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Influence of the Danish Co-morbidity Index Score on the Treatment and Outcomes of 2.5 Million Patients Admitted With Acute Myocardial Infarction in the United States

Open AccessPublished:July 14, 2022DOI:https://doi.org/10.1016/j.amjcard.2022.06.008
      This study aimed to determine the association between the Danish Co-morbidity Index for Acute Myocardial Infarction (DANCAMI) and restricted DANCAMI (rDANCAMI) scores and clinical outcomes in patients hospitalized with AMI. Using the National Inpatient Sample, all AMI hospitalizations were stratified into four groups based on their DANCAMI and rDANCAMI score (0; 1 to 3; 4 to 5; ≥6). The primary outcome was all-cause mortality, whereas secondary outcomes were major adverse cardiovascular/cerebrovascular events, major bleeding, ischemic stroke, and receipt of coronary angiography or percutaneous coronary intervention. Multivariate logistic regression was used to determine adjusted odds ratios (aOR) with 95% confidence intervals (95% CIs). Patients with DANCAMI risk score ≥6 were more likely to suffer mortality (aOR 2.30, 95% CI 2.24 to 2.37) and bleeding (aOR 5.85, 95% CI 5.52 to 6.21) and were less likely to receive coronary angiography (aOR 0.34, 95% CI 0.33 to 0.34) and percutaneous coronary intervention (aOR 0.29, 95% CI 0.28 to 0.29) compared with patients with DANCAMI score of 0. Similar results were observed for the rDANCAMI score. In conclusion, increased DANCAMI and rDANCAMI scores were associated with worse in-hospital outcomes in patients with AMI and lower odds of invasive management. The use of co-morbidity scores identifies patients at high risk of adverse outcomes and highlights disparities in care.

      Graphical Abstract

      Co-morbidities among patients with acute myocardial infarction (AMI) are common and associated with a poor prognosis.
      • Hall M
      • Dondo TB
      • Yan AT
      • Mamas MA
      • Timmis AD
      • Deanfield JE
      • Jernberg T
      • Hemingway H
      • Fox KAA
      • Gale CP.
      Multimorbidity and survival for patients with acute myocardial infarction in England and Wales: latent class analysis of a nationwide population-based cohort.
      Co-morbidity prediction models have previously been used in research to predict the prognosis of AMI, reflected by the co-morbidity burden of patients. Such examples include the Charlson Co-morbidity Index (CCI), the Elixhauser Co-morbidity Index (ECI), and more recently the Danish Co-morbidity Index for Acute Myocardial Infarction (DANCAMI).
      • Mamas MA
      • Fath-Ordoubadi F
      • Danzi GB
      • Spaepen E
      • Kwok CS
      • Buchan I
      • Peek N
      • de Belder MA
      • Ludman PF
      • Paunovic D
      • Urban P.
      Prevalence and impact of co-morbidity burden as defined by the Charlson co-morbidity index on 30-day and 1- and 5-year outcomes after coronary stent implantation (from the Nobori-2 Study).
      • Wellejus Albertsen L
      • Heide-Jørgensen U
      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      • van Walraven C
      • Austin PC
      • Jennings A
      • Quan H
      • Forster AJ.
      A modification of the Elixhauser co-morbidity measures into a point system for hospital death using administrative data.
      • Schmidt M
      • Jacobsen JB
      • Lash TL
      • Bøtker HE
      • Sørensen HT.
      25 year trends in first time hospitalisation for acute myocardial infarction, subsequent short and long term mortality, and the prognostic impact of sex and comorbidity: a Danish nationwide cohort study.
      Although CCI and ECI have been studied in different populations, the performance of novel co-morbidity risk scores such as DANCAMI and restricted DANCAMI (rDANCAMI) is not well defined in large populations.
      • Wellejus Albertsen L
      • Heide-Jørgensen U
      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      ,
      • Zhang F
      • Chiu Y
      • Ensor J
      • Mohamed MO
      • Peat G
      • Mamas MA
      Elixhauser outperformed Charlson co-morbidity index in prognostic value after ACS: insights from a national registry.
      ,
      • Zhang F
      • Bharadwaj A
      • Mohamed MO
      • Ensor J
      • Peat G
      • Mamas MA.
      Impact of Charlson co-morbidity index score on management and outcomes after acute coronary syndrome.
      The DANCAMI score was developed and validated to predict 1-year mortality post myocardial infarction in a cohort of Danish and New Zealand patients admitted for AMI including 24 cardiovascular and non-cardiovascular co-morbidities.
      • Wellejus Albertsen L
      • Heide-Jørgensen U
      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      The rDANCAMI score includes 17 non-cardiovascular co-morbidities only.
      • Wellejus Albertsen L
      • Heide-Jørgensen U
      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      This study aimed to investigate the use of the DANCAMI and rDANCAMI scores for the prognosis of patients admitted with AMI using a national cohort of the US hospitalizations and to compare the performance of these scores in predicting the in-hospital mortality.

      Methods

      The National Inpatient Sample (NIS) is the largest available database of the US hospitalizations developed for the Healthcare Cost and Utilization Project and sponsored by the Agency for Healthcare Research and Quality. The NIS contains anonymized data on diagnoses and procedures from over 7 million hospitalizations annually and represents a 20% stratified sample of all discharges from the US community hospitals, excluding rehabilitation and long-term acute care hospitals, with the sample representing 97% of the US population.

