Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation (Preprint)

St Segment ◽

BACKGROUND Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences. OBJECTIVE The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding. METHODS We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants: The model development data set was obtained from 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. A set of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). RESULTS In-hospital bleeding occurred in 112 of 4262 participants (2.6%) in the development data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. Logistic regression analysis showed differences between the groups with and without in-hospital bleeding in age (odds ratio [OR] 1.047, 95% CI 1.029-1.066; P<.001), Killip III (OR 3.265, 95% CI 2.008-5.31; P<.001), and Killip IV (OR 5.133, 95% CI 3.196-8.242; P<.001). We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic curve (AUC) was 0.777 (SD 0.021, 95% CI 0.73576-0.81823). We constructed a nomogram based on age and Killip classification. In-hospital bleeding occurred in 117 of 6015 participants (1.9%) in the validation data set. The AUC was 0.7234 (SD 0.0252, 95% CI 0.67392-0.77289). CONCLUSIONS We developed and externally validated a diagnostic model of in-hospital bleeding in patients with acute STEMI. The discrimination, calibration, and DCA of the model were found to be satisfactory. CLINICALTRIAL ChiCTR.org ChiCTR1900027578; http://www.chictr.org.cn/showprojen.aspx?proj=45926

Diagnostic Model for In-Hospital Bleeding in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation

JMIR Medical Informatics ◽

10.2196/20974 ◽

2020 ◽

Vol 8 (8) ◽

pp. e20974 ◽

Cited By ~ 1

Author(s):

Yong Li

Keyword(s):

Logistic Regression ◽

Hospitalized Patients ◽

Diagnostic Model ◽

Validation Data ◽

Data Set ◽

St Segment Elevation ◽

Acute Stemi ◽

St Segment ◽

Background Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences. Objective The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding. Methods We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants: The model development data set was obtained from 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. A set of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). Results In-hospital bleeding occurred in 112 of 4262 participants (2.6%) in the development data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. Logistic regression analysis showed differences between the groups with and without in-hospital bleeding in age (odds ratio [OR] 1.047, 95% CI 1.029-1.066; P<.001), Killip III (OR 3.265, 95% CI 2.008-5.31; P<.001), and Killip IV (OR 5.133, 95% CI 3.196-8.242; P<.001). We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic curve (AUC) was 0.777 (SD 0.021, 95% CI 0.73576-0.81823). We constructed a nomogram based on age and Killip classification. In-hospital bleeding occurred in 117 of 6015 participants (1.9%) in the validation data set. The AUC was 0.7234 (SD 0.0252, 95% CI 0.67392-0.77289). Conclusions We developed and externally validated a diagnostic model of in-hospital bleeding in patients with acute STEMI. The discrimination, calibration, and DCA of the model were found to be satisfactory. Trial Registration ChiCTR.org ChiCTR1900027578; http://www.chictr.org.cn/showprojen.aspx?proj=45926

Diagnostic Model of in-Hospital Mortality in Patient with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation (Preprint)

10.2196/preprints.24139 ◽

2020 ◽

Author(s):

Yong Li

Keyword(s):

