Abstract
Background
Spontaneous coronary artery dissection (SCAD) has been increasingly recognized in the past decades. SCAD patients can present with acute myocardial infarction (AMI), particularly in young healthy women without conventional risk factors. However, data on the outcomes of SCAD patients presenting with AMI or benefit of PCI for SCAD in the setting of AMI is inconclusive.
Methods
We evaluated the prevalence, recent trends, the incidence and in-hospital mortality among women with acute myocardial infarction (AMI) who presented with or without SCAD, and to evaluate the impact of PCI on in-hospital mortality from a population-based analysis, using the National Inpatient Sample (NIS) database between 2016 and 2019.
Results
From 2016-2019, there were 1,527,555 cases of females presenting with AMI. Of that number, there were 12,125 cases of SCAD. Mortality trends in the SCAD and non-SCAD group were comparable. There was a gradual increase in incidence each year for SCAD-STEMI.
Conclusion
Mortality did not differ from 2016-2019 in patients with MI found to have SCAD or not. However, it seems that the SCAD-MI cases are gradually increasing each year. More research needs to be performed to better elucidate treatment outcomes in these patients.
Introduction
Spontaneous coronary artery dissection (SCAD) has been increasingly recognized in the past decades. SCAD patients can present with acute myocardial infarction (AMI), particularly in young healthy women without conventional risk factors. However, data on the outcomes of SCAD patients presenting with AMI or benefit of PCI for SCAD in the setting of AMI is inconclusive. We evaluated the prevalence, recent trends, the incidence and in-hospital mortality among women with acute myocardial infarction (AMI) who presented with or without SCAD, and to evaluate the impact of PCI on in-hospital mortality from a population-based analysis, using the National Inpatient Sample (NIS) database between 2016 and 2019.
Methods
Data source
We utilized the National Inpatient Sample (NIS) database, analyzing it from the year 2016 to 2019. The NIS is one of the largest inpatient database, offering comprehensive estimates of inpatient service usage, accessibility, cost, quality, and outcomes at both national and regional scales within the United States. In its unweighted state, the NIS compiles data from about 7 million hospital stays annually. When weighted, this figure extends to an estimated 35 million hospitalizations nationwide each year. The NIS includes data from states participating in the Healthcare Cost and Utilization Project (HCUP), covering more than 97% of the United States population. It represents a 20% stratified sample of hospital patient discharges across the country, excluding specialized rehabilitation and long-term acute care facilities. Additionally, the de-identified nature of the NIS data meant that our study did not necessitate approval from an Institutional Review Board.
Study population
Between 2016 and 2019, there are up to 40 diagnoses and 25 procedures for each hospital admission within the database. We extracted our study group using the International Classification of Disease, Tenth Edition, Clinical Modification (ICD-10-CM) codes, detailed in supplementary Table 1 . Our focus was on patients diagnosed with acute myocardial infarction (AMI), defined as non-ST-segment elevation or ST-segment elevation myocardial infarction, identified through specific ICD-10-CM codes. Our selection process further narrowed down to patients who underwent coronary angiography or percutaneous coronary intervention (PCI). We excluded patients who had a coinciding diagnosis of accidental puncture or laceration to minimize the potential for coding inaccuracies. The study included all adult hospitalizations (age >18 years), while admissions lacking complete data on age, gender, or mortality were omitted from our analysis. This approach aligns with methodologies previously established in the literature and conforms to the standards set by the Agency for Healthcare Research and Quality.
Study covariates and outcomes
To conduct a comprehensive analysis and reduce the influence of unrecognized variables, our study incorporated an extensive range of covariates. These included demographic details such as age, gender, insurance status, size of the hospital, teaching status of the hospital, elective admission status, and race, all of which were directly accessible in the database. We also considered a wide range of comorbidities, including obesity, uncomplicated and complicated hypertension, valvular heart diseases, disorders of pulmonary circulation, chronic lung diseases, liver diseases, uncomplicated and complicated diabetes mellitus, peripheral vascular diseases, metastatic cancer, solid tumor, rheumatological disorders, coagulopathy, fluid and electrolyte disorders, chronic kidney disease, blood loss anemia, deficiency anemia, hiv, smoking, alcohol abuse, drug abuse, psychoses, paralysis, other neurological disorders, previous myocardial infarction (MI), and previous coronary artery bypass grafting (CABG). These were identified using their corresponding ICD-10-CM codes. The primary outcome was to examine the incidence and in-hospital mortality of women with AMI, stratified by presence of SCAD.
