Literature DB >> 34041091

Comparison of demographic profile, risk factors, and in-hospital outcome in young and old patients with acute coronary syndrome: A single-center experience.

Nikhil Bush1, Yash Paul Sharma2, Krishna Prasad2, Pankaj Kumar1, Saurabh Mehrotra2.   

Abstract

BACKGROUND: Coronary artery disease (CAD) is witnessing a demographic transition with increasing prevalence in younger individuals. Data is scarce comparing various characteristics of acute coronary syndrome (ACS) between young and old patients in an Indian setting. Hence, we evaluated the epidemiological, demographic, risk factor, and outcome profile of young and old ACS patients in Indian setting.
METHODS: This was a prospective observational study, which enrolled 50 consecutive ACS patients each into two groups: younger (≤45 years) and elderly (>45 years), respectively. Comparison of clinical presentation, electrocardiography, echocardiographic findings, conventional, nonconventional risk factors, and in-hospital outcomes including duration of hospital stay and major adverse cardiac events (MACE) were made between the two groups. Multivariate regression analysis of risk factors as determinants of MACE adjusting for other confounding factors was also performed.
RESULTS: Fifty patients in each group were compared. Mean age in the younger and elderly group was 36 ± 4.69 and 61.58 ± 10.69 years, respectively. Male sex, smoking, family history of CAD, hyperhomocysteinemia, and obesity were observed more in the younger population. While dyslipidemia, low physical activity, diabetes mellitus, and history of previous ACS was more in the older population. Single-vessel disease was more common in younger patients while multivessel involvement was more common in elderly patients. Older patients had longer hospital stays and more in-hospital MACE including deaths. By multivariate analysis, shock was found to be an independent predictor of MACE in both groups.
CONCLUSION: Younger ACS patients have a different risk profile and better in-hospital outcomes compared to older patients. Copyright:
© 2021 Journal of Family Medicine and Primary Care.

Entities:  

Keywords:  Acute coronary syndrome; major adverse cardiac events; risk factors; stroke

Year:  2021        PMID: 34041091      PMCID: PMC8138388          DOI: 10.4103/jfmpc.jfmpc_1975_20

Source DB:  PubMed          Journal:  J Family Med Prim Care        ISSN: 2249-4863


Introduction

The contribution of coronary artery disease (CAD) to cardiovascular disease burden is increasing in India.[12] Acute coronary syndrome (ACS), which includes unstable angina, non-ST elevation myocardial infarction (NSTEMI), and ST elevation myocardial infarction (STEMI) is the major cause of mortality in CAD.[3] Compared with people of European ancestry and western population, CAD occurs a decade earlier in Indians.[34] Recently, the frequency of acute myocardial infarction has been increased in the younger population.[4] Young patients (<40 years) with ACS had a high prevalence of smoking, family history of CAD, dyslipidemia, myocardial infarction with normal coronary arteries (MINOCA), and single-vessel disease (SVD).[56] Several risk factors of ACS have been reported; however, their role in the pathogenesis of ischemic heart disease and their importance in determining the clinical outcomes among young patients is still not convincingly established. Thus, the present study was designed to elucidate these lacunae in the demographic and risk profile of the younger ACS patients.

Material and Methods

This was a prospective, cross-sectional observational study conducted at a tertiary hospital of North India between January 2016 and May 2017. The study enrolled 50 consecutive patients with ACS, fulfilling the inclusion criteria, each into young (<45 years) and old (≥45 years) groups, respectively. The study strictly followed the standard clinical guidelines and institutional ethics committee has approved the study. Written informed consent was obtained from all patients or their guardians prior to enrollment. Patients with an age ≥18 years, unstable angina: STEMI and NSTEMI were included in the study. However, patients who had already undergone revascularization by percutaneous or surgical [percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG)] or had developed stent thrombosis were excluded.

