Publications eCART

Featured

American Thoracic Society, American Journal of Respiratory and Critical Care Medicine

Infection Specific Versus General Early Warning Scores for Predicting Sepsis on a Medical-Surgical Ward: A Multicenter Analysis

Am J Respir Crit Care Med. 2025;211:A5678.

JAMA Network Open

Early Warning Scores With and Without Artificial Intelligence

JAMA Netw Open. 2024;7(10):e2438986.

Critical Care Explorations

Causes, Diagnostic Testing, and Treatments Related to Clinical Deterioration Events Among High-Risk Ward Patients

Crit Care Explor. 2024;6(10):e1161.

U.S. Food and Drug Administration

510(k) Summary: eCARTv5 Clinical Deterioration Suite (“eCART”)

U.S. Food and Drug Administration. Premarket Notification (K233253), May 17, 2024.

Circulation

Measuring the Return on Investment of an Artificial Intelligence (AI) Early Warning System

Circulation. 2023;148(Suppl 1: Abstract 350).

Critical Care Medicine

The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial

Crit Care Med. 2022;50(9):1339-1347.

Additional

Circulation

The Benefits of Proactive Versus Reactive Rapid Response Activations

Circulation. 2025;152(Suppl 3).

2025

Critical Care Explorations

Multicenter Development and Prospective Validation of eCARTv5: A Gradient Boosted Machine Learning Early Warning Score

Crit Care Explor. 2025;7(4):e1232.

2025

Pediatric Critical Care Medicine

Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019–2023

Pediatric Critical Care Medicine. 2025;26(2):p e146-e154.

2025

Resuscitation

A novel structured debriefing program for consensus determinations of in-hospital cardiac arrest predictability and preventability

Resuscitation. 2024;197:110161.

2024

BMC Pregnancy Childbirth

Comparison of early warning scores for predicting clinical deterioration and infection in obstetric patients

BMC Pregnancy Childbirth. 2022;22(1):295.

2022

Resuscitation

Less is More: Detecting Clinical Deterioration in the Hospital with Machine Learning Using Only Age, Heart Rate, and Respiratory Rate

Resuscitation. 2021;168:6-10.

2021

Critical Care Medicine

Scratching the Surface of Clinical Deterioration With Deep Learning

Crit Care Med. 2021;49(8):1366-1368.

2021

Critical Care Medicine

Determining the Electronic Signature of Infection in Electronic Health Record Data

Crit Care Med. 2021;49(7):e673-e682.

2021

JAMA Network Open

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury

JAMA Netw Open. 2020;3(8):e2012892.

2020

Resuscitation

Predicting clinical deterioration with Q-ADDS compared to NEWS, Between the Flags, and eCART track and trigger tools

Resuscitation. 2020;153:28-34.

2020

Annals of the American Thoracic Society

Accuracy of Clinicians' Ability to Predict the Need for Intensive Care Unit Readmission

Ann Am Thorac Soc. 2020;17(7):847-853.

2020

JAMA Network Open

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;3(5):e205191.

2020

Critical Care Medicine

Validation of Early Warning Scores at Two Long-Term Acute Care Hospitals

Crit Care Med. 2019;47(12):e962-e965.

2019

Annals of Surgery

Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting

Ann Surg. 2019;269(6):1059-1063.

2019

Catheterization and Cardiovascular Interventions

Electronic cardiac arrest triage score best predicts mortality after intervention in patients with massive and submassive pulmonary embolism.

Catheter Cardiovasc Interv. 2018;92(2):366-371.

2018

Critical Care Medicine

American Heart Association’s Get With The Guidelines-Resuscitation Investigators. Predictors of In-Hospital Mortality After Rapid Response Team Calls in a 274 Hospital Nationwide Sample

Crit Care Med. 2018;46(7):1041-1048.

2018

Annals of the American Thoracic Society

Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data

Ann Am Thorac Soc. 2018;15(7):846-853.

2018

Chest

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;154(2):302-308.