      HCUP National Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). 2012. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/nisoverview.jsp.

      Using the International Classification of Diseases 10th revision, adult hospitalizations (>18 years old) between October 2015 to December 2018 with a primary discharge diagnosis of AMI were identified and stratified according to their DANCAMI and rDANCAMI scores. (Supplementary Table 1).
      • Wellejus Albertsen L
      • Heide-Jørgensen U
      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      Risk scores were computed using the predefined weights (Supplementary Table 2). Groups were constructed based on the cut-off values from the original research study into the following: no co-morbidity (score = 0), low burden (score = 1–3), moderate burden (score = 4–5), and severe co-morbidity burden (score ≥6).
      • Wellejus Albertsen L
      • Heide-Jørgensen U
      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      The International Classification of Diseases 10th revision codes were also used to extract data on patient characteristics, co-morbidities, management strategies, and hospital outcomes. Cases were excluded owing to missing data, elective admission, Type 2 myocardial infarction, and ages under 18 (Supplementary Figure 1). Analyses were weighted using discharge weights to estimate for national averages.
      The primary clinical outcome of this study was the association of DANCAMI and rDANCAMI scores with all-cause mortality. Secondary outcomes included other adverse in-hospital outcomes (major adverse cardiovascular and cerebrovascular events [MACCE], major bleeding, and acute ischemic stroke) and receipt of invasive management (coronary angiography [CA] and percutaneous coronary intervention [PCI]). MACCE was a composite of all-cause mortality, acute ischemic stroke, and reinfarction. Major bleeding included subarachnoid hemorrhage, intracerebral hemorrhage, intracranial hemorrhage, gastrointestinal hemorrhage, epistaxis, and hemoptysis. Finally, the performance of DANCAMI and rDANCAMI risk scores for the prediction of all-cause mortality was studied.
      Statistical Package for Social Sciences (SPSS) Statistics version 27 (IBM Corp, Armonk, New York) and Stata MP version 16.0 (StataCorp, College Station, Texas) were used for all statistical analyses.
      • Vedovati MC
      • Giustozzi M
      • Verdecchia P
      • Pierpaoli L
      • Conti S
      • Verso M
      • Di Filippo F
      • Marchesini E
      • Bogliari G
      • Agnelli G
      • Becattini C.
      Patients with cancer and atrial fibrillation treated with doacs: a prospective cohort study.
      Continuous variables such as age, length of stay, and total charges were summarized using median and interquartile range. Categorical variables were compared using the Chi-square test and summarized as percentages (%). Binomial multivariate logistic regression was performed to determine the adjusted odds ratio (aOR) for invasive management and adverse outcomes. The regression model was adjusted for the following variables: bed size of the hospital, region of the hospital, location/teaching status of the hospital, age, gender, primary expected payer, median household income, smoking status, previous myocardial infarction, previous PCI, previous coronary artery bypass graft, previous cerebrovascular accident, PCI, ST-elevation myocardial infarction, dyslipidemia, atrial fibrillation, and thrombocytopenia. Results were presented as aOR with 95% confidence intervals (CIs). The performance of DANCAMI and rDANCAMI scores in predicting all-cause mortality was tested using the receiver operating characteristic (ROC) curves, with a calculation of the area under the curve (AUC). Both continuous and categorical scores were used to test their performance in predicting mortality. To compare the AUC values with previous co-morbidity scores, ROC analysis of the CCI score was also produced. Finally, optimal cut-off points for DANCAMI and rDANCAMI risk scores were calculated using the Liu method (cutpt function) in the Stata software (StataCorp, College Station, Texas). Statistical significance was determined at the level of p <0.05.

      Results

      A total of 2,587,614 patients with AMI were diagnosed between October 2015 and December 2018 (Supplementary Figure 1). Of these, 134,280 (5.2%) patients had a DANCAMI score of 0, whereas 495,060 (19.1%), 332,845 (12.9%), and 1,625,340 (62.8%) patients had a DANCAMI score of 1 to 3, 4 to 5, and ≥6, respectively (p <0.001) (Table 1). Patients with a DANCAMI score of ≥6 were on average older, more likely to be women, and had the highest prevalence of cardiovascular co-morbidities such as atrial fibrillation (22.6%), previous AMI (16.6%), previous coronary artery bypass grafting (25.4%), previous cerebrovascular accident (CVA) (10.4%), and anemias (32.0%) compared with patients with a lower DANCAMI score (p <0.001) (Table 1).
