Dawit Zemedikun, Joseph Hung, Derrick Lopez, Matthew Knuiman, David Youens, Tom G Briffa, Frank Sanfilippo, Lee Nedkoff
{"title":"急性冠状动脉综合征的 ICD 编码住院率与心脏生物标记物分类住院率之间的一致性时间趋势:一项关联医院和生物标记物数据研究。","authors":"Dawit Zemedikun, Joseph Hung, Derrick Lopez, Matthew Knuiman, David Youens, Tom G Briffa, Frank Sanfilippo, Lee Nedkoff","doi":"10.1136/openhrt-2024-002995","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Since 2000, the definition of myocardial infarction (MI) has evolved with reliance on cardiac troponin (cTn) tests. The implications of this change on trends of acute coronary syndrome (ACS) subtypes obtained from routinely collected hospital morbidity data are unclear. Using person-linked hospitalisation data, we compared International Classification of Diseases (ICD)-coded data with biomarker-classified admission rates for ST-segment elevation MI (STEMI), non-STEMI (NSTEMI) and unstable angina (UA) in Western Australia (WA).</p><p><strong>Methods: </strong>We used linked hospitalisation data from all WA tertiary hospitals to identify patients with a principal diagnosis of STEMI, NSTEMI or UA between 2002 and 2016. Linked biomarker results were classified as 'diagnostic' for MI according to established criteria. We calculated age-standardised and sex-standardised rates (ASSRs) for ICD-coded versus biomarker-classified admissions by ACS subtypes and estimated annual change in admissions using Poisson regression adjusting for age and sex.</p><p><strong>Results: </strong>There were 37 272 ACS admissions in 30 683 patients (64.2% male), and 96% of cases had linked biomarker data, predominantly conventional cTn at the start and high-sensitive cTn from late 2013. Despite lower ASSRs, trends in MI classified with a diagnostic biomarker were concordant with ICD-coded admissions rates for both STEMI and NSTEMI. Between 2002 and 2010, STEMI rates declined by 4.1% (95% CI 5.0%, 3.1%) and 3.4% (95% CI 4.6%, 2.3%) in ICD-coded and biomarker-classified admissions, respectively, and both plateaued thereafter. For NSTEMI between 2002 and 2010, the ICD-coded and biomarker-classified rates increased 8.0% per year (95% CI 7.2%, 8.9%) and 8.0% (95% CI 7.0%, 9.0%), respectively, and both subsequently declined. For UA, both ICD-coded and biomarker-classified UA admission rates declined in a steady and concordant manner between 2002 and 2016.</p><p><strong>Conclusions: </strong>The present study supports the validity of using administrative data to monitor population trends in ACS subtypes as they appear to generally reflect the redefinition of MI in the troponin era.</p>","PeriodicalId":19505,"journal":{"name":"Open Heart","volume":"11 2","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11499754/pdf/","citationCount":"0","resultStr":"{\"title\":\"Temporal trends in concordance between ICD-coded and cardiac biomarker-classified hospitalisation rates for acute coronary syndromes: a linked hospital and biomarker data study.\",\"authors\":\"Dawit Zemedikun, Joseph Hung, Derrick Lopez, Matthew Knuiman, David Youens, Tom G Briffa, Frank Sanfilippo, Lee Nedkoff\",\"doi\":\"10.1136/openhrt-2024-002995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Since 2000, the definition of myocardial infarction (MI) has evolved with reliance on cardiac troponin (cTn) tests. The implications of this change on trends of acute coronary syndrome (ACS) subtypes obtained from routinely collected hospital morbidity data are unclear. Using person-linked hospitalisation data, we compared International Classification of Diseases (ICD)-coded data with biomarker-classified admission rates for ST-segment elevation MI (STEMI), non-STEMI (NSTEMI) and unstable angina (UA) in Western Australia (WA).</p><p><strong>Methods: </strong>We used linked hospitalisation data from all WA tertiary hospitals to identify patients with a principal diagnosis of STEMI, NSTEMI or UA between 2002 and 2016. Linked biomarker results were classified as 'diagnostic' for MI according to established criteria. We calculated age-standardised and sex-standardised rates (ASSRs) for ICD-coded versus biomarker-classified admissions by ACS subtypes and estimated annual change in admissions using Poisson regression adjusting for age and sex.