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      Racial and Ethnic Disparities in Management and Outcomes of Cardiac Arrest Complicating Acute Myocardial Infarction

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          Abstract

          Background

          The role of race and ethnicity in the outcomes of cardiac arrest (CA) complicating acute myocardial infarction (AMI) is incompletely understood.

          Methods and Results

          This was a retrospective cohort study of adult admissions with AMI‐CA from the National Inpatient Sample (2012–2017). Self‐reported race/ethnicity was classified as White, Black, and others (Hispanic, Asian or Pacific Islander, Native American, Other). Outcomes of interest included in‐hospital mortality, coronary angiography, percutaneous coronary intervention, palliative care consultation, do‐not‐resuscitate status use, hospitalization costs, hospital length of stay, and discharge disposition. Of the 3.5 million admissions with AMI, CA was noted in 182 750 (5.2%), with White, Black, and other races/ethnicities constituting 74.8%, 10.7%, and 14.5%, respectively. Black patients admitted with AMI‐CA were more likely to be female, with more comorbidities, higher rates of non–ST‐segment–elevation myocardial infarction, and higher neurological and renal failure. Admissions of patients of Black and other races/ethnicities underwent coronary angiography (61.9% versus 70.2% versus 73.1%) and percutaneous coronary intervention (44.6% versus 53.0% versus 58.1%) less frequently compared to patients of white race ( p<0.001). Admissions of patients with AMI‐CA had significantly higher unadjusted mortality (47.4% and 47.4%) as compared with White patients admitted (40.9%). In adjusted analyses, Black race was associated with lower in‐hospital mortality (odds ratio [OR], 0.95; 95% CI, 0.91–0.99; P=0.007) whereas other races had higher in‐hospital mortality (OR, 1.11; 95% CI, 1.08–1.15; P<0.001) compared with White race. Admissions of Black patients with AMI‐CA had longer length of hospital stay, higher rates of palliative care consultation, less frequent do‐not‐resuscitate status use, and fewer discharges to home (all P<0.001).

          Conclusions

          Racial and ethnic minorities received less frequent guideline‐directed procedures and had higher in‐hospital mortality and worse outcomes in AMI‐CA.

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          Most cited references47

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          Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

          Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms. ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms. Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyo's ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm. These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.
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            Adherence to Methodological Standards in Research Using the National Inpatient Sample

            Publicly available data sets hold much potential, but their unique design may require specific analytic approaches.
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              Acute Noncardiac Organ Failure in Acute Myocardial Infarction With Cardiogenic Shock

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                Author and article information

                Contributors
                svalla4@emory.edu
                Journal
                J Am Heart Assoc
                J Am Heart Assoc
                10.1002/(ISSN)2047-9980
                JAH3
                ahaoa
                Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
                John Wiley and Sons Inc. (Hoboken )
                2047-9980
                20 May 2021
                01 June 2021
                : 10
                : 11 ( doiID: 10.1002/jah3.v10.11 )
                : e019907
                Affiliations
                [ 1 ] Department of Medicine Mayo Clinic Rochester MN
                [ 2 ] Department of Cardiovascular Surgery Mayo Clinic Rochester MN
                [ 3 ] Division of Nephrology and Hypertension Department of Medicine Mayo Clinic Rochester MN
                [ 4 ] Division of Hospital Internal Medicine Department of Medicine Mayo Clinic Rochester MN
                [ 5 ] Division of Cardiovascular Medicine Department of Medicine Yale University School of Medicine New Haven CT
                [ 6 ] Department of Cardiovascular Medicine Mayo Clinic Rochester MN
                [ 7 ] Division of Pulmonary and Critical Care Medicine Department of Medicine Mayo Clinic Rochester MN
                [ 8 ] Center for Clinical and Translational Science Mayo Clinic Graduate School of Biomedical Sciences Rochester MN
                [ 9 ] Section of Interventional Cardiology Division of Cardiovascular Medicine Department of Medicine Emory University School of Medicine Atlanta GA
                Author notes
                [*] [* ] Correspondence to: Saraschandra Vallabhajosyula, MD MSc, Section of Interventional Cardiology, Division of Cardiovascular Medicine, Department of Medicine, Emory University School of Medicine, 1364 Clifton Road, Atlanta, Georgia 30322. E‐mail: svalla4@ 123456emory.edu

                [ * ]

                A.V. Subramaniam and S.H. Patlolla contributed equally as co‐first authors.

                Author information
                https://orcid.org/0000-0003-0077-8966
                https://orcid.org/0000-0001-7952-0217
                https://orcid.org/0000-0001-9954-9711
                https://orcid.org/0000-0002-0595-1492
                https://orcid.org/0000-0002-6353-6780
                https://orcid.org/0000-0002-0037-0373
                https://orcid.org/0000-0002-1631-8238
                Article
                JAH36248
                10.1161/JAHA.120.019907
                8483555
                34013741
                8c152bea-7819-4ee1-a748-9b3e5a5ccd48
                © 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 22 October 2020
                : 22 March 2021
                Page count
                Figures: 3, Tables: 2, Pages: 11, Words: 7576
                Funding
                Funded by: Clinical and Translational Science Award
                Award ID: UL1 TR000135
                Funded by: National Center for Advancing Translational Sciences , doi 10.13039/100006108;
                Funded by: National Institutes of Health , doi 10.13039/100000002;
                Categories
                Original Research
                Original Research
                Resuscitation Science
                Custom metadata
                2.0
                June 1, 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:01.06.2021

                Cardiovascular Medicine
                acute myocardial infarction,cardiac arrest,healthcare disparities,minorities,outcomes research,race,health equity

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