Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?

Body, Richard

doi:10.1016/j.tjem.2018.05.005

Cited by 15 publications

(5 citation statements)

References 35 publications

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“…ECG and serum cardiac biomarkers are well-known predictors for diagnosing AIHD [ 54 , 55 ]. Both variables can achieve a high level of performance, and prediction models and stratification tools tend to utilize these variables [ 10 , 56 ]. However, we did not use these variables because we considered that each variable would show dominant significant predictive power in the model by itself, which would make it difficult to evaluate other clinically important variables.…”

Section: Discussionmentioning

confidence: 99%

Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain

Kim

Park

et al. 2020

PLoS ONE

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Background Due to an aging population and the increasing proportion of patients with various comorbidities, the number of patients with acute ischemic heart disease (AIHD) who present to the emergency department (ED) with atypical chest pain is increasing. The aim of this study was to develop and validate a prediction model for AIHD in patients with atypical chest pain. Methods and results A chest pain workup registry, ED administrative database, and clinical data warehouse database were analyzed and integrated by using nonidentifiable key factors to create a comprehensive clinical dataset in a single academic ED from 2014 to 2018. Demographic findings, vital signs, and routine laboratory test results were assessed for their ability to predict AIHD. An extreme gradient boosting (XGB) model was developed and evaluated, and its performance was compared to that of a single-variable model and logistic regression model. The area under the receiver operating characteristic curve (AUROC) was calculated to assess discrimination. A calibration plot and partial dependence plots were also used in the analyses. Overall, 4,978 patients were analyzed. Of the 3,833 patients in the training cohort, 453 (11.8%) had AIHD; of the 1,145 patients in the validation cohort, 166 (14.5%) had AIHD. XGB, troponin (single-variable), and logistic regression models showed similar discrimination power (AUROC [95% confidence interval]: XGB model, 0.75 [0.71–0.79]; troponin model, 0.73 [0.69–0.77]; logistic regression model, 0.73 [0.70–0.79]). Most patients were classified as non-AIHD; calibration was good in patients with a low predicted probability of AIHD in all prediction models. Unlike in the logistic regression model, a nonlinear relationship-like threshold and U-shaped relationship between variables and the probability of AIHD were revealed in the XGB model. Conclusion We developed and validated an AIHD prediction model for patients with atypical chest pain by using an XGB model.

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Section: Discussionmentioning

confidence: 99%

Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain

Kim

Park

et al. 2020

PLoS ONE

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“…ОКС является одним из проявлений ишемической болезни сердца. Термин используется для описания множества симптомов, которое предполагает, что происходит острая ишемия миокарда [16]. ОКС охватывает следующие клинические варианты: нестабильная стенокардия, инфаркт миокарда без подъема сегмента ST (ИМбпST) и инфаркт миокарда с подъемом сегмента ST (ИМспST) [25].…”

Section: Selection Of a Modern Strategy For The Treatment Of Acute Co...unclassified

Selection of a modern strategy for the treatment of acute coronary syndrome with elevated ST segment

Шукурова¹,

Kabirzoda²,

Radzhabova³

et al. 2022

jour

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The review is based on the analysis of current literature data on acute coronary syndrome (ACS): definition, epidemiology, classification, and methods of modern therapy methods. The article presents in detail the premedication and reperfusion strategies of introduction with an emphasis on a differential approach in the choice of therapy depending on the state of the ST-segment elevation. According to the literature the choice of treatment differs in patients with ACS with ST. The results of multicenter studies on the use of anticoagulant therapy in ACS and the need for double anticoagulant therapy against the background of the use of statins, ACE inhibitors, and beta blockers are presented.

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“…For this purpose, a tool for Risk Of Bias In Non-randomized Studies-of Interventions (ROBINS-I) [18] was used. ROBINS-I examines seven domains of bias owing to the following: (1) confounding; (2) selection of participants; (3) the classification of interventions; (4) deviations from intended interventions; (5) missing data; (6) measurement of outcomes; and (7) the selection of the reported result. The overall ROBINS-I judgment at domain and study level was attributed to the criteria specified in the ROBVIS tool [19].…”

Section: Quality Assessmentmentioning

confidence: 99%

Performance of Copeptin for Early Diagnosis of Acute Coronary Syndromes: A Systematic Review and Meta-Analysis of 14,139 Patients

Szarpak

Łapiński

Pruc³

et al. 2021

JCDD

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Diagnosis of acute coronary syndrome (ACS) based on copeptin level may enable one to confirm or rule-out acute myocardial infarction (AMI) with higher sensitivity and specificity, which may in turn further reduce mortality rate and decrease the economic costs of ACS treatment. We conducted a systematic review and meta-analysis to investigate the relationship between copeptin levels and type of ACS. We searched Scopus, PubMed, Web of Science, Embase, and Cochrane to locate all articles published up to 10 October 2021. We evaluated a meta-analysis with random-effects models to evaluate differences in copeptin levels. A total of 14,139 patients (4565 with ACS) were included from twenty-seven studies. Copeptin levels in AMI and non-AMI groups varied and amounted to 68.7 ± 74.7 versus 14.8 ± 19.9 pmol/L (SMD = 2.63; 95% CI: 2.02 to 3.24; p < 0.001). Copeptin levels in the AMI group was higher than in the unstable angina (UAP) group, at 51.9 ± 52.5 versus 12.8 ± 19.7 pmol/L (SMD = 1.53; 95% CI: 0.86 to 2.20; p < 0.001). Copeptin levels in ST-elevation myocardial infarction (STEMI) versus non-ST elevation myocardial infarction (NSTEMI) patient groups were 54.8 ± 53.0 versus 28.7 ± 46.8 pmol/L, respectively (SMD = 1.69; 95% CI: = 0.70 to 4.09; p = 0.17). In summary, elevated copeptin levels were observed in patients with ACS compared with patients without ACS. Given its clinical value, copeptin levels may be included in the assessment of patients with ACS as well as for the initial differentiation of ACS.

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Acute coronary syndromes diagnosis, version 2.0: Tomorrow's approach to diagnosing acute coronary syndromes?

Cited by 15 publications

References 35 publications

Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain

Emergency department routine data and the diagnosis of acute ischemic heart disease in patients with atypical chest pain

Selection of a modern strategy for the treatment of acute coronary syndrome with elevated ST segment

Performance of Copeptin for Early Diagnosis of Acute Coronary Syndromes: A Systematic Review and Meta-Analysis of 14,139 Patients

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