      Table 1Patient characteristics according to the groups of DANCAMI risk score
      CharacteristicsDANCAMI score 0 (5.2%)DANCAMI score 1-3 (19.1%)DANCAMI score 4-5 (12.9%)DANCAMI score ≥6 (62.8%)Overall p-valueTrend p-value
      Number of hospitalizations134,280495,060332,8451,625,430
      Age (years), median (interquartile range)59 (50, 68)64 (55, 74)67 (57, 79)72 (62, 81)<0.001<0.001
      Women30.5%36.9%41.0%43.5%<0.001<0.001
      White79.9%78.7%75.5%72.4%<0.001<0.001
      Black6.6%9.4%11.6%13.9%<0.001<0.001
      Hispanic7.2%6.6%7.4%7.9%<0.001<0.001
      Other6.3%5.3%3.3%5.8%<0.001<0.001
      ST-elevation myocardial infarction42.5%31.6%25.5%15.7%<0.001<0.001
      Weekend admission27.3%27.0%26.7%26.3%<0.001<0.001
      Primary expected payer<0.001<0.001
      Medicare30.8%47.5%56.4%71.1%
      Medicaid10.1%9.1%10.2%9.1%
      Private Insurance47.2%34.0%24.9%14.6%
      Self-pay7.7%5.9%5.3%2.7%
      No charge0.7%0.6%0.6%0.3%
      Other3.5%3.0%2.7%2.2%
      Median household income (percentile)<0.001<0.001
      0-25th24.3%28.0%30.4%34.4%
      26th-50th27.2%27.5%27.6%27.5%
      51st-75th25.5%24.3%23.4%22.4%
      76th-100th23.0%18.6%18.6%16.6%
      Cardiogenic shock3.6%3.4%4.8%6.9%<0.001<0.001
      Cardiac arrest3.1%2.9%3.3%4.3%<0.001<0.001
      Ventricular tachycardia7.4%6.0%6.1%6.6%<0.001<0.001
      Ventricular fibrillation4.0%3.1%3.0%2.5%<0.001<0.001
      Atrial fibrillation7.1%12.1%17.1%22.6%<0.001<0.001
      Dyslipidaemia43.9%61.9%61.2%61.6%<0.001<0.001
      Thrombocytopenia<0.1%2.9%5.8%8.3%<0.001<0.001
      Smoker2.8%2.4%1.9%1.4%<0.001<0.001
      Previous acute myocardial infarction5.9%11.7%13.7%16.6%<0.001<0.001
      History of ischemic heart disease67.5%72.3%69.5%69.5%<0.001<0.001
      Previous percutaneous coronary intervention7.4%14.3%15.7%17.6%<0.001<0.001
      Previous coronary artery bypass grafting8.4%17.2%20.4%25.4%<0.001<0.001
      Previous cerebrovascular accident1.9%4.9%7.3%10.4%<0.001<0.001
      Anemia2.4%9.3%17.1%32.0%<0.001<0.001
      Heart failure<0.1%4.0%27.1%57.1%<0.001<0.001
      Valvular disease<0.1%4.9%4.7%14.0%<0.001<0.001
      Hypertension<0.1%74.4%57.0%32.2%<0.001<0.001
      Peripheral vascular disorders0.9%3.8%5.5%12.5%<0.001<0.001
      Chronic pulmonary disease3.1%14.3%13.9%32.4%<0.001<0.001
      Coagulopathy0.2%4.0%7.7%11.1%<0.001<0.001
      Dementia<0.1%0.9%5.3%7.9%<0.001<0.001
      Liver disease0.4%0.7%1.8%4.4%<0.001<0.001
      Chronic renal failure<0.1%<0.1%9.1%42.5%<0.001<0.001
      Metastatic cancer<0.1%<0.1%<0.1%2.7%<0.001<0.001
      Bed size of hospital<0.001<0.001
      Small16.9%17.0%17.2%17.4%
      Medium30.0%30.3%30.0%29.9%
      Large53.2%52.6%52.8%52.8%
      Hospital Region<0.001<0.001
      Northeast22.8%21.6%21.2%21.2%
      Midwest23.8%23.2%23.1%23.7%
      South38.6%41.4%41.6%40.8%
      West14.8%13.8%14.2%14.3%
      Location/teaching status of hospital<0.001<0.001
      Rural7.4%8.0%8.2%8.5%
      Urban non-teaching26.4%25.8%24.7%24.0%
      Urban teaching66.2%66.2%67.1%67.5%
      DANCAMI = Danish Co-morbidity Index for Acute Myocardial Infarction; rDANCAMI = Restricted Danish co-morbidity index for Acute Myocardial Infarction.
      DANCAMI risk score = Score to identify prognosis of patients with AMI, composed of the cardiovascular (heart failure, intermittent arterial claudication, aortic disease, valvular heart disease, stroke, hypertension, diabetes uncomplicated, diabetes with end-organ damage, chronic kidney disease) and non-cardiovascular co-morbidities (high-risk cancer, low-risk cancer, coagulopathy, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis).
      Patients with a DANCAMI score of ≥6 had the highest all-cause mortality (10.0%). This group also had the highest rate of major bleeding (5.4%) and lowest requirement of CA (41.8%), and PCI (25.5%) compared with their lower-risk counterparts (p <0.001) (Figure 1, Supplementary Table 3). Results of multivariable adjusted analysis show that patients with a DANCAMI risk score of ≥4 were more likely to experience all-cause mortality, with the odds of mortality for the patients with a DANCAMI score of 1 to 3 showing no significant change when compared with patients with a DANCAMI score of 0. Similarly, the odds of major bleeding incrementally increased with a DANCAMI score of ≥1 compared with patients with a DANCAMI score of 0 (Figure 2, Table 1). Moreover, patients with a DANCAMI risk score of ≥1 were less likely to receive invasive management in the form of CA and PCI compared with patients with an rDANCAMI score of 0 (Figure 2, Table 2).
