STEMI has high morbidity and mortality. Risk stratification is of extreme importance for better patient outcome [14]. Our goal was to test some of the previously reported predictors of mortality in STEMI patients in an Egyptian cohort. We specified 16 risk factors according to the data available in our archive. They were divided into clinical, biochemical, and physiological predictors. Univariate analysis was performed to define significant factors that affected mortality. We then selected 4 factors with the highest coefficients and odds ratios to construct a multivariate prediction model. The selection of only four factors was based on the standard statistical equation for building a well-fitted multivariate prediction model respecting the tested variables to sample size ratio [15]. We have paid special attention to eGFR calculated by CKD-EPI equation as an independent predictor of mortality and other adverse outcomes.
Clinical predictors of mortality
Effects of age and gender on the in-hospital prognosis of STEMI patients
The age was an independent risk factor of mortality in the present study, which is similar to previous recently published reports [16, 17]. Logically, aging is associated with chronic comorbidities and pathological changes in some organs, which affect the patient outcome and response to tissue injury and treatment, either directly or indirectly. Recent results of a systematic review and meta-analysis of 24 studies (430,914 STEMI patients) showed that the in-hospital mortality of male patients was significantly lower than that of females [18]. In consistence with these observations, we reported the same worse prognosis for females than males. In our cohort, the STEMI females were significantly older than the STEMI males. Also, the rates of having other diseases such as DM and HTN were higher in females. Previous studies showed that DM [19], HTN [20], and dyslipidemia were significant risk factors of mortality in STEMI patients. We did not find, any of them, having a significant impact on in-hospital mortality. Based on our analysis of the clinical predictors, we chose the age factor to share in the multivariate prognostic model construction for prediction of mortality in our cohort.
Effects of eGFR by CKD-EPI equation on the in-hospital prognosis of STEMI patients
The renal dysfunction in STEMI patients is a well-known predictor for the in-hospital and long-term mortality [21]. Also, the level of serum creatinine is one of the prognostic predictors after treatment [11, 22]. This is, in addition to, the interest of many studies to question the role of the various known equations that estimate the GFR to predict the patient outcomes [23]. The currently recommended equation for the estimation of GFR is CKD-EPI [6]; our study showed that reduced eGFR using this equation significantly affected the in-hospital prognosis of STEMI and eGFR below 60 ml/min was associated with about 4-fold increase in the mortality rate compared with those with eGFR above 60 ml/min. The rates of in-hospital incident HF and AF are also significantly higher in those with eGFR below 60 ml/min. This could be explained by the fact that lower eGFR levels are associated with advanced age, HTN, and DM in addition to the impact of nephropathy itself due to extensive atherosclerosis, calcifications, multiple organ affection, and limitation of medication such as ACE or ARBs. Therefore, eGFR should be considered as important predictors of prognosis, and risk stratifications should be conducted based on the functional status of the kidneys to reduce mortality and improve the outcome in STEMI patients.
Effects of admission vital signs and physiological predictors on the in-hospital prognosis of STEMI patients
Vital signs have received considerable research interest in the epidemiological studies concerned with STEMI risk prediction because of their importance in expressing the physiological and pathological cardiac changes. Tachycardia reflects the sympathetic overactivity, high myocardial oxygen consumption, and myocardial work in patients with STEMI [24, 25]. The blood pressure reflects the extent of myocardial damage and subsequently predicts the mortality [26].
The combination of more than one factor is always better than relying on a single one, and this motivated many researchers to test multiple indices with different components of vital signs to predict the risk magnitude among STEMI patients. Of those, SI [27] and MSI [28, 29] were the most proven to have a significant relation to mortality and adverse outcomes in STEMI with higher prediction power of MSI over the SI [30]. High Killip class was also described as a predictor of mortality in STEMI patients [31]. In the present study, we found that SI, MSI, MAP, SI-AGE, and Killip score were all significantly related to mortality with the highest coefficient and odds to the SI. Based on these results, SI was chosen for the multivariate prediction model.
Effects of admission cardiac enzymes and hemoglobin on the in-hospital prognosis of STEMI patients
The value of cardiac enzymes represents the infarction extent and size and is associated with the magnitude of myocardial necrosis and in-hospital mortality in STEMI patients [32]. Our study reported that either cardiac troponin positivity or the increase in CK-MB levels was associated with increased mortality risk with higher odds for troponin positivity. This is in contrast to a published report that showed higher predictability and prognostic significance for CK-MB levels [15].
In patients of acute STEMI, low baseline HB behaved independently as a risk factor for increased 30-day event rates [33]. In line with this report, we also found a positive correlation between the lower HB levels and mortality in STEMI patients.
Multivariate model was constructed from combination of clinical, laboratory, and physiological predictors of the highest coefficients and odds. We found that the most significant predictors of in-hospital mortality for STEMI in our setting were SI, cardiac troponin positivity, age, and eGFR. The model has the advantage of ease of application as it is based on simple clinical signs and routine laboratory assessment.
There were few limitations of our study. First, our study was a single-center study. Second, we used the qualitative test of cardiac troponin due to limited resources. Third, it had short-term follow-up till the patients’ discharge only. Although the results were significant in such period, short- and long-term follow-up analysis is required, which is undergoing and will be stated.