaccuracy at different stages of the process from powder bed formation to melting and solidification are reviewed. The sources of parameter uncertainty related to material properties and process parameters are also reviewed. The aim of this review is to support the development of an approach to quantify these sources of uncertainty in L-PBF models in the future. The quantification of uncertainty sources is necessary for understanding the tradeoffs in model fidelity and guiding the selection of a model suitable for its intended purpose.
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BACKGROUND: People with HIV (PWH) are at increased risk for venous thromboembolism (VTE). We conducted this study to characterize VTE including provoking factors among PWH in the current treatment era. METHODS: We included PWH with VTE between 2010 and 2020 at 6 sites in the CFAR Network of Integrated Clinical Systems cohort. We ascertained for possible VTE using diagnosis, VTE-related imaging, and VTE-related procedure codes, followed by centralized adjudication of primary data by expert physician reviewers. We evaluated sensitivity and positive predictive value of VTE ascertainment approaches. VTEs were classified by type and anatomic location. Reviewers identified provoking factors such as hospitalizations, infections, and other potential predisposing factors such as smoking. RESULTS: We identified 557 PWH with adjudicated VTE: 239 (43%) had pulmonary embolism with or without deep venous thrombosis, and 318 (57%) had deep venous thrombosis alone. Ascertainment with clinical diagnoses alone missed 6% of VTEs identified with multiple ascertainment approaches. DVTs not associated with intravenous lines were most often in the proximal lower extremities. Among PWH with VTE, common provoking factors included recent hospitalization (n = 134, 42%), infection (n = 133, 42%), and immobilization/bed rest (n = 78, 25%). Only 57 (10%) PWH had no provoking factor identified. Smoking (46%), HIV viremia (27%), and injection drug use (22%) were also common. CONCLUSIONS: We conducted a robust adjudication process that demonstrated the benefits of multiple ascertainment approaches followed by adjudication. Provoked VTEs were more common than unprovoked events. Nontraditional and modifiable potential predisposing factors such as viremia and smoking were common.
Asunto(s)
Infecciones por VIH , Tromboembolia Venosa , Trombosis de la Vena , Humanos , Estados Unidos/epidemiología , Tromboembolia Venosa/epidemiología , Tromboembolia Venosa/complicaciones , Factores de Riesgo , Viremia/complicaciones , Infecciones por VIH/complicaciones , Trombosis de la Vena/complicacionesRESUMEN
Objectives: People living with HIV (PWH) with substance or alcohol use often have unsuppressed plasma HIV viral loads (pVL). The degree to which substance and alcohol use effects on HIV viral suppression are mediated through medication nonadherence is incompletely understood. Methods: We included PWH prescribed antiretroviral therapy and receiving care at an academic HIV clinic between 2014 and 2018 who completed both patient-reported outcomes (PRO) questionnaires and had subsequent pVL measurements. Measures included assessments of alcohol use (AUDIT-C), drug use (NIDA-ASSIST), and self-reported adherence measured using four different methods. Substances found in bivariate analysis to predict detectable pVL were modeled separately for mediation effects through adherence. We report natural direct (NDE) and indirect effect (NIE), marginal total effect (MTE), and percentage mediated. Results: Among 3125 PWH who met eligibility criteria, 25.8% reported hazardous alcohol use, 27.1% cannabis, 13.1% amphetamines, 1.9% inhalants, 5.3% cocaine, 4.5% sedative-hypnotics, 2.9% opioids, and 2.3% hallucinogens. Excellent adherence was reported by 58% of PWH, and 10% had detectable pVL. Except for sedatives, using other substances was significantly associated with worse adherence. Bivariate predictors of detectable pVL were [OR (95% CI)]: amphetamine use 2.4 (1.8-3.2) and opioid use 2.3 (1.3-4.0). The percent of marginal total effect mediated by nonadherence varied by substance: 36% for amphetamine use, 27% for opioid use, and 39% for polysubstance use. Conclusion: Use of amphetamines, opioids, and multiple substances predicted detectable pVL. Up to 40% of their effects were mediated by self-reported nonadherence. Confirmation using longitudinal measurement models will strengthen causal inference from this cross-sectional analysis.