81 LONG-TERM OUTCOME OF LOWER RISK MDS PATIENTS RECEIVING ESA, AND IMPACT OF POST-ESA TREATMENTS ON SURVIVAL: A RETROSPECTIVE STUDY FROM THE GFM, DÜSSELDORF, AND GESMD REGISTRIES
S. ParkJ.F. HamelCharikleia KelaïdiMaría Díez‐CampeloJennifer SchemenauRosa SapenaKatharina GoetzeK. Mueller-ThomasOdile Beyne-RauzyAspasia StamatoullasA. Guerci-BreslerPascale Cony‐MakhoulStéphane CourbyS. ChèzeCarsten RoseNorbert VeyUlrich GermingGuillermo SanzPierre FenauxF. Dreyfus
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The evidence of outcome bias was explored in a two-player (Player 1: allocator and Player 2: evaluator) economic game experiment where the reward allocation was made between two players. The experimental factors were the intention of an allocator (Player 1), the type of chosen dice (selfish, fair, and generous), and the outcome (selfish, fair, and generous). The outcome bias occurred when the type of dice chosen by the allocator (Player 1) was not only a selfish one but also a generous one. The comparison between the two conditions (intentional and no-intentional conditions) definitely showed that Player 2 punished Player 1 to a larger extent when the outcome was disadvantageous for Player 2 (selfish outcome) and Player 2 rewarded Player 1 when the outcome was advantageous (generous outcome) irrespective of whether the die was chosen out of the three types intentionally or not. Moreover, the outcome bias was not observed when the outcome was fair. Thus, we could verify the hypothesis that we are readily got trapped in the outcome bias. Some implications were given for safety management that put more emphasis on the process than on the outcome.
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We formulate a dynamic learning-and-adjustment model of a market in which sellers choose signals that potentially reveal their types. If the dynamic process selects a unique limiting outcome, then that outcome must be an undefeated equilibrium; though to be undefeated does not suffice to be the sole limiting outcome. If a Riley outcome exists that provides type sellers with a higher utility than any other equilibrium outcome, then that outcome is the unique limiting outcome of our model. In the absence of a Riley outcome, or if high type workers obtain higher utility in a pooling equilibrium than in the Riley outcome, a unique limit outcome will only emerge under very stringent conditions. If these conditions fail, the market will cycle between various equilibria and, possibly, nonequilibrium outcomes
Limiting
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We formulate a dynamic learning-and-adjustment model of a market in which sellers choose signals that potentitally reveal their types. If the dynamic process selects a unique limiting outcome, then that outcome must be an undefeated equilibrium; though to be undefeated does not suffice to be the sole limiting outcome. If a Riley outcome exists that provides type sellers with a higher utility than any other equilibrim outcome, then that outcome is the unique limiting outcome of our model. In the absence of a Riley outcome,. or if high type workers obtain higher utility in a pooling equlibrium than in the Riley outcome, a unique limit outcome will only emerge under very stringent conditions. If these conditions fail, the market will cycle between various equlibria and, possibly, nonequilibrrium outcomes.
Limiting
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Background: Patients waiting for intensive care unit (ICU) admission cause emergency department (ED) crowding and have an increased risk of mortality and length of stay (LOS) in hospital, which increase the hospitalization cost. This study aimed to investigate the correlation between mortality and invasive mechanical ventilation (IMV) time in patients in the ED. Methods: A retrospective cohort study was conducted in patients who received IMV in the ED of Ramathibodi Hospital. The correlation between mortality at 28 days after intubation and IMV time in the ED was analyzed. The cutoff time was analyzed to determine prolonged and nonprolonged IMV times. ICU ventilation time, length of ICU stay, and LOS in the hospital were also analyzed to determine their correlations between IMV time in the ED. Results: In this study, 302 patients were enrolled, 71 died, and 231 survived 28 days after receiving IMV in the ED. We found that the duration of >12 h of IMV in the ED increased the 28-day mortality rate by 1.98 times ( P = 0.036). No correlations were found between IMV time in the ED and ventilation time in the ICU, length of ICU stay, and LOS in the hospital. Conclusion: More than 12 h of IMV time in the ED correlated with mortality at 28 days after initiation of IMV. No associations were found between prolonged IMV time in the ED with ventilation time in the ICU, length of ICU stay, and LOS in the hospital.