      Figure 1
      Figure 1Unadjusted rates of invasive management and clinical outcomes in different groups: (A) DANCAMI risk score; (B). rDANCAMI risk score. Note: ‘MACCE’ and ‘ischemic stroke’ were not calculated due to ‘stroke’ being a part of the DANCAMI risk score. DANCAMI risk score – score to identify prognosis of patients with AMI, composed of the cardiovascular (heart failure, intermittent arterial claudication, aortic disease, valvular heart disease, Stroke, hypertension, diabetes uncomplicated, diabetes with end-organ damage, chronic kidney disease) and non-cardiovascular co-morbidities (high-risk cancer, low-risk cancer, coagulopathy, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis). rDANCAMI risk score – score to identify prognosis of patients with AMI, composed of non-cardiovascular co-morbidities only (high-risk cancer, low-risk cancer, coagulopathy, obesity, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis, connective tissue disease).
      Figure 2
      Figure 2aOR of invasive management and clinical outcomes in different groups: (A) DANCAMI risk score; (B) rDANCAMI risk score. Reference group is group with a DANCAMI risk score of 0. Reference group is the group with an rDANCAMI risk score of 0. Note: ‘MACCE’ and ‘ischemic stroke’ were not calculated due to ‘stroke’ being a part of the DANCAMI risk score. Multivariable logistic regression model adjusted for bed size of the hospital, region of the hospital, location/teaching status of the hospital, age, gender , primary expected payer, median household income, smoking status, previous myocardial infarction, previous percutaneous coronary intervention, previous coronary artery bypass graft, previous cerebrovascular accident, dyslipidemia, atrial fibrillation, and thrombocytopenia. DANCAMI risk score – score to identify prognosis of patients with AMI, composed of the cardiovascular (heart failure, intermittent arterial claudication, aortic disease, valvular heart disease, stroke, hypertension, diabetes uncomplicated, diabetes with end-organ damage, chronic kidney disease) and non-cardiovascular co-morbidities (high-risk cancer, low-risk cancer, coagulopathy, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis). rDANCAMI risk score – score to identify prognosis of patients with AMI, composed of non-cardiovascular co-morbidities only (high-risk cancer, low-risk cancer, coagulopathy, obesity, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis, connective tissue disease).
      Table 2aOR of in-hospital invasive management and clinical outcomes in the groups of the DANCAMI risk score
      Reference group is the group with an rDANCAMI risk score of 0. rDANCAMI risk score – Score to identify prognosis of patients with AMI, composed of non-cardiovascular co-morbidities only (high-risk cancer, low-risk cancer, coagulopathy, obesity, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis, connective tissue disease).
      VariablesDANCAMI score 1-3 (19.1%)DANCAMI score 4-5 (12.9%)DANCAMI score ≥6 (62.8%)
      aOR [95% CI]p-valueaOR [95% CI]p-valueaOR [95% CI]p-value
      Invasive management:
      Coronary angiography0.84 [0.83-0.85]<0.0010.55 [0.55-0.56]<0.0010.34 [0.33-0.34]<0.001
      Percutaneous coronary intervention0.78 [0.77-0.79]<0.0010.54 [0.53-0.55]<0.0010.34 [0.33-0.34]<0.001
      Clinical outcomes:
      All-cause mortality0.99 [0.96-1.02]0.0771.32 [1.29-1.37]<0.0012.25 [2.18-2.32]<0.001
      Major adverse cardiac and coronary events//////
      Major bleeding1.94 [1.82-2.06]<0.0012.86 [2.69-3.04]<0.0014.79 [4.52-5.08]<0.001
      Ischemic stroke//////
      aOR = adjusted Odds Ratios; CI = Confidence Interval; DANCAMI = DANish co-morbidity index for Acute Myocardial Infarction; rDANCAMI = Restricted Danish co-morbidity index for Acute Myocardial Infarction.
      Note – ‘MACCE’ and ‘ischemic stroke’ were not calculated due to ‘stroke’ being a part of the DANCAMI risk score.
      Multivariable logistic regression model adjusted for: bed size of the hospital, region of the hospital, location/teaching status of the hospital, age, gender , primary expected payer, median household income, smoking status, previous myocardial infarction, previous percutaneous coronary intervention, previous coronary artery bypass graft, previous cerebrovascular accident, STEMI, PCI (for outcomes only)., Dyslipidemia, atrial fibrillation, and thrombocytopenia.
      DANCAMI risk score = Score to identify prognosis of patients with AMI, composed of the cardiovascular (heart failure, intermittent arterial claudication, aortic disease, valvular heart disease, stroke, hypertension, diabetes uncomplicated, diabetes with end-organ damage, chronic kidney disease) and non-cardiovascular co-morbidities (high-risk cancer, low-risk cancer, coagulopathy, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis).
      Reference group is the group with a DANCAMI risk score of 0.
      Similar results were observed when DANCAMI was modeled as a continuous variable whereby per 1-unit increase in DANCAMI score led to an increased odds of mortality (aOR 1.08, 95% CI 1.08 to 1.08), major bleeding (aOR 1.09, 95% CI 1.09 to 1.09), and decreased odds of invasive management in the form of CA (aOR 0.91, 95% CI 0.91 to 0.91) and PCI (aOR 0.90, 95% CI 0.90 to 0.90) (Supplementary Table 4).
