Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain
Aims: Existing risk scores for undifferentiated chest pain focus on excluding coronary events and do not represent a comprehensive risk assessment if an alternate serious diagnosis is present. This study aimed to develop and validate an all-inclusive risk prediction model among patients with undiffe...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-06-01
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| Series: | International Journal of Cardiology: Heart & Vasculature |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352906722000926 |
| _version_ | 1811231717904613376 |
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| author | Luke P. Dawson Emily Andrew Ziad Nehme Jason Bloom Danny Liew Shelley Cox David Anderson Michael Stephenson Jeffrey Lefkovits Andrew J. Taylor David Kaye Louise Cullen Karen Smith Dion Stub |
| author_facet | Luke P. Dawson Emily Andrew Ziad Nehme Jason Bloom Danny Liew Shelley Cox David Anderson Michael Stephenson Jeffrey Lefkovits Andrew J. Taylor David Kaye Louise Cullen Karen Smith Dion Stub |
| author_sort | Luke P. Dawson |
| collection | DOAJ |
| description | Aims: Existing risk scores for undifferentiated chest pain focus on excluding coronary events and do not represent a comprehensive risk assessment if an alternate serious diagnosis is present. This study aimed to develop and validate an all-inclusive risk prediction model among patients with undifferentiated chest pain. Methods: We developed and validated a multivariable logistic regression model for a composite measure of early all-inclusive risk (defined as hospital admission excluding a discharge diagnosis of non-specific pain, 30-day all-cause mortality, or 30-day myocardial infarction [MI]) among adults assessed by emergency medical services (EMS) for non-traumatic chest pain using a large population-based cohort (January 2015 to June 2019). The cohort was randomly divided into development (146,507 patients [70%]) and validation (62,788 patients [30%]) cohorts. Results: The composite outcome occurred in 28.4%, comprising hospital admission in 27.7%, mortality within 30-days in 1.8%, and MI within 30-days in 0.4%. The Early Chest pain Admission, MI, and Mortality (ECAMM) risk model was developed, demonstrating good discrimination in the development (C-statistic 0.775, 95% CI 0.772–0.777) and validation cohorts (C-statistic 0.765, 95% CI 0.761–0.769) with excellent calibration. Discriminatory performance for the composite outcome and individual components was higher than existing scores commonly used in undifferentiated chest pain risk stratification. Conclusions: The ECAMM risk score model can be used as an all-inclusive risk stratification assessment of patients with non-traumatic chest pain without the limitation of a single diagnostic outcome. This model could be clinically useful to help guide decisions surrounding the need for non-coronary investigations and safety of early discharge. |
| first_indexed | 2024-04-12T10:49:43Z |
| format | Article |
| id | doaj.art-24656e28c881413eac2ffbf31888f6aa |
| institution | Directory Open Access Journal |
| issn | 2352-9067 |
| language | English |
| last_indexed | 2024-04-12T10:49:43Z |
| publishDate | 2022-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Cardiology: Heart & Vasculature |
| spelling | doaj.art-24656e28c881413eac2ffbf31888f6aa2022-12-22T03:36:16ZengElsevierInternational Journal of Cardiology: Heart & Vasculature2352-90672022-06-0140101043Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest painLuke P. Dawson0Emily Andrew1Ziad Nehme2Jason Bloom3Danny Liew4Shelley Cox5David Anderson6Michael Stephenson7Jeffrey Lefkovits8Andrew J. Taylor9David Kaye10Louise Cullen11Karen Smith12Dion Stub13Department of Cardiology, The Alfred Hospital, Melbourne, Victoria, Australia; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Department of Cardiology, The Royal Melbourne Hospital, Melbourne, Victoria, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Ambulance Victoria, Melbourne, Victoria, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Ambulance Victoria, Melbourne, Victoria, Australia; Department of Paramedicine, Monash University, Melbourne, Victoria, AustraliaDepartment of Cardiology, The Alfred Hospital, Melbourne, Victoria, Australia; The Baker Institute, Melbourne, Victoria, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Ambulance