Definitions and data collection

Patients of unstable angina, NSTEMI, and STEMI were diagnosed based on previously established standard definitions.[78] Chest pain was recorded either as typical angina, atypical angina, or nonanginal chest pain.[9] Details of risk factors including age, gender, and family history of premature CAD (first-degree relatives with males <55 years and females <65 years) were noted. History of diabetes, hypertension, and other comorbidities in both groups were recorded. Anthropological data including body mass index (BMI) and waist circumference were recorded and categorized based on Asian standards and definitions.[10] Smoking history was also taken from all patients. Active smokers were defined as those who reported smoking at least 100 cigarettes in their lifetime and who, at the time of study, smoked either every day or some days. Ex-smokers as those who quit 30 days before enrollment and never smokers as those who had smoked less than 100 cigarettes in their lifetime. Self-reported physical activity data was collected using the international physical activity questionnaire form and based on these patients were divided into low, moderate, and high level of activity.[1112] Complete lipid profile was examined, and patients were classified as having dyslipidemia if they have represented low-density lipoprotein (LDL) >100 mg/dL, high density lipoprotein (HDL) <40 mg/dL in males and <50 mg/dL in females, triglycerides >150 mg/dL, or total cholesterol >200 mg/dL.[13] Clinical chemistry analyzer based on particle-enhanced turbid metric immunoassay method was used to estimate high-sensitive C-reactive protein (hs-CRP) levels in serum. Plasma homocysteine levels were measured using chemiluminescence immunoassay method, and apolipoprotein-A1 was analyzed based on nephelometry. All patients were followed up during hospital stay and in-hospital outcomes were noted. Pharmacotherapy in the form of aspirin, P2Y12 inhibitors (clopidogrel), statins, angiotensin converting enzyme inhibitor/angiotensin receptor blocker, beta-blockers, or novel antianginal drugs were given to all the patients. Major adverse cardiovascular events (MACE), including deaths, reinfarction, stroke, resuscitated cardiac arrest, and major bleeding were also determined during admission and at follow-up.

Statistical analysis

Mean or median was used for quantitative variables and frequencies or proportions for qualitative variables. Comparison between groups was done using Chi-square test for qualitative variables and independent t test or Mann Whitney U test for quantitative variables. Multivariate analysis was done to find independent predictors of MACE. All tests were two-tailed, and P value < 0.05 was considered as significant. Statistical analysis was done using SPSS 22 version.

Results

The mean age of patients in the younger group was 36 ± 4.69 years and in the elderly group was 61.58 ± 10.69 years. The percentage of females in the elderly group was almost double than that of younger group (33.3% vs 18.8%). A comparison of complete baseline and clinical profile of both groups is depicted in Table 1.
Table 1

Baseline demographic characteristics

VariablesYoung (≤45 years) (n=48)Old (>45 years) (n=48)P
Age, years (mean±SD)36.23±4.6961.58±10.690.001
Gender, n (%)
 Male39 (81.3)32 (66.7)0.162
 Female9 (18.8)16 (33.3)
Risk Factors, n (%)
 Diabetes mellitus10 (20.8)22 (45.8)0.009
 Hypertension18 (37.5)22 (45.8)0.408
 Current smoker31 (64.6)16 (33.3)0.011
 Ex-smoker3 (6.3)5 (10.4)
 Cerebrovascular accident4 (8.3)4 (8.3)1.000
 Family history of CAD15 (31.3)10 (20.8)0.245
 History of previous MI3 (6.3)7 (14.6)0.181
 Menopause 1 (11.1)15 (93.8)0.005
Physical Activity, n (%)
 Low13 (27.1%)20 (41.7%)0.118
 Moderate28 (58.3%)26 (54.2%)
 High7 (14.6%)2 (4.2%)
Body Mass Index, kg/m224.76±3.2524.33±3.030.507
 Underweight, n (%)1 (2.1)1 (2.1)0.879
 Normal, n (%)15 (31.3)15 (31.3)
 Overweight, n (%)21 (43.8)24 (50)
 Obese, n (%)11 (22.9)8 (16.7)
 Waist Circumference86.75±8.8191.16±8.950.017
Clinical Symptoms
Chest pain
 Angina33 (68.8)40 (83.3)0.132
 Atypical angina13 (27.1)8 (16.7)
Dyspnea10 (20.8)19 (39.6)0.045
Paroxysmal nocturnal dyspnea4 (8.3)7 (14.6)0.336
Orthopnea3 (6.3)12 (25)0.011
Shock4 (8.3)7 (14.6)0.336