      Patients with an rDANCAMI score of ≥6 were on average younger and had a higher prevalence of thrombocytopenia (14.4%), smoking (1.6%), and anemias (61.1%) than lower-risk patients (p <0.001) (Table 3). Patients with an rDANCAMI score of ≥6 had the highest all-cause mortality (13.8%, p <0.001), MACCE (19.4%, p <0.001), major bleeding (7.2%, p <0.001), and stroke (6.4%, p <0.001) (Figure 1, Supplementary Table 5). Patients with an rDANCAMI score of ≥6 had lower rates of CA (33.2%, p <0.001), coronary artery bypass grafting (6.0%, p <0.001), and PCI (18.7%, p <0.001) (Figure 1, Supplementary Table 5). With multivariable adjustment, patients with an increasing rDANCAMI score (≥1) were more likely to suffer all-cause mortality, MACCE, major bleeding, and ischemic stroke compared with patients with an rDANCAMI score of 0 (Figure 2, Table 4). Patients with an increasing rDANCAMI score (≥1) were less likely to receive CA and PCI compared with patients with an rDANCAMI score of 0 (Figure 2, Table 4).
      Table 3Patient characteristics according to the groups of rDANCAMI risk score
      CharacteristicsrDANCAMI score 0 (31.9%)rDANCAMI score 1-3 (30.8%)rDANCAMI score 4-5 (10.8%)rDANCAMI score ≥6 (26.4%)Overall p-valueTrend p-value
      Number of hospitalizations824,925798,170280,415684,105
      Age (years), median (interquartile range)67 (57, 78)68 (58, 78)71 (60, 82)71 (61, 81)<0.001<0.001
      Women35.6%40.5%48.8%45.8%<0.001<0.001
      White74.5%73.9%74.6%74.7%<0.0010.600
      Black10.7%12.7%13.4%13.6%<0.0010.600
      Hispanic8.0%7.9%7.2%6.9%<0.0010.600
      Other6.8%5.5%4.8%4.9%<0.0010.600
      ST-elevation myocardial infarction29.2%20.6%16.2%15.0%<0.001<0.001
      Weekend admission26.6%26.5%26.6%26.6%<0.001<0.001
      Primary expected payer<0.001<0.001
      Medicare55.1%60.5%68.9%71.6%
      Medicaid8.1%9.5%8.4%10.8%
      Private Insurance28.7%22.6%17.5%12.6%
      Self-pay5.0%4.4%2.7%2.5%
      No charge0.4%0.4%0.3%0.3%
      Other2.7%2.6%2.3%2.3%
      Median Household Income (percentile)<0.001<0.001
      0-25th28.7%31.9%31.9%34.4%
      26th-50th27.4%27.7%27.5%27.5%
      51st-75th24.0%23.2%27.5%21.9%
      76th-100th19.9%17.3%22.9%16.2%
      Cardiogenic shock4.4%5.3%5.0%8.3%<0.0010.039
      Cardiac arrest2.8%3.5%3.4%5.8%<0.001<0.001
      Ventricular tachycardia6.4%6.3%5.8%6.8%<0.001<0.001
      Ventricular fibrillation2.8%2.7%2.2%3.1%<0.001<0.001
      Atrial fibrillation15.119.0%21.7%23.0%<0.001<0.001
      Dyslipidaemia63.2%63.1%62.9%53.9%<0.001<0.001
      Thrombocytopenia<0.1%6.4%6.5%14.4%<0.001<0.001
      Smoker1.9%1.9%1.2%1.6%<0.001<0.001
      Previous acute myocardial Infarction13.8%15.6%15.1%14.6%<0.001<0.001
      History of ischemic heart disease74.9%72.9%67.6%61.3%<0.001<0.001
      Previous percutaneous coronary intervention16.8%17.5%16.2%14.0%<0.001<0.001
      Previous coronary artery bypass grafting22.4%23.9%22.5%20.3%<0.001<0.001
      Previous cerebrovascular accident6.8%8.0%10.0%10.4%<0.001<0.001
      Anemia4.8%26.1%26.3%44.8%<0.001<0.001
      Heart failure28.1%41.1%45.5%51.2%<0.001<0.001
      Valvular disease8.8%10.6%11.6%11.4%<0.001<0.001
      Hypertension49.7%42.1%39.9%33.8%<0.001<0.001
      Peripheral vascular disorders6.7%9.9%9.2%11.7%<0.001<0.001
      Chronic pulmonary disease3.0%26.2%24.8%50.4%<0.001<0.001
      Coagulopathy0.1%8.4%8.8%19.4%<0.001<0.001
      Dementia<0.1%<0.1%23.8%20.2%<0.001<0.001
      Liver disease0.5%1.0%3.0%8.8%<0.001<0.001
      Chronic renal failure18.0%29.5%32.9%35.8%<0.0010.03
      Metastatic cancer<0.1%<0.1%0.1%6.3%<0.0010.01
      Bed size of hospital<0.001<0.001
      Small17.0%17.1%17.8%17.5%
      Medium30.3%29.9%29.9%29.7%
      Large52.7%53.0%52.3%52.8%
      Hospital region<0.001<0.001
      Northeast23.0%20.9%21.2%20.0%
      Midwest22.0%23.5%25.0%24.8%
      South41.1%41.5%39.9%40.4%
      West13.9%14.1%13.9%14.8%
      Location/teaching status of hospital<0.001<0.001
      Rural8.0%8.3%8.9%8.4%
      Urban non-teaching25.2%24.5%24.4%23.9%
      Urban teaching66.8%67.2%66.7%67.7%
      DANCAMI – Danish co-morbidity index for Acute Myocardial Infarction; rDANCAMI – Restricted Danish co-morbidity index for Acute Myocardial Infarction.
