Predictors of long-term (10-year) mortality postmyocardial infarction: Age-related differences. Soroka Acute Myocardial Infarction (SAMI) Project

AbstractBackgroundCardiovascular diseases are the leading cause of death in elderly people. Over the past decades medical advancements in the management of patients with acute myocardial infarction (AMI) led to improved survival and increased life expectancy. As short-term survival from AMI improves, more attention is being shifted toward understanding and improving long-term outcomes.AimTo evaluate age-associated variations in the long-term (up to 10 years) prognostic factors following AMI in “real world” patients, focusing on improving risk stratification of elderly patients.MethodsA retrospective analysis of 2763 consecutive AMI patients according to age groups: ≤65 years (n=1230) and >65 years (n=1533). Data were collected from the hospital's computerized systems. The primary outcome was 10-year postdischarge all-cause mortality.ResultsHigher rates of women, non-ST-elevation AMI, and most comorbidities were found in elderly patients, while the rates of invasive treatment were lower. During the follow-up period, mortality rate was higher among the older versus the younger group (69.7% versus 18.6%). Some of the parameters included in the interaction multivariate model had stronger association with the outcome in the younger group (hyponatremia, anemia, alcohol abuse or drug addiction, malignant neoplasm, renal disease, previous myocardial infarction, and invasive interventions) while others were stronger predictors in the elderly group (higher age, left main coronary artery or three-vessel disease, and neurological disorders). The c-statistic values of the multivariate models were 0.75 and 0.74 in the younger and the elder groups, respectively, and 0.86 for the interaction model.ConclusionsLong-term mortality following AMI in young as well as elderly patients can be predicted from simple, easily accessible clinical information. The associations of most predictors and mortality were stronger in younger patients. These predictors can be used for optimizing patient care aiming at mortality reduction

When More Means Less: The Prognosis of Recurrent Acute Myocardial Infarctions

Recurrent acute myocardial infarctions (AMI) are common and associated with dismal outcomes. We evaluated the clinical characteristics and the prognosis of AMI survivors according to the number of recurrent AMIs (ReAMI) and the time interval of events (TI). A retrospective analysis of patients who survived following hospitalization with an AMI throughout 2002–2017 was conducted. The number of ReAMIs for each patient during the study period was recorded and classified based on following: 0 (no ReAMIs), 1, 2, ≥3. Primary outcome: all-cause mortality up to 10 years post-discharge from the last AMI. A total of 12,297 patients (15,697 AMI admissions) were analyzed (age: 66.1 ± 14.1 years, 68% males). The mean number of AMIs per patient was 1.28 ± 0.7; the rates of 0, 1, 2, ≥3 ReAMIs were 81%, 13.4%, 3.6% and 1.9%, respectively. The risk of mortality increased in patients with greater number of AMIs, HR = 1.666 (95% CI: 1.603–1.720, p p p < 0.001). The risk of mortality following AMI increased as the number of ReAMIs increased, and the TI between the events shortened. These findings should guide improved surveillance and management of this high-risk group of patients (i.e., ReAMI)

Psychological factors correlate meaningfully with percent-monocytes among acute coronary syndrome patients (in special issue on pschological risk factors and immune system involvement in cardiovascular disease)

Recent research demonstrates the importance of inflammatory parameters in the etiology and prognosis of the acute coronary syndrome (ACS). This study explored relations between psychological factors and immunological parameters routinely measured among ACS patients. Forty-two ACS patients completed questionnaires assessing perceived-control, emotional support, hostility, and life-events 2–4 days after hospitalization. Data on total leukocytes and percentages (%) of monocytes, %neutrophils, and %lymphocytes upon admission to hospital were collected from computerized medical charts as well as various biomedical information and risk-factors (e.g., diagnosis, left-ventricle—LV functioning, smoking, and hypertension). Of all significant biomedical variables, LV-function and arrival-time correlated uniquely with total leukocytes. Controlling for LV-function and arrival-time, hostility and life-events positively correlated with %monocytes, and perceived-control and emotional-support inversely correlated with %monocytes. Emotional-support was positively correlated and life-events were negatively correlated with %neutrophils. Macrophages play a pivotal role in plaque instability, the trigger of an ACS. This initiating role, and our finding of a relationship between recruitment of monocytes and a poor psychosocial profile, predictive of ACS, are consistent with a PNI component in the pathophysiology of ACS

