Diagnosis Of AMI Research Articles

Diagnostic and prognostic values of HCG15 and morrbid in acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) represents the gravest manifestation of ischemic heart disease, with the primary cause of mortality and morbidity worldwide. Although timely and accurate diagnosis of AMI is crucial in clinical practice, they are impeded by the limitation of current biomarkers. We aimed to explore the potential predictive value of two novel long non-coding RNA (lncRNA) HCG15 and Morrbid in AMI diagnosis and prognosis.MethodWe measured the lncRNA levels in the blood samples of 412 AMI patients and 111 healthy volunteers with the RT-PCR method. Receiver operating characteristic (ROC) curves were plotted to access the diagnostic value of selected lncRNAs. Restricted cubic splines (RCS) and the Kaplan-Meier method were utilized to examine the predictive value of the selected lncRNAs in AMI diagnosis.ResultROC curves identified an acceptable diagnostic value of HCG15 and Morrbid (AUC for HCG15: 0.937; AUC for Morrbid: 0.940). RCS and Kaplan-Meier analysis revealed the cut-off value of 3.6 for HCG15 and 4.0 for Morrbid have a good predictive value in MACCE within 12 months once AMI was diagnosed (p-value for HCG15: p = 0.025; p-value for Morrbid: p < 0.0001).ConclusionHCG15 and Morrbid were confirmed as promising lncRNA biomarkers for both diagnosis and prognosis of AMI in this study. Additionally, their importance of application in real-world clinical practice and underlying mechanisms in AMI diagnosis and prognosis remain to be explored.

Electrochemical detection of the cardiac biomarker cardiac troponin I

AbstractAcute myocardial infarction (AMI) is a major cause of cardiovascular disease‐related death. It is essential for patients with cardiovascular disease to receive an early diagnosis of AMI. The most popular technique for the early detection of AMI is the use of biosensors to monitor the concentration of pertinent biomarkers, such as cardiac troponin I (cTnI), in the blood. The electrochemical detection methods hold great promise because of their simplicity, miniaturization, ease of integration, high sensitivity, and rapid response. The prime motive of this review is to present a comprehensive understanding of the pros and cons of methodologies employed for the electrochemical approaches toward the detection of cTnI. A detailed summary is provided for the immunosensors, aptamer sensors, molecular imprinting sensors, and peptide sensors based on various affinity elements. We enumerate the modified electrode materials for electrochemical sensors as well as popular detection techniques. Furthermore, this paper reviews some recent significant advances in point‐of‐care assays for rapid, accurate detection of cTnI as a smart integrated device for home monitoring. The accumulation of knowledge about these functions will lead to new insights into and concepts for the design of portable miniature sensors for cardiovascular patients at risk of AMI. It is anticipated that the interdisciplinary collaboration can bring more enlightenment to the progress of cardiac biomarkers sensor in the future.

Outcomes for Mechanically Ventilated Patients With Acute Myocardial Infarction Admitted to Medical vs Cardiac Intensive Care Units

BackgroundAcute myocardial infarction (AMI) remains a common reason for admission to the intensive care unit (ICU). However, there is limited data comparing outcomes for patients with AMI admitted to specific ICUs. ObjectivesThe purpose of this study was to assess clinical outcomes between patients with AMI requiring invasive mechanical ventilation admitted to the medical ICU (MICU) compared to cardiac (CICU). MethodsWe utilized the Vizient Clinical Data Base to identify patients with a primary diagnosis of AMI between October 2015 and December 2019 and requiring invasive mechanical ventilation. Using multivariable logistic regression, we compared clinical outcomes for patients admitted to the MICU vs CICU. ResultsWe identified 12,639 patients, 25.2% (n = 3,185) of which were admitted to a MICU and 74.8% (n = 9,454) to a CICU. Patients admitted to a CICU were more likely to present with STEMI (57.0% vs 42.8%), cardiogenic shock (46.0% vs 37.4%), and require mechanical circulatory support and vasoactive medications (all, P < 0.001). Median ventilator days were 4 days in both ICUs and not statistically different after multivariable adjustment (P = 0.81). In-hospital mortality was 42.7% compared to 41.3% for MICU vs CICU admissions, respectively (P = 0.15). After multivariable adjustment, CICU admission was associated with lower in-hospital mortality (OR: 0.85, 95% CI: 0.78-0.93, P = 0.001), which persisted when stratified by cardiogenic shock, cardiac arrest, STEMI, largest hospital size (>750 beds), and teaching hospitals (all, P < 0.05). ConclusionsAdmission to the CICU, as compared to MICU, was associated with lower in-hospital mortality for patients with AMI. These findings may support optimal triage of critically ill patients with AMI.

