Passive Prescription of Secondary Prevention Medical Therapy During Index Hospitalization for Acute Myocardial Infarction is Prevalent and Associated with Adverse Clinical Outcomes

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Sanderson, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-59605/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Mar, 2014 Read the published version in Global Heart → Version 1 posted You are reading this latest preprint version Abstract Background: Secondary prevention therapy reduces death and re-infarction after acute myocardial infarction (AMI) but is under-utilized in clinical practice. Mechanisms for this therapeutic gap are not well established. We aimed to evaluate the impact of passive continuation compared to active initiation of secondary prevention therapy for AMI patients during index hospitalization. Methods: We analyzed 1083 consecutive patients with AMI to a tertiary referral hospital in Hong Kong and assessed discharge prescription rates of secondary prevention therapies (aspirin, clopidogrel, beta-blockers, statins, angiotensin-converting enzyme inhibitor or angiotensin II receptor blockers (ACEI/ARBs)). Multivariate analysis was used to identify independent predictors of discharge and 6-month medication, Kaplan-Meier survival curve was used to evaluate 12-month survival. Results: Overall prescription rates of aspirin, clopidogrel, beta-blockers, statins, ACEI/ARBs on discharge was 94.8%, 54.2%, 64.5%, 83.5% and 61.4%, respectively. Multivariate analysis showed that prior use of each therapy, except clopidogrel, was an independent predictor of prescription of the same therapy on discharge: aspirin [Odds ratio (OR) =4.8, 95% CI =1.9-12.3, P<0.01]; beta-blockers (OR=2.5, 95%CI =1.8-3.4, P<0.01); statins (OR=8.3, 95%CI =0.4-15.7, P<0.01) and ACEI/ARBs (OR=2.9, 95%CI =2.0-4.3, P<0.01). Passive continuation of prior medication was associated with higher 1-year mortality rates than active initiation in treatment naïve patient [aspirin (13.7% vs. 5.7%), beta-blockers (12.9% vs. 5.6%), statins (11.0% vs. 4.6%), all P<0.01].Active prescription was more common in lower risk patients (who were younger, with less co-morbidity, and with higher left ventricular ejection fraction) who were treated more aggressively with secondary prevention medication on discharge. Also patients who were not on a given medication before admission were less likely to be prescribed it on discharge. Conclusions: Overall use of secondary prevention medication for AMI was suboptimal compared to guideline recommendations. Our findings suggested the practice of passive continuation of prior medication was prevalent and associated with adverse clinical outcomes compared to those who received secondary preventive medication for the first time during index hospitalization. Failure to start additional medication and possible inadequate dose titration in the passive continuation group may be in part the reason for the poorer clinical outcome in this group. Cardiac & Cardiovascular Systems Cardiothoracic Surgery Secondary Prevention Acute Myocardial Infarction Quality of Care Figures Figure 1 1. Introduction AMI has become one of the most common causes for hospital admission and is associated with significant risk of mortality and morbidity in the world [ 1 ], especially in China [ 2 ]. Despite that guideline recommendations are well-established, many AMI patients still do not receive optimal care resulting in suboptimal clinical outcomes[ 3 – 5 ]. Multiple studies have been performed to explore the factors associated with non-adherence in order to improve quality of care. Many