Statistical analysis
Our statistical analysis involved deriving national weighted estimates using the discharge weights provided by the Healthcare Cost and Utilization Project (HCUP). For categorical variables, we presented them as frequencies and percentages, and made comparison using the chi-square test Continuous variables, on the other hand, were presented as means and standard deviations. In strict adherence to the data use agreement for nationwide databases from HCUP, we ensured privacy by not reporting any variable with a frequency of 10 or less, due to the risk of patient identification. Linear trend of PCI and in-hospital mortality was compared using the chi-square test for trend. For in-hospital mortality, we implemented a multivariate regression analysis using multilevel fixed effect models. The variables integrated into this model encompassed age, race, primary payment information, hospital bed size, hospital teaching status, elective admission, and any variable that showed significance in the univariate analysis (with a threshold of 0.2). Additionally, we included variables deemed clinically pertinent from prior research. We also implemented propensity-score matching to ensure baseline differences were appropriately accounted for. The nearest neighbor matching method was employed and a 1:1 ratio was chosen. We performed all the analysis using R programming version 4.3 (R Foundation for Statistical Computing, Vienna, Austria) and Stata version 17.0 (StataCorp, College Station, Texas).
Results
In this paper, we sought to examine the incidence and in-hospital mortality among women with acute myocardial infarction (AMI) who presented with or without spontaneous coronary artery dissection (SCAD). From 2016-2019, there were 1,527,555 cases of females presenting with AMI. Of that number, there were 12,125 cases of SCAD. In addition, there were 4,685 STEMI cases and 7,440 NSTEMI cases.
Comparing women with AMI who were found to have SCAD compared to women with AMI not found to have SCAD, the average age of the SCAD group was 58.2 years compared to 57.8 years in the non-SCAD group ( Table 1 ). The only statistically significant difference in the SCAD group compared to the non-SCAD group was a prior history of coronary artery bypass surgery. Other comorbidities including obesity, hypertension, valvular heart disease, congestive heart failure, liver disease, pulmonary disease, cancers, chronic kidney disease, smoking use, alcohol use, and depression were not statistically significant between the two groups.
| Variables | SCAD | No SCAD | p-value | ||
|---|---|---|---|---|---|
| N/% | 12,125 | % | 767,800 | % | |
| Age | 58.15 ± 14.69 | 67.43 ± 12.79 | <0.001 | ||
| Race | 0.0754 | ||||
| White | 8295 | 68.41237113 | 537755 | 70.03842146 | |
| Black | 1675 | 13.81443299 | 100355 | 13.07046106 | |
| Hispanic | 1090 | 8.989690722 | 62715 | 8.168142746 | |
| Asian or Pacific Islander | 225 | 1.855670103 | 17630 | 2.296170878 | |
| Native American | 40 | 0.329896907 | 4675 | 0.608882521 | |
| Other | 275 | 2.268041237 | 20205 | 2.631544673 | |
| Obesity | 2735 | 22.55670103 | 177365 | 23.10041678 | 0.5252 |
| Cardiac Arrhythmias | 3060 | 25.2371134 | 159665 | 20.79512894 | <0.001 |
| CHF | 2580 | 21.27835052 | 277720 | 36.17087783 | <0.001 |
| HTN, uncomplicated | 8020 | 66.1443299 | 634755 | 82.67191977 | <0.001 |
| HTN, complicated | 2575 | 21.2371134 | 295110 | 38.43579057 | <0.001 |
| Valvular HD | 1340 | 11.05154639 | 126640 | 16.49387861 | <0.001 |
| Pulmonary Circulation Disorders | 410 | 3.381443299 | 55820 | 7.270122428 | <0.001 |
| Chronic Lung Diseases | 2130 | 17.56701031 | 200450 | 26.10705913 | <0.001 |
