Inflammatory cell response following ST-elevation myocardial infarction treated with primary percutaneous coronary intervention and its impact on cardiovascular outcomes: A systematic review and meta-analysis

Lim, Jinkang; Davies, Allan; Brienesse, S.; Mabotuwana, Nishani S.; Boyle, Andrew

doi:10.1016/j.ijcard.2023.01.082

Cited by 3 publications

(3 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Inflammatory response, as one of the pathogenesis of atherosclerosis, is an important risk factor for cardiovascular events. 31 , 32 NLR, the neutrophil-to-lymphocyte ratio, can compensate for mutual deficiencies and provides a more stable and flexible response to the inflammatory status of the body. 33 It has been reported that the increased NLR is an independent predictor of poor prognosis after PCI in patients with MI.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of Nomogram for the Prediction of Malignant Ventricular Arrhythmia Including Circulating Inflammatory Cells in Patients with Acute ST-Segment Elevation Myocardial Infarction

Wang¹,

Yang²,

Li³

et al. 2023

JIR

View full text Add to dashboard Cite

Background Malignant ventricular arrhythmia (MVA) can seriously affect the hemodynamic changes of the body. In this study, we developed and validated a nomogram to predict the in-hospital MVA risk in patients with STEMI after emergency PCI. Methods The multivariable logistic regression analysis included variables with a P<0.05 in the univariate logistic regression analysis and investigated the independent predictors affecting in-hospital MVA after PCI in patients with STEMI in the training cohort. The construction of a nomogram model used independent predictors to predict the risk of in-hospital MVA, and C-index, Hosmer-Lemeshow (HL) test, calibration curves, decision curve analysis (DCA), and receiver operating characteristic (ROC) were used to validate the nomogram. Results Killip class [OR=5.034 (95% CI: 1.596–15.809), P=0.005], CK-MB [OR=1.002 (95% CI: 1.001–1.004), P=0.022], serum potassium [OR=0.618 (95% CI: 0.406–0.918), P=0.020], NLR [OR=1.073 (95% CI: 1.034–1.115), P<0.001], and monocyte [OR=1.974 (95% CI: 1.376–2.925), P<0.001] were the independent predictors of in-hospital MVA after PCI in patients with STEMI. A nomogram including the 5 independent predictors was developed to predict the risk of in-hospital MVA. The C-index, equivalent to the area under the ROC curve (AUC), was 0.803 (95% confidence interval [CI]: 0.738–0.868) in the training cohort, and 0.801 (95% CI:0.692–0.911) in the validation cohort, showing that the nomogram had a good discrimination. The HL test ( χ 2 =8.439, P=0.392 in the training cohort; χ 2 =9.730, P=0.285 in the validation cohort) revealed a good calibration. The DCA suggested an obvious clinical net benefit. Conclusion Killip class, CK-MB, serum potassium, NLR, and monocyte were independent factors for in-hospital MVA after PCI in patients with STEMI. The nomogram model constructed based on the above factors to predict the risk of in-hospital MVA had satisfactory discrimination, calibration, and clinical effectiveness, and was an excellent tool for early prediction of the risk of in-hospital MVA after PCI in patients with STEMI.

show abstract

Section: Discussionmentioning

confidence: 99%

Development and Validation of Nomogram for the Prediction of Malignant Ventricular Arrhythmia Including Circulating Inflammatory Cells in Patients with Acute ST-Segment Elevation Myocardial Infarction

Wang¹,

Yang²,

Li³

et al. 2023

JIR

View full text Add to dashboard Cite

show abstract

“…Одним из важных лабораторных признаков, отличающих больных первой группы от второй, был существенный подъем уровня WBC крови (14,1*10 9 /л vs 10,5*10 9 /л, p<0,0001). Необходимо отметить, что в последние годы показатели клинического анализа крови все чаще используются в качестве предикторов прогностических моделей в кардиологии [8]. Повышение содержания WBC является ключевым индикатором интенсивности воспалительного ответа и эндогенной интоксикации при различных патологических состояниях, в т.ч.…”

Section: рукопись полученаunclassified

“…В нашем исследовании повышение точности прогностических моделей с предикторами шкалы GRACE ассоциировалось с влиянием 4 дополнительных факторов: ФВ ЛЖ, ФП, ПТИ и WBC. Вместе с тем наибольшее значение для повышения прогностической точности имело сочетание факторов шкалы GRACE и показателей ФВ ЛЖ и WBC в модели МЛР (8). Наличие этих предикторов демонстрировало патофизиологическое значение систолической дисфункции ЛЖ и системной воспалительной реакции в прогнозировании неблагоприятных исходов ИМпST, что повышает объяснимость результатов моделирования и возможность их клинической интерпретации.…”

Section: рукопись полученаunclassified

Prediction of in-hospital mortality in patients with ST-segment elevation acute myocardial infarction after percutaneous coronary intervention

Geltser,

Shahgeldyan,

Domzhalov

et al. 2023

Russ J Cardiol

View full text Add to dashboard Cite

Aim. Development of models for predicting in-hospital mortality (IHM) in patients with ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary intervention (PCI) based on multivariate logistic regression (MLR).Material and methods. This retrospective cohort study of 4735 electronic health records of patients (3249 men and 1486 women) with STEMI aged 26 to 93 years with a median of 63 years who underwent PCI was performed. Two groups of persons were identified, the first of which consisted of 321 (6,8%) patients who died in the hospital, while the second — 4413 (93,2%) patients with a favorable PCI outcome. To develop predictive models, univariate logistic regression (ULR) and MLR were used. Model accuracy was assessed using 3 following metrics: area under the ROC curve (AUC), sensitivity, and specificity. The end point was represented by the IHM score in STEMI patients after PCI.Results. Statistical analysis made it possible to identify factors that are linearly associated with IHM. ULR was used to determine their weight coefficients characterizing the predictive potential. IHM predictive algorithms based on GRACE scale predictors, represented both by ULR model and by 5 factors in continuous MLR model, had acceptable predictive accuracy (AUC — 0,83 and 0,86, respectively). The MLR model had the best quality metrics, the structure of which, in addition to 5 GRACE factors, included left ventricular ejection fraction (LVEF) parameters and white blood cell (WBC) count (AUC — 0,93, sensitivity — 0,87, specificity — 0,86) . The greatest contribution to endpoint was associated with the Killip class and LVEF, and the smallest contribution was associated with WBC and the age of patients.Conclusion. The predictive accuracy of the developed MLR models was higher than that of the GRACE score. The model with the structure represented by 5 factors GRACE, LV EF and WBC had the highest quality metrics.

show abstract

Clonal hematopoiesis, NETosis and arterial thrombosis: A deadly combination

Bonaventura,

Liberale

2024

International Journal of Cardiology

View full text Add to dashboard Cite

Inflammatory cell response following ST-elevation myocardial infarction treated with primary percutaneous coronary intervention and its impact on cardiovascular outcomes: A systematic review and meta-analysis

Cited by 3 publications

References 53 publications

Development and Validation of Nomogram for the Prediction of Malignant Ventricular Arrhythmia Including Circulating Inflammatory Cells in Patients with Acute ST-Segment Elevation Myocardial Infarction

Development and Validation of Nomogram for the Prediction of Malignant Ventricular Arrhythmia Including Circulating Inflammatory Cells in Patients with Acute ST-Segment Elevation Myocardial Infarction

Prediction of in-hospital mortality in patients with ST-segment elevation acute myocardial infarction after percutaneous coronary intervention

Clonal hematopoiesis, NETosis and arterial thrombosis: A deadly combination

Contact Info

Product

Resources

About