factors have been reported to be associated with this gap including patient’s risk status[ 6 ], age[ 7 ], relevant medical history [ 8 ], ethnicity [ 9 ], the type of institution and clinician [ 10 ]. However, the reasons for this treatment gap in Asia especially the Chinese population still remain unknown. Moreover, most of the investigations were mainly focused on the inpatient quality of care during the acute period of disease and discharge time point, while the potential factors related to 6-month prescriptions are still unclear. In this study, we mainly sought to 1) analyze the potential reasons for the therapeutic gap by discharge and 6-month physician adherence, 2) estimate the clinical impact of these gaps for patients with AMI, in particular of the comparison between passive prescription and active prescription. 2. Methods 2.1 Study population and definition We analyzed consecutive patients presenting with AMI to a tertiary referral hospital in Hong Kong from February 2006 to March 2012. Besides unstable angina (UA), our registry consecutively recruited 1083 patients with AMI (ST-elevation and non ST-elevation myocardial infarction (STEMI/NSTEMI)), involving all causes of AMI in our health institution. And UA patients were excluded from analysis because of the AMI performance measures we used. The study protocol was approved by the ethics committee of the joint Chinese University of Hong Kong-New Territories East Cluster and was performed in accordance with the Declaration of Helsinki and Good Clinical Practice. All subjects provided written informed consent to participate. 2.2 Adherence to clinical guidelines We selected five of secondary prevention therapies recommended by American College of Cardiology (ACC) and American Heart Association (AHA), and classified as performance measures by ACC/AHA (aspirin, clopidogrel, beta-blockers, and ACEI/ARBs for patients with left ventricular systolic dysfunction (LVSD) is defined as chart documentation of an left ventricular ejection fraction (LVEF) less than 40% or narrative description of LVEF consistent with moderate or severe systolic dysfunction), and statins (if serum LDL-cholesterol > 100 mg/dL)). In order to measure the physician adherence rate more accurately, we analyzed their use in patients without known contra-indications that was clearly defined in ACC/AHA 2008 performance measures for AMI [ 11 ]. Thus, those patients with contra-indications and who were not prescribed according to the guideline recommendations, we did not regard it as non-adherence and these patients were excluded. The prescription of evidence-based therapies at two time points, discharge and six-month, was assessed. The use of medications on discharge was examined in patients who survived to hospital discharge, and the rate of 6-month prescription was assessed among patients who had survived up to 6-month post discharge. Two prescription patterns emerged in our preliminary analysis, active and passive prescription patterns. Active prescription was defined as patients who received the prescription on discharge and but were not taking any of the same medications before admission (active prescription pattern). And the passive pattern was the patients who received guideline recommended treatment but were already treated with the same therapy before admission to hospital (passive prescription pattern). 