CALIBER Acute myocardial infarction phenotype

person Phenotype Acute myocardial infarction
person Type Disease or syndrome
person Data sources Primary care (CPRD), hospital admission data (HES), mortality data (ONS)
person Clinical Terminologies Read, ICD-10, ICD-9, OPCS-4
person Valid event date range 01/01/1999 - 01/07/2016
person Sex Female/Male
person Agreed 23.11.2012 (Revision 2)
person Authors Julie George, Emily Herrett, Liam Smeeth, Harry Hemingway, Anoop Shah, Spiros Denaxas

Primary Care (incident)

In the Clinical Practice Research Datalink (CPRD, primary care data) we ascertained myocardial infarction (MI) cases by searching for Read terms related to MI diagnosis OR ST elevation MI (STEMI), OR non-ST elevation MI (NSTEMI).

Read codeRead termCALIBER category
G30X000 Acute ST segment elevation myocardial infarction STEMI
G307100 Acute non-ST segment elevation myocardial infarction NSTEMI
323..00 ECG: myocardial infarction Acute MI not further specified
3233.00 ECG: antero-septal infarct. Acute MI not further specified
3234.00 ECG:posterior/inferior infarct Acute MI not further specified
3235.00 ECG: subendocardial infarct Acute MI not further specified
3236.00 ECG: lateral infarction Acute MI not further specified
323Z.00 ECG: myocardial infarct NOS Acute MI not further specified
889A.00 Diab mellit insulin-glucose infus acute myocardial infarct Acute MI not further specified
G30..00 Acute myocardial infarction Acute MI not further specified
G30..12 Coronary thrombosis Acute MI not further specified
G30..13 Cardiac rupture following myocardial infarction (MI) Acute MI not further specified
G30..15 MI - acute myocardial infarction Acute MI not further specified
G30..16 Thrombosis - coronary Acute MI not further specified
G300.00 Acute anterolateral infarction Acute MI not further specified
G301.00 Other specified anterior myocardial infarction Acute MI not further specified
G301000 Acute anteroapical infarction Acute MI not further specified
G301100 Acute anteroseptal infarction Acute MI not further specified
G301z00 Anterior myocardial infarction NOS Acute MI not further specified
G302.00 Acute inferolateral infarction Acute MI not further specified
G303.00 Acute inferoposterior infarction Acute MI not further specified
G304.00 Posterior myocardial infarction NOS Acute MI not further specified
G305.00 Lateral myocardial infarction NOS Acute MI not further specified
G306.00 True posterior myocardial infarction Acute MI not further specified
G307.00 Acute subendocardial infarction Acute MI not further specified
G307000 Acute non-Q wave infarction Acute MI not further specified
G308.00 Inferior myocardial infarction NOS Acute MI not further specified
G309.00 Acute Q-wave infarct Acute MI not further specified
G30B.00 Acute posterolateral myocardial infarction Acute MI not further specified
G30X.00 Acute transmural myocardial infarction of unspecif site Acute MI not further specified
G30y.00 Other acute myocardial infarction Acute MI not further specified
G30y000 Acute atrial infarction Acute MI not further specified
G30y100 Acute papillary muscle infarction Acute MI not further specified
G30y200 Acute septal infarction Acute MI not further specified
G30yz00 Other acute myocardial infarction NOS Acute MI not further specified
G30z.00 Acute myocardial infarction NOS Acute MI not further specified
G31y100 Microinfarction of heart Acute MI not further specified
G38..00 Postoperative myocardial infarction Acute MI not further specified
G380.00 Postoperative transmural myocardial infarction anterior wall Acute MI not further specified
G381.00 Postoperative transmural myocardial infarction inferior wall Acute MI not further specified
G384.00 Postoperative subendocardial myocardial infarction Acute MI not further specified
G38z.00 Postoperative myocardial infarction, unspecified Acute MI not further specified
Gyu3400 [X]Acute transmural myocardial infarction of unspecif site Acute MI not further specified
Read terms are hierarhically organized in top-level chapters i.e. chapter G....00 is related to Circulatory System Diseases and sub-headings i.e. heading G2...00 is related to Hypertensive Heart Disease while G3...00 is related to Ischaemic Heart Disease.