Victoria, Melbourne, Victoria, AustraliaAmbulance Victoria, Melbourne, Victoria, Australia; Department of Intensive Care Medicine, The Alfred Hospital, Melbourne, Victoria, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Ambulance Victoria, Melbourne, Victoria, Australia; Department of Paramedicine, Monash University, Melbourne, Victoria, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Department of Cardiology, The Royal Melbourne Hospital, Melbourne, Victoria, AustraliaDepartment of Cardiology, The Alfred Hospital, Melbourne, Victoria, Australia; Department of Medicine, Monash University, Victoria, AustraliaDepartment of Cardiology, The Alfred Hospital, Melbourne, Victoria, Australia; The Baker Institute, Melbourne, Victoria, AustraliaEmergency and Trauma Centre, Royal Brisbane and Women’s Hospital, Brisbane, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; Ambulance Victoria, Melbourne, Victoria, Australia; Department of Paramedicine, Monash University, Melbourne, Victoria, AustraliaDepartment of Cardiology, The Alfred Hospital, Melbourne, Victoria, Australia; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; The Baker Institute, Melbourne, Victoria, Australia; Corresponding author at: Monash University Department of Epidemiology and Preventive Medicine and Alfred Health, 55 Commercial Rd, Prahran, Victoria 3004, Australia.Aims: Existing risk scores for undifferentiated chest pain focus on excluding coronary events and do not represent a comprehensive risk assessment if an alternate serious diagnosis is present. This study aimed to develop and validate an all-inclusive risk prediction model among patients with undifferentiated chest pain. Methods: We developed and validated a multivariable logistic regression model for a composite measure of early all-inclusive risk (defined as hospital admission excluding a discharge diagnosis of non-specific pain, 30-day all-cause mortality, or 30-day myocardial infarction [MI]) among adults assessed by emergency medical services (EMS) for non-traumatic chest pain using a large population-based cohort (January 2015 to June 2019). The cohort was randomly divided into development (146,507 patients [70%]) and validation (62,788 patients [30%]) cohorts. Results: The composite outcome occurred in 28.4%, comprising hospital admission in 27.7%, mortality within 30-days in 1.8%, and MI within 30-days in 0.4%. The Early Chest pain Admission, MI, and Mortality (ECAMM) risk model was developed, demonstrating good discrimination in the development (C-statistic 0.775, 95% CI 0.772–0.777) and validation cohorts (C-statistic 0.765, 95% CI 0.761–0.769) with excellent calibration. Discriminatory performance for the composite outcome and individual components was higher than existing scores commonly used in undifferentiated chest pain risk stratification. Conclusions: The ECAMM risk score model can be used as an all-inclusive risk stratification assessment of patients with non-traumatic chest pain without the limitation of a single diagnostic outcome. This model could be clinically useful to help guide decisions surrounding the need for non-coronary investigations and safety of early discharge.http://www.sciencedirect.com/science/article/pii/S2352906722000926Chest painPre-hospitalEmergency medical servicesRisk scorePrediction model |
| spellingShingle | Luke P. Dawson Emily Andrew Ziad Nehme Jason Bloom Danny Liew Shelley Cox David Anderson Michael Stephenson Jeffrey Lefkovits Andrew J. Taylor David Kaye Louise Cullen Karen Smith Dion Stub Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain International Journal of Cardiology: Heart & Vasculature Chest pain Pre-hospital Emergency medical services Risk score Prediction model |
| title | Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain |
| title_full | Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain |
| title_fullStr | Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain |
| title_full_unstemmed | Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain |
| title_short | Development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain |
| title_sort | development and validation of a comprehensive early risk prediction model for patients with undifferentiated acute chest pain |
| topic | Chest pain Pre-hospital Emergency medical services Risk score Prediction model |
| url | http://www.sciencedirect.com/science/article/pii/S2352906722000926 |
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