Thrombomodulin as a potential diagnostic marker of acute myocardial infarction and correlation with immune infiltration: Comprehensive analysis based on multiple machine learning

BackgroundAcute myocardial infarction (AMI) is a global health problem with high mortality. Early diagnosis can prevent the development of AMI and provide valuable information for subsequent treatment. Angiogenesis has been shown to be a critical factor in the development of infarction and targeting this process may be a potential protective strategy for preventing myocardial injury and improving the prognosis of AMI patients. This study aimed to screen and verify diagnostic markers related to angiogenesis in AMI and to investigate the molecular mechanisms of action associated with AMI in terms of immune cell infiltration. MethodsThe GSE66360 and the GSE60993 datasets were both downloaded from the GEO database and were used as the training cohort and the external validation cohort, respectively. Angiogenesis-related genes (ARGs) were downloaded from the MSigDB database. The hub ARGs were identified via LASSO, RF, and SVM-RFE algorithms. ROC curves were used to assess the accuracy of the hub ARGs. The potential mechanisms of the hub ARGs were analyzed by GSEA. The ssGSEA algorithm was used to determine differences in immune cell infiltration and immune function. The CIBERSORT algorithm was used for immune cell infiltration analysis. In addition, we constructed a ceRNA network map of differentially expressed ARGs. ResultsWe identified the thrombomodulin (THBD) gene from ARGs as a potential diagnostic marker for AMI based on the LASSO, SVM-RFE, and RF algorithms. THBD was differentially expressed and had a potential diagnostic value (area under the curve [AUC] = 0.931 and 0.765 in the training and testing datasets, respectively). GSEA showed that the MAPK signaling pathway was more enriched in the high-expression group of THBD (P < 0.05). Immune cell infiltration analysis demonstrated that THBD was mainly positively correlated with monocytes (R = 0.48, P = 0.00055) and neutrophils (R = 0.36, P = 0.013). Finally, in the ceRNA regulatory network, THBD was closely associated with 9 miRNAs and 42 lncRNAs involved in AMI. ConclusionTHBD can be used as a potential diagnostic marker for AMI. This study provides new insights for future AMI diagnosis and molecular mechanism research. Moreover, immune cell infiltration plays an essential role in the occurrence and development of AMI.

