Author + information
- Burak Hünük1,
- Özgür Çağaç2,
- İsmail Erdoğu3,
- Onur Öztürk3,
- Murat Sünbül2,
- Dursun Akaslan2,
- Erdal Durmuş2,
- Tarık Kıvrak2 and
- Bülent Mutlu2
Emerging data revealed the significant role of 25 (OH) vitamin D (vitD) in cardiovascular (CV) events. Clinical indices like Thrombolysis in Myocardial Infarction (TIMI) risk score, corrected TIMI frame count (CTFC) and high sensitivity cardiac troponin T (hs-cTnT) levels have short and long-term predictive values regarding CV mortality and morbidity in ST-segment elevation acute myocardial infarction (STEMI). The aim of this study was to determine the predictive value of vitD for clinical severity parameters in STEMI.
Patients with STEMI admitted to our hospital were prospectively and consecutively evaluated and proceeded to primary percutaneous coronary intervention (PCI). Patients with a previous history of coronary artery bypass graft (CABG), renal/hepatic failure and patients in need for emergency CABG were excluded from the study. 102 subjects ([mean±SD]age, 57±11 years) were enrolled in the study (female n [%]:18 [17,6%]). VitD levels were obtained on admission. VitD < 20 ng/ml was defined as vitD deficiency. CTFC were calculated after PCI for culprit lesion.
VitD deficiency was detected in 63,4% (<30 ng/ml in 92,7%) of the study population. In vitD deficient group, significantly higher hs-cTnT admission values ([median] 3598 ng/L vs 2576 ng/L, p=0,015), TIMI-STEMI scores (25th-75th percentiles; 2-5 vs 1-3, p<0,001), LAD CTFC (Data±SEM; 18,4±2,3 vs 12,6±1,4 p=0,042) and RCA CTFC (27,5,4±3,6 vs 19,6±1,6 p=0,044) were detected compared with non vitD deficient group. VitD levels were inversely correlated with TIMI STEMI risk scores (r:-0,438, p<0,001). In multivariate regression analyses, vitD levels was found as an independent predictor of higher TIMI-STEMI scores after adjusting for age, gender, HT and DM (Table-1).
Our findings suggest that low vitD levels might play a role in disease severity of STEMI patients by means of its independent associations with risk algorithms.
|Variables||β||p||Confidence Interval (95%)|
|Age (years)||0,327||< 0,04||(0,01 - 0,10)|
|Gender||0,139||0,44||(-1,29 - 2,91)|
|HT||0,059||0,78||(-1,49 - 1,97)|
|DM||0,082||0,66||(-1,45 - 2,26)|
|VitD||-0,440||0,01||(-0,16 - -0,02)|
Regression model for TIMI-STEMI risk score