Molecular and cellular interface between behavior and acute coronary syndromes

This review article integrates empirical findings from various scientific disciplines into a proposed psychoneuroimmunological (PNI) model of the acute coronary syndrome (ACS). Our starting point is an existing, mild, atherosclerotic plaque and a dysfunctional endothelium. The ACS is triggered by three stages. (1) Plaque instability: Pro-inflammatory cytokines (IL-1, IL-6, TNF-?) and chemoattractants (MCP-1, IL-8) induce leukocyte chemoattraction to the endothelium, and together with other triggers such as the CD40L–CD40 co-stimulation system activate plaque monocytes (macrophages). The macrophages then produce matrix metalloproteinases that disintegrate extra-cellular plaque matrix, causing coronary plaque instability. Acute stress, hostility, depression and vital exhaustion (VE) have been associated with elevated pro-inflammatory cytokines and leukocyte levels and their recruitment. (2) Extra-plaque factors promoting rupture: Neuro-endocrinological factors (norepinephrine) and cytokines induce vasoconstriction and elevated blood pressure (BP), both provoking a vulnerable plaque to rupture. Hostility/anger and acute stress can lead to vasoconstriction and elevated BP via catecholamines. (3) Superimposed thrombosis at a ruptured site: Increases in coagulation factors and reductions in anticoagulation factors (e.g. protein C) induced by inflammatory factors enhance platelet aggregation, a key stage in thrombosis. Hostility, depression and VE have been positively correlated with platelet aggregation. Thrombosis can lead to severe coronary occlusion, clinically manifested as an ACS. Thus, PNI processes might, at least in part, contribute to the pathogenesis of the ACS. This chain of events may endure due to lack of neuroendocrine-to-immune negative feedback stemming from cortisol resistance. This model has implications for the use of psychological interventions in ACS patients

A case series of concomitant treatment of perhexiline with amiodarone

Concomitant treatment with amiodarone and perhsexiline has been considered to be relatively contraindicated because of the hypothetical risk of potentiated adverse effects mediated by additive inhibition of carnitine palmitoyl transferase 1

An empirical approach for life expectancy estimation based on survival analysis among a post-acute myocardial infarction population

Background: Practical communication of prognosis is pertinent in the clinical setting. Survival analysis techniques are standardly used in cohort studies; however, their results are not straightforward for interpretation as compared to the graspable notion of life expectancy (LE). The present study empirically examines the relationship between Cox regression coefficients (HRs), which reflect the relative risk of the investigated risk factors for mortality, and years of potential life lost (YPLL) values after acute myocardial infarction (AMI). Methods: This retrospective population-based study included patients aged 40–80 years, who survived AMI hospitalization from January 1, 2002, to October 25, 2017. A survival analysis approach assessed relationships between variables and the risk for all-cause mortality in an up to 21-year follow-up period. The total score was calculated for each patient as the summation of the Cox regression coefficients (AdjHRs) values. Individual LE and YPLL were calculated. YPLL was assessed as a function of the total score. Results: The cohort (n = 6316, age 63.0 ± 10.5 years, 73.4 % males) was randomly split into training (n = 4243) and validation (n = 2073) datasets. Sixteen main clinical risk factors for mortality were explored (total score of 0–14.2 points). After adjustment for age, sex and nationality, a one-point increase in the total score was associated with YPLL of ∼one year. A goodness-of-fit of the prediction model found 0.624 and 0.585 for the training and validation datasets respectively. Conclusions: This functional derivation for converting coefficients of survival analysis into the comprehensible form of YPLL/LE allows for practical prognostic calculation and communication