CAD: coronary artery disease; MI: myocardial infarction

Baseline demographic characteristics CAD: coronary artery disease; MI: myocardial infarction In the elderly group, STEMI was found in 62.5%. However, in the younger group NSTEMI and unstable angina were more common (58.4%). Majority of patients presented with typical angina pain (83.3% in elderly group vs 68.8% in the younger group). Dyspnea and palpitations were more common in the elderly group. Furthermore, sympathetic over activity manifested as tachypnea, tachycardia, and sweating were more prevalent in the older age group. Among all, 79.2% younger patients presented with Killip class-1, while 58.3% of the elderly group had Killip class-1, and the remaining 41.7% of elderly belonged to Killip class ≥2. More number of elderly patients (6) than younger patients (1) developed cardiogenic shock (Killip class 4). Two patients from the elderly group reported a murmur of mitral regurgitation on examination. More number of elderly patients were diabetic (20.8% vs 41.7%, P = 0.009). Four patients in each group had a history of a prior stroke. Low level of physical activity was significantly prevalent in the elderly patients. Arrhythmias were also of higher prevalence in the older age group. Left ventricular systolic function was preserved (ejection fraction >55%) in a higher proportion in younger patients compared to the elderly group (27 vs 21 patients, P = 0.031). Severe left ventricular systolic dysfunction (9 vs 1 patients) and mitral regurgitation was higher in the older patients (5 vs 2 patients). Total cholesterol (209.82 ± 35.47 vs 197.96 ± 43.57, P = 0.147), low-density lipoprotein (LDL) (162.03 ± 31.21 vs 141.53 ± 40.27, P = 0.006), triglyceride (192.32 ± 34.78 vs 177.19 ± 52.92, P = 0.10), and high-sensitivity C-reactive Protein (hs-CRP) levels (39.16 ± 29.21 vs 29.52 ± 30.42, P = 0.11) were numerically higher in the elderly group. On the other hand, the younger group had higher levels of high-density lipoprotein (HDL) (42.48 ± 12.81 vs 40.99 ± 12.23, P = 0.56), homocysteine (16.23 ± 12.42 vs 13.86 ± 7.00, P = 0.25), and apolipoprotein A1 (125.44 ± 39.25 vs 122.74 ± 30.09, P = 0.706). One patient in each group was taken up for coronary artery bypass graft (CABG). Thrombolysis was done in a higher proportion of the older patients (27.1% vs 22.9%, P = 0.63). Coronary angiography was done in all patients, while percutaneous coronary intervention (PCI) was carried out in a higher number of younger patients compared to the older subjects (79.2% vs 70.8%, P = 0.346) Clinical findings and procedural characteristics were shown in Table 2.
Table 2

Clinical findings and procedural characteristics

VariablesYoung (≤45 years) (n=48)Old (>45 years) (n=48)P
Clinical Presentation, n (%)
 STEMI20 (41.7)30 (62.5)0.086
 NSTEMI13 (27.1)6 (12.5)
 Unstable Angina15 (31.3)12 (25)
Lipid Profile, mg/dL (mean±SD)
 Total cholesterol197.96±43.57209.82±35.470.147
 Low density lipoprotein141.53±40.27162.03±31.210.006
 High density lipoprotein42.48±12.8140.99±12.230.562
 Triglycerides177.19±52.91192.32±34.780.101
 Apolipoprotein A1125.44±39.25122.74±30.090.706
 Homocysteine16.23±12.4213.86±7.000.253
 High-sensitive C-reactive protein29.52±30.4239.16±29.210.117
Angiographic Findings, n (%)
 Significant CAD40 (83.3)41 (85.4)0.779
Culprit Vessel
 Left main coronary disease001 (2.1)--
 Left circumflex artery22 (45.8)22 (45.8)--
 Right coronary artery20 (41.7)23 (47.9)0.538
 Left anterior descending27 (56.3)29 (60.4)0.679
Number of Vessel Involved
 Single vessel disease19 (39.6)13 (27.1)0.527
 Double vessel disease16 (33.3)22 (45.8)
 Triple vessel disease7 (14.6)6 (12.5)
 None6 (12.5)7 (14.6)

CAD: coronary artery disease

Clinical findings and procedural characteristics CAD: coronary artery disease The incidence of MACE was reported in 17 (35.4%) elderly patients and 5 (10.4%) younger patients. The incidences of arrhythmias (6.3% vs 2.1%, P = 0.61), cardiac arrest (10.4% vs 4.2%, P = 0.435), and in-hospital myocardial infarction (2.1% in older group and none in younger group) were numerically higher in the older age group. The management and clinical outcomes are depicted in both the groups are depicted in Table 3. A univariate analysis represented a significant association of MACE with shock, dyslipidemia, hs-CRP levels, and significant CAD on angiography [Table 4]. Furthermore, multivariate logistic regression analysis of significant univariate variables with that of MACE showed shock to be a significant variable in determining MACE [Table 5].
Table 3