Logistic Regression ◽

Hospital Mortality ◽

Hospitalized Patients ◽

Diagnostic Model ◽

Validation Data ◽

Data Set ◽

St Segment Elevation ◽

Acute Stemi ◽

St Segment ◽

BACKGROUND Coronary heart disease, including ST-segment elevation myocardial infarction (STEMI), is still the leading cause of death. OBJECTIVE The objective of our study was to develop and externally validate a diagnostic model of in-hospital mortality in the patients with acute STEMI . METHODS We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants: The model development data set was obtained from 2,183 hospitalized patients with acute STEMI from January 2002 to December 2011. A set of 7,485 hospitalized patients with acute STEMI from January 2012 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital mortality in the development data set. We developed a diagnostic model of in-hospital mortality and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). RESULTS In-hospital mortality occurred in 61 of 2,183 participants (2.8%) in the development data set. The strongest predictors of in-hospital mortality were advanced age and high Killip classification. Logistic regression analysis showed differences between the groups with and without in-hospital mortality in age (odds ratio [OR] 1.058, 95% CI 1.029-1.088; P<.001), Killip III (OR 8.249, 95% CI 3.502-19.433; P<.001), and Killip IV (OR 39.234, 95% CI 18.178-84.679; P<.001). We developed a diagnostic model of in-hospital mortality. The area under the receiver operating characteristic curve (AUC) was 0. 9126 (SD 0. 0166, 95% CI 0. 88015-0. 94504). We constructed a nomogram based on age and Killip classification. In-hospital mortality occurred in 127 of 7,485 participants (1.7%) in the validation data set. The AUC was 0 .9305 (SD 0.0113, 95% CI 0. 90827-0. 95264). CONCLUSIONS We developed and externally validated a diagnostic model of in-hospital mortality in patient with acute STEMI . The discrimination, calibration, and DCA of the model were found to be satisfactory. CLINICALTRIAL Trial Registration: ChiCTR.org ChiCTR1900027129; http://www.chictr.org.cn/edit.aspx?pid=44888&htm=4.

Diagnostic Model of in-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction: Algorithm Development and Validation (Preprint)

10.2196/preprints.25644 ◽

2020 ◽

Author(s):

Yong Li

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Hospital Mortality ◽

Logistic Regression Analysis ◽

Diagnostic Model ◽

Validation Data ◽

Data Set ◽

St Segment Elevation ◽

Acute Stemi ◽

BACKGROUND Coronary heart disease, including ST-segment elevation myocardial infarction (STEMI), remains the main cause of death. OBJECTIVE The objective of our research was to develop and externally validate a diagnostic model of in-hospital mortality in acute STEMI patients. METHODS We performed multiple logistic regression analysis on a cohort of hospitalized acute STEMI patients. Participants: From January 2002 to December 2011, a total of 2,183 inpatients with acute STEMI were admitted for development.The external validation data set of this model comes from 7,485 hospitalized patients with acute STEMI from January 2012 to August 2019.We used logistic regression analysis to analyze the risk factors of in-hospital mortality in the development data set.We developed a diagnostic model of in-hospital mortality and constructed a nomogram. We evaluated the predictive performance of the diagnostic model in the validation data set by examining the measures of discrimination, calibration, and decision curve analysis (DCA). RESULTS In the development data set, 61 of the 2,183 participants (2.8%) experienced in-hospital mortality. The strongest predictors of in-hospital mortality were advanced age and high Killip classification. Logistic regression analysis showed the difference between the two groups with and without in-hospital mortality (odds ratio [OR] 1.058, 95% CI 1.029-1.088; P <.001), Killip III (OR 8.249, 95% CI 3.502-19.433; P <.001) and Killip IV (OR 39.234, 95% CI 18.178-84.679; P <.001). We had developed a diagnostic model of in-hospital mortality. The area under the receiver operating characteristic curve (AUC) was 0.9126 (SD 0.0166, 95% CI 0.88015-0.94504). We constructed a nomogram based on age and Killip classification. In-hospital mortality occurred in 127 of 7,485 participants(1.7%) in the validation data set. The AUC was 0 .9305(SD 0.0113, 95% CI 0. 90827-0. 95264). CONCLUSIONS We had developed and externally validated a diagnostic model of in-hospital mortality in acute STEMI patients. It was found that the discrimination, calibration and DCA of this model were satisfactory. CLINICALTRIAL ChiCTR.org ChiCTR1900027129; http://www.chictr.org.cn/edit.aspx?pid=44888&htm=4.

Development and External Validation of Diagnostic Model for in-Hospital Mortality in Patient with Acute ST Elevation Myocardial Infarction: Algorithm Development and Validation (Preprint)

10.2196/preprints.22614 ◽

2020 ◽

Author(s):

Yong Li

Keyword(s):