2.3 Follow-up (outcomes) The clinical impact was calculated at two time-points: six-month post discharge, and one-year post discharge. Clinical outcome was defined as event (including death, recurrent myocardial infarction, cardiac hospitalization, bleeding). Mortality involved the death caused by all reasons. Outside-hospital clinical events of 6-month and 1-year were obtained from the record of patient’s primary care system or through phone call follow-up. 2.4 Statistical analysis Baseline information were summarized using continuous or categorical data depending the characteristics of the variables. Shapiro–Wilks test was done to test the normality of the data. Continuous data with normal distributions were presented as mean ± standard deviation (SD),otherwise they were showed as median with interquartile range (IQR). For categorical data, they were showed as frequency and percentage (%). Patients who received complete guidelines recommended secondary prevention treatments were compared with those who received partial guideline recommended treatments. Further comparisons were also done between the two-prescription pattern groups (i.e. active and passive prescription) for each evidence-based medical therapy. Independent t-test and Chi-square test (fisher exact test if one cell has the count below 5) were performed to establish the difference of baseline informal between the two-prescription pattern groups. Logistic regression was conducted to explore the potential mechanism of adherence and influence of adherence on clinical outcomes. Univariate regression model including the following variables (baseline characteristics, medical histories, medication before admission, presentation of AMI, laboratory results during hospitalization, and procedures during index admission). And variables with P values of < 0.05 on univariate analysis were entered into multivariate logistic regression model. A multivariate regression model was performed to determine the predictors of adherence. The effect of prescription patterns of all five drugs on the clinical outcomes including 6-month mortality and 1-year mortality rate were explored after controlling for the following variables: age, gender, cardiovascular medical histories, diabetes, hypertension, hyperlipidemia, smoking status, and discharge diagnosis. Survival was evaluated by Kaplan–Meier survival curve, and differences in survival between two prescription patterns (active prescription and passive prescription) were calculated by the log-rank test. A two-sided p-value below 0.05 were considered statistically significant. Statistical analysis was performed using SPSS version 22.0 (SPSS Inc., Chicago, IL, USA). 3. Results 3.1 Patient population and Performance measure (Quality of care) During the whole study period, a total of 1083 AMI patients with 459 of STEMI (42.4%) or 624 of NSTEMI (57.6%) were enrolled. 54 patients died before discharge, therefore, the analysis of prescription of discharge guideline recommended medications were estimated with 1029 patients. 108 AMI patients died within six months after admission, so 975 patients were taken into account for 6-month physician adherence assessment. Finally, totally 149 patients cumulatively died during the one-year period post admission as AMI in our registry. Overall, physician adherence rates for the key performance measures (discharge medication)were: 94.8% for aspirin, 54.2% for clopidogrel, 64.5% for beta-blockers, 61.4% for ACEI/ARBs use in patients with LVSD, 83.5% for statins. For secondary prevention adherence at 6-month: calculated by the type of AMI, the STEMI population had a significantly higher usage than NSTEMI of aspirin (94.8% vs. 91.4%, P = 0.042), ACEI/ARBs (67.6% vs. 58.8%, P = 0.006), statins (90.3% vs. 81.5%, P < 0.001) and all 5 medications (21.1% vs.14.4%, P = 0.012). Table 1 showed the baseline clinical characteristics of two different