Internal and emergency medicine
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Observational Study
Perfusion index: could it be a new tool for early identification of pulmonary embolism severity?
Perfusion index (PI) is a promising indicator for monitoring peripheral perfusion. The present study aimed to compare the efficiency of PI and PESI score in estimating the 30-day mortality and treatment needs of patients diagnosed with pulmonary embolism in the emergency department. This study was prospective and observational. ⋯ PESI score and PI were statistically significant to predict the need for mechanical ventilation (PI, p = 0.004; PESI score, p < 0.001), inotropic treatment (PI, p = 0.047; PESI score p = 0.005), and thrombolytic therapy (PI, p = 0.035; PESI score p = 0.003). According to the ROC curve, the mortality prediction power of both PESI (AUC: 0.787, 95% CI 0.688-0.886, cutoff: 109.5, p < 0.001) and PI index (AUC: 0.668, 95% CI 0.543-0.793, cutoff: 1, p = 0.011) were determined as statistically significant. PI might be helpful in clinical practice as a tool that can be applied to predict mortality and treatment needs in PE.
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Background Predicting potential overcrowding is a significant tool in efficient emergency department (ED) management. Our aim was to develop and validate overcrowding predictive models using accessible and high quality information. Methods Retrospective cohort study of consecutive days in the Hospital Italiano de Buenos Aires ED from june 2016 to may 2018. ⋯ Discrimination for the main model had an area under the receiveroperator curve of 0.997 (95% CI 0.994 - 1) in the validation group. Calibration for the model was very high on internal validation and acceptable on external validation. Conclusion The Sustained Critical EDOC predictive model includes variables that are easily obtained and can be used for effective resource management in situations of overcrowding.