Objective:To describe the management of anemia at PICU discharge by pediatric intensivists.Design:Self-administered, online, scenario-based survey.Setting:PICUs in Australia/New Zealand, Europe,... Show moreObjective:To describe the management of anemia at PICU discharge by pediatric intensivists.Design:Self-administered, online, scenario-based survey.Setting:PICUs in Australia/New Zealand, Europe, and North America.Subjects:Pediatric intensivists.Interventions:None.Measurements and Main Results:Respondents were asked to report their decisions regarding RBC transfusions, iron, and erythropoietin prescription to children ready to be discharged from PICU, who had been admitted for hemorrhagic shock, cardiac surgery, craniofacial surgery, and polytrauma. Clinical and biological variables were altered separately in order to assess their effect on the management of anemia. Two-hundred seventeen responses were analyzed. They reported that the mean (+/- sem) transfusion threshold was a hemoglobin level of 6.9 +/- 0.09 g/dL after hemorrhagic shock, 7.6 +/- 0.10 g/dL after cardiac surgery, 7.0 +/- 0.10 g/dL after craniofacial surgery, and 7.0 +/- 0.10 g/dL after polytrauma (p < 0.001). The most important increase in transfusion threshold was observed in the presence of a cyanotic heart disease (mean increase ranging from 1.80 to 2.30 g/dL when compared with baseline scenario) or left ventricular dysfunction (mean increase, 1.41-2.15 g/dL). One third of respondents stated that they would not prescribe iron at PICU discharge, regardless of the hemoglobin level or the baseline scenario. Most respondents (69.4-75.0%, depending on the scenario) did not prescribe erythropoietin.Conclusions:Pediatric intensivists state that they use restrictive transfusion strategies at PICU discharge similar to those they use during the acute phase of critical illness. Supplemental iron is less frequently prescribed than RBCs, and prescription of erythropoietin is uncommon. Optimal management of post-PICU anemia is currently unknown. Further studies are required to highlight the consequences of this anemia and to determine appropriate management. Show less
Botvinik-Nezer, R.; Holzmeister, F.; Camerer, C.F.; Dreber, A.; Huber, J.; Johannesson, M.; ... ; Schonberg, T. 2020
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance... Show moreData analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses. Show less
Botvinik-Nezer, R.; Holzmeister, F.; Camerer, C.F.; Dreber, A.; Huber, J.; Johannesson, M.; ... ; Schonberg, T. 2020
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance... Show moreData analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses. Show less
Botvinik-Nezer, R.; Holzmeister, F.; Camerer, C.F.; Dreber, A.; Huber, J.; Johannesson, M.; ... ; Schonberg, T. 2020
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance... Show moreData analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses. Show less
