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Differential association between significant coronary stenosis and cardiac troponin T serial algorithms in renal dysfunction patients diagnosed with non-ST-segment elevation acute coronary syndromes. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehab849.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public Institution(s). Main funding source(s): Faculty of Medicine Khon Kaen University
Background
High-sensitivity cardiac troponin T (hs-cTnT) is recommended for diagnosing non-ST segment elevation acute coronary syndromes (NSTE-ACS). While the standard practice guidelines recommend using the 0,1-hour (hr) and 0,3-hr hs-cTnT algorithms, their efficacy has been not clearly established in chronic kidney disease (CKD) patients.
Purpose
We aimed to assess the differential associations between the two algorithms mentioned above with significant coronary stenosis in CKD patients.
Methods
This was a retrospective cohort study. Patients aged ≥18 years (yr) who were diagnosed with NSTE-ACS and had undergone coronary angiogram were recruited. The differential association between significant coronary stenosis and being ruled in based on the 0,1-hr and 0,3-hr hs-cTnT algorithm in both CKD patients and those normal renal function was analyzed and reported.
Results
There were 158 and 160 patients in the CKD group and the normal renal function group, respectively. The prevalence of significant coronary stenosis was higher in the CKD group (70.4% vs. 57.8%, P =0.028). Among CKD patients, factors associated with significant coronary stenosis were hypertension (OR =2.68; 95%CI 1.10-6.50) and being ruled in by the 0,3-hr algorithm (OR =3.65; 95%CI 1.27-10.52). In the normal renal function group, age (OR =1.04; 95%CI 1.01-1.06), male sex (OR =2.15; 95%CI 1.09-4.22), and being ruled in by the 0,1-hr algorithm (OR =3.12; 95%CI 1.20-8.10) were associated with significant coronary stenosis.
Conclusions
Being ruled in according to the 0,3-hr algorithm was significantly associated with coronary stenosis in CKD patients, making this a likely algorithm of choice in these patients. Abstract Figure. Adjusted OR of a coronary stenosis
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The impact of blood pressure variation on mortality and symptomatic intracerebral hemorrhage in stroke patients after thrombolytic therapy. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehab849.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public Institution(s). Main funding source(s): Faculty of Medicine, Khon Kaen University
Introduction Blood pressure variation (BPV) was one of the risk factors for unfavorable stokes outcomes. However, the association between BPV and short-term outcomes in stroke patients after received thrombolysis (recombinant tissue plasminogen activator; rt-PA) was limited.
Objectives We aimed to determine the association between BPV and mortality and symptomatic intracerebral hemorrhage (s-ICH) in stroke patients after rt-PA administration.
Methods This was a cross-sectional study in a specialized stroke unit of our university hospital, during 2015-2019. Adult ischemic-stroke patients who were eligible for receiving rt-PA were enrolled. Supine BP was measured just before starting rt-PA and at 0, 4, 8, 12, 16, 20, and 24 hours after completing rt-PA administration. The standard deviation (SD), coefficient of variation (CV), and successive variation (SV) of both systolic blood pressure (SBP) and diastolic blood pressure (DBP) were calculated. Final outcomes were in-hospital mortality, or s-ICH.
Results There were 278 patients enrolled, 138 men (49.6%), and mean age 65 ± 13 years old. Ten patients died (3.6%) and 27 patients had s-ICH (9.7%). There were 86 (30.9%) patients who received IV nicardipine before and after rt-PA. All BPV profiles of SBP were associated with mortality and s-ICH. Odds ratio (OR) for mortality were as follows; SD, 1.10 (1.02-1.19); CV, 1.13 (1.02-1.25); and SV, 1.07 (1.01-1.13), and OR for s-ICH were as follows; SD, 1.07 (1.02-1.14); CV, 1.11 (1.03-1.19); and SV, 1.05 (1.01-1.10). The BPV profiles of DBP also showed significant positive association with mortality and s-ICH. However, mean SBP and DBP, and time to rt-PA were not associated with both outcomes.
Conclusions BPV profiles of both SBP and DPB were positively associated with mortality and s-ICH in stroke patients after receiving rt-PA, independent of BP levels. Further study on the optimal BPV and the treatment towards it is crucial.
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P254 The differential impact of renal resistive index on future cardiovascular event in the hospitalised cardiovascular patients according to left ventricular ejection fraction: J-VAS study. Eur Heart J 2020. [DOI: 10.1093/ehjci/ehz872.082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Introduction
Renal resistive index (RRI) not only reflects renal vascular hemodynamics but also correlates well with systemic arterial stiffness. RRI associated with cardiovascular events in the selected group of cardiovascular patients including heart failure (HF). However, previous study limited only in the preserved ejection fraction (EF) patients.
Purpose
To determine the differential impact of RRI on cardiovascular events among cardiovascular patients according to EF.
Methods
A retrospective analysis of the Jichi Vascular Hemodynamics in Hospitalised Cardiovascular Patients (J-VAS) cohort. EF and RRI were measured in all patients, then categorised into groups of reduced EF (rEF < 40%), mid-range EF (mrEF 41-49%), and preserved EF (pEF≥50%). The latter group was subdivided into RRI≥0.8 and <0.8 to identify the risk of the primary endpoint, which was the composite of cardiac death, HF, acute coronary syndrome (ACS), aortic disease, arterial occlusion, and stroke.
Results
We included 1765 patients (mean age 64.7 years, 76% men). The most common diagnoses were ACS(66%) and HF(25%). During the median follow up of 1.9 years, 252 cardiovascular events occurred, 30.7%, 17.7%, and 10.4% in the rEF, mrEF and pEF group. RRI≥0.8 associated with the primary endpoint in the patients with pEF (Hazard ratio(HR), 1.69; 95%confident interval(CI) 1.11-2.58), but the association was not found in the other EF groups. Multivariate Cox regression analysis putting the pEF with RRI < 0.8 as a reference, pEF with RRI≥0.8 had a comparable risk for the primary endpoint to the mrEF group (HR, 1.55; 95%CI, 1.04-2.30 and HR, 1.92; 95%CI, 1.31-2.80, respectively), while the risk was highest in the rEF group (HR, 3.80; 95%CI, 2.73-5.29).
Conclusions
The risk of cardiovascular events in cardiovascular patients with pEF related to renal vascular hemodynamic alterations justified by RRI. In the patients with pEF, those with high RRI had comparable risk to the mrEF patients.
Risk of RRI≥0.8 for the primary endpoint Preserved EF HR (95%CI); P Mid-range EF HR (95%CI); P Reduced EF HR (95%CI); P Model 1 2.05 (1.39-3.02); P <0.001 1.60 (0.81-3.18); P =0.179 0.94 (0.53-1.67); P =0.838 Model 2 1.86 (1.25-2.78); P =0.002 1.33 (0.65-2.72); P =0.430 0.93 (0.52-1.66); P =0.792 Model 3 1.69 (1.11-2.58); P =0.015 1.10 (0.51-2.36); P =0.810 0.70 (0.38-1.28); P =0.242 Adjusted hazard ratio of RRI≥0.8 for the primary endpoint, RRI≥0.8 associated with a significant risk for the primary endpoint in the pEF group but not in the mrEF and rEF group. Model 1 was adjusted for age, sex and body mass index (BMI). Model 2 was adjusted for age, sex, BMI, smoking, dyslipidemia, and diabetes. Model 3 was adjusted for age, sex, BMI, smoking, dyslipidemia, diabetes, and glomerular filtration rate (GFR).
Abstract P254 Figure. Survival plot of the 4 subgroups
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