Myocardial Infarction ◽

Hospital Mortality ◽

External Validation ◽

Hospitalized Patients ◽

Diagnostic Model ◽

Validation Data ◽

Data Set ◽

Acute Stemi ◽

Development Data ◽

St Elevation

BACKGROUND Coronary heart disease, including ST elevation myocardial infarction(STEMI), was still the leading cause of mortality. OBJECTIVE The objective of our study was to develop and externally validate a diagnostic model of in-hospital mortality in the patients with acute STEMI . METHODS Design: Multivariable logistic regression of a cohort of hospitalized patients with acute STEMI. Setting: Emergency department ward of a university hospital. Participants: Diagnostic model development: A total of 2,183 hospitalized patients with acute STEMI from January 2002 to December 2011.External validation: A total of 7,485 hospitalized patients with acute STEMI from January 2012 to August 2019. Outcomes: In-hospital mortality. All cause in-hospital mortality was defined as cardiac or non-cardiac death during hospitalization. We used logistic regression analysis to analyze the risk factors of in-hospital mortality in the development data set. We developed a diagnostic model of in-hospital mortality and constructed a nomogram.We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). RESULTS In-hospital mortality occurred in 61out of 2,183 participants (2.8%) in the development data set. The strongest predictors of in-hospital mortality were age and Killip classification. We developed a diagnostic model of in-hospital mortality .The area under the receiver operating characteristic (ROC) curve (AUC) was .9126±.0166, 95% confidence interval(CI)= .88015 ~ .94504 in the development set .We constructed a nomogram based on age and Killip classification. In-hospital mortality occurred in 127 out of 7,485 participants(1.7%) in the validation data set. The AUC was .9305±.0113, 95% CI= .90827 ~ .95264 in the validation set . Discrimination, calibration ,and DCA were satisfactory. Date of approved by ethic committee:25 October 2019. Date of data collection start: 6 November 2019. Numbers recruited as of submission of the manuscript:9,668. CONCLUSIONS Conclusions: We developed and externally validated a diagnostic model of in-hospital mortality in patient with acute STEMI . CLINICALTRIAL We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027129; registered date: 1 November 2019). http://www.chictr.org.cn/edit.aspx?pid=44888&htm=4.

Development and External Validation of Diagnostic Model for Coronary Microvascular Obstruction: Algorithm Development and Validation (Preprint)

10.2196/preprints.23052 ◽

2020 ◽

Author(s):

Yong Li ◽

Shuzheng Lyu

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Microvascular Obstruction ◽

External Validation ◽

Diagnostic Model ◽

Total Occlusion ◽

Validation Data ◽

Data Set ◽

Acute Stemi

BACKGROUND Prevention of coronary microvascular obstruction /no-reflow phenomenon(CMVO/NR) is a crucial step in improving prognosis of patients with acute ST segment elevation myocardial infarction (STEMI )during primary percutaneous coronary intervention (PPCI). OBJECTIVE The objective of our study was to develop and externally validate a diagnostic model of CMVO/NR in patients with acute STEMI underwent PPCI. METHODS Design: Multivariate logistic regression of a cohort of acute STEMI patients. Setting: Emergency department ward of a university hospital. Participants: Diagnostic model development: Totally 1232 acute STEMI patients who were consecutively treated with PPCI from November 2007 to December 2013. External validation: Totally 1301 acute STEMI patients who were treated with PPCI from January 2014 to June 2018. Outcomes: CMVO/NR during PPCI. We used logistic regression analysis to analyze the risk factors of CMVO/NR in the development data set. We developed a diagnostic model of CMVO/NR and constructed a nomogram.We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). RESULTS A total of 147 out of 1,232 participants (11.9%) presented CMVO/NR in the development dataset.The strongest predictors of CMVO/NR were age, periprocedural bradycardia, using thrombus aspiration devices during procedure and total occlusion of culprit vessel. Logistic regression analysis showed that the differences between two group with and without CMVO/NR in age( odds ratios (OR)1.031; 95% confidence interval(CI), 1.015 ~1.048 ; P <.001), periprocedural bradycardia (OR 2.151;95% CI,1.472~ 3.143 ; P <.001) , total occlusion of the culprit vessel (OR 1.842;95% CI, 1.095~ 3.1 ; P =.021) , and using thrombus aspirationdevices during procedure (OR 1.631; 95% CI, 1.029~ 2.584 ; P =.037).We developed a diagnostic model of CMVO/NR. The area under the receiver operating characteristic curve (AUC) was .6833±.023. We constructed a nomogram. CMVO/NR occurred in 120 out of 1,301 participants (9.2%) in the validation data set. The AUC was .6547±.025. Discrimination, calibration, and DCA were satisfactory. Date of approved by ethic committee:16 May 2019. Date of data collection start: 1 June 2019. Numbers recruited as of submission of the manuscript:2,533. CONCLUSIONS We developed and externally validated a diagnostic model of CMVO/NR during PPCI. CLINICALTRIAL We registered this study with WHO International Clinical Trials Registry Platform on 16 May 2019. Registration number: ChiCTR1900023213. http://www.chictr.org.cn/edit.aspx?pid=39057&htm=4.