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The Quasi-purchase system of research outcome is a research funds' system based upon research outcome. The thesis analyses the characteristics of research outcomes' honour under the quasi-purchase system of research outcome. It researches the evaluation of the follow-up impact of the honoured outcome. And make a greater impact on the honoured outcome for incentives and penalties for false results of the proposal.
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Background:
Trauma care in Nunavik, Quebec, is highly challenging. Geographic distances and delays in transport can translate into precarious patient transfers to tertiary trauma care centres. The objective of this study was to identify predictors of clinical deterioration during transport and eventual intensive care unit (ICU) admission for trauma patients transferred from Nunavik to a tertiary trauma care centre.Methods:
This is a retrospective cohort study using the Montreal General Hospital (MGH) trauma registry. All adult trauma patients transferred from Nunavik and admitted to the MGH from 2010 to 2019 were included. Main outcomes of interest were hemodynamic and neurologic deterioration during transport and ICU admission.Results:
In total, 704 patients were transferred from Nunavik and admitted to the MGH during the study period. The median age was 33 (interquartile range [IQR] 23–47) years and the median Injury Severity Score was 10 (IQR 5–17). On multiple regression analysis, transport time from site of injury to the MGH (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.01–1.06), thoracic injuries (OR 1.75, 95% CI 1.03–2.99), and head and neck injuries (OR 3.76, 95% CI 2.10–6.76) predicted clinical deterioration during transfer. Injury Severity Score (OR 1.04, 95% CI 1.01–1.08), abnormal local Glasgow Coma Scale score (OR 2.57, 95% CI 1.34–4.95), clinical deterioration during transfer (OR 4.22, 95% CI 1.99–8.93), traumatic brain injury (OR 2.44, 95% CI 1.05–5.68), and transfusion requirement at the MGH (OR 4.63, 95% CI 2.35–9.09) were independent predictors of ICU admission.Conclusion:
Our study identified several predictors of clinical deterioration during transfer and eventual ICU admission for trauma patients transferred from Nunavik. These factors could be used to refine triage criteria in Nunavik for more timely evacuation and higher level care during transport.Interquartile range
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Abbreviated Injury Scale
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Pulse oximetry is routinely used to continuously and noninvasively monitor arterial oxygen saturation (SaO2) in critically ill patients. Although pulse oximeter oxygen saturation (SpO2) has been studied in several patient populations, including the critically ill, its accuracy has never been studied in emergency department (ED) patients with severe sepsis and septic shock. Sepsis results in characteristic microcirculatory derangements that could theoretically affect pulse oximeter accuracy. The purposes of the present study were twofold: 1) to determine the accuracy of pulse oximetry relative to SaO2 obtained from ABG in ED patients with severe sepsis and septic shock, and 2) to assess the impact of specific physiologic factors on this accuracy.This analysis consisted of a retrospective cohort of 88 consecutive ED patients with severe sepsis who had a simultaneous arterial blood gas and an SpO2 value recorded. Adult ICU patients that were admitted from any Calgary Health Region adult ED with a pre-specified, sepsis-related admission diagnosis between October 1, 2005 and September 30, 2006, were identified. Accuracy (SpO2 - SaO2) was analyzed by the method of Bland and Altman. The effects of hypoxemia, acidosis, hyperlactatemia, anemia, and the use of vasoactive drugs on bias were determined.The cohort consisted of 88 subjects, with a mean age of 57 years (19 - 89). The mean difference (SpO2 - SaO2) was 2.75% and the standard deviation of the differences was 3.1%. Subgroup analysis demonstrated that hypoxemia (SaO2 < 90) significantly affected pulse oximeter accuracy. The mean difference was 4.9% in hypoxemic patients and 1.89% in non-hypoxemic patients (p < 0.004). In 50% (11/22) of cases in which SpO2 was in the 90-93% range the SaO2 was <90%. Though pulse oximeter accuracy was not affected by acidoisis, hyperlactatementa, anemia or vasoactive drugs, these factors worsened precision.Pulse oximetry overestimates ABG-determined SaO2 by a mean of 2.75% in emergency department patients with severe sepsis and septic shock. This overestimation is exacerbated by the presence of hypoxemia. When SaO2 needs to be determined with a high degree of accuracy arterial blood gases are recommended.
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