Hypoxia-induced circRNAs encoded by PPARA are highly expressed in human cardiomyocytes and are potential clinical biomarkers of acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) is a serious cardiovascular disease that adversely affects human health. Circular RNAs (circRNAs) are involved in the pathological and physiological processes of AMI, but the biological mechanism of their involvement and their clinical significance remain unknown. We aimed to identify circRNAs that are significantly associated with morbidity in the peripheral blood of patients with AMI and evaluate their diagnostic utility.MethodsHigh-throughput sequencing was used to screen for differentially expressed circRNAs in peripheral blood samples obtained from five patients with AMI and five sex- and age-matched healthy controls. A series of bioinformatics tools and databases were used to determine the biological functional classification and pathway enrichment of the circRNAs based on data obtained from sequencing. A hypoxia model was established and used to evaluate the effect of hypoxia on circRNA expression in human cardiomyocytes. A cytoplasmic separation assay and enzyme resistance assay were employed to identify the biological characteristics of circRNA. Polymerase chain reaction validity testing and receiver operating characteristic (ROC) curve analysis were used to evaluate the utility of circRNA assessments in the diagnosis of AMI.ResultsA large number of circRNAs were found to be differentially expressed in the peripheral blood of patients with AMI, and significantly more of these circRNAs were highly expressed than lowly expressed. The genes encoding these circRNAs have a wide range of effects on various functions in the body. A hypoxic environment promoted the upregulation of circRNA expression in human cardiomyocytes, and hsa_circ_0116795 encoded by PPARA was highly expressed in the peripheral blood of the patients with AMI. In terms of biological characteristics, under physiological conditions, hsa_circ_0116795 (circ_PPARA) was mainly located in the cytoplasm of cardiomyocytes and found to be resistant to exonuclease. The ROC curve analysis showed that the expression levels of circ_PPARA in the peripheral blood of patients with AMI were significantly different from those in the peripheral blood of healthy controls.ConclusionA large number of abnormally expressed circRNAs are detectable in the peripheral blood of patients with AMI. In particular, circ_PPARA is highly expressed in human myocardial cells under hypoxic conditions, and its biological characteristics indicate that it could be employed as a biomarker for the early diagnosis of AMI.

Hypertension and poor control of systolic blood pressure after a myocardial infarction with non-obstructive coronary arteries are associated with incident heart failure

Abstract Introduction Myocardial infarction with non-obstructive coronary arteries (MINOCA) occurs in up to 10% of all acute myocardial infarctions. Although previously believed to be a benign condition, recent studies have observed an increased risk for long-term adverse cardiovascular events in this group. However, data on risk markers for specific outcomes following MINOCA are limited. Hypertension is an important risk factor for heart failure (HF), but it is yet unknown whether blood pressure control after MINOCA is associated with incident HF. Aims To investigate whether history of hypertension and control of systolic blood pressure at two-month follow-up visit after MINOCA were associated with hospitalization for HF during long-term follow-up. Material and Methods This was a nationwide cohort study using data from SWEDEHEART and the National Patient Registry. Patients with first-time MINOCA between 2005-2020 were included and divided into grades of hypertension based on systolic blood pressure (SBP) in mmHg at a two-month follow-up visit. The grades were low normal (&amp;lt;120), normal (120-129), high normal (130-139), grade 1 hypertension (140-159), grade 2 hypertension (160-179) and grade 3 hypertension (&amp;gt;180). MINOCA was defined as a discharge diagnosis of AMI combined with a coronary angiography showing less than 50% stenosis in all coronary arteries. Patients with a diagnosis of heart failure or cardiomyopathy one month or earlier before index hospitalization with MINOCA were excluded. After the two-month visit all patients were followed in the registries regarding hospitalization for HF, until December 2020. The association between SBP and time to first HF hospitalization was studied with univariate and multivariate Cox regression models, using high normal SBP as the reference group. Results Among the 5018 included patients (57.8% women, mean age 62.6 years), 197 (3.9%) were hospitalized for HF during a median follow-up of 6.5 years (IQR 3.2-9.9). A diagnosis of hypertension at index hospitalization for MINOCA was associated with hospitalization for HF, both in univariate analysis (HR 1.97 95% CI 1.49-2.62) and after age and sex adjustments (HR 1.45 95% CI 1.09-1.93). The highest hospitalization rate of 7.6% was seen among patients with grade 2-3 hypertension at the two-month follow-up visit. In univariate analysis a SBP &amp;gt;160 mmHg was associated with hospitalization for HF (HR 2.17 CI 1.36-3.45). After exclusion of patients with 30-49% stenosis, these findings remained after age and sex adjustments (HR 1.71 CI 1.04-2.83). Conclusions Both history of hypertension and a poor blood pressure control two-months after MINOCA were associated with hospitalization for HF during long-term follow-up. These findings highlight the importance of adequate blood pressure control following MINOCA. To better detect and treat high SBP should be seen as an opportunity to reduce HF hospitalizations in this group of patients.