Development and external validation of a diagnostic model for in-hospital bleeding in patients with acute ST elevation myocardial infarction

10.1101/2020.05.28.20115501 ◽

2020 ◽

Author(s):

Yong Li

Keyword(s):

Myocardial Infarction ◽

External Validation ◽

Hospitalized Patients ◽

Bleeding Complications ◽

Diagnostic Model ◽

Validation Data ◽

Data Set ◽

Acute Stemi ◽

Increased Risk ◽

Medical University

AbstractBackgroundBleeding complications in patients with acute ST segment elevation myocardial infarction (STEMI) are associated with an increased risk of subsequent adverse consequences. We want to develop and externally validate a diagnostic model of in-hospital bleeding in the population of unselected real-world patients with acute STEMI.MethodsDesign: Multivariable logistic regression of a cohort for hospitalized patients with acute STEMI. Setting: Emergency department ward of a university hospital. Participants: Diagnostic model development: Totally 4262 hospitalized patients with acute STEMI from January 2002 to December 2013 in Beijing Anzhen Hospital, Capital Medical University. External validation: Totally 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 in Beijing Anzhen Hospital, Capital Medical University. Outcomes: All-cause in-hospital bleeding not related to coronary artery bypass graft surgery or catheterization.ResultsIn-hospital bleeding occurred in 2.6% (112/4262) of patients in the development data set (117/6015) of patients in the validation data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic ROC curve (AUC) was 0.777±0.021, 95% confidence interval(CI) = 0.73576 ~ 0.81823. We constructed a nomograms using the development database based on age, and Killip classification. The AUC was 0.7234±0.0252,95% CI = 0.67392 ~ 0.77289 in the validation data set. Discrimination, calibration, and decision curve analysis were satisfactory.ConclusionsWe developed and externally validated a moderate diagnostic model of in-hospital bleeding in patients with acute STEMI.We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027578; registered date: 19 Novmober 2019). http://www.chictr.org.cn/edit.aspx?pid=45926&htm=4.

Cardiac rehabilitation in patients with ST-segment elevation myocardial infarction: can its failure be predicted?

Therapeutic Advances in Cardiovascular Disease ◽

10.1177/1753944717706845 ◽

2017 ◽

Vol 11 (7) ◽

pp. 177-184

Author(s):

Robert Irzmański ◽

Joanna Kapusta ◽

Agnieszka Obrębska-Stefaniak ◽

Beata Urzędowicz ◽

Jan Kowalski

Keyword(s):

