Dataset Information

Prediction of major adverse cardiac, cerebrovascular events in patients with diabetes after acute coronary syndrome.

ABSTRACT:

Background and objectives

The risk of major adverse cardiac and cerebrovascular events following acute coronary syndrome is increased in people with diabetes. Predicting out-of-hospital outcomes upon follow-up remains difficult, and no simple, well-validated tools exist for this population at present. We aim to evaluate several factors in a competing risks model for actionable evaluation of the incidence of major adverse cardiac and cerebrovascular events in diabetic outpatients following acute coronary syndrome.

Methods

Retrospective analysis of consecutive patients admitted for acute coronary syndrome in two centres. A Fine-Gray competing risks model was adjusted to predict major adverse cardiac and cerebrovascular events and all-cause mortality. A point-based score is presented that is based on this model.

Results

Out of the 1400 patients, there were 783 (55.9%) with at least one major adverse cardiac and cerebrovascular event (417 deaths). Of them, 143 deaths were due to non-major adverse cardiac and cerebrovascular events. Predictive Fine-Gray models show that the 'PG-HACKER' risk factors (gender, age, peripheral arterial disease, left ventricle function, previous congestive heart failure, Killip class and optimal medical therapy) were associated to major adverse cardiac and cerebrovascular events.

Conclusion

The PG-HACKER score is a simple and effective tool that is freely available and easily accessible to physicians and patients. The PG-HACKER score can predict major adverse cardiac and cerebrovascular events following acute coronary syndrome in patients with diabetes.

SUBMITTER: Baluja A

PROVIDER: S-EPMC7510367 | biostudies-literature | 2020 Jan-Feb

REPOSITORIES: biostudies-literature

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Publications

Prediction of major adverse cardiac, cerebrovascular events in patients with diabetes after acute coronary syndrome.

Baluja Aurora A Rodríguez-Mañero Moisés M Cordero Alberto A Kreidieh Bahij B Iglesias-Alvarez Diego D García-Acuña Jose M JM Martínez-Gómez Alvaro A Agra-Bermejo Rosa R Alvarez-Rodríguez Leyre L Abou-Jokh Charigan C López-Ratón Mónica M Gude-Sampedro Francisco F Alvarez-Escudero Julián J González-Juanatey Jose R JR

Diabetes & vascular disease research 20191216 1

<h4>Background and objectives</h4>The risk of major adverse cardiac and cerebrovascular events following acute coronary syndrome is increased in people with diabetes. Predicting out-of-hospital outcomes upon follow-up remains difficult, and no simple, well-validated tools exist for this population at present. We aim to evaluate several factors in a competing risks model for actionable evaluation of the incidence of major adverse cardiac and cerebrovascular events in diabetic outpatients followin ...[more]

PMID: 31841030

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Project description:Background and Objective: This study aims to develop and validate a nomogram for the occurrence of in-hospital major adverse cardiovascular and cerebrovascular events (MACCE) in acute coronary syndrome (ACS) patients. Methods: A total of 1,360 ACS patients admitted between November 2014 and October 2019 from Zhongda Hospital and Yancheng Third People's Hospital were included. Patients admitted in Zhongda Hospital before 2018 were split into the training cohort (n = 793). Those admitted after 2018 in Zhongda Hospital and patients from Yancheng Third People's Hospital were split into the validation cohort (n = 567). Twenty eight clinical features routinely assessed including baseline characteristics, past medical history and auxiliary examinations were used to inform the models to predict in-hospital MACCE (all-cause mortality, reinfarction, stroke, and heart failure) in ACS patients. The best-performing model was tested in the validation cohort. The accuracy and clinical applicability were tested by the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analyses (DCA). Results: The in-hospital MACCE occurred in 93 (6.83%) patients. The final prediction model consists of four variables: age, Killip grading, fasting blood-glucose (FBG) and whether percutaneous coronary intervention (PCI) was performed at early stage. A nomogram was used to present the final result. Individualized nomogram exhibited comparable discrimination to the Global Registry of Acute Coronary Events (GRACE) score [AUC: 0.807 (95% CI 0.736-0.878) vs. 0.761 (95% CI 0.69-0.878)], P = 0.10) and a better discrimination than the Evaluation of the Methods and Management of Acute Coronary Events (EMMACE) score [AUC: 0.807 (95% CI 0.736-0.878) vs. 0.723(95% CI 0.648-0.798), P = 0.01] in predicting the risk of in-hospital MACCE in ACS patients. A good prediction performance was maintained in the validation cohort (AUC =0.813, 95% CI 0.738-0.889). The prediction model also exhibited decent calibration (P = 0.972) and clinical usefulness. Conclusion: The nomogram may be a simple and effective tool in predicting the occurrence of in-hospital MACCE in ACS patients. Further longitudinal studies are warranted to validate its value in guiding clinical decision-making and optimizing the treatment of high-risk patients.