Abstract 13688: Association Between Daylight Saving Time and Acute Myocardial Infarction in Canada

Background: Recent studies have suggested an increased risk of AMI following daylight saving time (DST) transitions in cohorts of American and European patients. We aim to validate this finding in a Canadian population. Methods: We performed a retrospective cohort study of patients admitted to the Hôpital du Sacré-Coeur de Montréal, with a diagnosis of AMI requiring a PCI. Patients aged ≥18 years hospitalized between 2018 and 2022 were included. The primary endpoint was the incidence of AMI two weeks following DST transitions. The secondary endpoint was infarct size by biomarker assessment and LVEF. Results: 1142 charts were reviewed with 775 patients meeting the inclusion criteria (244 in the study group and 531 in the control group). Baseline clinical characteristics were comparable between both groups. (Table 1) The rate of AMI per day following DST transitions was 1.74 compared to 1.90 during control periods. DST was not associated with an increase in AMI (IRR = 0.92, 95% CI 0.79 - 1.07, p = 0.295). (Table 2) During the spring shift, the IRR was 0.83, p = 0.106, and during the autumn shift, the IRR was 1.01, p = 0.933. The rate of AMI was higher on the first day following DST, but it did not reach statistical significance (rate of AMI per day = 2.00; IRR = 1.05; p = 0.845). The transition to DST was not associated with a larger infarct size by CK-MB assessment, but LVEF was significantly slightly higher following DST transitions (LVEF 50 ± 11 % vs 48 ± 10 %, p = 0.038). Conclusion: In this cohort of Canadian patients, there was no significant association between DST transitions and the incidence of AMI. LVEF was higher following DST transitions, but infarct size was similar between study and control groups.

Abstract 19203: Predictors of Mortality Among Patients Admitted With Both Acute Myocardial Infarction and Non-Alcoholic Fatty Liver Disease

Introduction: Non-alcoholic fatty liver disease (NAFLD) is associated with an increased risk of cardiovascular disease (CVD). Indeed, cardiovascular disease is the most common cause of death among NAFLD patients We aimed to assess the association between NAFLD and mortality due to acute myocardial infarction and the predictors of in-hospital mortality among patients with both diagnosis in the USA. Methods: Hospitalizations with AMI with a concurrent diagnosis of NAFLD were identified in the National Inpatient Sample (2016-2019) using ICD-10 codes. The prevalence and trends over four years were calculated among different sociodemographic groups. Regression model was used to determine mortality outcomes due to AMI among NAFLD patients by age, race, and gender. A multivariable regression analysis was done to determine NAFLD as an independent predictor of mortality. Results: A total of 5450 patients were hospitalized with concurrent diagnosis of AMI and NAFLD during the study period. Among them, 5.11% (279) died in the hospital. Males were more likely to die compared to the females [OR 1.58, 95% CI 1.25-1.91]. Also, patients &gt; 50 had higher odds of dying due to AMI if they had NAFLD compared to those &lt;50 [OR 4.29, 95% CI 2.94-6.27]. Compared with the white population, Blacks [OR 0.79, 95% CI 0.54-1.15, p &lt;0.001] Hispanics [OR 1.21, 95% CI 0.85-1.74, p &lt;0.001], Asian and Pacific Islanders [OR 0.95, 95% CI 0.45-2.03, p &lt;0.001], and Native Americans [OR 0.58, 95% CI 0.08-4.17, p &lt;0.001] are less likely to die due to AMI if they have NAFLD. The NAFLD patients had higher odds of dying if they were admitted to the hospital with AMI [OR 1.96, 95% CI 1.74-2.21, p &lt;0.001]. Conclusion: Elderly white males with NAFLD are more likely to die if they are admitted to the hospital due to AMI. NAFLD was found to be an independent predictor of death among patients who had AMI.

