AIM:To study if impaired renal function is associated with increased risk of peri-infarct heart failure (HF) in patients with preserved ejection fraction (EF).METHODS:Patients with occluded infarct-related arteries (I...
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AIM:To study if impaired renal function is associated with increased risk of peri-infarct heart failure (HF) in patients with preserved ejection fraction (EF).METHODS:Patients with occluded infarct-related arteries (IRAs) between 1 to 28 d after myocardial infarction (MI) were grouped into chronic kidney disease (CKD) stages based on estimated glomerular filtration rate (eGFR).Rates of early post-MI HF were compared among eGFR *** regression was used to explore independent predictors of ***:Reduced eGFR was present in 71.1% of 2160 patients,with significant renal impairment (eGFR < 60 mL/min every 1.73 m2) in 14.8%.The prevalence of HF was higher with worsening renal function:15.5%,17.8% and 29.4% in patients with CKD stages 1,2 and 3 or 4,respectively (P < 0.0001),despite a small absolute difference in mean EF across eGFR groups:48.2 ± 10.0,47.9 ± 11.3 and 46.2 ± 12.1,respectively (P=0.02).The prevalence of HF was again higher with worsening renal function among patients with preserved EF:10.1%,13.6% and 23.6% (P < 0.0001),but this relationship was not significant among patients with depressed EF:27.1%,26.2% and 37.9% (P= 0.071).Moreover,eGFR was an independent correlate of HF in patients with preserved EF (P=0.003) but not in patients with depressed EF (P=0.181).CONCLUSION:A significant proportion of post-MI patients with occluded IRAs have impaired renal *** renal function was associated with an increased rate of early post-MI HF,the association being strongest in patients with preserved *** findings have implications for management of peri-infarct HF.
Job shop scheduling problem is typically a NP-Hard problem. In the recent past efforts put by researchers were to provide the most generic genetic algorithm to solve efficiently the job shop scheduling problems. Less ...
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Job shop scheduling problem is typically a NP-Hard problem. In the recent past efforts put by researchers were to provide the most generic genetic algorithm to solve efficiently the job shop scheduling problems. Less attention has been paid to initial population aspects in genetic algorithms and much attention to recombination operators. Therefore authors are of the opinion that by proper design of all the aspects in genetic algorithms starting from initial population may provide better and promising solutions. Hence this paper attempts to enhance the effectiveness of genetic algorithm by providing a new look to initial population. This new technique along with job based representation has been used to obtain the optimal or near optimal solutions of 66 benchmark instances which comprise of varying degree of complexity.
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