Dana Edelson to Retrospective Studies
This is a "connection" page, showing publications Dana Edelson has written about Retrospective Studies.
Connection Strength
1.051
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Less is more: Detecting clinical deterioration in the hospital with machine learning using only age, heart rate, and respiratory rate. Resuscitation. 2021 11; 168:6-10.
Score: 0.078
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Determining the Electronic Signature of Infection in Electronic Health Record Data. Crit Care Med. 2021 07 01; 49(7):e673-e682.
Score: 0.077
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Validation of Early Warning Scores at Two Long-Term Acute Care Hospitals. Crit Care Med. 2019 12; 47(12):e962-e965.
Score: 0.069
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Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting: Retrospective Cohort Study. Ann Surg. 2019 06; 269(6):1059-1063.
Score: 0.067
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Comparison of the Between the Flags calling criteria to the MEWS, NEWS and the electronic Cardiac Arrest Risk Triage (eCART) score for the identification of deteriorating ward patients. Resuscitation. 2018 02; 123:86-91.
Score: 0.060
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Investigating the Impact of Different Suspicion of Infection Criteria on the Accuracy of Quick Sepsis-Related Organ Failure Assessment, Systemic Inflammatory Response Syndrome, and Early Warning Scores. Crit Care Med. 2017 Nov; 45(11):1805-1812.
Score: 0.060
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The value of vital sign trends for detecting clinical deterioration on the wards. Resuscitation. 2016 May; 102:1-5.
Score: 0.053
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Comparison of mental-status scales for predicting mortality on the general wards. J Hosp Med. 2015 Oct; 10(10):658-63.
Score: 0.052
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Relationship between ICU bed availability, ICU readmission, and cardiac arrest in the general wards. Crit Care Med. 2014 Sep; 42(9):2037-41.
Score: 0.048
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Using electronic health record data to develop and validate a prediction model for adverse outcomes in the wards*. Crit Care Med. 2014 Apr; 42(4):841-8.
Score: 0.047
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Cardiopulmonary resuscitation outcomes in hospitalized community-dwelling individuals and nursing home residents based on activities of daily living. J Am Geriatr Soc. 2013 Jan; 61(1):34-9.
Score: 0.043
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Derivation of a cardiac arrest prediction model using ward vital signs*. Crit Care Med. 2012 Jul; 40(7):2102-8.
Score: 0.041
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Safety and efficacy of defibrillator charging during ongoing chest compressions: a multi-center study. Resuscitation. 2010 Nov; 81(11):1521-6.
Score: 0.037
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Temperature Trajectory Subphenotypes in Oncology Patients with Neutropenia and Suspected Infection. Am J Respir Crit Care Med. 2023 05 15; 207(10):1300-1309.
Score: 0.022
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Identifying infected patients using semi-supervised and transfer learning. J Am Med Inform Assoc. 2022 09 12; 29(10):1696-1704.
Score: 0.021
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Predicting neurological outcomes after in-hospital cardiac arrests for patients with Coronavirus Disease 2019. Resuscitation. 2022 09; 178:55-62.
Score: 0.021
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Development and External Validation of a Machine Learning Model for Prediction of Potential Transfer to the PICU. Pediatr Crit Care Med. 2022 07 01; 23(7):514-523.
Score: 0.020
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Comparison of early warning scores for predicting clinical deterioration and infection in obstetric patients. BMC Pregnancy Childbirth. 2022 Apr 06; 22(1):295.
Score: 0.020
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A Vital Sign-Based Model to Predict Clinical Deterioration in Hospitalized Children. Pediatr Crit Care Med. 2020 09; 21(9):820-826.
Score: 0.018
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Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury. JAMA Netw Open. 2020 08 03; 3(8):e2012892.
Score: 0.018
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Predicting clinical deterioration with Q-ADDS compared to NEWS, Between the Flags, and eCART track and trigger tools. Resuscitation. 2020 08; 153:28-34.
Score: 0.018
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Comparison of Early Warning Scoring Systems for Hospitalized Patients With and Without Infection at Risk for In-Hospital Mortality and Transfer to the Intensive Care Unit. JAMA Netw Open. 2020 05 01; 3(5):e205191.
Score: 0.018
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Characteristics of Rapid Response Calls in the United States: An Analysis of the First 402,023 Adult Cases From the Get With the Guidelines Resuscitation-Medical Emergency Team Registry. Crit Care Med. 2019 10; 47(10):1283-1289.
Score: 0.017
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Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data. Ann Am Thorac Soc. 2018 07; 15(7):846-853.
Score: 0.016
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Implications of Centers for Medicare & Medicaid Services Severe Sepsis and Septic Shock Early Management Bundle and Initial Lactate Measurement on the Management of Sepsis. Chest. 2018 08; 154(2):302-308.
Score: 0.016
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Electronic cardiac arrest triage score best predicts mortality after intervention in patients with massive and submassive pulmonary embolism. Catheter Cardiovasc Interv. 2018 08 01; 92(2):366-371.
Score: 0.016
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Association Between Survival and Time of Day for Rapid Response Team Calls in a National Registry. Crit Care Med. 2017 10; 45(10):1677-1682.
Score: 0.015
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Mechanical chest compressions improve rate of return of spontaneous circulation and allow for initiation of percutaneous circulatory support during cardiac arrest in the cardiac catheterization laboratory. Resuscitation. 2017 06; 115:56-60.
Score: 0.014
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Location of In-Hospital Cardiac Arrest in the United States-Variability in Event Rate and Outcomes. J Am Heart Assoc. 2016 09 29; 5(10).
Score: 0.014
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Early cardiac arrest in patients hospitalized with pneumonia: a report from the American Heart Association's Get With The Guidelines-Resuscitation Program. Chest. 2012 Jun; 141(6):1528-1536.
Score: 0.010
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Perishock pause: an independent predictor of survival from out-of-hospital shockable cardiac arrest. Circulation. 2011 Jul 05; 124(1):58-66.
Score: 0.010
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Derangements in blood glucose following initial resuscitation from in-hospital cardiac arrest: a report from the national registry of cardiopulmonary resuscitation. Resuscitation. 2009 Jun; 80(6):624-30.
Score: 0.008
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Difficulty of cardiac arrest rhythm identification does not correlate with length of chest compression pause before defibrillation. Crit Care Med. 2006 Dec; 34(12 Suppl):S427-31.
Score: 0.007