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find Author "HUANG Baotao" 3 results
  • Association between acute kidney injury and clinical outcomes in non-surgical patients receiving intensive cardiac care

    Objective To explore the clinical characteristics, in-hospital outcomes, and short-term survival of patients with acute kidney injury (AKI) in a large non-surgical cardiac intensive care unit (ICCU) in China. Methods Patients who had been admitted to the ICCU of the Department of Cardiology, West China Hospital of Sichuan University between June 2016 and May 2017 were retrospectively included. The diagnosis and staging of AKI were based on the Kidney Disease: Improving Global Outcomes criteria. The in-hospital outcomes were the composite of all-cause death or discharge against medical advice under extremely critical conditions. Patients without in-hospital composite outcomes were followed up to determine whether all-cause death occurred during the study period. The association of AKI with in-hospital composite outcomes or short-term survival was analyzed. Normally distributed quantitative data were expressed as mean±standard deviation, and non-normally distributed quantitative data were expressed as median (lower quartile, upper quartile). Results This study included 2083 patients, with an average age of (65.5±14.6) years old, and 681 (32.7%) were women. The prevalence rate of AKI was 15.0% (312/2083) (stage 1: 6.9%; stage 2: 4.9%; stage 3: 3.2%; respectively). Compared with patients without AKI, patients with AKI were older [(68.9±14.3) vs. (64.9±14.6) years old, P<0.001], had a higher Charles Comorbidity Index [4.0 (3.0, 6.0) vs. 2.0 (1.0, 3.0), P<0.001] and a greater Oxford Acute Illness Severity Score [32.0 (24.0, 41.2) vs. 21.0 (16.0, 26.0), P<0.001]. The incidence of in-hospital composite endpoint events was 8.4% (174/2083). Multiple logistic regression analysis showed that as the AKI stage increased, the risk of in-hospital composite endpoint events was higher [AKI stage 1 vs. no AKI: odds ratio (OR)=1.13, 95% confidence interval (CI) (0.57, 2.24); AKI stage 2 vs. no AKI: OR=2.21, 95%CI (1.08, 4.51); AKI stage 3 vs. no AKI: OR=10.88, 95%CI (4.50, 26.34); P for trend<0.001]. The patients without in-hospital composite endpoint events were followed up for a median time of 13.5 (10.7, 16.6) months, and the all-cause mortality rate was 5.5% (105/1909). Multiple Cox regression analysis showed that AKI was independently associated with all-cause death [hazard ratio=2.27, 95%CI (1.40, 3.69), P<0.001]. Conclusions AKI is common in the large ICCU in China and is more likely to occur in older patients who have more significant chronic illness complexity and acute illness severity. Moreover, AKI is independently associated with the in-hospital composite endpoint events and short-term survival.

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  • Effect of cardiac systolic and diastolic dysfunction on the prognosis of patients with coronary artery disease

