Development and validation of a cardiovascular risk score for patients in the community after acute coronary syndrome
ObjectiveFollowing acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed...
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Published in | Heart (British Cardiac Society) Vol. 106; no. 7; pp. 506 - 511 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
BMJ Publishing Group Ltd and British Cardiovascular Society
01.04.2020
BMJ Publishing Group LTD |
Subjects | |
Online Access | Get full text |
ISSN | 1355-6037 1468-201X 1468-201X |
DOI | 10.1136/heartjnl-2019-315809 |
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Abstract | ObjectiveFollowing acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed in the community after ACS.MethodsAdults aged 30–79 years with prior ACS were identified from a New Zealand primary care CVD risk management database (PREDICT) with linkage to national mortality, hospitalisation, pharmaceutical dispensing and regional laboratory data. A Cox model incorporating clinically relevant factors was developed to estimate the time to a subsequent fatal or non-fatal CVD event and transformed into a 5-year risk score. External validation was performed in patients (Coronary Disease Cohort Study) assessed 4 months post-ACS.ResultsThe PREDICT-ACS cohort included 13 703 patients with prior hospitalisation for ACS (median 1.9 years prior), 69% men, 58% European, median age 63 years, who experienced 3142 CVD events in the subsequent 5 years. Median estimated 5 year CVD risk was 24% (IQR 17%–35%). The validation cohort consisted of 2014 patients, 72% men, 92% European, median age 67 years, with 712 CVD events in the subsequent 5 years. Median estimated 5-year risk was 33% (IQR 24%–51%). The risk score was well calibrated in the derivation and validation cohorts, and Harrell’s c-statistic was 0.69 and 0.68, respectively.ConclusionsThe PREDICT-ACS risk score uses data routinely available in community care to predict the risk of recurrent clinical events. It was derived and validated in real-world contemporary populations and can inform management decisions with patients living in the community after experiencing an ACS. |
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AbstractList | ObjectiveFollowing acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed in the community after ACS.MethodsAdults aged 30–79 years with prior ACS were identified from a New Zealand primary care CVD risk management database (PREDICT) with linkage to national mortality, hospitalisation, pharmaceutical dispensing and regional laboratory data. A Cox model incorporating clinically relevant factors was developed to estimate the time to a subsequent fatal or non-fatal CVD event and transformed into a 5-year risk score. External validation was performed in patients (Coronary Disease Cohort Study) assessed 4 months post-ACS.ResultsThe PREDICT-ACS cohort included 13 703 patients with prior hospitalisation for ACS (median 1.9 years prior), 69% men, 58% European, median age 63 years, who experienced 3142 CVD events in the subsequent 5 years. Median estimated 5 year CVD risk was 24% (IQR 17%–35%). The validation cohort consisted of 2014 patients, 72% men, 92% European, median age 67 years, with 712 CVD events in the subsequent 5 years. Median estimated 5-year risk was 33% (IQR 24%–51%). The risk score was well calibrated in the derivation and validation cohorts, and Harrell’s c-statistic was 0.69 and 0.68, respectively.ConclusionsThe PREDICT-ACS risk score uses data routinely available in community care to predict the risk of recurrent clinical events. It was derived and validated in real-world contemporary populations and can inform management decisions with patients living in the community after experiencing an ACS. Following acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed in the community after ACS. Adults aged 30-79 years with prior ACS were identified from a New Zealand primary care CVD risk management database (PREDICT) with linkage to national mortality, hospitalisation, pharmaceutical dispensing and regional laboratory data. A Cox model incorporating clinically relevant factors was developed to estimate the time to a subsequent fatal or non-fatal CVD event and transformed into a 5-year risk score. External validation was performed in patients (Coronary Disease Cohort Study) assessed 4 months post-ACS. The PREDICT-ACS cohort included 13 703 patients with prior hospitalisation for ACS (median 1.9 years prior), 69% men, 58% European, median age 63 years, who experienced 3142 CVD events in the subsequent 5 years. Median estimated 5 year CVD risk was 24% (IQR 17%-35%). The validation cohort consisted of 2014 patients, 72% men, 92% European, median age 67 years, with 712 CVD events in the subsequent 5 years. Median estimated 5-year risk was 33% (IQR 24%-51%). The risk score was well calibrated in the derivation and validation cohorts, and Harrell's c-statistic was 0.69 and 0.68, respectively. The PREDICT-ACS risk score uses data routinely available in community care to predict the risk of recurrent clinical events. It was derived and validated in real-world contemporary populations and can inform management decisions with patients living in the community after experiencing an ACS. Following acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed in the community after ACS.OBJECTIVEFollowing acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed in the community after ACS.Adults aged 30-79 years with prior ACS were identified from a New Zealand primary care CVD risk management