discharge prescription patterns (active vs. passive). Additionally, this pattern of active prescription was seen in those lower risk patients (who were younger, with less comorbidities, had better LVEF value) and who were treated more aggressively with secondary prevention on discharge. However, for clopidogrel, the discharge medication pattern was highly associated with the patients’ vascular histories and in-hospital percutaneous coronary intervention (PCI) treatment. Table 1 Baseline characteristics & intervention therapy of active and passive prescription patterns Aspirin P value Clopidogrel P value Beta-blocker P value ACEI/ARBs P value Statins P value Prescription Pattern Active Passive Active Passive Active Passive Active Passive Active Passive Number 652 307 542 16 392 249 393 215 545 219 Demographics Age, mean(SD) 66.2 ± 12.7 73.4 ± 1.3 < 0.001 64.7 ± 11.8 66.0 ± 14.4 0.657 66.5 ± 13.3 70.9 ± 11.3 < 0.001 67.8 ± 13.3 70.2 ± 11.2 0.018 66.2 ± 12.8 70.1 ± 11.2 < 0.001 Male, no.% 71.9 61.6 0.001 75.5 87.5 0.268 70.9 60.6 0.007 73.5 63.3 0.008 72.8 63.9 0.015 Smoker, no.% 51.7 42.0 0.005 54.1 56.2 0.862 50.3 39.8 0.009 53.7 43.7 0.019 53.2 45.2 0.045 Medical histories , no.% MI 2.5 29.0 < 0.001 7.9 43.8 < 0.001 3.1 21.7 < 0.001 6.6 21.4 < 0.001 3.1 27.4 < 0.001 PVD 0.9 3.3 0.008 0.6 12.5 < 0.001 1.3 1.6 0.729 1.8 2.3 0.645 0.6 3.2 0.004 Stroke 2.0 22.5 < 0.001 5.0 25.0- 0.001 7.4 11.2 0.095 5.6 14.0 < 0.001 4.2 16.0 < 0.001 Diabetes mellitus 26.8 49.8 < 0.001 28.2 43.8 0.176 29.3 48.6 < 0.001 26.2 58.6 < 0.001 26.2 48.4 < 0.001 Hypertension 52.0 73.3 < 0.001 54.6 43.8 0.390 54.8 81.5 < 0.001 54.2 81.4 < 0.001 53.6 71.2 < 0.001 Hyperlipidemia 21.9 34.5 < 0.001 25.3 18.8 0.553 23.0 34.5 0.001 21.6 34.9 < 0.001 16.5 57.5 < 0.001 CRF 4.3 20.2 < 0.001 5.4 6.2 0.875 5.6 19.7 < 0.001 3.6 15.3 < 0.001 4.2 18.7 < 0.001 CHF 2.8 19.5 < 0.001 3.9 25.0 < 0.001 4.6 14.1 < 0.001 5.1 15.8 < 0.001 5.0 13.7 < 0.001 Physical characteristics at admission Heart rate (bpm), mean(SD) 79.7 ± 20.9 85.6 ± 21.6 < 0.001 79.1 ± 19.0 96.2 ± 23.9 0.002 84.2 ± 20.1 81.9 ± 21.0 0.186 82.4 ± 22.4 83.8 ± 20.9 0.486 80.6 ± 20.3 83.1 ± 21.4 0.139 SBP (mmHg), mean(SD) 141.6 ± 30.1 148.5 ± 33.0 0.003 29.2 ± 1.3 30.7 ± 8.5 0.580 147.3 ± 28.1 150.6 ± 33.1 0.196 145.1 ± 30.2 151.4 ± 33.9 0.028 144.3 ± 29.8 145.7 ± 35.2 0.583 LVEF(%), mean(SD) 51.6 ± 12.1 49.2 ± 13.9 0.039 11.7 ± 0.6 17.8 ± 6.7 0.224 11.7 ± 0.70 13.2 ± 1.0 0.418 50.1 ± 12.4 51.2 ± 13.9 0.416 51.0 ± 12.2 50.5 ± 13.8 0.639 Killip class III–IV, no.% 8.1 11.7 0.073 5.7 6.2 0.928 7.1 9.8 0.252 6.2 11.4 0.015 STEMI, no.% 50.6 22.8 < 0.001 51.7 25.0 0.036 42.9 29.7 0.001 50.6 30.2 < 0.001 51.0 28.3 < 0.001 Laboratory results, mean (SD) Serum LDL (mmol/L) 3.1 ± 1.0 2.4 ± 1.0 < 0.001 3.0 ± 1.0 1.8 ± 0.8 < 0.001 3.1 ± 1.0 2.6 ± 1.1 < 0.001 2.9 ± 1.0 2.6 ± 1.0 < 0.001 3.2 ± 1.0 2.4 ± 1.1 < 0.001 eGFR, mL/min/1.73 m 2 65.2 ± 25.3 49.6 ± 13.9 < 0.001 64.9 ± 21.8 72.5 ± 35.3 0.408 65.1 ± 22.9 50.6 ± 26.5 < 0.001 51.3 ± 25.9 50.1 ± 12.4 < 0.001 65.4 ± 25.0 52.6 ± 26.1 < 0.001 In-hospital Treatment PCI, no.% 63.3 38.8 < 0.001 89.1 56.2 < 0.001 61.0 45.4 < 0.001 60.8 47.0 0.001 65.5 48.9 < 0.001 *All the data used in analyzing were after adjusted with excluding the patients who have contraindications. ACEI/ARBs, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blockers (ARB); CI, confidence interval; OR, Odds ratio; STEMI, ST elevated myocardial infarction; eGFR, estimated glomerular filtration rate; CHF: congestive heart failure; CRF, chronic renal failure; MI, myocardial infarction; PVD, peripheral vascular disease; PCI, percutaneous coronary intervention; LDL, low-density