Integration of machine learning to identify diagnostic genes in leukocytes for acute myocardial infarction patients

BackgroundAcute myocardial infarction (AMI) has two clinical characteristics: high missed diagnosis and dysfunction of leukocytes. Transcriptional RNA on leukocytes is closely related to the course evolution of AMI patients. We hypothesized that transcriptional RNA in leukocytes might provide potential diagnostic value for AMI. Integration machine learning (IML) was first used to explore AMI discrimination genes. The following clinical study was performed to validate the results.MethodsA total of four AMI microarrays (derived from the Gene Expression Omnibus) were included in bioanalysis (220 sample size). Then, the clinical validation was finished with 20 AMI and 20 stable coronary artery disease patients (SCAD). At a ratio of 5:2, GSE59867 was included in the training set, while GSE60993, GSE62646, and GSE48060 were included in the testing set. IML was explicitly proposed in this research, which is composed of six machine learning algorithms, including support vector machine (SVM), neural network (NN), random forest (RF), gradient boosting machine (GBM), decision trees (DT), and least absolute shrinkage and selection operator (LASSO). IML had two functions in this research: filtered optimized variables and predicted the categorized value. Finally, The RNA of the recruited patients was analyzed to verify the results of IML.ResultsThirty-nine differentially expressed genes (DEGs) were identified between controls and AMI individuals from the training sets. Among the thirty-nine DEGs, IML was used to process the predicted classification model and identify potential candidate genes with overall normalized weights > 1. Finally, two genes (AQP9 and SOCS3) show their diagnosis value with the area under the curve (AUC) > 0.9 in both the training and testing sets. The clinical study verified the significance of AQP9 and SOCS3. Notably, more stenotic coronary arteries or severe Killip classification indicated higher levels of these two genes, especially SOCS3. These two genes correlated with two immune cell types, monocytes and neutrophils.ConclusionAQP9 and SOCS3 in leukocytes may be conducive to identifying AMI patients with SCAD patients. AQP9 and SOCS3 are closely associated with monocytes and neutrophils, which might contribute to advancing AMI diagnosis and shed light on novel genetic markers. Multiple clinical characteristics, multicenter, and large-sample relevant trials are still needed to confirm its clinical value.

Diagnostic accuracy of biomarkers to detect acute mesenteric ischaemia in adult patients: a systematic review and meta-analysis

BackgroundAcute mesenteric ischaemia (AMI) is a disease with different pathophysiological mechanisms, leading to a life-threatening condition that is difficult to diagnose based solely on clinical signs. Despite widely acknowledged need for biomarkers in diagnosis of AMI, a broad systematic review on all studied biomarkers in different types of AMI is currently lacking. The aim of this study was to estimate the diagnostic accuracy of all potential biomarkers of AMI studied in humans.MethodsA systematic literature search in PubMed, The Cochrane Library, Web of Science and Scopus was conducted in December 2022. Studies assessing potential biomarkers of AMI in (at least 10) adult patients and reporting their diagnostic accuracy were included. Meta-analyses of biomarkers’ sensitivity, specificity, and positive and negative likelihood ratios were conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, and the study quality was assessed with the QUADAS-2 tool.ResultsSeventy-five studies including a total of 9914 patients assessed 18 different biomarkers in serum/plasma and one in urine (each reported in at least two studies), which were included in meta-analyses. None of the biomarkers reached a conclusive level for accurate prediction. The best predictive value overall (all studies with any type and stage of AMI pooled) was observed for Ischaemia-modified albumin (2 studies, sensitivity 94.7 and specificity 90.5), interleukin-6 (n = 4, 96.3 and 82.6), procalcitonin (n = 6, 80.1 and 86.7), and intestinal fatty acid-binding protein (I-FABP) measured in serum (n = 16, 73.9 and 90.5) or in urine (n = 4, 87.9 and 78.9). In assessment of transmural mesenteric ischaemia, urinary I-FABP (n = 2, 92.3 and 85.2) and D-dimer (n = 3, 87.6 and 83.6) showed moderate predictive value. Overall risk of bias was high, mainly because of selected study populations and unclear timings of the biomarker measurements after onset of symptoms. Combinations of biomarkers were rarely studied, not allowing meta-analyses.ConclusionsNone of the studied biomarkers had sufficient sensitivity and specificity to diagnose AMI, although some biomarkers showed moderate predictive accuracy. Future studies should focus on timing of measurements of biomarkers, distinguishing between early stage and transmural necrosis, and between different types of AMI. Additionally, studies on combinations of biomarkers are warranted.PROSPERO registration: CRD42022379341.

