Background Exacerbations of heart failure appear frequently associated with precipitating factors not directly related to the evolution of cardiac disease. There still a paucity of data on the proportional distributio...Background Exacerbations of heart failure appear frequently associated with precipitating factors not directly related to the evolution of cardiac disease. There still a paucity of data on the proportional distribution of precipitating factors specifically in elderly patients. The aim of this study was to examine prospectively the precipitating factors leading to hospitalization in elderly patients with heart failure in our community hospital. Methods We evaluate elderly patients who need admissions for decompensate heart failure. All patients were reviewed daily by the study investigators at the first 24 h and closely followed-up. Decompensation was defined as the worsening in clinical NYHA class associated with the need for an increase in medical treatment （at minimum intravenously diuretics）. Results We included 102 patients （mean age 79 ± 12 years）. Precipitating factors were identified in 88.5%. The decompensation was sudden in 35% of the cases. Noncompliance with diet was identified in 52% of the patients, lack of adherence to the prescribed medications amounted to 30%. Others precipitating factors were infections （29%）, arrhythmias （25%）, acute coronary ischemia （22%）, and uncontrolled hypertension （15%）, miscellaneous causes were detected in 18% of the cases （progression of renal disease 60%, anemia 30% and iatrogenic factors 10%）. Concomitant cause was not recognizable in 11.5%. Conclusions Large proportion heart failure hospitalizations are associated with preventable precipitating factors. Knowledge of potential precipitating factors may help to optimize treatment and provide guidance for patients with heart failure. The presence of potential precipitating factors should be routinely evaluated in patients presenting chronic heart failure.展开更多
Background Resistance to anti-platelet therapy is detrimental to patients. Our aim was to establish a predictive model for aspirin resistance to identify high-risk patients and to propose appropriate intervention. Met...Background Resistance to anti-platelet therapy is detrimental to patients. Our aim was to establish a predictive model for aspirin resistance to identify high-risk patients and to propose appropriate intervention. Methods Elderly patients （n = 1130） with stable chronic coronary heart disease who were taking aspirin （75 mg） for 〉 2 months were included. Details of their basic characteristics, laboratory test results, and medications were collected. Logistic regression analysis was performed to establish a predictive model for aspirin resistance. Risk score was finally established according to coefficient B and type of variables in logistic regression. The Hosmer-Lemeshow （HL） test and receiver operating characteristic curves were performed to respectively test the calibration and discrimination of the model. Results Seven risk factors were included in our risk score. They were serum creatinine （〉 110 μmol/L, score of 1）; fasting blood glucose （〉 7.0 mmol/L, score of 1）; hyperlipidemia （score of 1）; number of coronary arteries （2 branches, score of 2; 〉 3 branches, score of 4）; body mass index （20-25 kg/m2, score of 2; 〉 25 kg/m2, score of 4）; percutaneous coronary intervention （score of 2）; and smoking （score of 3）. The HL test showed P ≥ 0.05 and area under the receiver operating characteristic curve ≥ 0.70. Conclusions We explored and quantified the risk factors for aspirin resistance. Our predictive model showed good calibration and discriminative power and therefore a good foundation for the further study of patients undergoing anti-platelet therapy.展开更多
文摘Background Exacerbations of heart failure appear frequently associated with precipitating factors not directly related to the evolution of cardiac disease. There still a paucity of data on the proportional distribution of precipitating factors specifically in elderly patients. The aim of this study was to examine prospectively the precipitating factors leading to hospitalization in elderly patients with heart failure in our community hospital. Methods We evaluate elderly patients who need admissions for decompensate heart failure. All patients were reviewed daily by the study investigators at the first 24 h and closely followed-up. Decompensation was defined as the worsening in clinical NYHA class associated with the need for an increase in medical treatment （at minimum intravenously diuretics）. Results We included 102 patients （mean age 79 ± 12 years）. Precipitating factors were identified in 88.5%. The decompensation was sudden in 35% of the cases. Noncompliance with diet was identified in 52% of the patients, lack of adherence to the prescribed medications amounted to 30%. Others precipitating factors were infections （29%）, arrhythmias （25%）, acute coronary ischemia （22%）, and uncontrolled hypertension （15%）, miscellaneous causes were detected in 18% of the cases （progression of renal disease 60%, anemia 30% and iatrogenic factors 10%）. Concomitant cause was not recognizable in 11.5%. Conclusions Large proportion heart failure hospitalizations are associated with preventable precipitating factors. Knowledge of potential precipitating factors may help to optimize treatment and provide guidance for patients with heart failure. The presence of potential precipitating factors should be routinely evaluated in patients presenting chronic heart failure.
文摘Background Resistance to anti-platelet therapy is detrimental to patients. Our aim was to establish a predictive model for aspirin resistance to identify high-risk patients and to propose appropriate intervention. Methods Elderly patients （n = 1130） with stable chronic coronary heart disease who were taking aspirin （75 mg） for 〉 2 months were included. Details of their basic characteristics, laboratory test results, and medications were collected. Logistic regression analysis was performed to establish a predictive model for aspirin resistance. Risk score was finally established according to coefficient B and type of variables in logistic regression. The Hosmer-Lemeshow （HL） test and receiver operating characteristic curves were performed to respectively test the calibration and discrimination of the model. Results Seven risk factors were included in our risk score. They were serum creatinine （〉 110 μmol/L, score of 1）; fasting blood glucose （〉 7.0 mmol/L, score of 1）; hyperlipidemia （score of 1）; number of coronary arteries （2 branches, score of 2; 〉 3 branches, score of 4）; body mass index （20-25 kg/m2, score of 2; 〉 25 kg/m2, score of 4）; percutaneous coronary intervention （score of 2）; and smoking （score of 3）. The HL test showed P ≥ 0.05 and area under the receiver operating characteristic curve ≥ 0.70. Conclusions We explored and quantified the risk factors for aspirin resistance. Our predictive model showed good calibration and discriminative power and therefore a good foundation for the further study of patients undergoing anti-platelet therapy.
