To the Editor. In the recently published study by Lazzeri et al. , microalbuminuria and other clinical variables were evaluated in hypertensive, nondiabetic patients with ST elevation myocardial infarction . "The authors concluded that microalbuminuria does not yield prognostic information about the inhospital mortality or complications and claimed an association between acute glucose dysmetabolism and outcomes. We believe that, in this study, the predictive power of microalbuminuria has been overlooked by the authors due to a series of methodological problems.
The long-term event-free survival (EFS) after acute myocardial infarction (AMI) is largelyuninvestigated. We analyzed noninvasive clinical variables in association with long-termEFS after AMI. The present prospective study included 504 consecutive patients with AMIat 3 hospitals from 1995 to 1998 (Adria, Bassano, Conegliano, and Padova Hospitals [ABC]study).
Thirty-seven variables were examined, including demographics, cardiovascular riskfactors, in-hospital characteristics, and blood components. The end point was 10-year EFS.Logistic and Cox regression models were used to identify the predictive factors. Wecompared 3 predictive models according to the goodness of fit and C-statistic analyses. Atenrollment, the median age was 67 years (interquartile range 58 to 75), 29% were women,38% had Killip class>1, and the median left ventricular ejection fraction was 51%(interquartile range 43% to 60%).
The 10-year EFS rate was 19%. Both logistic and Coxanalyses identified independent predictors, including young age (hazard ratio 1.2, 95%confidence interval 1.1 to 1.3, p=0.0006), no history of angina (hazard ratio 1.4, 95%confidence interval 1.1 to 1.8, p=0.009), no previous myocardial infarction (hazard ratio1.4, 95% confidence interval 1.1 to 1.7, p0.01), high estimated glomerular filtration rate(hazard ratio 0.8, 95% confidence interval 0.7 to 0.9, p=0.001), low albumin/creatinineexcretion ratio (hazard ratio 1.2, 95% confidence interval 1.1 to 1.3, p<0.0001), andhighleft ventricular ejection fraction (hazard ratio 0.8, 95% confidence interval 0.7 to 0.9, p=0.006).These variables had greater predictive power and improved the predictive power of 2 othermodels, including Framingham cardiovascular risk factors and the recognized predictors ofacute heart damage. In conclusion, 10-year EFS was strongly associated with 4 factors (ABCmodel) typically neglected in studies of AMI survival, including estimated glomerular filtrationrate, albumin/creatinine excretion ratio, a history of angina, and previous myocardial infarc-tion. This model had greater predictive power and improved the power of 2 other models usingtraditional cardiovascular risk factors and indicators of heart damage during AMI.
Traduzione dall’originale: Rosanna Sedran, RN, Giuseppe Berton, MD.
Predittori clinici della sopravvivenza libera da eventi per 10 anni dopo infarto miocardico acuto (da: “the Adria, Bassano, Conegliano, and Padova Hospitals [ABC] Study on Myocardial Infarction")
La sopravvivenza a lungo termine libera da eventi (EFS) dopo infarto miocardico acuto (AMI) è poco conosciuta.
Abbiamo analizzato variabili cliniche non invasive in associazione con EFS per un lungo periodo dopo un infarto miocardico acuto. Questo studio prospettico ha riguardato 504 pazienti con infarto miocardico acuto, non selezionati, arruolati consecutivamente in 3 ospedali generali dal 1995 al 1998 (the ABC study). Trentasette variabili cliniche sono state esaminate, compresi fattori demografici, fattori di rischio cardiovascolare, caratteristiche ospedaliere e componenti ematochimici.
L’obbiettivo dello studio è stato verificare l'EFS per 10 anni dopo l’AMI. Per l’analisi statistica sono stati usati modelli di regressione logistica e di Cox per identificare i fattori associati con EFS. Abbiamo confrontato 3 modelli predittivi usando analisi basate su “goodness of fit” e “C-‐ statistic”. All'inizio dello studio l'età mediana dei pazienti era di 67 anni (interquartili 58-‐75), il 29% donne, il 38% in classe di Killip > 1, e la mediana della frazione di eiezione ventricolare sinistra è stata del 51% (interquartili 43-‐60%). L’EFS a 10 anni è stato del 19%. All’analisi logistica e di
Cox sono stati identificati i seguenti fattori predittivi indipendenti: giovane età (hazard ratio 1,2, intervallo di confidenza 95%, 1.1-‐1.3, p=0,0006), non-‐storia di angina (hazard ratio 1,4, 95% intervallo di confidenza 1,1-‐1,8, p = 0,009), non-‐precedente infarto miocardico (hazard ratio 1,4, intervallo di confidenza 95% 1,1-‐1,7, p = 0,01), elevata velocità di filtrazione glomerulare stimata (hazard ratio 0.8, intervallo di confidenza 95% 0,7-‐0,9, p = 0.001), basso livello di escrezione di albumina/creatinina (hazard ratio 1.2, intervallo di confidenza 95% 1,1-‐1,3, p <0,0001) ed elevata frazione di eiezione ventricolare sinistra (hazard ratio 0.8, intervallo di confidenza 95% 0,7-‐0,9, p = 0.006). Queste variabili hanno mostrato maggiore potere predittivo di altri 2 modelli, che includono fattori di rischio cardiovascolare di Framingham e predittori di danno cardiaco acuto. In conclusione l'EFS per 10 anni dopo AMI è risultato fortemente associato a 4 fattori (the ABC model) sinora poco considerati negli studi di sopravvivenza dopo AMI, tra cui filtrazione glomerulare stimata, rapporto albumina/creatinina, storia di angina e precedente infarto miocardico. Questo modello ha maggiore capacità predittiva e risulta migliorativo rispetto ad altri due modelli tradizionali basati sui fattori di rischio cardiovascolare ed indicatori di danno cardiaco durante AMI.