Secondary Care (incident and prevalent)

In Hospital Episode Statistics (HES, secondary care data) we used primary diagnosis of ICD-10 codes (see below) for MI diagnosis, OR ST elevation MI (STEMI), OR non-ST elevation MI, OR procedural codes (OPCS 4) of transluminal coronary thrombolysis.

Diagnoses

ICD-10 codeICD-10 termCALIBER category
I21 Acute myocardial infarction Acute MI not further specified
Thrombolytic treatment

OPCS-4 codeOPCS-4 termCALIBER category
K50.2 Percutaneous transluminal coronary thrombolysis using streptokinase Transluminal coronary thrombolysis
K50.3 Percutaneous transluminal injection of therapeutic substance into coronary artery NEC Transluminal coronary thrombolysis
In the Myocardial Ischaemia National Audit Project (MINAP) we used the discharge diagnosis of acute STEMI OR acute NSTEMI as diagnosis of MI. Further classification was based on raised cardiac enzymes and electrocardiogram determing treatment.

In the Office for National Statistics (ONS) mortality register, we used ICD-10 and ICD-9 terms to identify fatal MI cases where an MI diagnosis was recorded as the underlying cause of death.

ICD-10 codeICD-10 termCALIBER category
I21 Acute myocardial infarction Myocardial Infarction
I22 Subsequent myocardial infarction Myocardial Infarction
I23 Certain current complications following acute myocardial infarction Myocardial Infarction

ICD-9 codeICD-9 termCALIBER category
410 Acute myocardial infarction Myocardial infarction
4110 Other acute and subacute forms of ischemic heart disease ; Postmyocardial infarction syndrome Myocardial infarction
4297 Ill-defined descriptions and complications of heart disease ; Certain sequelae of myocardial infarction, not elsewhere classified Myocardial infarction

Combining evidence across sources to define and date phenotypes

If there are records of non-ST elevation MI and ST elevation MI on the same date, the more severe diagnosis (STEMI) is taken as correct. If there is a record of unspecified MI and STEMI / NSTEMI on the same date, the non-specific diagnosis is ignored. MI may be recorded multiple times in the different datasets with slightly different dates. It is up to the researcher to decide what time interval should be used as a cut-off for considering that two events close to each other are distinct events rather than multuiple records of the same event; we would suggest 7 days because this is just greater than the usual duration of hospitalization for myocardial infarction.
For primary care or hospital discharge patients with an associated record in the disease registry (MINAP), the positive predictive value of the acute myocardial infarction diagnosis (the probability that the diagnosis recorded in the disease registry was myocardial infarction rather than unstable angina or a non-cardiac diagnosis) was 92.2% (6660/7224, 95% confidence interval 91.6% to 92.8%) in primary care and 91.5% (6851/7489, 90.8% to 92.1%) in hospital care. Eighty five per cent of patients recorded in primary care and hospital discharge (7386/8707) had a record of raised cardiac markers and half (3766/8707) had a record of ST segment elevation on electrocardiography.
Number and percentage of records recorded in primary care (Clinical Practice Research Datalink), hospital care (Hospital Episode Statistics), and disease registry (Myocardial Ischaemia National Audit Project) for non-fatal myocardial infarction across the three sources (n=17 964 patients). More information.