      rDANCAMI risk score = Score to identify prognosis of patients with AMI, composed of non-cardiovascular co-morbidities only (high-risk cancer, low-risk cancer, coagulopathy, obesity, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis, connective tissue disease).
      Table 4aOR of in-hospital invasive management and clinical outcomes in the groups of the rDANCAMI risk score
      VariablesrDANCAMI score 1-3 (30.8%)rDANCAMI score 4-5 (10.8%)rDANCAMI score ≥6 (26.4%)
      aOR [95% CI]p-valueaOR [95% CI]p-valueaOR [95% CI]p-value
      Invasive management:
      Coronary angiography0.72 [0.71-0.72]<0.0010.54 [0.53-0.55]<0.0010.34 [0.34-0.35]<0.001
      Percutaneous Coronary Intervention0.68 [0.67-0.68]<0.0010.51 [0.51-0.52]<0.0010.33 [0.33-0.33]<0.001
      Clinical outcomes:
      All-cause mortality1.21 [1.20-1.23]<0.0011.38 [1.36-1.41]<0.0012.34 [2.31-2.37]<0.001
      Major adverse cardiac and cerebrovascular events1.16 [1.14-1.17]<0.0011.33 [1.31-1.35]<0.0012.58 [2.51-2.61]<0.001
      Major bleeding1.55 [1.52-1.58]<0.0012.31 [2.26-2.36]<0.0012.80 [2.75-2.86]<0.001
      Ischemic stroke0.98 [0.95-1.00]<0.0011.18 [1.14-1.21]<0.0013.38 [3.31-3.46]<0.001
      AOR = adjusted Odds Ratios; CI = Confidence Interval; DANCAMI = Danish co-morbidity index for Acute Myocardial Infarction; rDANCAMI = Restricted Danish co-morbidity index for Acute Myocardial Infarction.
      Multivariable logistic regression model adjusted for: bed size of the hospital, region of the hospital, location/teaching status of the hospital, age., gender primary expected payer, median household income, smoking status, previous myocardial infarction, previous percutaneous coronary intervention, previous coronary artery bypass graft, previous cerebrovascular accident, AMI, PCI (for outcomes only) dyslipidemia, atrial fibrillation, and thrombocytopenia.
      low asterisk Reference group is the group with an rDANCAMI risk score of 0.rDANCAMI risk score – Score to identify prognosis of patients with AMI, composed of non-cardiovascular co-morbidities only (high-risk cancer, low-risk cancer, coagulopathy, obesity, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis, connective tissue disease).
      Similar results were observed when rDANCAMI was modeled as a continuous variable whereby per 1-unit increase in rDANCAMI score led to an increased odds of mortality (aOR 1.10, 95% CI 1.10 to 1.10). There were also increased odds of major bleeding (aOR 1.10, 95% CI 1.10 to 1.10), MACCE (aOR 1.11, 95% CI 1.11 to 1.11) and stroke (aOR 1.14, 95% CI 1.14 to 1.14), and decreased odds of invasive management in the form of CA (aOR 0.88, 95% CI 0.88 to 0.89) and PCI (aOR 0.88, 95% CI 0.87 to 0.88) (Supplementary Table 4).
      ROC analysis suggested that the AUC of DANCAMI for mortality (AUC 0.646, 95% CI 0.643 to 0.648, p <0.001 as a continuous variable; and AUC 0.593, 95% CI 0.590 to 0.595, p <0.001 as a categorical variable) was relatively modest (Figure 3). Similarly, rDANCAMI had an AUC of 0.638 for mortality (95% CI 0.635 to 0.641, p <0.001) when treated as a continuous variable, and AUC of 0.625 (95% CI 0.622 to 0.628, p <0.001) when treated as a categorical variable (Figure 3). These AUC values were poorer than those of CCI score (AUC 0.697, 95% CI 0.695 to 0.700, p <0.001). The optimal cut-off values for DANCAMI and rDANCAMI risk scores were ≥8 (sensitivity of 61.0% and specificity of 60.0%) and ≥3 (sensitivity of 57.0% and specificity of 64.0%), respectively (Supplementary Table 6).Calibration plots of DANCAMI and rDANCAMI scores for mortality are presented in Supplementary Figure 2.
