Emergency medical service predictive instrument-Aided diagnosis and treatment of acute coronary syndromes and st-segment elevation myocardial infarction in the immediate trial

Harry P. Selker, Joni R. Beshansky, Robin Ruthazer, Patricia R. Sheehan, Assaad J. Sayah, James M Atkins, Tom P. Aufderheide, Ronald G. Pirrallo, Ralph B. D'Agostino, Joseph M. Massaro, John L. Griffith

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Background. A challenge for emergency medical service (EMS) is accurate identification of acute coronary syndromes (ACS) and ST-segment elevation myocardial infarction (STEMI) for immediate treatment and transport. The electrocardiograph-based acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) and the thrombolytic predictive instrument (TPI) have been shown to improve diagnosis and treatment in emergency departments (EDs), but their use by paramedics in the community has been less studied. Objective. To identify candidates for participation in the Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency Care (IMMEDIATE) Trial, we implemented EMS use of the ACI-TIPI and the TPI in out-of-hospital electrocardiographs and evaluated its impact on paramedic on-site identification of ACS and STEMI as a community-based approach to improving emergency cardiac care. Methods. Ambulances in the study municipalities were outfitted with electrocardiographs with ACI-TIPI and TPI software. Using a before-after quasi-experimental design, in Phase 1, for seven months, paramedics were provided with the ACI-TIPI/TPI continuous 0-100% predictions automatically printed on electrocardiogram (ECG) text headers to supplement their identification of ACS; in Phase 2, for 11 months, paramedics were told to identify ACS based on an ACI-TIPI cutoff probability of ACS ≥ 75% and/or TPI detection of STEMI. In Phase 3, this cutoff approach was used in seven additional municipalities. Confirmed diagnoses of ACS, acute myocardial infarction (AMI), and STEMI were made by blinded physician review for 100% of patients. Results. In Phase 1, paramedics identified 107 patients as having ACS; in Phase 2, 104. In Phase 1, 45.8% (49) of patients so identified had ACS confirmed, which increased to 76.0% (79) in Phase 2 (p < 0.001). Of those with ACS, 59.2% (29) had AMI in Phase 1 versus 84.8% (67) with AMI in Phase 2 (p < 0.01), and STEMI was confirmed in 40.8% (20) versus 68.4% (54), respectively (p < 0.01). In Phase 3, of 226 patients identified by paramedics as having ACS, 74.3% (168) had ACS confirmed, of whom 81.0% (136) had AMI and 65.5% (110) had STEMI. Among patients with ACS, the proportion who received percutaneous coronary intervention (PCI) was 30.6% (15) in Phase 1, increasing to 57.0% (45) in Phase 2 (p < 0.004) and 50.6% (85) in Phase 3, and the proportions of patients with STEMI receiving PCI rose from 75.0% (15) to 83.3% (45) (p < 0.4) and 82.7% (91). Conclusions. In a wide range of EMS systems, use of electrocardiographs with ACI-TIPI and TPI decision support using a 75% ACI-TIPI cutoff improves paramedic diagnostic performance for ACS, AMI, and STEMI and increases the proportions of patients who receive PCI.

Original languageEnglish (US)
Pages (from-to)139-148
Number of pages10
JournalPrehospital Emergency Care
Volume15
Issue number2
DOIs
StatePublished - Apr 2011

Fingerprint

Emergency Medical Services
Acute Coronary Syndrome
Myocardial Infarction
Allied Health Personnel
Ischemia
Electrocardiography
Therapeutics
Percutaneous Coronary Intervention
Ambulances
Hospital Emergency Service
Research Design
Software

Keywords

  • acute coronary syndromes
  • acute myocardial infarction
  • clinical decision support
  • electrocardiology
  • emergency medical service

ASJC Scopus subject areas

  • Emergency Medicine
  • Emergency
  • Medicine(all)

Cite this

Emergency medical service predictive instrument-Aided diagnosis and treatment of acute coronary syndromes and st-segment elevation myocardial infarction in the immediate trial. / Selker, Harry P.; Beshansky, Joni R.; Ruthazer, Robin; Sheehan, Patricia R.; Sayah, Assaad J.; Atkins, James M; Aufderheide, Tom P.; Pirrallo, Ronald G.; D'Agostino, Ralph B.; Massaro, Joseph M.; Griffith, John L.

In: Prehospital Emergency Care, Vol. 15, No. 2, 04.2011, p. 139-148.