Management and in-hospital major adverse cardiac events

VariablesYoung (≤45 years) (n=48)Old (>45 years) (n=48)P
Pharmacotherapy48 (100%)48 (100%)-
Thrombolysis11 (22.9%)13 (27.1%)0.637
Streptokinase9 (18.7%)12 (25%)
Reteplase2 (4.2%)1 (2.1%)
CABG1 (2.1%)1 (2.1%)-
PCI38 (79.2%)34 (70.8%)0.346
Death1 (2.1%)4 (8.3%)0.362
In-hospital MI001 (2.1%)1.000
Stroke001 (2.1%)1.000
Bleeding1 (2.1%)3 (6.3%)0.617
Cardiac arrest2 (4.2%)5 (10.4%)0.435
Arrhythmias1 (2.1%)3 (6.3%)0.617

CABG: coronary artery bypass grafting; PCI: percutaneous coronary intervention; MI: myocardial infarction

Table 4

Univariate analysis of risk factors for major adverse cardiovascular events

Risk factorFrequencyP
Age56.5±14.540.042
Male sex12 (85.7%)0.278
Diabetes5 (35.7%)0.838
Hypertension6 (42.9%)0.922
Cerebrovascular accident2 (14.3%)0.386
Peripheral vascular disease2 (14.3%)0.010
Family history5 (35.7%)0.375
Previous myocardial infarction3 (21.4%)0.144
Shock7 (50%)0.001
Menopause1 (50%)0.673
Physical activity7 (50%)0.100
Obese4 (28.6%)0.625
Waist-hip ratio (>1)6 (42.9%)0.185
Current smoker6 (42.9%)0.158
Low density lipoprotein (>100 mg/dL)11 (78.6%)0.021
Apolipoprotien A19 (64.3%)0.950
Significant CAD14 (100%)0.023
Homocysteine15.47±90.868
Hs-CRP56.67±230.002

CAD: coronary artery disease; hs-CRP: high-sensitive C-reactive protein

Table 5

Multivariate logistic regression for risk factors for major adverse cardiac events

Independent variableBWald95% CIP

LowerUpper
Age0.0241.0180.9781.0730.313
Shock-2.6198.6160.0130.4190.003
Hs-CRP0.0120.8440.9871.0380.358
LDL (>150 mg/dL)-1.2102.1030.0581.5300.147

Hs-CRP: high-sensitive C-reactive protein; LDL: low density lipoprotein

Management and in-hospital major adverse cardiac events CABG: coronary artery bypass grafting; PCI: percutaneous coronary intervention; MI: myocardial infarction Univariate analysis of risk factors for major adverse cardiovascular events CAD: coronary artery disease; hs-CRP: high-sensitive C-reactive protein Multivariate logistic regression for risk factors for major adverse cardiac events Hs-CRP: high-sensitive C-reactive protein; LDL: low density lipoprotein