      Figure 3
      Figure 3ROC curves for DANCAMI and rDANCAMI. DANCAMI risk score – score to identify prognosis of patients with AMI, composed of the cardiovascular (heart failure, intermittent arterial claudication, aortic disease, valvular heart disease, stroke, hypertension, diabetes uncomplicated, diabetes with end-organ damage, chronic kidney disease) and non-cardiovascular co-morbidities (high-risk cancer, low-risk cancer, coagulopathy, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis). rDANCAMI risk score – score to identify prognosis of patients with AMI, composed of non-cardiovascular co-morbidities only (high-risk cancer, low-risk cancer, coagulopathy, obesity, dementia, alcohol and drug abuse, schizophrenia, affective disorder, epilepsy, neurodegenerative disorder, hemiplegia, chronic pulmonary disease, ulcer disease, mild liver disease, moderate to severe liver disease, chronic pancreatitis, connective tissue disease.
      When stratifying patients by their DANCAMI/rDANCAMI score and whether they experienced an ST-elevated myocardial infarction (STEMI) or Non-STEMI (NSTEMI), the results were consistent with the findings in the total cohort, irrespective of the AMI type (Supplementary Tables 7 and 8). When investigating the interaction between mortality and PCI and STEMI and previous AMI, the odds with PCI (aOR 0.30, 95% CI 0.30 to 0.30) and previous AMI (aOR 0.82, 95% CI 0.80 to 0.83) were lower but higher with STEMI (aOR 3.39 95% CI 3.36 to 3.43).

      Discussion

      This is the first study to externally validate the DANCAMI and rDANCAMI scores in a national cohort of over 2.5 million patients with AMI. We report several important findings. First, only minority of patients had no co-morbid conditions, highlighting the significant prevalence of co-morbid conditions in patients presenting with AMI. Second, patients with increasing DANCAMI and rDANCAMI scores (≥1) were less likely to receive invasive management and experienced more adverse outcomes. Finally, the use of only non-cardiovascular co-morbidities in the rDANCAMI score yielded a similar performance as DANCAMI in predicting mortality.
      The DANCAMI and rDANCAMI risk scores were initially derived and validated in Danish (36,685 patients) and New Zealand (75,069 patients) AMI cohorts.
      • Wellejus Albertsen L
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      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      These scores marginally outperformed the CCI and ECI in predicting 1-year mortality.
      • Wellejus Albertsen L
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      • Schmidt SAJ
      • Grey C
      • Jackson R
      • Sørensen HT
      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      Novel scores had similar c-statistics to CCI and ECI (AUC 0.77 and 0.76 for DANCAMI and rDANCAMI, respectively, vs AUC 0.77 for CCI and AUC 0.76 for ECI) and similar integrated discrimination improvement, but CCI had a lower Net Reclassification Index.
      • Wellejus Albertsen L
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      • Schmidt M.
      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      However, in this study, AUC values of DANCAMI and rDANCAMI were poorer than those of CCI, suggesting the need for further comparisons in different populations.
      Our findings support those reported in the initial study. Increased DANCAMI and rDANCAMI scores were associated with an increased risk of adverse outcomes.
      • Wellejus Albertsen L
      • Heide-Jørgensen U
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      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      Our work adds novelty by externally validating risk scores in a 7-fold larger cohort and investigating score performance to several additional outcome measures. The differences between the original and this study include follow-up duration, as the original study reported 1-year outcomes, whereas this study investigated in-hospital outcomes. Therefore, it may be possible that these risk scores are useful in predicting long-term mortality, but their value is less certain for in-hospital mortality. This may be because other factors contributing to the patient presentation (e.g., size of infarction, hemodynamic stability, time from presentation to intervention) could be more important than co-morbidities when predicting short-term outcomes.
      • Tehrani BN
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      Acute myocardial infarction and cardiogenic shock: should we unload the ventricle before percutaneous coronary intervention?.
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      Infarct size as predictor of systolic functional recovery after myocardial infarction.
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      Time-to-reperfusion in patients with acute myocardial infarction and mortality in prehospital emergency care: meta-analysis.
      Several studies have demonstrated an association between co-morbidity burden and AMI prognosis. A large UK study concluded that co-morbid illness significantly impacts 180-day mortality among 330,367 patients with AMI.
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      Another Swiss study demonstrated a strong association of co-morbidity burden with in-hospital adverse outcomes.
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      Association of co-morbidities with clinical outcomes in patients after acute myocardial infarction.
      Few studies have investigated the impact of non-cardiovascular co-morbidities only on AMI prognosis. Canivell et al
      • Canivell S
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      demonstrated that both cardiovascular and non-cardiovascular co-morbidities increased the risk of future cardiovascular events. Other studies showed that patients with AMI with multiple co-morbidities have lower survival and increased length of stay.
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      There are several possible reasons for why co-morbidities lead to poorer outcomes. First, increased co-morbidity burden could be associated with lower utilization of guideline-directed medical treatment (“risk-treatment paradox”) and reduced effectiveness of clinical management.
      • Canivell S
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      Prognosis of cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome.
      ,
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      Cardiovascular co-morbidities have direct effects on cardiovascular prognosis, either by potentiating a positive feedback loop, or by multiple perturbations in cardiovascular homeostasis (multiple parallel hits hypothesis), or simply by labeling patients with a higher-risk profile.
      • Tilg H
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      Similarly, the mechanisms by which non-cardiovascular co-morbidities contribute to poorer outcomes are numerous and could be related to a pro-inflammatory environment, accelerated atherosclerosis, drug toxicity impaired pharmacokinetics, and later diagnosis/diagnosis mimicking.
