scholarly journals Positive predictive value of the diagnosis of acute myocardial infarction in an administrative database

1999 ◽  
Vol 14 (9) ◽  
pp. 555-558 ◽  
Author(s):  
Laura A. Petersen ◽  
Steven Wright ◽  
Sharon-Lise T. Normand ◽  
Jennifer Daley
2013 ◽  
Vol 20 (06) ◽  
pp. 871-875
Author(s):  
MUHAMMAD SHAFIQ ◽  
MUHAMMAD AKRAM ◽  
M. NASARULLAH KHAN NASSER

A delay in confirming a diagnosis of AMI may increase the risk of complication and a delay in ruling out the diagnosiscontributes to overcrowding in the emergency department. A crucial step in confirming or ruling out the diagnosis of AMI is themeasurement of myocardial enzymes in the serum. Early administration of thrombolytic therapy results in improved survival after AMI. Sothis study was planned to find out the serum marker with a better predictive value for the identification of acute myocardial infarction at thetime of admission. Design: Cross-sectional study. Setting: Emergency department of Punjab Institute of Cardiology, Lahore. Period:15th May, 2008 to 15th July, 2008. Methods: The study population consisted of 70 patients. Patients from both sexes, with clinicalhistory of typical chest pain for more than 30 minutes in duration with evidence of acute changes of myocardial infarction on ECG wereincluded in the study. This study was conducted to compare the positive predictive value and negative predictive value of creatine kinase-MB (CK-MB), cardiac troponin T (CTnT) and cardiac troponin I (CTnI) for detection of AMI. Data analysis was performed with StatisticalPackage for Social Sciences 11.5 (SPSS 11.5). Results: 88.6% cases had CTnI concentration more than the limit value while 11.4%cases had CTnI less than the limit value. The concentration of CTnT was more than the limit value in 70% cases and below the limit value in30% cases. The concentration of CK-MB was more than the limit value in 35.7% cases and 64.3% cases had CK-MB value less than thelimit value. The positive predictive value (PPV) of CtnI is 100% and negative predictive value (NPV) of CTnT is 100% in this study.Conclusions: It is concluded that CTnl is the better marker for the identification of acute myocardial infarction and CTnT is the bettermarker to exclude AMI as compared to CK-MB.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Side Gao ◽  
Qingbo Liu ◽  
Hui Chen ◽  
Mengyue Yu ◽  
Hongwei Li

Abstract Background Acute hyperglycemia has been recognized as a robust predictor for occurrence of acute kidney injury (AKI) in nondiabetic patients with acute myocardial infarction (AMI), however, its discriminatory ability for AKI is unclear in diabetic patients after an AMI. Here, we investigated whether stress hyperglycemia ratio (SHR), a novel index with the combined evaluation of acute and chronic glycemic levels, may have a better predictive value of AKI as compared with admission glycemia alone in diabetic patients following AMI. Methods SHR was calculated with admission blood glucose (ABG) divided by the glycated hemoglobin-derived estimated average glucose. A total of 1215 diabetic patients with AMI were enrolled and divided according to SHR tertiles. Baseline characteristics and outcomes were compared. The primary endpoint was AKI and secondary endpoints included all-cause death and cardiogenic shock during hospitalization. The logistic regression analysis was performed to identify potential risk factors. Accuracy was defined with area under the curve (AUC) by a receiver-operating characteristic (ROC) curve analysis. Results In AMI patients with diabetes, the incidence of AKI (4.4%, 7.8%, 13.0%; p < 0.001), all-cause death (2.7%, 3.6%, 6.4%; p = 0.027) and cardiogenic shock (4.9%, 7.6%, 11.6%; p = 0.002) all increased with the rising tertile levels of SHR. After multivariate adjustment, elevated SHR was significantly associated with an increased risk of AKI (odds ratio 3.18, 95% confidence interval: 1.99–5.09, p < 0.001) while ABG was no longer a risk factor of AKI. The SHR was also strongly related to the AKI risk in subgroups of patients. At ROC analysis, SHR accurately predicted AKI in overall (AUC 0.64) and a risk model consisted of SHR, left ventricular ejection fraction, N-terminal B-type natriuretic peptide, and estimated glomerular filtration rate (eGFR) yielded a superior predictive value (AUC 0.83) for AKI. Conclusion The novel index SHR is a better predictor of AKI and in-hospital mortality and morbidity than admission glycemia in AMI patients with diabetes.


1988 ◽  
Vol 1 (3) ◽  
pp. 187-193 ◽  
Author(s):  
Wybren Jaarsma ◽  
Cees A. Visser ◽  
Machiel J. Eenige van ◽  
Freek W.A. Verheugt ◽  
Albert J. Funke Kupper ◽  
...  

Author(s):  
Mikhail Kirnus ◽  
Adeyemi Iyanoye ◽  
Elizabeth Hubbard ◽  
Mikhail Torosoff

Background Historic data suggests 65-70% prevalence of Q-waves and concurrent wall motion abnormalities in patients with ST-elevation myocardial infarction (STEMI) treated with thrombolytics. We investigated prevalence of post-MI Q-waves and correlation between Q-waves and left ventricular wall motion abnormalities in STEMI patients treated with primary percutaneous coronary intervention (PCI). Study Design A retrospective study cohort included 145 patients (24% females, 57+/-13 years old) without prior Q-wave MI who underwent successful primary PCI for STEMI at a single academic tertiary center. New York State Angioplasty Registry endpoints were utilized. Echocardiograms and ECGs (median 53 days post STEMI) were reviewed for presence or absence of segmental wall motion abnormalities (WMAs) and Q-waves. ANOVA and chi-square analyses were performed. Results Prevalence of post PCI Q-waves in STEMI patients was 69%, similar to historic 64% in TIMI 14 trial patients (p=0.258). Timing of PCI was not a significant predictor of Q-waves, but there was a trend towards higher pre- and post-PCI creatine kinase and troponin levels in patients with Q-waves. Patients with history of hypertension were less likely to develop Q-waves (62% vs. 77%, p=0.048), while age, gender, history of CHF, COPD, diabetes, renal failure, smoking, and admission hemodynamic status were not predictive of post-PCI Q-waves. WMAs were present in 38% of patients with Q-waves vs. 9% in the rest of the cohort (p=0.0003). Q-waves were equally likely to develop regardless of location of ST elevations at presentation; however, WMAs were more likely in patients with Q-waves in leads II-III-AVF (p=0.008) and V1-2-3 (p<0.0001), V4-5-6 (p=0.008), but not I-AVL (p=0.07). Positive predictive value for WMAs in patients with Q waves was 38%, while negative predictive value for lack of WMAs in patients without Q waves was 91%. Conclusions Prevalence of Q waves, reflective of myocardial damage, in STEMI patients treated with primary coronary intervention is similar to such observed in thrombolysis trials. Positive predictive value of Q-waves for WMAs is low. In CAD patients without Q-waves segmental WMAs are unlikely.


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