ABSTRACT
Background: To reduce the risk of hospital-acquired venous thrombosis (HA-VTE) in medical patients, guidelines recommend assessing HA-VTE risk and providing prophylaxis for those at high risk. Risk assessment models (RAMS) including objective risk factors available at admission remain an unmet clinical need. Aim(s): To develop and validate a RAM for HA-VTE in medical inpatients using data available to providers within 24-h of hospital admission. Method(s): We developed a HA-VTE RAM at the University of Vermont Medical Center (Burlington, Vermont, USA, Table 1) and validated this RAM at Michigan Medicine (Ann Arbor, Michigan, USA, Table 2). HA-VTE and the risk factors were identified using previously validated computable phenotypes. The RAM was developed using a Bayesian LASSO approach with model performance assessed using area under the receiver operating curves (AUC) and the slope of observed versus expected plot. People admitted with VTE were excluded. The research was approved by the Institutional Review Board funded by the National Institutes of Health and the Centers for Disease Control and Prevention, USA. Result(s): Table 1 presents the risk factors, odds ratios (OR) and 95% credible intervals (CI) for the HA-VTE RAM, which included 11 risk factors. For the development cohort, based on 219 events among 62,468 admissions, the AUC of the model was 0.75 and the observed versus expected slope was 1.11 (Table 2). In the validation cohort there were 48,265 admissions and 363 HA-VTE events with a younger population and a higher incidence of HA-VTE. The AUC and the observed versus expected slope were 0.69 and 0.89 (Table 2). Conclusion(s): We developed and validated a HA-VTE RAM in populations. The model fit and calibration are promising especially given these are two geographically diverse institutions. Further validation is in progress at additional hospitals as well as in people hospitalized with COVID-19.
ABSTRACT
Science twines through many of the discussions related to hope for a return to normalcy within public discussions of COVID-19. The framings of techno-scientific solutions for COVID-19 are similar to those that are presented to address many societal problems. The messy scientific and regulatory underpinnings of this desired silver bullet rarely make it fully into view. Technoscientific-related hope and its associated affects can operate as a kind of "cruel optimism" (Berlant 2010, 2011). It can be an affective response to return to life as "normal" that is psychologically soothing, even as its enactment may replicate destructive social, political, and economic structures. Hope and technoscience thread throughout the interactions between journalists and health officials in the health press briefings in the first wave of the COVID-19 pandemic. Technoscientific complexity that challenges the desire to return to normal is rarely brought up in Ontario and Nova Scotia public health briefings. But when it is, health officials in this zone of interaction balance explanations of scientific reality and caution, while attempting to not crush hope for a techno-scientifically mediated return to normal. As such, public health discourse obscures or tempers cruel optimism rather than directly confronting it. © 2021 University of Toronto. All rights reserved.