Geographical and sociodemographic differences in statin dispensation after acute myocardial infarction in Sweden: a register-based prospective cohort study applying analysis of individual heterogeneity and discriminatory accuracy (AIHDA) for basic comparisons of healthcare quality

BackgroundIn Sweden, as in many other countries, official monitoring of healthcare quality is mostly focused on geographical disparities in relation to a desirable benchmark. However, current evaluations could be improved...

Diagnostic potential of plasma biomarkers and exhaled volatile organic compounds in predicting the different stages of acute mesenteric ischaemia: protocol for a multicentre prospective observational study (TACTIC study)

IntroductionAcute mesenteric ischaemia (AMI) is a life-threatening condition with short-term mortality of up to 80%. The diagnosis of AMI has remained troublesome due to the non-specific clinical presentation, symptoms and...

Triple signal-enhancing sandwich-type electrochemical immunosensor based on Au@SNHC and PtPdCu/BNC for detection of Cardiac Troponin I

A novel multiple amplification strategy for electrochemical immunoassay was developed elaborately. The realization of this strategy is based on the high efficiency catalysis of boron nitrogen double-doped carbon loaded trimetallic PtPdCu mulberry-like nanospheres (PtPdCu/BNC) and the satisfactory conductivity of gold nanoparticles modified with sulfur nitrogen co-doped hollow porous carbon (Au@SNHC). Single crystal anisotropic Pt octahedral seeds were synthesized with sodium citrate as shape-directing agent, and then three metals were grown in situ to prepare the trimetallic PtPdCu mulberry nanospheres, which had excellent utilization of atoms and a significant number of catalytic active centers. Boron nitrogen double-doped carbon (BNC) with abundant free electrons and high electron density micro-mesoporous can be used as the supported dispersion material of PtPdCu MBNSs, further catalytically enrich H2O2. Moreover, the etching vulcanization of small ZIF template and the co-doping of sulfur and nitrogen endow sulfur nitrogen co-doped hollow porous carbon (SNHC) with shorter the diffusion distance of charge carrier and lower mass transfer resistance. Under optimal conditions, the developed immunosensor exhibits good sensing performance with a detection limit of 4.27 fg⋅mL−1, and the wide linear dynamic range (10 fg⋅mL−1–100 ng⋅mL−1). This study provides a possible strategy for early diagnosis and postoperative monitoring of AMI.

Temporal relation of disease onsets in patients with acute myocardial infarction and atrial fibrillation - results from a nationwide registry study

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Helsinki and Uusimaa Hospital District TYH2019309 and The Finnish Foundation for Cardiovascular Research Background/Introduction Acute myocardial infarction (AMI) and atrial fibrillation (AF) are commonly seen in a same patient. It is not unusual that patients are diagnosed with new-onset AF as a complication of AMI. Nevertheless, little is known about the temporal relations of these two diagnoses. Purpose We evaluated the temporal relations of AMI and new-onset AF in the Nationwide Finnish Anticoagulation in Atrial Fibrillation (FinACAF) comprising all patients with AF during 2004-2018 in Finland. Methods Patients with AF and AMI in Finland during 2010 to 2017 were analyzed, and individual patient data from the different registries were merged. Results Of the 157,658 patients with new-onset AF, a total of 16,971 (10.8%) patients were diagnosed with AMI at any point. The mean-age was 77.5 years (SD 10.6) and 72.3 years (SD 13.2), and the proportion of females 7,864 (46.3%) and 70,873 (50.4%) in AF patients with and without AMI, respectively. Altogether 8,889 (52.4%) of the AMI-AF patients had a history of established AMI diagnosis; whereas 4,278 (25.2%) were diagnosed with AMI during the same hospitalization period as new-onset AF or within 30 days; and 3,804 (22.4%) over 30 days after new-onset AF. A total of 6,928 (40.83%) of all AMI diagnoses were diagnosed within 1 year from new-onset AF. The temporal relation between new-onset AF and AMI are described in the Figure. Conclusions AMI-AF patients are older than AF patients without AMI at the time of new-onset AF. The diagnoses of AMI and AF tend to accumulate close to one another. One fourth of all AMI-AF patients were diagnosed with both diseases occurring same hospitalization period or within 30 days from new-onset AF.