Discussion

India as a developing nation has witnessed major transitions in all spheres. One arena of change relevant to us has been the change in demographic patterns of certain diseases.[14] Widespread globalization and alteration in socio-economic factors have altered the epidemiology of major noncommunicable diseases as well. Recently, CAD has grown to epidemic proportions, and there has been a demographic shift of the ACS spectrum in younger populations.[34] In this comparative cross-sectional study between young and old ACS patients, we found STEMI as common in the older patient while NSTEMI and unstable angina were more prevalent in the younger patients. Diabetes mellitus, hypertension, dyslipidemia, and ex-smoking were more prevalent in the elderly group. While current smoking, family history of premature CAD, and hyper homocystinemia were more common in the younger group. Single-vessel involvement on angiography was more prevalent in the younger population while multi-vessel involvement was more common in the older population. MACE including in-hospital mortality was higher in the older population, and shock was found be an independent predictor of the same during hospital stay. In our study, mean age of young and elderly patients was (36.23 ± 4.69 years vs. 61.58 ± 10.69 years) with 1/3rd being male population in both groups. These findings were similar to majority of all previous studies including the national registry of myocardial infarction (NRMI), which showed the ACS frequency in older group to be double than that in the younger age group (32.3 vs 16%).[14] STEMI was more frequent in elderly patients than younger patients (62.5% vs 41.7%). NSTEMI and unstable angina were more frequent in the younger population. These results were supported by the observations of Avezum et al. from the Global Registry of Acute Coronary Events (GRACE).[15] In the Kerala registry, STEMI was found in 37%, NSTEMI in 31%, and unstable angina in 32% of the patients.[16] While in the HP ACS registry, NSTEMI and unstable angina (54.5%) outnumbered the number of STEMI cases (45.5%).[17] This difference could be attributed to multitude of factors ranging from berkesonian bias, sample size, population genetics, difference in risk factors, and heterogeneity of presentation of ACS spectrum. Another most common risk factor is the lifestyle and physical activity status of the individual. In our study, we found that majority of patient had moderate levels of physical activity as calculated by the International Physical Activity Questionnaires (IPAQ) scoring system (58.3% in the younger group and 54.2% in the older group). Sedentary lifestyle/low-level activity was more prevalent in the elderly group (41.7% vs 27.1%). These findings were discordant with a study by Marcus et al. where sedentary behavior was found as a significant risk factor in younger individuals as well.[18] The difference in these results could be attributed to different methods of measuring physical activity, different population with different socio-demographic features, and difference in sample size. Prevalence of diabetes was higher in the older group (45.8% vs 20.8%). We found the mean levels of cholesterol, LDL, triglycerides, and hs-CRP were significantly higher in the elderly population while HDL levels in elderly was comparatively lower. Similarly, Obaya et al. found dyslipidemia to be the most common risk factor for the elderly (96.8%) patients.[19] This was, however, discordant with Avezum et al. of the GRACE registry, which stated that dyslipidemia in the elderly patients was 35%.[15] In our study, homocysteine levels were higher in the younger group. F Martin–Herrero et al. found that high levels of homocysteine were strong predictors of cardiac events in young patients with ACS.[20] Single-vessel involvement was more common in the younger group (39.6% vs 27.1%) while double-vessel involvement was more common in the elderly group (45.8% vs 33.3%). Similarly, Zimmermann et al. also found single-vessel involvement to be more common in the younger group while multi-vessel in the elderly population.[5] Thrombolytic therapy was given to 27.1% and 22.9% in the older and younger age group, respectively. We found PCI rates were higher in the younger population (79.2% vs 70.8%), which was in line with previous studies.[192122] We found shorter hospital stays and better clinical outcomes in younger patients. The presence of shock was found to be a significant determinant of MACE. These findings were in line with previous reports.[192324] The overall in hospital mortality was 9.3%, which was higher than that reported in HP registry (7.6%), CREATE registry (5.6%), and the Kerala registry, which can be explained by our study being limited to a single tertiary center receiving terminal referrals and the limited sample size compared to these studies.[31617] Acute coronary syndrome is initially diagnosed by primary care physicians. The knowledge of demographic profile, risk factors, and the nature of the disease helps primary physicians in identifying at early stages those who require aggressive management and risk factor modification. With our study, we could identify the demographic profile and risk factor pattern of young and old patients of ACS. Empowered with the findings of this study, primary care physicians could be able to identify those high-risk patients at first contact, and it will help in effective management of ACS patients.

Study Limitations

The major drawback of this study is the sample size. Moreover, multiple comparisons with small sample size increase the probability of type-1 and type-2 errors. Despite these, the study has allayed relevant doubts with regards to the demographic and risk factor profile of ACS in young patients. A longer outpatient follow-up after discharge could have added more validity to our observations.

Conclusion

In conclusion, NSTEMI ACS with atypical angina tends to be more frequent in the young patients with involvement of single-vessel CAD. In elderly patients, Killip class ≥2 and MACE including in-hospital mortality were higher, and shock was found to be an independent predictor of the MACE during hospital stay.

Ethics approval and consent to participate

The institutional ethics committee PGIMER Chandigarh has approved the study, with reference number NK/2569/MD/1564-65. Written and informed consent has been taken from the participants.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.
  21 in total

1.  International physical activity questionnaire: 12-country reliability and validity.

Authors:  Cora L Craig; Alison L Marshall; Michael Sjöström; Adrian E Bauman; Michael L Booth; Barbara E Ainsworth; Michael Pratt; Ulf Ekelund; Agneta Yngve; James F Sallis; Pekka Oja
Journal:  Med Sci Sports Exerc       Date:  2003-08       Impact factor: 5.411

Review 2.  Physical activity intervention studies: what we know and what we need to know: a scientific statement from the American Heart Association Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity); Council on Cardiovascular Disease in the Young; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research.

