Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction

Baars, Theodor; Sowa, Jan-Peter; Neumann, Ursula; Hendricks, S; Jinawy, Mona; Kälsch, Julia; Gerken, Guido; Rassaf, Tienush; Heider, Dominik; Canbay, Ali

doi:10.5114/aoms.2018.75678

Cited by 13 publications

(13 citation statements)

References 59 publications

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“…A few recent studies reported that elevated serum transaminases were independently associated with poor clinical outcomes in patients with AMI. The extent of liver injury, in particular in patients with preexisting metabolic syndrome, may have a direct impact on cardiac outcomes [13]. Hypoxic liver injury (HLI) is commonly diagnosed in the emergency room in patients with STEMI (in 22% of patients), and those patients with HLI have higher mortality rate and higher frequency of major adverse cardiovascular events (MACE) after percutaneous coronary intervention [14].…”

Section: Table 2 Multivariate Analysis Of Variables Associated With Imentioning

confidence: 99%

Predictive value of elevated alanine aminotransferase for in-hospital mortality in patients with acute myocardial infarction

Zhao

Jiang

et al. 2021

BMC Cardiovasc Disord

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Background and aims Liver enzymes, including alanine aminotransferase (ALT) and aspartate aminotransferase (AST), are markers of hepatic dysfunction and fatty liver disease. Although ALT and AST have been suggested as risk factors for cardiovascular disease, their role as predictors of mortality after acute myocardial infarction (AMI) has not been established. The objective of this study was to investigate the predictive value of ALT and AST for mortality in patients with AMI. Methods We analyzed records of 712 patients with AMI and no known liver disease treated at the Department of Cardiovascular Center in the First Hospital of Jilin University. The primary outcome was all-cause in-hospital mortality. Relationships between primary outcome and various risk factors, including serum transaminase levels, were assessed using multivariate logistic regression analysis. Results Age (P < 0.001), hypertension (P = 0.034), prior myocardial infarction (P < 0.001), AST (P < 0.001), ALT (P < 0.001), creatinine (P = 0.007), blood urea nitrogen (P = 0.006), and troponin I (P < 0.001) differed significantly between ST-segment elevation myocardial infarction (STEMI) and non-STEMI. The following factors were associated with an increased risk of in-hospital all-cause mortality in patients with AMI: ALT ≥ 2ULN (adjusted odds ratio [AOR] 2.240 [95% confidence interval (CI), 1.331–3.771]; P = 0.002); age ≥ 65 year (AOR 4.320 [95% CI 2.687–6.947]; P < 0.001); increased fasting plasma glucose (FPG) (AOR 2.319 [95% CI 1.564–3.438]; P < 0.001); elevated D-dimer (AOR 2.117 [95% CI 1.407–3.184]; P < 0.001); elevated fibrinogen (AOR 1.601 [95% CI 1.077–2.380]; P = 0.20); and reduced estimated glomerular filtration rate (eGFR) (AOR 2.279 [95% CI 1.519–3.419]; P < 0.001). Conclusions Our findings demonstrated that elevated ALT was independently associated with increased in-hospital all-cause mortality in patients with AMI. Other risk factors were increased age, FPG, D-dimer, and fibrinogen and decreased eGFR.

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Section: Table 2 Multivariate Analysis Of Variables Associated With Imentioning

confidence: 99%

Predictive value of elevated alanine aminotransferase for in-hospital mortality in patients with acute myocardial infarction

Zhao

Jiang

et al. 2021

BMC Cardiovasc Disord

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“…Data have shown that cardiovascular diseases are often accompanied by impaired liver function (as a result of reduced arterial perfusion or congestion); hence, this transaminase’s activity as a prognostic factor for morbidity and mortality in cardiovascular patient groups has been the main focus of studies. In a retrospective center study conducted on 569 AMI patients, AST was found to be a predictor factor for cardiac death and MACEs (AMI, unstable angina, TLR or another segment or coronary vessel, stroke and saphenous vein aortocoronary bypass grafting) at 6 years of follow-up, its value being significantly correlated with troponin and myoglobin [ 136 ]. Li et al [ 137 ] reported that, in AMI patients, increased AST was not an independent predictor for in-hospital mortality, in contrast to alanine aminotransferase (ALT), which was found to be a marker of elevated risk of early death, together with older age; increased d-dimers, fibrinogen or fasting plasma glucose; and decreased eGFR.…”