Myocardial Infarction ◽

Logistic Regression ◽

Blood Cell ◽

Cardiac Rehabilitation ◽

Blood Cells ◽

Blood Cell Count ◽

St Segment Elevation ◽

Failure Index ◽

St Segment

Background: The prognosis in patients after acute coronary syndromes (ACS) is significantly burdened by coexisting anaemia, leukocytosis and low glomerular filtration rate (GFR). Hyperglycaemia in the early stages of ACS is a strong predictor of death and heart failure in non-diabetic subjects. This study aimed to evaluate the effect of hyperglycaemia, anaemia, leukocytosis, thrombocytopaenia and decreased GFR on the risk of the failure of cardiac rehabilitation (phase II at the hospital) in post-ST-segment elevation myocardial infarction (STEMI) patients. Methods: The study included 136 post-STEMI patients, 96 men and 40 women, aged 60.1 ± 11.8 years, admitted for cardiac rehabilitation (phase II) to the Department of Internal Medicine and Cardiac Rehabilitation, WAM University Hospital in Lodz, Poland. On admission fasting blood cell count was performed and serum glucose and creatinine level was determined (GFR assessment). The following results were considered abnormal: glucose ⩾ 100 mg/dl, GFR < 60 ml/min/1, 73 m², red blood cells (RBCs) < 4 × 106/μl, white blood cells (WBCs) > 10 × 103/μl; platelets (PLTs) < 150 × 10³/ml. In all patients an exercise test was performed twice, before and after the completion of the second stage of rehabilitation, to assess its effects. Results: Based on logistic regression analysis and the results of an individual odds ratio (OR) of the tested parameters, their prognostic impact was determined on the risk of failure of cardiac rehabilitation. This risk has been defined on the basis of the patient’s inability to tolerate workload increment >5 Watt in spite of the applied program of cardiac rehabilitation. As a result of building a logistic regression model, the most statistically significant risk factors were selected, on the basis of which cardiac rehabilitation failure index was determined. leukocytosis and reduced GFR determined most significantly the risk of failure of cardiac rehabilitation (respectively OR = 6.42 and OR = 3.29, p = 0.007). These parameters were subsequently utilized to construct a rehabilitation failure index. Conclusions: Peripheral blood cell count and GFR are important in assessing the prognosis of cardiac rehabilitation effects. leukocytosis and decreased GFR determine to the highest degree the risk of cardiac rehabilitation failure. Cardiac rehabilitation failure index may be useful in classifying patients into an appropriate model of rehabilitation. These findings support our earlier reports.

Gender-Related Difference in D-Dimer Level Predicts In-Hospital Heart Failure after Primary PCI for ST-Segment Elevation Myocardial Infarction

Disease Markers ◽

10.1155/2021/7641138 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Li Li ◽

Wei Wang ◽

Tai Li ◽

Ying Sun ◽

Yanjun Gao ◽

...

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Logistic Regression ◽

Study Endpoint ◽

St Segment Elevation ◽

Female Patients ◽

St Segment ◽

The Relationship ◽

D Dimer

Aims. The prognostic value of plasma D-dimer in patients with coronary artery disease (CAD) remains controversial. The study is aimed at investigating the relationship between plasma D-dimer levels and in-hospital heart failure (HF) in ST-segment elevation myocardial infarction (STEMI) patients who underwent primary percutaneous coronary intervention (pPCI). Methods. STEMI patients who underwent pPCI were enrolled in this study. Venous blood samples were collected from patients on admission before pPCI procedure. The study endpoint was the occurrence of in-hospital HF. The participants were divided into two groups according to plasma D-dimer levels and further compared baseline D-dimer levels between male and female. Logistic regression and receiver operating characteristic (ROC) curves were performed to evaluate the relationship of D-dimer and in-hospital HF. Results. A total of 778 patients were recruited in the study, of which 539 (69.3%) patients had normal D-dimer levels (≤0.5 mg/L) while 239 (30.7%) had increased D-dimer levels (>0.5 mg/L). The female patients have higher D-dimer levels and higher incident rate of in-hospital HF than that in male patients ( p < 0.001 ). The multivariate logistic regression model revealed that D-dimer was an independent predictor for in-hospital HF in overall population (adjusted odds ratio [OR]: 1.197, 95% CI: 1.003-1.429, and p = 0.046 ) and female patients (adjusted OR: 1.429, 95% CI: 1.083-1.885, and p = 0.012 ). Conclusion. Increased plasma D-dimer levels were an independent risk factor for incidence of in-hospital HF in STEMI patients who underwent pPCI, especially in female patients, which provides guidance for clinicians in identifying patients at high risk of developing HF and lowering their risk.

Prognostic of Interatrial Block after an Acute ST-Segment Elevation Myocardial Infarction

Cardiology ◽

10.1159/000499501 ◽

2019 ◽

Vol 142 (2) ◽

pp. 109-115 ◽

Cited By ~ 8

Author(s):

Vanesa Bruña ◽

Jesús Velásquez-Rodríguez ◽

María Jesús Valero-Masa ◽

Beatriz Pérez-Guillem ◽

Lourdes Vicent ◽

...