| Liver Diseases | 595 | 4.907216495 | 41050 | 5.346444387 | 0.3446 |
| Diabetes, uncomplicated | 1260 | 10.39175258 | 134780 | 17.55405053 | <0.001 |
| Diabetes, complicated | 1255 | 10.35051546 | 200320 | 26.09012764 | <0.001 |
| Peripheral Vascular Disease | 1020 | 8.412371134 | 79410 | 10.34253712 | 0.0027 |
| Lymphoma | 30 | 0.24742268 | 1835 | 0.23899453 | 0.933 |
| Metastatic Cancer | 50 | 0.412371134 | 5015 | 0.653164887 | 0.1435 |
| Solid tumor | 135 | 1.113402062 | 13575 | 1.768038552 | 0.0155 |
| Rheumatological Disorders | 430 | 3.546391753 | 35495 | 4.622948685 | 0.0113 |
| Coagulopathy | 725 | 5.979381443 | 43550 | 5.672050013 | 0.5123 |
| Fluid Disorders | 2705 | 22.30927835 | 222155 | 28.93396718 | <0.001 |
| CKD | 1175 | 9.690721649 | 169435 | 22.06759573 | <0.001 |
| Hypothyroidism | 1770 | 14.59793814 | 149905 | 19.52396457 | <0.001 |
| Blood loss anemia | 80 | 0.659793814 | 5695 | 0.741729617 | 0.6392 |
| Deficiency anemia | 460 | 3.793814433 | 30260 | 3.941130503 | 0.7128 |
| Peptic ulcer disease | 40 | 0.329896907 | 4825 | 0.628418859 | 0.0639 |
| Depression | 1610 | 13.27835052 | 101320 | 13.19614483 | 0.9039 |
| Smoking | 4785 | 39.46391753 | 343075 | 44.68286012 | <0.001 |
| Alcohol abuse | 160 | 1.319587629 | 11055 | 1.43982808 | 0.621 |
| Drug abuse | 420 | 3.463917526 | 22,920 | 2.985152383 | 0.1751 |
| HIV | 5 | 0.041237113 | 725 | 0.094425632 | 0.3959 |
| Psychoses | 35 | 0.288659794 | 4765 | 0.620604324 | 0.0372 |
| Paralysis | 45 | 0.371134021 | 6680 | 0.870018234 | 0.0082 |
| Other neurological disorders | 515 | 4.24742268 | 32885 | 4.283016411 | 0.9311 |
| Weight loss | 290 | 2.391752577 | 24,945 | 3.248892941 | 0.017 |
| Family history of IHD | 2210 | 18.22680412 | 114220 | 14.87626986 | <0.001 |
| Prior MI | 1265 | 10.43298969 | 105250 | 13.70799687 | <0.001 |
| Prior CABG | 325 | 2.680412371 | 51820 | 6.749153425 | <0.001 |
| Acute HF | 1570 | 12.94845361 | 169680 | 22.09950508 | <0.001 |
| Acute systolic HF | 1020 | 8.412371134 | 90510 | 11.7882261 | <0.001 |
| Atrial fibrillation | 1310 | 10.80412371 | 137500 | 17.90830946 | <0.001 |
| VT | 11595 | 95.62886598 | 749860 | 97.66345402 | <0.001 |
| VF | 715 | 5.896907216 | 21340 | 2.779369628 | <0.001 |
| Hospital Bed Size | <0.001 | ||||
| Small | 1685 | 13.89690722 | 124365 | 16.19757749 | |
| Medium | 3370 | 27.79381443 | 233840 | 30.45584788 | |
| Large | 7070 | 58.30927835 | 409595 | 53.34657463 | |
| Hospital Teaching Status | <0.001 | ||||
| Rural | 490 | 4.041237113 | 48665 | 6.338239125 | |
| Urban Non-teaching | 2105 | 17.36082474 | 169405 | 22.06368846 | |
| Urban Teaching | 9530 | 78.59793814 | 549730 | 71.59807241 | |
| Admission | |||||
| Elective | 850 | 7.010309278 | 38700 | 5.040375098 | <0.001 |
| LOS, days | 4.76 ± 6.72 | 5.04 ± 5.92 | 0.049 | ||
| Primary payment coverage | |||||
| Medicare | <0.001 | ||||
| Medicaid | 4295 | 480435 | |||
| Private insurance | 1470 | 78545 | |||
| Self-pay | 5470 | 163635 | |||
| No charge | 555 | 29930 | |||
| Other | 60 | 2650 | |||
| AMI | 260 | 11860 | |||
| STEMI | |||||
| NSTEMI | 4685 | 38.63917526 | 200475 | 26.11031519 | <0.001 |
| Revascularization | 7440 | 61.36082474 | 567325 | 73.88968481 | <0.001 |
| PCI | |||||
| CABG | 6545 | 53.97938144 | 437380 | 56.96535556 | 0.0045 |
| Cardiogenic shock | 835 | 6.886597938 | 50335 | 6.555743683 | 0.5278 |
| Acute ischemic stroke | 1130 | 9.319587629 | 51020 | 6.644959625 | <0.001 |
| Hemorrhagic stroke | 155 | 1.278350515 | 13575 | 1.768038552 | 0.0672 |
| In-hospital Mortality | 35 | 0.288659794 | 1780 | 0.231831206 | 0.5649 |
| 530 | 4.371134021 | 30,550 | 3.978900755 | 0.3295 | |
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