ST segment elevation myocardial infarction in patients hospitalized for non-cardiac conditions

Tiulim, Justin; Mak, Kevin; Shavelle, David M.

doi:10.1016/j.carrev.2017.05.021

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…ese characteristics lead to STEMI having a high rate of misdiagnosis and missed diagnosis, delaying the optimal timing of treatment for patients [13].…”

Section: Discussionmentioning

confidence: 99%

“…Studies have shown that some STEMI patients have no typical early clinical symptoms, and myocardial injury markers are not significantly elevated. These characteristics lead to STEMI having a high rate of misdiagnosis and missed diagnosis, delaying the optimal timing of treatment for patients [ 13 ]. Therefore, how to diagnose STEMI early and time has become the focus of research, and it is particularly important to find biological markers with strong sensitivity and specificity for the diagnosis of STEMI.…”

Section: Discussionmentioning

confidence: 99%

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The Value of Serum YKL-40 and TNF-α in the Diagnosis of Acute ST-Segment Elevation Myocardial Infarction

Fang

Chen

Zhang

et al. 2022

Cardiology Research and Practice

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Background. Acute ST-segment elevation myocardial infarction (STEMI) is a serious cardiovascular disease that poses a great threat to the life and health of patients. Therefore, early diagnosis is important for STEMI patient treatment and prognosis. The purpose of this study was to investigate the value of serum YKL-40 and TNF-α in the diagnosis of STEMI. Methods. From October 2020 to February 2022, 120 patients with STEMI were admitted to the Chest Pain Center of the Second People’s Hospital of Hefei, and 81 patients with negative coronary angiography were selected as the control group. Serum YKL-40 and TNF-α concentrations were measured by sandwich ELISA. Pearson correlation was used to analyze the correlation between serum YKL-40, TNF-α, and serum troponin I (cTnI) in STEMI patients; multivariate logistic regression analysis was used to screen independent risk factors for STEMI. Three diagnostic models were constructed: cTnI univariate model (model A), combined serum YKL-40 and TNF-α model other than cTnI (model B), and combined cTnI and serum YKL-40 and TNF-α model (model C). We assessed the clinical usefulness of the diagnostic model by comparing AUC with decision curve analysis (DCA). Results. Serum YKL-40 and TNF-α in the STEMI group were significantly higher than those in the control group ( P < 0.001 ). On Pearson correlation analysis, there was a significant positive correlation between serum YKL-40, TNF-α, and cTnI levels in STEMI patients. Multivariate logistic regression analysis showed that serum YKL-40 and TNF-α were independent risk factors for the development of STEMI. The results of ROC analysis showed that the area under the curve (AUC) of serum YKL-40 for predicting the occurrence of STEMI was 0.704. The AUC of serum TNF-α for predicting the occurrence of STEMI was 0.852. The AUC of cTnI as a traditional model, model A, for predicting the occurrence of STEMI was 0.875. Model B predicted STEMI with an AUC of 0.851. The addition of serum YKL-40 and serum TNF-α to the traditional diagnostic model composed of cTnI constituted a new diagnostic model; that is, the AUC of model C for predicting the occurrence of STEMI was 0.930. Model C had a better net benefit between a threshold probability of 70–95% for DCA. Conclusion. In this study, we demonstrate the utility of serum YKL-40 and TNF-α as diagnostic markers for STEMI and the clinical utility of diagnostic models by combining serum YKL-40 and TNF-α with cTnI.

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“…ese characteristics lead to STEMI having a high rate of misdiagnosis and missed diagnosis, delaying the optimal timing of treatment for patients [13].…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%