Crude incidence of acute fatal and non-fatal myocardial infarction estimated using different combinations of data from primary care (Clinical Practice Research Datalink), hospital admissions (Hospital Episode Statistics), disease registry (MINAP, Myocardial Ischaemia National Audit Project), and death registry (Office for National Statistics). More information.
Kaplan Meier curves showing all cause mortality, stratified by record source in 20 819 patients: Clinical Practice Research Datalink (n=15 819), Hospital Episode Statistics (n=13 831), Myocardial Ischaemia National Audit Project (MINAP) (n=10 351). Myocardial infarctions recorded by the Office for National Statistics are not shown as they are by definition fatal on the date of myocardial infarction. More information.

Denaxas, SC; Fatemifar, G; Patel, R; Hemingway, H; (2017) Deriving research-quality phenotypes from national electronic health records to advance precision medicine: a UK Biobank case-study. In: Proceedings of the BHI-2017 International Conference on Biomedical and Health Informatics. IEEE Engineering in Medicine and Biology Society (EMBS): Orlando, FL, USA.
Risks of all-cause death in post-myocardial infarction survivors aged 65 years and older followed from 1 year after the index myocardial infarction. Observed (Kaplan–Meier) risks (top left), adjusted risks (top right), and relative risks vs. Sweden (bottom) in post-myocardial infarction survivors from Sweden (n = 54 841), USA (n = 53 909), England (n = 4653), and France (n = 961). CABG, coronary artery bypass graft; CI, confidence interval; KM, Kaplan–Meier; PCI, percutaneous coronary intervention; RR, relative risk. More information.

Kaplan-Meier curves for cumulative mortality at 30 days after admission with acute myocardial infarction in Sweden and the UK. More information.
Gho JMIH et al. An electronic health records cohort study on heart failure following myocardial infarction in England: incidence and predictors. BMJ Open. 2018 Mar 3;8(3):e018331. doi: 10.1136/bmjopen-2017-018331. PMID: 29502083


Steele AJ et al. Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease. PLoS One. 2018 Aug 31;13(8):e0202344. doi: 10.1371/journal.pone.0202344. eCollection 2018. PMID: 30169498


Archangelidi O et al. Clinically recorded heart rate and incidence of 12 coronary, cardiac, cerebrovascular and peripheral arterial diseases in 233,970 men and women: A linked electronic health record study. Eur J Prev Cardiol. 2018 Sep;25(14):1485-1495. doi: 10.1177/2047487318785228. Epub 2018 Jul 2. PMID: 29966429


Koudstaal S et al. Prognostic burden of heart failure recorded in primary care, acute hospital admissions, or both: a population-based linked electronic health record cohort study in 2.1 million people. Eur J Heart Fail. 2017 Sep;19(9):1119-1127. doi: 10.1002/ejhf.709. Epub 2016 Dec 23. PMID: 28008698


Chung SC et al. Time spent at blood pressure target and the risk of death and cardiovascular diseases. PLoS One. 2018 Sep 5;13(9):e0202359. doi: 10.1371/journal.pone.0202359. eCollection 2018. PMID: 30183734


Bell S et al. Association between clinically recorded alcohol consumption and initial presentation of 12 cardiovascular diseases: population based cohort study using linked health records. BMJ. 2017 Mar 22;356:j909. PMID: 28331015


Pasea L et al. Personalising the decision for prolonged dual antiplatelet therapy: development, validation and potential impact of prognostic models for cardiovascular events and bleeding in myocardial infarction survivors. Eur Heart J. 2017 Apr 7;38(14):1048-1055. doi: 10.1093/eurheartj/ehw683. PMID: 28329300


Shah AD et al. Neutrophil Counts and Initial Presentation of 12 Cardiovascular Diseases: A CALIBER Cohort Study. J Am Coll Cardiol. 2017 Mar 7;69(9):1160-1169. doi: 10.1016/j.jacc.2016.12.022. PMID: 28254179


Asaria M et al. Using electronic health records to predict costs and outcomes in stable coronary artery disease. Heart. 2016 May 15;102(10):755-62. doi: 10.1136/heartjnl-2015-308850. Epub 2016 Feb 10. PMID: 26864674