External validation of the Manchester Acute Coronary Syndromes ECG risk model within a pre-hospital setting

ObjectivesThe Manchester Acute Coronary Syndromes ECG (MACS-ECG) prediction model calculates a score based on objective ECG measurements to give the probability of a non-ST elevation myocardial infarction (NSTEMI). The model...

Potential diagnostic value of N1LR and SNHG1 in acute myocardial infarction

IntroductionAcute myocardial infarction (AMI) is a common cardiovascular disease that can lead to myocardial necrosis and a poor prognosis. Clinical practice requires an accurate and quick diagnosis of AMI due to the inherent limitations of current biomarkers. Therefore, research into novel biomarkers is necessary. We aimed to explore the diagnostic potency of the long non-coding RNA (lncRNA) N1LR and SNHG1 in patients diagnosed with AMI.MethodWe measured lncRNA levels in 148 AMI patients and 50 healthy volunteers with quantitative RT-PCR method. Receiver operating characteristic (ROC) analysis was administered to detect the diagnostic power of selected lncRNAs. Correlation analysis was performed to explore the relationship between N1LR as well as SNHG1 and the conventional myocardial biomarkers (LDH, CK, CKMB and cTnI).ResultsROC analysis reveals the possibility of N1LR and SNHG1 as biomarkers in AMI diagnosis (AUC of N1LR: 0.873; AUC of SNHG1: 0.890). Correlation analysis revealed that N1LR was negatively correlated with the conventional biomarkers and SNHG1 was positively correlated with the conventional biomarkers.ConclusionFor the first time, we investigated the potential predictive diagnostic value of N1LR and SNHG1 in AMI diagnosis and substantial outcomes were obtained. Also, they may be capable of reflecting the progress of the disease during clinical practice from the correlation analysis.

Uncovering potential diagnostic biomarkers of acute myocardial infarction based on machine learning and analyzing its relationship with immune cells

BackgroundAcute myocardial infarction (AMI) is a common cardiovascular disease. This study aimed to mine biomarkers associated with AMI to aid in clinical diagnosis and management.MethodsAll mRNA and miRNA data were downloaded from public database. Differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNAs (DEmiRNAs) were identified using the metaMA and limma packages, respectively. Functional analysis of the DEmRNAs was performed. In order to explore the relationship between miRNA and mRNA, we construct miRNA-mRNA negative regulatory network. Potential biomarkers were identified based on machine learning. Subsequently, ROC and immune correlation analysis were performed on the identified key DEmRNA biomarkers.ResultsAccording to the false discovery rate < 0.05, 92 DEmRNAs and 272 DEmiRNAs were identified. GSEA analysis found that kegg_peroxisome was up-regulated in AMI and kegg_steroid_hormone_biosynthesis was down-regulated in AMI compared to normal controls. 5 key DEmRNA biomarkers were identified based on machine learning, and classification diagnostic models were constructed. The random forests (RF) model has the highest accuracy. This indicates that RF model has high diagnostic value and may contribute to the early diagnosis of AMI. ROC analysis found that the area under curve of 5 key DEmRNA biomarkers were all greater than 0.7. Pearson correlation analysis showed that 5 key DEmRNA biomarkers were correlated with most of the differential infiltrating immune cells.ConclusionThe identification of new molecular biomarkers provides potential research directions for exploring the molecular mechanism of AMI. Furthermore, it is important to explore new diagnostic genetic biomarkers for the diagnosis and treatment of AMI.