2018

Journal of Hospital Medicine

Accuracy Comparisons between Manual and Automated Respiratory Rate for Detecting Clinical Deterioration in Ward Patients

J Hosp Med. 2018;13(7):486-487.

2018

Resuscitation

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;123:86–91.

2017

Critical Care Medicine

Investigating the impact of different suspicion of infection criteria on the accuracy of qSOFA, SIRS, and early warning scores

Crit Care Med. 2017;45(11):1805-1812.

2017

Journal of Hospital Medicine

Association Between Opioid and Benzodiazepine Use and Clinical Deterioration in Ward Patients

J Hosp Med. 2017;12(6):428-434.

2017

Annals of Internal Medicine

Annals for Hospitalists Inpatient Notes - Predicting Codes-A Future With Fewer In-Hospital Cardiac Arrests

Ann Intern Med. 2017;166(10):HO2-HO3.

2017

American Journal of Respiratory and Critical Care Medicine

Quick sepsis-related organ failure assessment, systemic inflammatory response syndrome, and early warning scores for detecting clinical deterioration in infected patients outside the intensive care unit

Am J Respir Crit Care Med. 2017;195(7):906-911.

2017

Chest

Identifying Patients With Sepsis on the Hospital Wards

Chest. 2017;151(4):898-907.

2017

Critical Care Medicine

Moving Beyond Single-Parameter Early Warning Scores for Rapid Response System Activation

Crit Care Med. 2016;44(12):2283-2285.

2016

Clinical Journal of the American Society of Nephrology

Development of a Multicenter Ward-Based AKI Prediction Model

Clin J Am Soc Nephrol. 2016;11(11):1935-1943.

2016

Critical Care Medicine

Real-Time Risk Prediction on the Wards: A Feasibility Study.

Crit Care Med. 2016;44(8):1468-1473.

2016

Journal of Hospital Medicine

Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation

J Hosp Med. 2016;11(11):757-762.

2016

Resuscitation

The value of vital sign trends for detecting clinical deterioration on the wards

Resuscitation. 2016;102:1-5.

2016

Critical Care Medicine

Multicenter comparison of machine learning methods and conventional regression for predicting clinical deterioration on the wards

Crit Care Med. 2016;44(2):368-374.

2016

Journal of Hospital Medicine

In reference to "Development, implementation, and impact of an automated early warning and response system for sepsis"

J Hosp Med. 2015;10(5):340.

2015

JAMA Internal Medicine

The value of clinical judgment in the detection of clinical deterioration

JAMA Intern Med. 2015;175(3):456–458.

2015

American Journal of Respiratory and Critical Care Medicine

Multicenter development and validation of a risk stratification tool for ward patients

Am J Respir Crit Care Med. 2014;190(6):649-655.

2014

Critical Care Medicine

Using electronic health record data to develop and validate a prediction model for adverse outcomes in the wards

Crit Care Med. 2014;42(4):841-848.

2014

JAMA Internal Medicine

Acutely ill patients will likely benefit from more monitoring, not less--reply

JAMA Intern Med. 2014;174(3):475-476.

2014

JAMA Internal Medicine

A prospective study of nighttime vital sign monitoring frequency and risk of clinical deterioration

JAMA Intern Med. 2013;173(16):1554-1555.

2013

Chest

Risk stratification of hospitalized patients on the wards.

Chest. 2013;143(6):1758-1765.

2013

Journal of General Internal Medicine

Supplementing cross-cover communication with the patient acuity rating

J Gen Intern Med. 2013;28(3):406-411.

2012

Resuscitation

Predicting clinical deterioration in the hospital: the impact of outcome selection

Resuscitation. 2013;84(5):564-568.

2012

Critical Care Medicine

Derivation of a cardiac arrest prediction model using ward vital signs

Crit Care Med. 2012;40(7):2102-2108.

2012

Chest

Predicting cardiac arrest on the wards: a nested case-control study

Chest. 2012;141(5):1170-1176.

2012

Journal of Hospital Medicine

The Patient Acuity Rating: Quantifying clinical judgment regarding inpatient stability

J Hosp Med. 2011; 6(8):480-8.

