The Predictive Value of R Wave Peak Time to Detect Thrombus Burden in St-segment Elevation Myocardial Infarction: A Retrospective Cohort Study in a Tertiary Medical Center
Rev. invest. clín
; 75(4): 212-220, Jul.-Aug. 2023. tab, graf
Article
in En
|
LILACS-Express
| LILACS
| ID: biblio-1515325
Responsible library:
MX1.1
ABSTRACT
Abstract Background:
Patients with higher thrombus burden have higher procedural complications and more long-term adverse cardiac events. Detecting patients with high thrombus burden (HTB) before coronary intervention could help avoid procedural complications.Objective:
The research aimed to analyze the R wave peak time (RWPT) on the electrocardiogram to predict thrombus burden before coronary angiography in patients with acute ST-segment elevation myocardial infarction (STEMI). Materials andMethods:
A total of 159 patients with STEMI were included in the study conducted at a tertiary medical center. The thrombolysis in myocardial infarction (TIMI) thrombus scale was applied to assess the thrombus burden. TIMI thrombus grades 0, 1, 2, and 3 were accepted as low; 4 and 5 had HTB. RWPT was measured from the beginning of the QRS complex to the R-peak from the leads pointing to the infarct-related artery.Results:
Patients were divided into two groups according to their angiographically defined thrombus burden as low and high. The low thrombus burden group (LTB) comprised fifty-four patients, whereas the HTB group comprised 105 patients. In the LTB group, RWPT was 47.96 ± 9.17 ms, and in the HTB group was 53.58 ± 8.92 ms; it was significantly longer (p < 0.01). Receiver operating characteristic analysis showed that a cut-off value of preprocedural RWPT of > 46.5 ms predicted the occurrence of HTB with a sensitivity and specificity of 87.62% and 51.85%, respectively (AUC 0.682, 95% CI 0.590-0.774, p < 0.001).Conclusion:
The present study evaluated the relationship between the RWPT and thrombus burden in STEMI patients. Based on the results, RWPT is an independent predictor of HTB.
Full text:
1
Index:
LILACS
Language:
En
Journal:
Rev. invest. clín
Journal subject:
MEDICINA
Year:
2023
Type:
Article
/
Project document