Project description:BackgroundTriglyceride-glucose index (TyG), a surrogate marker of insulin resistance (IR), could be a potential prognostic marker in patients with acute coronary syndromes (ACS). We evaluated the effect of the TyG index on major adverse cardiac and cerebrovascular events (MACCE) in patients with ACS undergoing percutaneous coronary intervention (PCI).MethodsThis registry-based cohort study was conducted at Tehran Heart Center from 2015 to 2021 and the median follow-up duration was 378 days. The primary outcome was MACCE and the secondary outcomes were MACCE components: all-cause mortality, myocardial infarction, stroke, target vessel revascularization, target lesion revascularization, and coronary artery bypass grafting. For comparison among TyG quartiles (Q), the log-rank test was used. Unadjusted and adjusted hazard ratios (HRs) and their 95% confidence intervals (CIs) were used to describe the association between TyG quartiles and MACCE. A subgroup of euglycemic patients was also evaluated.ResultsA total of 13,542 patients were included. Patients in the fourth TyG quartile (Q4) were younger, had higher mean BMI, and higher prevalence of hypertension, diabetes, and dyslipidemia. The adjusted Cox model showed that a 1-unit increment of the TyG index was associated with a significantly higher risk of MACCE (aHR 1.18, 95% CI 1.08 to 1.30, p < 0.001). Among TyG quartiles, there was a higher MACCE incidence in Q4 compared to Q1 (aHR 1.29, 95% CI 1.08 to 1.53, p = 0.005). In the euglycemic subgroup of the population, there was no significant association between MACCE incidence and a 1-unit increase in TyG or among TyG quartiles.ConclusionBased on our findings, while higher TyG levels and quartiles were associated with higher rates of MACCE in ACS, there was no such effect in the euglycemic population. If confirmed in future studies, these results can be beneficial for clinicians to risk stratify these patients with an easy-to-use index and determine clinical plans based on their risk.

Project description:ImportanceGuidelines currently recommend ticagrelor over clopidogrel for patients with acute coronary syndrome (ACS) based on randomized clinical trial data in which ticagrelor reduced major adverse coronary events (MACE) vs clopidogrel but increased bleeding and dyspnea.ObjectiveTo compare the risk of MACE with ticagrelor vs clopidogrel in patients with ACS treated with percutaneous coronary intervention (PCI), to compare major bleeding and dyspnea, and to evaluate the association between P2Y12 inhibitor adherence and MACE.Design, setting, and participantsPopulation-based cohort study using data of patients discharged alive after PCI for ACS from the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease registry from April 1, 2012, to March 31, 2016, with follow-up to 1 year. Analysis began April 2018.ExposuresOutpatient prescription for ticagrelor or clopidogrel within 31 days after PCI. Adherence was defined as a medication refill adherence value of 80% or higher.Main outcomes and measuresMajor adverse coronary events, a composite of all-cause death, hospitalization for ACS, unplanned coronary revascularization, or stent thrombosis within 365 days after index PCI. Secondary outcomes included hospitalization for major bleeding and emergency department visit for dyspnea.ResultsOf 11 185 individuals who underwent PCI, the median (interquartile range) age was 61 (54-71) years, and 2760 (24.7%) were women. Ticagrelor users (4076 [36.4%]) were generally younger and had fewer cardiac and noncardiac comorbidities than clopidogrel users. Ticagrelor was not associated with lower risk of MACE (adjusted hazard ratio [aHR], 0.97; 95% CI, 0.85-1.10); however, it was associated with an increased risk of major bleeding (aHR, 1.51; 95% CI, 1.29-1.78) and dyspnea (aHR, 1.98; 95% CI, 1.47-2.65). A total of 3328 ticagrelor users (81.6%) were adherent during the study vs 5256 of clopidogrel users (73.9%) (P < .001; χ2 = 86.4). In the full cohort, adherence was associated with a lower MACE risk (aHR, 0.79; 95% CI, 0.69-0.90 for adherence of ≥80% vs <80%). Differences in other secondary outcomes were not statistically significant. Sensitivity and subgroup analyses were consistent with primary analyses.Conclusions and relevanceIn this population-based cohort study of patients with ACS who underwent PCI, outpatient use of ticagrelor was not associated with a statistically significant reduction in MACE vs clopidogrel; however, it was associated with more major bleeding and dyspnea.

Dataset Information

Prediction of major adverse cardiac, cerebrovascular events in patients with diabetes after acute coronary syndrome.

Background and objectives

Methods

Results

Conclusion

Publications

Prediction of major adverse cardiac, cerebrovascular events in patients with diabetes after acute coronary syndrome.

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