Research output: Contribution to journalArticle

Selker, HP, Beshansky, JR, Ruthazer, R, Sheehan, PR, Sayah, AJ, Atkins, JM, Aufderheide, TP, Pirrallo, RG, D'Agostino, RB, Massaro, JM & Griffith, JL 2011, 'Emergency medical service predictive instrument-Aided diagnosis and treatment of acute coronary syndromes and st-segment elevation myocardial infarction in the immediate trial', Prehospital Emergency Care, vol. 15, no. 2, pp. 139-148. https://doi.org/10.3109/10903127.2010.545478
Selker, Harry P. ; Beshansky, Joni R. ; Ruthazer, Robin ; Sheehan, Patricia R. ; Sayah, Assaad J. ; Atkins, James M ; Aufderheide, Tom P. ; Pirrallo, Ronald G. ; D'Agostino, Ralph B. ; Massaro, Joseph M. ; Griffith, John L. / Emergency medical service predictive instrument-Aided diagnosis and treatment of acute coronary syndromes and st-segment elevation myocardial infarction in the immediate trial. In: Prehospital Emergency Care. 2011 ; Vol. 15, No. 2. pp. 139-148.
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abstract = "Background. A challenge for emergency medical service (EMS) is accurate identification of acute coronary syndromes (ACS) and ST-segment elevation myocardial infarction (STEMI) for immediate treatment and transport. The electrocardiograph-based acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) and the thrombolytic predictive instrument (TPI) have been shown to improve diagnosis and treatment in emergency departments (EDs), but their use by paramedics in the community has been less studied. Objective. To identify candidates for participation in the Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency Care (IMMEDIATE) Trial, we implemented EMS use of the ACI-TIPI and the TPI in out-of-hospital electrocardiographs and evaluated its impact on paramedic on-site identification of ACS and STEMI as a community-based approach to improving emergency cardiac care. Methods. Ambulances in the study municipalities were outfitted with electrocardiographs with ACI-TIPI and TPI software. Using a before-after quasi-experimental design, in Phase 1, for seven months, paramedics were provided with the ACI-TIPI/TPI continuous 0-100{\%} predictions automatically printed on electrocardiogram (ECG) text headers to supplement their identification of ACS; in Phase 2, for 11 months, paramedics were told to identify ACS based on an ACI-TIPI cutoff probability of ACS ≥ 75{\%} and/or TPI detection of STEMI. In Phase 3, this cutoff approach was used in seven additional municipalities. Confirmed diagnoses of ACS, acute myocardial infarction (AMI), and STEMI were made by blinded physician review for 100{\%} of patients. Results. In Phase 1, paramedics identified 107 patients as having ACS; in Phase 2, 104. In Phase 1, 45.8{\%} (49) of patients so identified had ACS confirmed, which increased to 76.0{\%} (79) in Phase 2 (p < 0.001). Of those with ACS, 59.2{\%} (29) had AMI in Phase 1 versus 84.8{\%} (67) with AMI in Phase 2 (p < 0.01), and STEMI was confirmed in 40.8{\%} (20) versus 68.4{\%} (54), respectively (p < 0.01). In Phase 3, of 226 patients identified by paramedics as having ACS, 74.3{\%} (168) had ACS confirmed, of whom 81.0{\%} (136) had AMI and 65.5{\%} (110) had STEMI. Among patients with ACS, the proportion who received percutaneous coronary intervention (PCI) was 30.6{\%} (15) in Phase 1, increasing to 57.0{\%} (45) in Phase 2 (p < 0.004) and 50.6{\%} (85) in Phase 3, and the proportions of patients with STEMI receiving PCI rose from 75.0{\%} (15) to 83.3{\%} (45) (p < 0.4) and 82.7{\%} (91). Conclusions. In a wide range of EMS systems, use of electrocardiographs with ACI-TIPI and TPI decision support using a 75{\%} ACI-TIPI cutoff improves paramedic diagnostic performance for ACS, AMI, and STEMI and increases the proportions of patients who receive PCI.",
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T1 - Emergency medical service predictive instrument-Aided diagnosis and treatment of acute coronary syndromes and st-segment elevation myocardial infarction in the immediate trial

AU - Selker, Harry P.

AU - Beshansky, Joni R.

AU - Ruthazer, Robin

AU - Sheehan, Patricia R.

AU - Sayah, Assaad J.

AU - Atkins, James M

AU - Aufderheide, Tom P.

AU - Pirrallo, Ronald G.

AU - D'Agostino, Ralph B.

AU - Massaro, Joseph M.

AU - Griffith, John L.