2011

Publications

eCART™

Featured

Infection Specific Versus General Early Warning Scores for Predicting Sepsis on a Medical-Surgical Ward: A Multicenter Analysis

Early Warning Scores With and Without Artificial Intelligence

Causes, Diagnostic Testing, and Treatments Related to Clinical Deterioration Events Among High-Risk Ward Patients

510(k) Summary: eCARTv5 Clinical Deterioration Suite (“eCART”)

Measuring the Return on Investment of an Artificial Intelligence (AI) Early Warning System

The Impact of a Machine Learning Early Warning Score on Hospital Mortality: A Multicenter Clinical Intervention Trial

Additional

The Benefits of Proactive Versus Reactive Rapid Response Activations

Multicenter Development and Prospective Validation of eCARTv5: A Gradient Boosted Machine Learning Early Warning Score

Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019–2023

A novel structured debriefing program for consensus determinations of in-hospital cardiac arrest predictability and preventability

Comparison of early warning scores for predicting clinical deterioration and infection in obstetric patients

Less is More: Detecting Clinical Deterioration in the Hospital with Machine Learning Using Only Age, Heart Rate, and Respiratory Rate

Scratching the Surface of Clinical Deterioration With Deep Learning

Determining the Electronic Signature of Infection in Electronic Health Record Data

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury

Predicting clinical deterioration with Q-ADDS compared to NEWS, Between the Flags, and eCART track and trigger tools

Accuracy of Clinicians' Ability to Predict the Need for Intensive Care Unit Readmission

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

Validation of Early Warning Scores at Two Long-Term Acute Care Hospitals

Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting

Electronic cardiac arrest triage score best predicts mortality after intervention in patients with massive and submassive pulmonary embolism.

American Heart Association’s Get With The Guidelines-Resuscitation Investigators. Predictors of In-Hospital Mortality After Rapid Response Team Calls in a 274 Hospital Nationwide Sample

Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data

Implications of Centers for Medicare & Medicaid Services Severe Sepsis and Septic Shock Early Management Bundle and Initial Lactate Measurement on the Management of Sepsis

Accuracy Comparisons between Manual and Automated Respiratory Rate for Detecting Clinical Deterioration in Ward Patients

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

Investigating the impact of different suspicion of infection criteria on the accuracy of qSOFA, SIRS, and early warning scores

Association Between Opioid and Benzodiazepine Use and Clinical Deterioration in Ward Patients

Annals for Hospitalists Inpatient Notes - Predicting Codes-A Future With Fewer In-Hospital Cardiac Arrests

Quick sepsis-related organ failure assessment, systemic inflammatory response syndrome, and early warning scores for detecting clinical deterioration in infected patients outside the intensive care unit

Identifying Patients With Sepsis on the Hospital Wards

Moving Beyond Single-Parameter Early Warning Scores for Rapid Response System Activation

Development of a Multicenter Ward-Based AKI Prediction Model

Real-Time Risk Prediction on the Wards: A Feasibility Study.

Association between intensive care unit transfer delay and hospital mortality: A multicenter investigation

The value of vital sign trends for detecting clinical deterioration on the wards

Multicenter comparison of machine learning methods and conventional regression for predicting clinical deterioration on the wards

In reference to "Development, implementation, and impact of an automated early warning and response system for sepsis"

The value of clinical judgment in the detection of clinical deterioration

Multicenter development and validation of a risk stratification tool for ward patients

Using electronic health record data to develop and validate a prediction model for adverse outcomes in the wards

Acutely ill patients will likely benefit from more monitoring, not less--reply

A prospective study of nighttime vital sign monitoring frequency and risk of clinical deterioration

Risk stratification of hospitalized patients on the wards.

Supplementing cross-cover communication with the patient acuity rating

Predicting clinical deterioration in the hospital: the impact of outcome selection

Derivation of a cardiac arrest prediction model using ward vital signs

Predicting cardiac arrest on the wards: a nested case-control study

The Patient Acuity Rating: Quantifying clinical judgment regarding inpatient stability

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