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Connection

Dana Edelson to Adult

This is a "connection" page, showing publications Dana Edelson has written about Adult.
Connection Strength

0.795
  1. 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.
    View in: PubMed
    Score: 0.050
  2. Determining the Electronic Signature of Infection in Electronic Health Record Data. Crit Care Med. 2021 07 01; 49(7):e673-e682.
    View in: PubMed
    Score: 0.049
  3. Interim Guidance for Basic and Advanced Life Support in Adults, Children, and Neonates With Suspected or Confirmed COVID-19: From the Emergency Cardiovascular Care Committee and Get With The Guidelines-Resuscitation Adult and Pediatric Task Forces of the American Heart Association. Circulation. 2020 06 23; 141(25):e933-e943.
    View in: PubMed
    Score: 0.045
  4. 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.
    View in: PubMed
    Score: 0.043
  5. 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.
    View in: PubMed
    Score: 0.039
  6. 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.
    View in: PubMed
    Score: 0.038
  7. Real-Time Risk Prediction on the Wards: A Feasibility Study. Crit Care Med. 2016 08; 44(8):1468-73.
    View in: PubMed
    Score: 0.035
  8. Incidence and Prognostic Value of the Systemic Inflammatory Response Syndrome and Organ Dysfunctions in Ward Patients. Am J Respir Crit Care Med. 2015 Oct 15; 192(8):958-64.
    View in: PubMed
    Score: 0.033
  9. Comparison of mental-status scales for predicting mortality on the general wards. J Hosp Med. 2015 Oct; 10(10):658-63.
    View in: PubMed
    Score: 0.033
  10. Multicenter development and validation of a risk stratification tool for ward patients. Am J Respir Crit Care Med. 2014 Sep 15; 190(6):649-55.
    View in: PubMed
    Score: 0.031
  11. Relationship between ICU bed availability, ICU readmission, and cardiac arrest in the general wards. Crit Care Med. 2014 Sep; 42(9):2037-41.
    View in: PubMed
    Score: 0.031
  12. 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.
    View in: PubMed
    Score: 0.030
  13. A prospective study of nighttime vital sign monitoring frequency and risk of clinical deterioration. JAMA Intern Med. 2013 Sep 09; 173(16):1554-5.
    View in: PubMed
    Score: 0.029
  14. Predicting clinical deterioration in the hospital: the impact of outcome selection. Resuscitation. 2013 May; 84(5):564-8.
    View in: PubMed
    Score: 0.027
  15. Predicting cardiac arrest on the wards: a nested case-control study. Chest. 2012 May; 141(5):1170-1176.
    View in: PubMed
    Score: 0.025
  16. Patient acuity rating: quantifying clinical judgment regarding inpatient stability. J Hosp Med. 2011 Oct; 6(8):475-9.
    View in: PubMed
    Score: 0.025
  17. Capnography and chest-wall impedance algorithms for ventilation detection during cardiopulmonary resuscitation. Resuscitation. 2010 Mar; 81(3):317-22.
    View in: PubMed
    Score: 0.022
  18. Improving in-hospital cardiac arrest process and outcomes with performance debriefing. Arch Intern Med. 2008 May 26; 168(10):1063-9.
    View in: PubMed
    Score: 0.020
  19. Development and Validation of a Machine Learning Model for Early Detection of Untreated Infection. Crit Care Explor. 2024 Oct 01; 6(10):e1165.
    View in: PubMed
    Score: 0.015
  20. Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score. Crit Care Explor. 2024 Jul 01; 6(7):e1116.
    View in: PubMed
    Score: 0.015
  21. Temperature Trajectory Subphenotypes in Oncology Patients with Neutropenia and Suspected Infection. Am J Respir Crit Care Med. 2023 05 15; 207(10):1300-1309.
    View in: PubMed
    Score: 0.014
  22. The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial. Crit Care Med. 2022 09 01; 50(9):1339-1347.
    View in: PubMed
    Score: 0.013
  23. 2022 Interim Guidance to Health Care Providers for Basic and Advanced Cardiac Life Support in Adults, Children, and Neonates With Suspected or Confirmed COVID-19: From the Emergency Cardiovascular Care Committee and Get With The Guidelines-Resuscitation Adult and Pediatric Task Forces of the American Heart Association in Collaboration With the American Academy of Pediatrics, American Association for Respiratory Care, the Society of Critical Care Anesthesiologists, and American Society of Anesthesiologists. Circ Cardiovasc Qual Outcomes. 2022 04; 15(4):e008900.
    View in: PubMed
    Score: 0.013
  24. 2021 Interim Guidance to Health Care Providers for Basic and Advanced Cardiac Life Support in Adults, Children, and Neonates With Suspected or Confirmed COVID-19. Circ Cardiovasc Qual Outcomes. 2021 10; 14(10):e008396.
    View in: PubMed
    Score: 0.013
  25. Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury. JAMA Netw Open. 2020 08 03; 3(8):e2012892.
    View in: PubMed
    Score: 0.012
  26. Accuracy of Clinicians' Ability to Predict the Need for Intensive Care Unit Readmission. Ann Am Thorac Soc. 2020 07; 17(7):847-853.
    View in: PubMed
    Score: 0.012
  27. Predicting clinical deterioration with Q-ADDS compared to NEWS, Between the Flags, and eCART track and trigger tools. Resuscitation. 2020 08; 153:28-34.
    View in: PubMed
    Score: 0.011
  28. Characteristics and outcomes of maternal cardiac arrest: A descriptive analysis of Get with the guidelines data. Resuscitation. 2018 11; 132:17-20.
    View in: PubMed
    Score: 0.010
  29. 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.
    View in: PubMed
    Score: 0.010
  30. Association Between Opioid and Benzodiazepine Use and Clinical Deterioration in Ward Patients. J Hosp Med. 2017 06; 12(6):428-434.
    View in: PubMed
    Score: 0.009
  31. Association Between In-Hospital Critical Illness Events and Outcomes in Patients on the Same Ward. JAMA. 2016 12 27; 316(24):2674-2675.
    View in: PubMed
    Score: 0.009
  32. Development of a Multicenter Ward-Based AKI Prediction Model. Clin J Am Soc Nephrol. 2016 11 07; 11(11):1935-1943.
    View in: PubMed
    Score: 0.009
  33. Obstructive sleep apnea and adverse outcomes in surgical and nonsurgical patients on the wards. J Hosp Med. 2015 Sep; 10(9):592-8.
    View in: PubMed
    Score: 0.008
  34. Neurologic prognostication and bispectral index monitoring after resuscitation from cardiac arrest. Resuscitation. 2010 Sep; 81(9):1133-7.
    View in: PubMed
    Score: 0.006
  35. Lamotrigine: an unusual etiology for aseptic meningitis. Neurologist. 2010 Jan; 16(1):35-6.
    View in: PubMed
    Score: 0.006
  36. Quality of cardiopulmonary resuscitation during in-hospital cardiac arrest. JAMA. 2005 Jan 19; 293(3):305-10.
    View in: PubMed
    Score: 0.004
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.