database (PREDICT) with linkage to national mortality, hospitalisation, pharmaceutical dispensing and regional laboratory data. A Cox model incorporating clinically relevant factors was developed to estimate the time to a subsequent fatal or non-fatal CVD event and transformed into a 5-year risk score. External validation was performed in patients (Coronary Disease Cohort Study) assessed 4 months post-ACS.METHODSAdults aged 30-79 years with prior ACS were identified from a New Zealand primary care CVD risk management database (PREDICT) with linkage to national mortality, hospitalisation, pharmaceutical dispensing and regional laboratory data. A Cox model incorporating clinically relevant factors was developed to estimate the time to a subsequent fatal or non-fatal CVD event and transformed into a 5-year risk score. External validation was performed in patients (Coronary Disease Cohort Study) assessed 4 months post-ACS.The PREDICT-ACS cohort included 13 703 patients with prior hospitalisation for ACS (median 1.9 years prior), 69% men, 58% European, median age 63 years, who experienced 3142 CVD events in the subsequent 5 years. Median estimated 5 year CVD risk was 24% (IQR 17%-35%). The validation cohort consisted of 2014 patients, 72% men, 92% European, median age 67 years, with 712 CVD events in the subsequent 5 years. Median estimated 5-year risk was 33% (IQR 24%-51%). The risk score was well calibrated in the derivation and validation cohorts, and Harrell's c-statistic was 0.69 and 0.68, respectively.RESULTSThe PREDICT-ACS cohort included 13 703 patients with prior hospitalisation for ACS (median 1.9 years prior), 69% men, 58% European, median age 63 years, who experienced 3142 CVD events in the subsequent 5 years. Median estimated 5 year CVD risk was 24% (IQR 17%-35%). The validation cohort consisted of 2014 patients, 72% men, 92% European, median age 67 years, with 712 CVD events in the subsequent 5 years. Median estimated 5-year risk was 33% (IQR 24%-51%). The risk score was well calibrated in the derivation and validation cohorts, and Harrell's c-statistic was 0.69 and 0.68, respectively.The PREDICT-ACS risk score uses data routinely available in community care to predict the risk of recurrent clinical events. It was derived and validated in real-world contemporary populations and can inform management decisions with patients living in the community after experiencing an ACS.CONCLUSIONSThe PREDICT-ACS risk score uses data routinely available in community care to predict the risk of recurrent clinical events. It was derived and validated in real-world contemporary populations and can inform management decisions with patients living in the community after experiencing an ACS. |
Author | Poppe, Katrina K Wells, Susan Kerr, Andrew J Doughty, Rob N Richards, A Mark Earle, Nikki J Troughton, Richard W Wu, Billy Jackson, Rod |
Author_xml | – sequence: 1 givenname: Katrina K orcidid: 0000-0002-4418-4476 surname: Poppe fullname: Poppe, Katrina K email: k.poppe@auckland.ac.nz organization: Department of Medicine, University of Auckland, Auckland, New Zealand – sequence: 2 givenname: Rob N surname: Doughty fullname: Doughty, Rob N organization: Green Lane Cardiovascular Service, Auckland City Hospital, Auckland, New Zealand – sequence: 3 givenname: Susan surname: Wells fullname: Wells, Susan organization: Epidemiology & Biostatistics, University of Auckland, Auckland, New Zealand – sequence: 4 givenname: Billy surname: Wu fullname: Wu, Billy organization: Epidemiology & Biostatistics, University of Auckland, Auckland, New Zealand – sequence: 5 givenname: Nikki J surname: Earle fullname: Earle, Nikki J organization: Department of Medicine, University of Auckland, Auckland, New Zealand – sequence: 6 givenname: A Mark surname: Richards fullname: Richards, A Mark organization: Cardiovascular Research Institute, National University of Singapore, Singapore, Singapore – sequence: 7 givenname: Richard W surname: Troughton fullname: Troughton, Richard W organization: Christchurch Heart Institute, University of Otago Christchurch, Christchurch, New Zealand – sequence: 8 givenname: Rod orcidid: 0000-0001-5914-6934 surname: Jackson fullname: Jackson, Rod organization: Epidemiology & Biostatistics, University of Auckland, Auckland, New Zealand – sequence: 9 givenname: Andrew J surname: Kerr fullname: Kerr, Andrew J organization: Cardiology, Counties Manukau District Health Board, Auckland, New Zealand |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31822573$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1055_s_0042_1758687 crossref_primary_10_1136_bmj_2021_069116 crossref_primary_10_1093_eurjpc_zwaa098 crossref_primary_10_1136_heartjnl_2019_316189 crossref_primary_10_3390_cardiogenetics11020010 crossref_primary_10_1093_eurjpc_zwad314 crossref_primary_10_1097_MD_0000000000035849 |
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Snippet | ObjectiveFollowing acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician... Following acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication... |
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SubjectTerms | acute coronary syndrome Acute coronary syndromes Body mass index Cardiac risk factors and prevention Diabetes Ethics Ethnicity Heart attacks Laboratories Mortality Patients Primary care Risk assessment risk score secondary prevention Sensitivity analysis Software Studies |
Title | Development and validation of a cardiovascular risk score for patients in the community after acute coronary syndrome |
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