Pandemia in translation: a comparative understanding of European social values

This volume, resulting from the training and research activities of the “Pandemic in translation” project – FORTHEM’s Experiencing Europe Lab, University of Palermo –, deals with central issues related to COVID-19 pandemic, and aims at contributing to a comparative understanding of mainly, but not exclusively European values challenged during this contingency. This interdisciplinary projects mobilizes a multicultural and multilingual debate about norms and beliefs, cultural identities and societal values, public policies and emotional communities. Using methodologies drawn from Comparative and International Law to Comparative Literature, from discourse analysis to Translation Studies, this book clarifies the socially constructed nature of the pandemic reality and calls for a redefinition of some long-assumed categories. Although translation can function culturally, epistemologically and cognitively as a metaphor, in fact translation seems more like “a process endogenous to social life”: in this sense – and from an anthropological point of view – it allows for the articulation of ethical, legal, normative and ideological representations. In some cases, translation can highlight the hermeneutic impasse between public policy actions and the discursive politics that emerge from them. The social suffering caused by the pandemic crisis calls into question both scientific mediation as a whole and scientists’ position in particular: how can scientific accuracy be reconciled with the need to make certain warnings known? Who is qualified to speak about the pandemic and its societal implications? Which authority figures are expressing their thoughts on the matter, and how trustworthy are they? Indeed, the methodological combination of 1 the approaches of Translation Studies and Multilingual crisis communication points to translation as a key theoretical concept not only in social and human sciences, but also in the anthropological and epistemological construction of global public health discourses

Predicting Emergency Department Volume Using Forecasting Methods to Create a “Surge Response” for Noncrisis Events

Objectives:  This study investigated whether emergency department (ED) variables could be used in mathematical models to predict a future surge in ED volume based on recent levels of use of physician capacity. The models may be used to guide decisions related to on‐call staffing in non–crisis‐related surges of patient volume. Methods:  A retrospective analysis was conducted using information spanning July 2009 through June 2010 from a large urban teaching hospital with a Level I trauma center. A comparison of significance was used to assess the impact of multiple patient‐specific variables on the state of the ED. Physician capacity was modeled based on historical physician treatment capacity and productivity. Binary logistic regression analysis was used to determine the probability that the available physician capacity would be sufficient to treat all patients forecasted to arrive in the next time period. The prediction horizons used were 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 8 hours, and 12 hours. Five consecutive months of patient data from July 2010 through November 2010, similar to the data used to generate the models, was used to validate the models. Positive predictive values, Type I and Type II errors, and real‐time accuracy in predicting noncrisis surge events were used to evaluate the forecast accuracy of the models. Results:  The ratio of new patients requiring treatment over total physician capacity (termed the care utilization ratio [CUR]) was deemed a robust predictor of the state of the ED (with a CUR greater than 1 indicating that the physician capacity would not be sufficient to treat all patients forecasted to arrive). Prediction intervals of 30 minutes, 8 hours, and 12 hours performed best of all models analyzed, with deviances of 1.000, 0.951, and 0.864, respectively. A 95% significance was used to validate the models against the July 2010 through November 2010 data set. Positive predictive values ranged from 0.738 to 0.872, true positives ranged from 74% to 94%, and true negatives ranged from 70% to 90% depending on the threshold used to determine the state of the ED with the 30‐minute prediction model. Conclusions:  The CUR is a new and robust indicator of an ED system’s performance. The study was able to model the tradeoff of longer time to response versus shorter but more accurate predictions, by investigating different prediction intervals. Current practice would have been improved by using the proposed models and would have identified the surge in patient volume earlier on noncrisis days.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92015/1/j.1553-2712.2012.01359.x.pd

Missed Opportunities in Preventing Hospital Readmissions: Redesigning Post‐Discharge Checkup Policies

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147049/1/poms12858.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147049/2/poms12858_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147049/3/poms12858-sup-0001-AppendixS1.pd

Predicting fever in neutropenia with safety-relevant events in children undergoing chemotherapy for cancer: The prospective multicenter SPOG 2015 FN Definition Study

BACKGROUND Fever in neutropenia (FN) remains a frequent complication in pediatric patients undergoing chemotherapy for cancer. Preventive strategies, like primary antibiotic prophylaxis, need to be evidence-based. PROCEDURE Data on pediatric patients with any malignancy from the prospective multicenter SPOG 2015 FN Definition Study (NCT02324231) were analyzed. A score predicting the risk to develop FN with safety-relevant events (SRE; bacteremia, severe sepsis, intensive care unit admission, death) was developed using multivariate mixed Poisson regression. Its predictive performance was assessed by internal cross-validation and compared with the performance of published rules. RESULTS In 238 patients, 318 FN episodes were recorded, including 53 (17%) with bacteremia and 68 (21%) with SRE. The risk-prediction score used three variables: chemotherapy intensity, defined according to the expected duration of severe neutropenia, time since diagnosis, and type of malignancy. Its cross-validated performance, assessed by the time needed to cover (TNC) one event, exceeded the performance of published rules. A clinically useful score threshold of ≥11 resulted in 2.3% time at risk and 4.1 months TNC. Using external information on efficacy and timing of intermittent antibiotic prophylaxis, 4.3 months of prophylaxis were needed to prevent one FN with bacteremia, and 5.2 months to prevent one FN with SRE, using a threshold of ≥11. CONCLUSIONS This score, based on three routinely accessible characteristics, accurately identifies pediatric patients at risk to develop FN with SRE during chemotherapy. The score can help to design clinical decision rules on targeted primary antibiotic prophylaxis and corresponding efficacy studies

Predicting fever in neutropenia with safety-relevant events in children undergoing chemotherapy for cancer: The prospective multicenter SPOG 2015 FN Definition Study.

BACKGROUND Fever in neutropenia (FN) remains a frequent complication in pediatric patients undergoing chemotherapy for cancer. Preventive strategies, like primary antibiotic prophylaxis, need to be evidence-based. PROCEDURE Data on pediatric patients with any malignancy from the prospective multicenter SPOG 2015 FN Definition Study (NCT02324231) were analyzed. A score predicting the risk to develop FN with safety-relevant events (SRE; bacteremia, severe sepsis, intensive care unit admission, death) was developed using multivariate mixed Poisson regression. Its predictive performance was assessed by internal cross-validation and compared with the performance of published rules. RESULTS In 238 patients, 318 FN episodes were recorded, including 53 (17%) with bacteremia and 68 (21%) with SRE. The risk-prediction score used three variables: chemotherapy intensity, defined according to the expected duration of severe neutropenia, time since diagnosis, and type of malignancy. Its cross-validated performance, assessed by the time needed to cover (TNC) one event, exceeded the performance of published rules. A clinically useful score threshold of ≥11 resulted in 2.3% time at risk and 4.1 months TNC. Using external information on efficacy and timing of intermittent antibiotic prophylaxis, 4.3 months of prophylaxis were needed to prevent one FN with bacteremia, and 5.2 months to prevent one FN with SRE, using a threshold of ≥11. CONCLUSIONS This score, based on three routinely accessible characteristics, accurately identifies pediatric patients at risk to develop FN with SRE during chemotherapy. The score can help to design clinical decision rules on targeted primary antibiotic prophylaxis and corresponding efficacy studies