Keyword(s):

Myocardial Infarction ◽

Sinus Rhythm ◽

P Wave ◽

St Segment Elevation ◽

Acute Stemi ◽

Wave Duration ◽

P Wave Duration ◽

St Segment

Background: The influence of interatrial block (IAB) in the prognosis after an acute ST-segment elevation myocardial infarction (STEMI) is unknown. Objectives: To assess the prognostic impact of IAB after an acute STEMI regarding long-term mortality, development of atrial fibrillation, and stroke. Methods: Registry of 972 consecutive patients with STEMI and sinus rhythm at discharge, with a long-term follow-up (49.6 ± 24.9 months). P wave duration was analyzed using digital calipers, and patients were divided into three groups: normal P wave duration (<120 ms), partial IAB (pIAB) (P wave ≥120 ms and positive in inferior leads), and advanced IAB (aIAB) (P wave ≥120 ms plus biphasic [positive/negative] morphology in inferior leads). Results: Mean age was 62.6 ± 13.5 years. A total of 708 patients had normal P wave (72.8%), 207 pIAB (21.3%), and 57 aIAB (5.9%). Patients with aIAB were older (mean age 73 years) than the rest (62 years in the other two groups, p < 0.001). They also had a higher rate of hypertension (70 vs. 55% in pIAB and 49% in normal P wave, p = 0.006) and higher all-cause mortality (26.3 vs. 12.6% in pIAB and 10.3% in normal P wave, p = 0.001). However, multivariable analysis did not show an independent association between IAB and prognosis. Conclusion: About a quarter of patients discharged in sinus rhythm after an acute STEMI have IAB. Patients with aIAB have a poor prognosis, although this is explained mainly by the association of aIAB with age and other variables.

Association of Waist-Hip Ratio with Angiographic Severity of Coronary Artery Disease in Patients with Acute ST- Segment Elevation Myocardial Infarction

Bangladesh Heart Journal ◽

10.3329/bhj.v32i2.36091 ◽

2018 ◽

Vol 32 (2) ◽

pp. 70-76

Author(s):

Mohammad Anowar Hossain ◽

Md Abdul Kader Akanda ◽

Mohammad Ullah ◽

Lakshman Chandra Barai ◽

ABM Nizam Uddin ◽

...

Keyword(s):

Myocardial Infarction ◽

Coronary Artery Disease ◽

Coronary Artery ◽

Significant Positive Correlation ◽

St Segment Elevation ◽

Acute Stemi ◽

St Segment ◽

Artery Disease ◽

Vessel Score

Objective: Coronary artery disease (CAD) is rising in South Asia and is taking a more malignant proportion in South Asians than in Caucasians. Having a similar socioeconomic and cultural background, the scenario is same in Bangladesh. Obesity, especially abdominal is concerned as an important and modifiable risk factor for CAD which is now also raising both in developed and under developed countries. Waist-Hip ratio (WHR) is considered as an important tool for assessing abdominal obesity. The aim of this study is to evaluate the association between WHR and the severity of CAD of acute ST-segment elevation myocardial infarction (STEMI) patients so that primary prevention, early detection and proper management strategy can be taken to reduce the disease burden, morbidity and mortality.Methods: This cross sectional observational study was carried out among 105 patients with acute STEMI who received thrombolytic and underwent coronary angiography (CAG) at National Institute of Cardiovascular Diseases (NICVD), Dhaka from May, 2016 to November, 2016. They were divided into two groups, Group I (normal WHR) = 51 and group II (increased WHR) = 54, according to WHR level. Angiographic severity of coronary artery disease was assessed by vessel score and Genseni’s score.Results: Significant positive correlation was found between WHR and vessel score (r= 0.62, p=0.003). Moderate to severe CAD patients were significantly higher in increased WHR group than in normal WHR group (77.8% vs. 29.4%, p=<0.001). Significant positive correlation was also found between WHR and Genseni’s score (r= 0.71, p=0.001). Logistic regression analysis showed that a patient with increased WHR had 2.75 times higher risk of having significant CAD compared with those with the normal WHR.Conclusions: Increased WHR group had more significant coronary artery disease in terms of vessel score and Genseni’s score and can be considered as a predictor of the severity of the CAD disease in acute STEMI patients.Bangladesh Heart Journal 2017; 32(2) : 70-76