Daskalopoulou M et al. Depression as a Risk Factor for the Initial Presentation of Twelve Cardiac, Cerebrovascular, and Peripheral Arterial Diseases: Data Linkage Study of 1.9 Million Women and Men. PLoS One. 2016 Apr 22;11(4):e0153838. doi: 10.1371/journal.pone.0153838. eCollection 2016. PMID: 27105076


Pujades-Rodriguez M et al. Associations between polymyalgia rheumatica and giant cell arteritis and 12 cardiovascular diseases. Heart. 2016 Mar;102(5):383-9. doi: 10.1136/heartjnl-2015-308514. Epub 2016 Jan 19. PMID: 26786818


Pujades-Rodriguez M et al. Rheumatoid Arthritis and Incidence of Twelve Initial Presentations of Cardiovascular Disease: A Population Record-Linkage Cohort Study in England. PLoS One. 2016 Mar 15;11(3):e0151245. doi: 10.1371/journal.pone.0151245. eCollection 2016. PMID: 26978266


Shah AD et al. Low eosinophil and low lymphocyte counts and the incidence of 12 cardiovascular diseases: a CALIBER cohort study. Open Heart. 2016 Sep 5;3(2):e000477. doi: 10.1136/openhrt-2016-000477. eCollection 2016. PMID: 27621833


Timmis A et al. Prolonged dual antiplatelet therapy in stable coronary disease: comparative observational study of benefits and harms in unselected versus trial populations. BMJ. 2016 Jun 22;353:i3163. PMID: 27334486


Walker S et al. Long-term healthcare use and costs in patients with stable coronary artery disease: a population-based cohort using linked health records (CALIBER). Eur Heart J Qual Care Clin Outcomes. 2016 Jan 20;2(2):125-140. doi: 10.1093/ehjqcco/qcw003. PMID: 27042338


George J et al. How Does Cardiovascular Disease First Present in Women and Men? Incidence of 12 Cardiovascular Diseases in a Contemporary Cohort of 1,937,360 People. Circulation. 2015 Oct 6;132(14):1320-8. doi: 10.1161/CIRCULATIONAHA.114.013797. Epub 2015 Sep 1. PMID: 26330414


Morley KI et al. Defining disease phenotypes using national linked electronic health records: a case study of atrial fibrillation. PLoS One. 2014 Nov 4;9(11):e110900. doi: 10.1371/journal.pone.0110900. eCollection 2014. PMID: 25369203


Pujades-Rodriguez M et al. Heterogeneous associations between smoking and a wide range of initial presentations of cardiovascular disease in 1937360 people in England: lifetime risks and implications for risk prediction. Int J Epidemiol. 2015 Feb;44(1):129-41. doi: 10.1093/ije/dyu218. Epub 2014 Nov 20. PMID: 25416721


Pujades-Rodriguez M et al. Socioeconomic deprivation and the incidence of 12 cardiovascular diseases in 1.9 million women and men: implications for risk prediction and prevention. PLoS One. 2014 Aug 21;9(8):e104671. doi: 10.1371/journal.pone.0104671. eCollection 2014. PMID: 25144739


Rapsomaniki E et al. Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1.25 million people. Lancet. 2014 May 31;383(9932):1899-911. doi: 10.1016/S0140-6736(14)60685-1. PMID: 24881994


Shah AD et al. Type 2 diabetes and incidence of cardiovascular diseases: a cohort study in 1.9 million people. Lancet Diabetes Endocrinol. 2015 Feb;3(2):105-13. doi: 10.1016/S2213-8587(14)70219-0. Epub 2014 Nov 11. PMID: 25466521


Rapsomaniki E et al. Prognostic models for stable coronary artery disease based on electronic health record cohort of 102 023 patients. Eur Heart J. 2014 Apr;35(13):844-52. doi: 10.1093/eurheartj/eht533. Epub 2013 Dec 17. PMID: 24353280