Machine Learning (Ml) Integrated Paper-Based Multiplexed Colorimetric Biosensing of Cardiac and Lipid Biomarkers for Accurate Acute Myocardial Infarction (Ami) Diagnosis and Prognosis

Machine Learning (Ml) Integrated Paper-Based Multiplexed Colorimetric Biosensing of Cardiac and Lipid Biomarkers for Accurate Acute Myocardial Infarction (Ami) Diagnosis and Prognosis

The High Cost of Death After Acute Myocardial Infarctions: Results from a National US Hospital Database.

This study described the differences in costs and length of stay (LOS) among patients with AMI who died versus survived using a large, nationally representative cohort of AMI patients. The 2019 HCUP NIS was used to analyze costs, and LOS among all patients with a principal diagnosis of AMI. A propensity-score matched analysis and multivariable regression were used to adjust for patient and hospital characteristics. There were 4559 visits in each of the cohorts (total 9118). The adjusted mean hospital cost was $18,970 (95% CI $16,453 - $21,871) for those that survived and $23,173 (95% CI $20,167 - $26,626; p <0.001) for those that died. The LOS was 3.95 (95% CI 3.41-4.57) in survivors and 4.24 (95% CI 3.67-4.89; p <0.001) in those who died. Survivors of AMI incurred lower costs and length of stay than those who died. Higher costs were attributed to greater LOS and higher-level care. The results suggest that economic evaluations of cardiovascular interventions that do not include the cost of dying may underestimate the benefits of the intervention.

Serum Creatinine Levels Have Been Shown to Accurately Predict in-Hospital Mortality in Individuals who have Been Effectively Treated with PPCI

Objective: The purpose of this study was to assess the predictive value of serum creatinine for in-hospital mortality among patients who had acute coronary syndromes. Study Design: An observational study Place and Duration: This observational study was conducted at Department of Cardiology, Rashid Latif Medical College, Lahore and Nowshera Medical College, Nowshera, KPK in the duration from 1st May, 2022 to 31 October, 2022. Methods: Total 198 patients had acute coronary syndromes who underwent successful primary percutaneous coronary intervention (PCI) were included. Patients were aged between 25-80 years. After receiving written consent, we recorded the subjects' ages, sexes, BMIs, and diagnoses in detail. Within 12 hours of an AMI diagnosis, serum creatinine levels were taken. Patients were split into two groups based on their serum creatinine levels upon admission. There are two categories, those with high levels of serum creatinine (over 1.3 mg/dL) and those with normal levels (below 1.3 mg/dL). Life expectancy at death was measured at one year. All of the information was analyzed with SPSS 22.0. Results: There were majority 140 (70.7%) males and 58 (29.3%) females in this study. Mean age of the patients was 55.18±11.24 years and had mean BMI was 24.6±14.52 kg/m2. Mean serum urea level was 37.3±0.22 mg/dL. Diabetes found in 40 (20.2%) cases and frequency of hypertension was 82 (41.4%). Anterior myocardial infarction was found in 79 (39.9%) cases followed by Inferior MI in 73 (36.9%) cases and non-ST MI in 46 (23.2%) cases. Mean left ventricular ejection fraction (LVEF) was 45±7.17 %. We found elevated serum creatinine in 37 (18.7%) cases and normal creatinine in 161 (81.3%) cases. Mortality in elevated group was higher found in 10 (27.02%) cases and as compared to normal group 8 (4.96%). Conclusion: The results of this study indicate that patients with AMI who had even slightly raised serum creatinine levels at admission have a significantly higher risk of dying within a year. Keywords: Myocardial Infarction, Comorbidities, Primary percutaneous coronary intervention, Mortality, Serum Creatinine