Predictive Biomarkers for Postmyocardial Infarction Heart Failure Using Machine Learning: A Secondary Analysis of a Cohort Study

Background. There are few biomarkers with an excellent predictive value for postacute myocardial infarction (MI) patients who developed heart failure (HF). This study aimed to screen candidate biomarkers to predict post-MI HF. Methods. This is a secondary analysis of a single-center cohort study including nine post-MI HF patients and eight post-MI patients who remained HF-free over a 6-month follow-up. Transcriptional profiling was analyzed using the whole blood samples collected at admission, discharge, and 1-month follow-up. We screened differentially expressed genes and identified key modules using weighted gene coexpression network analysis. We confirmed the candidate biomarkers using the developed external datasets on post-MI HF. The receiver operating characteristic curves were created to evaluate the predictive value of these candidate biomarkers. Results. A total of 6,778, 1,136, and 1,974 genes (dataset 1) were differently expressed at admission, discharge, and 1-month follow-up, respectively. The white and royal blue modules were most significantly correlated with post-MI HF (dataset 2). After overlapping dataset 1, dataset 2, and external datasets (dataset 3), we identified five candidate biomarkers, including FCGR2A, GSDMB, MIR330, MED1, and SQSTM1. When GSDMB and SQSTM1 were combined, the area under the curve achieved 1.00, 0.85, and 0.89 in admission, discharge, and 1-month follow-up, respectively. Conclusions. This study demonstrates that FCGR2A, GSDMB, MIR330, MED1, and SQSTM1 are the candidate predictive biomarker genes for post-MI HF, and the combination of GSDMB and SQSTM1 has a high predictive value.

Rare Case of Left Ventricular Thrombus Postmyocardial Infarction for Emergency Decompressive Craniectomy

Left ventricular (LV) thrombus formation is a notorious complication encountered in postmyocardial infarction patients. Such cases, when coming for noncardiac surgery, put the patient at greater risk of embolic events. Anesthesiologists play a pivotal role in the management of such rare and difficult cases. There is sparse evidence on management of such cases for noncardiac surgery. Hence, we would like to share our experience of a young patient with LV thrombus posted for left decompressive craniectomy.

Periodontitis is associated to increased systemic inflammation in postmyocardial infarction patients

ObjectivePeriodontitis has been independently associated to cardiovascular disease. However, the biological mechanisms underlying such association are still partially unknown. Thus, this study aimed to discover immunological clues accounting for the increased risk of myocardial infarction (MI) in patients having periodontitis.MethodsWe included 100 patients with a first MI, 50 with and 50 without severe periodontitis, and 100 age-matched, sex-matched and area-matched controls from the Periodontitis and Its Relation to Coronary Artery Disease Study. Participants underwent comprehensive clinical and laboratory examinations 6–10 weeks after the MI and plasma expression of 92 inflammation-related markers was assessed through proximity extension assay.ResultsPatients who had an MI displayed altered expression of CCL19, TNFRSF9 and LAP TGF-β1 in comparison with controls. TNFRSF9 correlated significantly with the amount of alveolar bone loss. MI patients with deep periodontal pockets showed increased white cell count and higher expression of FGF-21, HGF, OSM, CCL20 and IL-18R1 than patients without. White cell count correlated significantly with four of these proteins.ConclusionsCollectively, our results indicate molecular markers that could be responsible for the increased systemic inflammatory activity in patients with MI with periodontitis.

Ethical issues in two parallel trials of personalised criteria for implantation of implantable cardioverter defibrillators for primary prevention: the PROFID project—a position paper

AimTo discuss ethical issues related to a complex study (PROFID) involving the development of a new, partly artificial intelligence-based, prediction model to enable personalised decision-making about the implantation of an implantable cardioverter defibrillator (ICD) in postmyocardial infarction patients, and a parallel non-inferiority and superiority trial to test decision-making informed by that model.MethodThe position expressed in this paper is based on an analysis of the PROFID trials using concepts from high-profile publications in the ethical literature.ResultsWe identify ethical issues related to the testing of the model in the treatment setting, and to both the superiority and the non-inferiority trial. We underline the need for ethical-empirical studies about these issues, also among patients, as a parallel to the actual trials. The number of ethics committees involved is an organisational, but also an ethical challenge.ConclusionThe PROFID trials, and probably other studies of similar scale and complexity, raise questions that deserve dedicated parallel ethics and social science research, but do not constitute a generic obstacle. A harmonisation procedure, comparable to the Voluntary Harmonization Procedure (VHP) for medication trials, could be needed for this type of trials.

Recurrent ventricular tachycardia associated with lipomatous metaplasia of a myocardial scar

Lipomatous metaplasia in chronic postmyocardial infarction scars is a common and underappreciated finding seen in histopathology and cardiac MRI. Evidence suggests that lipomatous metaplasia is capable of altering the electroconductivity of the myocardium leading to re-entry pathways that are implicated in the pathogenesis of postmyocardial infarction arrhythmogenesis. We report a case of a patient who presented with non-sustained ventricular tachycardia and was found to have lipomatous metaplasia of a prior myocardial infarct-related scar.

Assessment of Concentrations of Heavy Metals in Postmyocardial Infarction Patients and Patients Free from Cardiovascular Event

Cardiovascular diseases (CVDs) constitute the first cause of death among the population of developing and developed countries. Atherosclerosis, which is a disorder with multifactorial etiopathogenesis, underlies most CVDs. The available literature includes ample research studies on the influence of classic cardiovascular (CV) risk factors. However, environmental exposure to heavy metals, among other substances, is still an unappreciated risk factor of CVDs. This study aimed to assess the concentration of some heavy metals (copper (Cu), zinc (Zn), manganese (Mn), cobalt (Co), and iron (Fe)) in the blood serum of postmyocardial infarction (post-MI) patients and patients free from myocardial infarction (MI) as well as estimate the relationship between the occurrence of MI and increased concentration of heavy metals. The concentration of heavy metals (Cu, Zn, Mn, Co, and Fe) was assessed using the inductively coupled plasma mass spectrometry technique in a group of 146 respondents divided into two groups: post-MI group (study group (SG), n = 74) and group without cardiovascular event (CVE) having a low CV risk (control group (CG), n = 72). The concentration of the analyzed heavy metals was higher in SG. All the heavy metals showed a significant diagnostic value p < 0.001 . The highest value of area under the curve (AUC) was observed for manganese (Mn) (0.955; 95% confidence interval (CI) = 0.922–0.988), while the lowest value was found for zinc (Zn) (0.691; 95% CI = 0.599–0.782). In one-dimensional models, high concentrations of each of the analyzed heavy metals significantly increased the chances of having MI from 7-fold (Cu) to 128-fold (Mn). All the models containing a particular metal showed a significant and high discrimination value for MI occurrence (AUC 0.72–0.92). Higher concentrations of Cu, Zn, Mn, Co, and Fe were found to considerably increase the chances of having MI. Considering the increasingly higher environmental exposure to heavy metals in recent times, their concentrations can be distinguished as a potential risk factor of CVDs.