Authors:  Bess H Marcus; David M Williams; Patricia M Dubbert; James F Sallis; Abby C King; Antronette K Yancey; Barry A Franklin; David Buchner; Stephen R Daniels; Randal P Claytor
Journal:  Circulation       Date:  2006-12-04       Impact factor: 29.690

3.  Risk factors for early myocardial infarction in South Asians compared with individuals in other countries.

Authors:  Prashant Joshi; Shofiqul Islam; Prem Pais; Srinath Reddy; Prabhakaran Dorairaj; Khawar Kazmi; Mrigendra Raj Pandey; Sirajul Haque; Shanthi Mendis; Sumathy Rangarajan; Salim Yusuf
Journal:  JAMA       Date:  2007-01-17       Impact factor: 56.272

4.  Presentation, management, and outcomes of 25 748 acute coronary syndrome admissions in Kerala, India: results from the Kerala ACS Registry.

Authors:  Padinhare Purayil Mohanan; Rony Mathew; Sadasivan Harikrishnan; Mangalath Narayanan Krishnan; Geevar Zachariah; Jhony Joseph; Koshy Eapen; Mathew Abraham; Jaideep Menon; Manoj Thomas; Sonny Jacob; Mark D Huffman; Dorairaj Prabhakaran
Journal:  Eur Heart J       Date:  2012-09-07       Impact factor: 29.983

Review 5.  Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine.

Authors:  R R Pate; M Pratt; S N Blair; W L Haskell; C A Macera; C Bouchard; D Buchner; W Ettinger; G W Heath; A C King
Journal:  JAMA       Date:  1995-02-01       Impact factor: 56.272

6.  Risk adjustment for in-hospital mortality of contemporary patients with acute myocardial infarction: the acute coronary treatment and intervention outcomes network (ACTION) registry-get with the guidelines (GWTG) acute myocardial infarction mortality model and risk score.

Authors:  Chee Tang Chin; Anita Y Chen; Tracy Y Wang; Karen P Alexander; Robin Mathews; John S Rumsfeld; Christopher P Cannon; Gregg C Fonarow; Eric D Peterson; Matthew T Roe
Journal:  Am Heart J       Date:  2011-01       Impact factor: 4.749

Review 7.  Multicenter HP ACS Registry.

Authors:  Prakash Chand Negi; Rajeev Merwaha; Deveshwar Panday; Vivek Chauhan; Rajesh Guleri
Journal:  Indian Heart J       Date:  2016-01-18

8.  Treatment and outcomes of acute coronary syndromes in India (CREATE): a prospective analysis of registry data.

Authors:  Denis Xavier; Prem Pais; P J Devereaux; Changchun Xie; D Prabhakaran; K Srinath Reddy; Rajeev Gupta; Prashant Joshi; Prafulla Kerkar; S Thanikachalam; K K Haridas; T M Jaison; Sudhir Naik; A K Maity; Salim Yusuf
Journal:  Lancet       Date:  2008-04-26       Impact factor: 79.321

9.  2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC).

Authors:  Borja Ibanez; Stefan James; Stefan Agewall; Manuel J Antunes; Chiara Bucciarelli-Ducci; Héctor Bueno; Alida L P Caforio; Filippo Crea; John A Goudevenos; Sigrun Halvorsen; Gerhard Hindricks; Adnan Kastrati; Mattie J Lenzen; Eva Prescott; Marco Roffi; Marco Valgimigli; Christoph Varenhorst; Pascal Vranckx; Petr Widimský
Journal:  Eur Heart J       Date:  2018-01-07       Impact factor: 29.983

10.  Role of N-terminal pro-B-type natriuretic peptide in the prediction of outcomes in ST-elevation myocardial infarction complicated by cardiogenic shock.

Authors:  Yash Paul Sharma; Kewal Kanabar; Krishna Santosh; Ganesh Kasinadhuni; Darshan Krishnappa
Journal:  Indian Heart J       Date:  2020-07-12
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.