Background: The aim of this study was to examine the prognostic value of several clinical characteristics on long-term mortality and causes of death after acute coronary syndrome.
Methods: The ABC-2 study is a prospective investigation comprising 557 patients with acute coronary syndrome. During hospitalization, 33 clinical variables, including demographics, cardiovascular risk factors, in-hospital characteristics, and blood components, were examined. “Acute models” were survival models containing the variables accrued within 72 h from admission, and “sub-acute models” contained data accrued over a 7-day period. Cox regression models were used for the survival analysis.
Results: The 12-year follow-up study revealed that 51.2% of the patients died (15.8% of the patients died from coronary artery disease and/or heart failure, 12.6% of the patients experienced sudden death, 8.3% of the patients died from other-cardiovascular diseases, and 14.5% of the patients died from non-cardiovascular causes. The following factors were independently associated with all-cause mortality in both the acute and sub-acute models: age, left ventricular ejection fraction (negative), body mass index (non-linear), previous myocardial infarction, diabetes mellitus, blood glucose (non-linear), Killip class>1, albumin/creatinine ratio, and pre-hospital time delay. The variables associated with coronary artery disease and/or heart failure included age, left ventricular ejection fraction (negative), body mass index (non-linear), previous myocardial infarction, Killip class>1, albumin/creatinine ratio, and pre-hospital time delay, while the variables associated with sudden death included age, hypertension (negative), uric acid, left ventricular ejection fraction (negative), and pre-hospital time delay, and those associated with other- cardiovascular causes included age, hypertension, and albumin/creatinine ratio. The only variable associated with non- cardiovascular mortality was age. The C-statistic of the predictive models was 0.86 for all-cause mortality, whereas the C-statistic ranged from 0.74 to 0.80 for cardiovascular causes.
Conclusions: The ABC-2 study revealed clinical predictors of long-term mortality after acute coronary syndrome that might help prognostication, patient education, and risk modification. Furthermore, the results showed that the modes of death are independently associated with different baseline clinical features.
Keywords: Acute coronary syndrome; Mortality; Risk prediction; Survival analysis
Aims: We investigated the gender-based differences in the association between heart failure (HF) during acutecoronary syndrome (ACS) and post-discharge, long-term cardiovascular (CV) mortality.
Methods and results: The present study included 557 patients enrolled in three intensive coronary care units anddischarged alive. HF during ACS was evaluated by Killip class and left ventricular ejection fraction (LVEF). Inter-action between gender and HF after 15 years of follow up was studied using Cox models including a formal inter-action term. Median age was 67 (interquartile range [IQR], 59–75) years, 29% were females, 37% had non-STelevation myocardial infarction and 32% Killip classN1, and median LVEF was 53% (IQR 46–61). All butfive pa-tients were followed up to 15 years, representing 5332 person-years. Of these, 40.2% died of CV-related causes.Crude CV mortality rate was higher among women (52.2%) than men (35.3%;Pb0.0001). At a univariablelevel, a negative interaction between female gender and Killip class for CV mortality was found [hazard ratio(HR) = 0.51 (0.34–0.77),P=0.002].Infive multivariable models after controlling for age, main CV risk factors,clinical features, post-discharge medical treatment, and mechanical coronary reperfusion, the interaction wassignificant across all models [HR = 0.63 (0.42–0.95),P= 0.02 in the fully adjusted model]. LVEF showed no sig-nificant hazard associated with female gender on univariable analysis [HR = 1.4 (0.9–0.2.0),P= 0.11] but did soin all adjusted models [HR = 1.7 (1.2–2.5),P= 0.005 in the fully adjusted model].
Conclusion: Gender is a consistent, independent effect modifier in the association between HF and long-term CVmortality after ACS.
Keywords: Gender, Heart failure, Killip class, LVEF, Acute coronary syndrome, Cardiovascular mortality, Surviving analysis