</p><p><strong>Results: </strong>There were 37 272 ACS admissions in 30 683 patients (64.2% male), and 96% of cases had linked biomarker data, predominantly conventional cTn at the start and high-sensitive cTn from late 2013. Despite lower ASSRs, trends in MI classified with a diagnostic biomarker were concordant with ICD-coded admissions rates for both STEMI and NSTEMI. Between 2002 and 2010, STEMI rates declined by 4.1% (95% CI 5.0%, 3.1%) and 3.4% (95% CI 4.6%, 2.3%) in ICD-coded and biomarker-classified admissions, respectively, and both plateaued thereafter. For NSTEMI between 2002 and 2010, the ICD-coded and biomarker-classified rates increased 8.0% per year (95% CI 7.2%, 8.9%) and 8.0% (95% CI 7.0%, 9.0%), respectively, and both subsequently declined. For UA, both ICD-coded and biomarker-classified UA admission rates declined in a steady and concordant manner between 2002 and 2016.</p><p><strong>Conclusions: </strong>The present study supports the validity of using administrative data to monitor population trends in ACS subtypes as they appear to generally reflect the redefinition of MI in the troponin era.</p>\",\"PeriodicalId\":19505,\"journal\":{\"name\":\"Open Heart\",\"volume\":\"11 2\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11499754/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Heart\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/openhrt-2024-002995\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Heart","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/openhrt-2024-002995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Temporal trends in concordance between ICD-coded and cardiac biomarker-classified hospitalisation rates for acute coronary syndromes: a linked hospital and biomarker data study.
Background: Since 2000, the definition of myocardial infarction (MI) has evolved with reliance on cardiac troponin (cTn) tests. The implications of this change on trends of acute coronary syndrome (ACS) subtypes obtained from routinely collected hospital morbidity data are unclear. Using person-linked hospitalisation data, we compared International Classification of Diseases (ICD)-coded data with biomarker-classified admission rates for ST-segment elevation MI (STEMI), non-STEMI (NSTEMI) and unstable angina (UA) in Western Australia (WA).
Methods: We used linked hospitalisation data from all WA tertiary hospitals to identify patients with a principal diagnosis of STEMI, NSTEMI or UA between 2002 and 2016. Linked biomarker results were classified as 'diagnostic' for MI according to established criteria. We calculated age-standardised and sex-standardised rates (ASSRs) for ICD-coded versus biomarker-classified admissions by ACS subtypes and estimated annual change in admissions using Poisson regression adjusting for age and sex.
Results: There were 37 272 ACS admissions in 30 683 patients (64.2% male), and 96% of cases had linked biomarker data, predominantly conventional cTn at the start and high-sensitive cTn from late 2013. Despite lower ASSRs, trends in MI classified with a diagnostic biomarker were concordant with ICD-coded admissions rates for both STEMI and NSTEMI. Between 2002 and 2010, STEMI rates declined by 4.1% (95% CI 5.0%, 3.1%) and 3.4% (95% CI 4.6%, 2.3%) in ICD-coded and biomarker-classified admissions, respectively, and both plateaued thereafter. For NSTEMI between 2002 and 2010, the ICD-coded and biomarker-classified rates increased 8.0% per year (95% CI 7.2%, 8.9%) and 8.0% (95% CI 7.0%, 9.0%), respectively, and both subsequently declined. For UA, both ICD-coded and biomarker-classified UA admission rates declined in a steady and concordant manner between 2002 and 2016.
Conclusions: The present study supports the validity of using administrative data to monitor population trends in ACS subtypes as they appear to generally reflect the redefinition of MI in the troponin era.
期刊介绍:
Open Heart is an online-only, open access cardiology journal that aims to be “open” in many ways: open access (free access for all readers), open peer review (unblinded peer review) and open data (data sharing is encouraged). The goal is to ensure maximum transparency and maximum impact on research progress and patient care. The journal is dedicated to publishing high quality, peer reviewed medical research in all disciplines and therapeutic areas of cardiovascular medicine. Research is published across all study phases and designs, from study protocols to phase I trials to meta-analyses, including small or specialist studies. Opinionated discussions on controversial topics are welcomed. Open Heart aims to operate a fast submission and review process with continuous publication online, to ensure timely, up-to-date research is available worldwide. The journal adheres to a rigorous and transparent peer review process, and all articles go through a statistical assessment to ensure robustness of the analyses. Open Heart is an official journal of the British Cardiovascular Society.