Section: Resultsmentioning

confidence: 99%

From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction

Stătescu

Anghel

Tudurachi

et al. 2022

IJMS

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Despite all the important advances in its diagnosis and treatment, acute myocardial infarction (AMI) is still one of the most prominent causes of morbidity and mortality worldwide. Early identification of patients at high risk of poor outcomes through the measurement of various biomarker concentrations might contribute to more accurate risk stratification and help to guide more individualized therapeutic strategies, thus improving prognoses. The aim of this article is to provide an overview of the role and applications of cardiac biomarkers in risk stratification and prognostic assessment for patients with myocardial infarction. Although there is no ideal biomarker that can provide prognostic information for risk assessment in patients with AMI, the results obtained in recent years are promising. Several novel biomarkers related to the pathophysiological processes found in patients with myocardial infarction, such as inflammation, neurohormonal activation, myocardial stress, myocardial necrosis, cardiac remodeling and vasoactive processes, have been identified; they may bring additional value for AMI prognosis when included in multi-biomarker strategies. Furthermore, the use of artificial intelligence algorithms for risk stratification and prognostic assessment in these patients may have an extremely important role in improving outcomes.

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“…Therefore, ALT reflects the state of organ perfusion and congestion based on cardiac pump function. A clinical trial ( 32 ) involving 105 patients with reduced ejection fraction found that AST/ALT ratio independently predicted the severity of cardiac dysfunction while a large study ( 33 ) also found that elevated ALT not only strongly correlated with MACEs, but also served as an important predictor of long-term mortality in AMI patients. Therefore, the inclusion of ALT as a predictor in the model reflects the organ-organ interactions in STEMI patients with early cardiac decompensation.…”

Section: Discussionmentioning

confidence: 99%

A nomogramic model for predicting the left ventricular ejection fraction of STEMI patients after thrombolysis-transfer PCI

Liu,

Jiang,

Zhang

et al. 2023

Front. Cardiovasc. Med.

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BackgroundThe prognosis of ST-segment elevation myocardial infarction (STEMI) is closely linked to left ventricular ejection fraction (LVEF). In contrast to primary percutaneous coronary intervention (PPCI), thrombolysis-transfer PCI (TTPCI) is influenced by multiple factors that lead to heterogeneity in cardiac function and prognosis. The aim of this study is to develop a nomogram model for predicting early LVEF in STEMI patients with TTPCI, based on routine indicators at admission.MethodWe retrospectively reviewed data from patients diagnosed with STEMI at five network hospitals of our PCI center who performed TTPCI as door-to-balloon time (the interval between arrival at the hospital and intracoronary balloon inflation) over 120 min, from February 2018 to April 2022. Categorical variables were analyzed using Pearson χ2 tests or Fisher exact tests, while Student's t-test or Mann–Whitney U-test was used to compare continuous variables. Subsequently, independent risk factors associated with reduced LVEF one week after TTPCI were identified through comprehensive analysis by combining All-Subsets Regression with Logistic Regression. Based on these indicators, a nomogram model was developed, and validated using the area under the receiver operating characteristic (ROC) curve and the Bootstrap method.ResultsA total of 288 patients were analyzed, including 60 with LVEF < 50% and 228 with LVEF ≥ 50%. The nomogram model based on six independent risk factors including age, heart rate (HR), hypertension, smoking history, Alanine aminotransferase (ALT), and Killip class, demonstrated excellent discrimination with an AUC of 0.84 (95% CI: 0.78–0.89), predicted C-index of 0.84 and curve fit of 0.713.ConclusionsThe nomogram model incorporating age, HR, hypertension, smoking history, ALT and Killip class could accurately predict the early LVEF ≥ 50% probability of STEMI patients undergoing TTPCI, and enable clinicians' early evaluation of cardiac function in STEMI patients with TTPCI and early optimization of treatment.

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Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction

Cited by 13 publications

References 59 publications

Predictive value of elevated alanine aminotransferase for in-hospital mortality in patients with acute myocardial infarction

Predictive value of elevated alanine aminotransferase for in-hospital mortality in patients with acute myocardial infarction

From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction

A nomogramic model for predicting the left ventricular ejection fraction of STEMI patients after thrombolysis-transfer PCI

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