    Objective To explore the role of systolic and diastolic dysfunction in the prognosis of Chinese patients with coronary artery disease (CAD). Methods CAD patients who underwent coronary arteriography in the Department of Cardiology of West China Hospital between July 2008 and June 2012 were included in this study. All the patients underwent color Doppler echocardiographic examination. Based on patients’ systolic and diastolic cardiac function, left ventricular ejection fraction (LVEF) <55% was as the systolic dysfunction and the ratio of mitral peak velocity of early filling to early diastolic mitral annular velocity (E/e’) >15 was as the diastolic dysfuntion. They were divided into normal cardiac function group (LVEF≥55%, E/e’ ratio≤15), systolic and diastolic dysfunction group (LVEF<55%, E/e’ ratio>15), diastolic dysfunction group (LVEF≥55%, E/e’ ratio>15) and systolic dysfunction group (LVEF<55%, E/e’ ratio≤15). The end points of follow-up were all-cause death and a major cardiovascular event (MACE). Results A total of 985 patients with complete echocardiographic report were included in this study. During the follow-up of (21.4±9.7) months, 46 patients (4.7%) died, and 52 (5.4%) had a MACE. Systolic dysfunction concomitant with diastolic dysfunction group and systolic dysfunction group patients had a higher risk of 36-month all-cause death (4.8%, 10.7%,P<0.001) and a higher risk of 41-month MACE (8.6%, 7.6%,P=0.028). Single factor analysis of all-cause death mortality showed that compared with the normal group, all-cause death mortality was the highest in systolic and diastolic dysfunction group (P<0.05), followed by diastolic dysfunction group (P<0.05) and systolic dysfunction group (P>0.05). Single factor analysis of MACE showed that compared with the normal group, MACE was still the highest in systolic and diastolic dysfunction group (P<0.05), followed by systolic dysfunction group (P<0.05) and diastolic dysfunction group (P>0.05). A multivariate Cox regression model analysis showed that compared with the normal group, the risk of all-cause death was the highest in the systolic and diastolic dysfunction group [hazard ratio (HR)=2.96, 95% confidence interval (CI) (1.34, 6.54),P=0.007], followed by the systolic dysfunction group [HR=1.91, 95%CI (0.67, 5.42),P=0.224] and the diastolic dysfunction group [HR=0.95, 95%CI (0.40, 2.23),P=0.905]. Conclusion Compared with normal patients, patients with either systolic or diastolic dysfunction have a poorer prognosis, and patients with systolic dysfunction concomitant with diastolic dysfunction have the poorest prognosis.

    Release date:2017-05-18 01:09 Export PDF Favorites Scan
  • A prediction model for long-term death in patients with acute myocardial infarction and reduced left ventricular ejection fraction

    Objective To explore the risk factors for long-term death of patients with acute myocardial infarction (AMI) and reduced left ventricular ejection fraction (LVEF), and develop and validate a prediction model for long-term death. Methods This retrospective cohort study included 1013 patients diagnosed with AMI and reduced LVEF in West China Hospital of Sichuan University between January 2010 and June 2019. Using the RAND function of Excel software, patients were randomly divided into three groups, two of which were combined for the purpose of establishing the model, and the third group was used for validation of the model. The endpoint of the study was all-cause mortality, and the follow-up was until January 20th, 2021. Cox proportional hazard model was used to evaluate the risk factors affecting the long-term death, and then a prediction model based on those risk factors was established and validated. Results During a median follow-up of 1377 days, 296 patients died. Multivariate Cox regression analysis showed that age≥65 years [hazard ratio (HR)=1.842, 95% confidence interval (CI) (1.067, 3.179), P=0.028], Killip class≥Ⅲ[HR=1.941, 95%CI (1.188, 3.170), P=0.008], N-terminal pro-brain natriuretic peptide≥5598 pg/mL [HR=2.122, 95%CI (1.228, 3.665), P=0.007], no percutaneous coronary intervention [HR=2.181, 95%CI (1.351, 3.524), P=0.001], no use of statins [HR=2.441, 95%CI (1.338, 4.454), P=0.004], and no use of β-blockers [HR=1.671, 95%CI (1.026, 2.720), P=0.039] were independent risk factors for long-term death. The prediction model was established and patients were divided into three risk groups according to the total score, namely low-risk group (0-2), medium-risk group (4-6), and high-risk group (8-12). The results of receiver operating characteristic curve [area under curve (AUC)=0.724, 95%CI (0.680, 0.767), P<0.001], Hosmer-Lemeshow test (P=0.108), and Kaplan-Meier survival curve (P<0.001) showed that the prediction model had an efficient prediction ability, and a strong ability in discriminating different groups. The model was also shown to be valid in the validation group [AUC=0.758, 95%CI (0.703, 0.813), P<0.001]. Conclusions In patients with AMI and reduced LVEF, age≥65 years, Killip class≥Ⅲ, N-terminal pro-brain natriuretic peptide≥5598 pg/mL, no percutaneous coronary intervention, no use of statins, and no use of β-blockers are independent risk factors for long-term death. The developed risk prediction model based on these risk factors has a strong prediction ability.

    Release date:2022-04-25 03:47 Export PDF Favorites Scan
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