PY - 2011/4

Y1 - 2011/4

N2 - Background. A challenge for emergency medical service (EMS) is accurate identification of acute coronary syndromes (ACS) and ST-segment elevation myocardial infarction (STEMI) for immediate treatment and transport. The electrocardiograph-based acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) and the thrombolytic predictive instrument (TPI) have been shown to improve diagnosis and treatment in emergency departments (EDs), but their use by paramedics in the community has been less studied. Objective. To identify candidates for participation in the Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency Care (IMMEDIATE) Trial, we implemented EMS use of the ACI-TIPI and the TPI in out-of-hospital electrocardiographs and evaluated its impact on paramedic on-site identification of ACS and STEMI as a community-based approach to improving emergency cardiac care. Methods. Ambulances in the study municipalities were outfitted with electrocardiographs with ACI-TIPI and TPI software. Using a before-after quasi-experimental design, in Phase 1, for seven months, paramedics were provided with the ACI-TIPI/TPI continuous 0-100% predictions automatically printed on electrocardiogram (ECG) text headers to supplement their identification of ACS; in Phase 2, for 11 months, paramedics were told to identify ACS based on an ACI-TIPI cutoff probability of ACS ≥ 75% and/or TPI detection of STEMI. In Phase 3, this cutoff approach was used in seven additional municipalities. Confirmed diagnoses of ACS, acute myocardial infarction (AMI), and STEMI were made by blinded physician review for 100% of patients. Results. In Phase 1, paramedics identified 107 patients as having ACS; in Phase 2, 104. In Phase 1, 45.8% (49) of patients so identified had ACS confirmed, which increased to 76.0% (79) in Phase 2 (p < 0.001). Of those with ACS, 59.2% (29) had AMI in Phase 1 versus 84.8% (67) with AMI in Phase 2 (p < 0.01), and STEMI was confirmed in 40.8% (20) versus 68.4% (54), respectively (p < 0.01). In Phase 3, of 226 patients identified by paramedics as having ACS, 74.3% (168) had ACS confirmed, of whom 81.0% (136) had AMI and 65.5% (110) had STEMI. Among patients with ACS, the proportion who received percutaneous coronary intervention (PCI) was 30.6% (15) in Phase 1, increasing to 57.0% (45) in Phase 2 (p < 0.004) and 50.6% (85) in Phase 3, and the proportions of patients with STEMI receiving PCI rose from 75.0% (15) to 83.3% (45) (p < 0.4) and 82.7% (91). Conclusions. In a wide range of EMS systems, use of electrocardiographs with ACI-TIPI and TPI decision support using a 75% ACI-TIPI cutoff improves paramedic diagnostic performance for ACS, AMI, and STEMI and increases the proportions of patients who receive PCI.

AB - Background. A challenge for emergency medical service (EMS) is accurate identification of acute coronary syndromes (ACS) and ST-segment elevation myocardial infarction (STEMI) for immediate treatment and transport. The electrocardiograph-based acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) and the thrombolytic predictive instrument (TPI) have been shown to improve diagnosis and treatment in emergency departments (EDs), but their use by paramedics in the community has been less studied. Objective. To identify candidates for participation in the Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency Care (IMMEDIATE) Trial, we implemented EMS use of the ACI-TIPI and the TPI in out-of-hospital electrocardiographs and evaluated its impact on paramedic on-site identification of ACS and STEMI as a community-based approach to improving emergency cardiac care. Methods. Ambulances in the study municipalities were outfitted with electrocardiographs with ACI-TIPI and TPI software. Using a before-after quasi-experimental design, in Phase 1, for seven months, paramedics were provided with the ACI-TIPI/TPI continuous 0-100% predictions automatically printed on electrocardiogram (ECG) text headers to supplement their identification of ACS; in Phase 2, for 11 months, paramedics were told to identify ACS based on an ACI-TIPI cutoff probability of ACS ≥ 75% and/or TPI detection of STEMI. In Phase 3, this cutoff approach was used in seven additional municipalities. Confirmed diagnoses of ACS, acute myocardial infarction (AMI), and STEMI were made by blinded physician review for 100% of patients. Results. In Phase 1, paramedics identified 107 patients as having ACS; in Phase 2, 104. In Phase 1, 45.8% (49) of patients so identified had ACS confirmed, which increased to 76.0% (79) in Phase 2 (p < 0.001). Of those with ACS, 59.2% (29) had AMI in Phase 1 versus 84.8% (67) with AMI in Phase 2 (p < 0.01), and STEMI was confirmed in 40.8% (20) versus 68.4% (54), respectively (p < 0.01). In Phase 3, of 226 patients identified by paramedics as having ACS, 74.3% (168) had ACS confirmed, of whom 81.0% (136) had AMI and 65.5% (110) had STEMI. Among patients with ACS, the proportion who received percutaneous coronary intervention (PCI) was 30.6% (15) in Phase 1, increasing to 57.0% (45) in Phase 2 (p < 0.004) and 50.6% (85) in Phase 3, and the proportions of patients with STEMI receiving PCI rose from 75.0% (15) to 83.3% (45) (p < 0.4) and 82.7% (91). Conclusions. In a wide range of EMS systems, use of electrocardiographs with ACI-TIPI and TPI decision support using a 75% ACI-TIPI cutoff improves paramedic diagnostic performance for ACS, AMI, and STEMI and increases the proportions of patients who receive PCI.

KW - acute coronary syndromes

KW - acute myocardial infarction

KW - clinical decision support

KW - electrocardiology

KW - emergency medical service

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