      • Canivell S
      • Muller O
      • Gencer B
      • Heg D
      • Klingenberg R
      • Räber L
      • Carballo D
      • Matter C
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      Prognosis of cardiovascular and non-cardiovascular multimorbidity after acute coronary syndrome.
      ,
      • Chen HY
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      • Goldberg RJ.
      The impact of cardiac and noncardiac comorbidities on the short-term outcomes of patients hospitalized with acute myocardial infarction: a population-based perspective.
      ,
      • Mohamed MO
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      DANCAMI and rDANCAMI included contemporary co-morbidities such as psychiatric disorders and excluded non-contemporary co-morbidities from previous indices, such as AIDS.
      • Wellejus Albertsen L
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      The Danish comorbidity index for acute myocardial infarction (DANCAMI): development, validation and comparison with existing comorbidity indices.
      Although ECI and CCI include psychiatric conditions, their weighting was low, whereas in DANCAMI and rDANCAMI, weighting was relatively high.
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      This is supported by previous studies that have highlighted the association between mental health diagnoses and cardiovascular risk, the mechanism of which is poorly understood.
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      Several studies have investigated the use of other well-known co-morbidity indices in hospitalized patients. The ECI has repeatedly been demonstrated to significantly outperform the CCI in predicting prognosis of patients with AMI in five different European countries as well as the United States and Taiwan.
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      Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality.
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      Comparison of the performance of two co-morbidity measures, with and without information from prior hospitalizations.
      However, these studies included co-morbidities as separate variables instead of weighing and scoring each variable.
      • Wellejus Albertsen L
      • Heide-Jørgensen U
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      ,
      • Zhang F
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      • Ensor J
      • Mohamed MO
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      Elixhauser outperformed Charlson co-morbidity index in prognostic value after ACS: insights from a national registry.
      ,
      • Chu YT
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      Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality.
      • Gutacker N
      • Bloor K
      • Cookson R.
      Comparing the performance of the Charlson/Deyo and Elixhauser comorbidity measures across five European countries and three conditions.
      • Stukenborg GJ
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      Comparison of the performance of two co-morbidity measures, with and without information from prior hospitalizations.
      The European Society of Cardiology guidelines advise that clinicians should consider co-morbidity burden in conjunction with the clinical presentation of the patient to tailor the use of invasive management and estimate prognosis.
      • Collet JP
      • Thiele H
      • Barbato E
      • Barthelemy O
      • Bauersachs J
      • Bhatt DL
      • Dendale P
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      • Jobs A
      • Juni P
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      • Rutten FH
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      • Siontis GCM
      ESC Scientific Document Group
      2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation.
      However, no specific co-morbidity indices have been recommended, and this study re-affirms the potential for co-morbidity indices to be used in clinical practice, utilizing both cardiovascular and non-cardiovascular co-morbidities.
      • Austin SR
      • Wong YN
      • Uzzo RG
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      Why summary co-morbidity measures such as the Charlson comorbidity index and Elixhauser score work.
      For example, the rDANCAMI score could be used to risk-stratify different subpopulations with AMI with less common co-morbidities in everyday practice.
      • Moledina SM
      • Rashid M
      • Nolan J
      • Nakao K
      • Sun LY
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      • Wilton SB
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      • Mamas MA.
      Addressing disparities of care in non-ST-segment elevation myocardial infarction patients without standard modifiable risk factors: insights from a nationwide cohort study.
      ,
      • Figtree GA
      • Vernon ST
      • Hadziosmanovic N
      • Sundström J
      • Alfredsson J
      • Arnott C
      • Delatour V
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      Mortality in STEMI patients without standard modifiable risk factors: a sex-disaggregated analysis of SWEDEHEART registry data.
      Finally, it encourages cardiovascular clinicians to consider cross-specialty input to optimize non-cardiovascular risk factors as a potential means to improve AMI outcomes.
      The limitations of this study include several inherent to the use of the NIS database. Data coding is potentially subject to errors due to inaccuracies with coding and missing data.
      • van Walraven C
      • Austin P.
      Administrative database research has unique characteristics that can risk biased results.
      In addition , detailed clinical information such as cardiac markers and medications that could have an impact on mortality are not available in the NIS database. Only the in-hospital data are available in the NIS, and the use of DANCAMI and rDANCAMI for long-term outcomes is not studied. Finally, this is an observational study and hence, confounders not included in this study could contribute to adverse outcomes despite the broad scope of diseases covered by the NIS.
      In conclusion, increased DANCAMI and rDANCAMI scores were associated with lower utilization of invasive management and more adverse in-hospital outcomes in patients admitted for AMI. Despite the omission of cardiovascular risk factors, rDANCAMI showed good performance emphasizing the importance of non-cardiovascular co-morbidities. These findings reassure that DANCAMI and rDANCAMI could be useful for risk stratification of patients with AMI in addition to other conventional risk scores.

      Disclosures

      Christian Mallen has received funding from the NIHR, MRC, Versus Arthritis, and AHRC. The School of Medicine has supported a BMS-funded non-pharmacological AF screening trial. The other authors have no conflicts of interest to declare.

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