lipoprotein; LVEF, left ventricular ejection fraction; SBP, systolic blood pressure 3.2 Predictors of adherence to guideline therapy 3.2.1 Discharge prescription As shown in Table 2 increasing age was related to the lower prescription rates of aspirin (OR = 0.94; 95% CI = 0.91–0.97; P = 0.001, per year), beta-blockers (OR = 0.97; 95% CI = 0.96–0.99; P < 0.001, per year) and statins (OR = 0.95; 95% CI = 0.94–0.97; P < 0.001, per year) on discharge. Traditional risk features (corresponding medical histories and comorbidities) were correlated with lower usage of beta-blockers and ACEI/ARBs, but did not significantly influence the prescription rate of aspirin and statins on discharge. Table 2 Predictors of adherence to discharged &6-month medical therapy Adjusted OR 95% CI P value Aspirin on discharge Age (per year) 0.94 0.91–0.97 0.001 Index revascularization 2.77 1.13–6.82 0.026 Aspirin before admission 4.84 1.90–12.30 0.001 Clopidogrel on discharge eGFR( mL/min/1.73 m 2 ) 1.01 1.00-1.02 0.037 Hemoglobin(g/dL) 1.17 1.05–1.29 0.004 Killip class (III-IV) 0.45 0.23–0.86 0.016 Index revascularization 34.28 22.94–51.22 < 0.001 Beta-blockers on discharge Age (per year) 0.97 0.96–0.99 < 0.001 NSTEMI 1.54 1.18–2.02 0.002 History of Hypertension 1.75 1.31–2.32 < 0.001 Heart Failure on admission 0.58 0.35–0.95 0.032 Beta-blockers before admission 2.50 1.83–3.42 < 0.001 ACEI/ARBs on discharge Systolic Blood Pressure (per mmHg) 1.01 1.00-1.02 < 0.001 Diabetes mellitus 1.43 1.03–1.98 0.033 ACEI/ARBs before admission 2.93 1.97–4.34 < 0.001 Statins on discharge Age (per year) 0.95 0.94–0.97 < 0.001 STEMI 1.94 1.32–2.87 0.001 Albumin (per g/l) 1.08 1.04–1.12 < 0.001 Peak Creatinine (per µmol/l) 0.99 0.98–1.01 0.018 Statins before admission 8.27 0.35–15.71 < 0.001 Combined medication use on discharge Diastolic Blood Pressure (per mmHg) 1.01 1.00-1.03 0.005 Index revascularization 9.6 5.60–16.5 < 0.001 ACEI/ARBs before admission 1.92 1.26–2.92 0.003 Aspirin at 6-month Index revascularization 1.97 1.08–3.58 0.027 Aspirin on discharge 15.13 7.13–32.13 < 0.001 Clopidogrel at 6-month Albumin during hospitalization (g/L) 1.05 1.01–1.09 0.018 History of revascularization 2.04 1.15–3.63 0.015 Index revascularization 2.51 1.45–4.35 0.001 Clopidogrel on discharge 6.02 3.42–10.60 < 0.001 Beta-blockers at 6-month Current smoker 0.54 0.34–0.85 0.008 Heart rate during hospitalization (bpm) 1.01 1.00-1.02 0.029 Albumin during hospitalization (g/L) 1.04 1.01–1.08 0.047 Beta-blockers on discharge 19.70 13.00-29.85 < 0.001 ACEI/ARBs at 6-month Hypertension 1.51 1.01–2.26 0.044 CHF 2.27 1.32–3.91 0.003 AF 0.274 0.09–0.87 0.029 Presented with STEMI 1.92 1.28–2.89 0.002 ACEI/ARBs on discharge 15.43 10.36–22.98 < 0.001 Statins at 6-month Statins on discharge 26.30 15.90-43.51 < 0.001 Combined medication use at 6-month History of revascularization 1.97 1.09–3.53 0.024 Index revascularization 2.80 1.59–4.93 < 0.001 Statins on discharge 8.24 5.35–12.70 < 0.001 *All the data used in analyzing were after adjusted with excluding the patients who have contraindications. +Analysis performed using multivariable logistic regression, variables in the model including baseline characteristics, medical histories, medication before admission, presentation of AMI, laboratory results during hospitalization, and procedures during index admission. ACEI/ARBs, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blockers (ARB); CI, confidence interval; OR, Odds ratio; STEMI, ST elevated myocardial infarction; NSTEMI, non- ST elevated myocardial infarction; eGFR, estimated glomerular filtration rate; CHF: congestive heart failure; AF: atrial fibrillation; Combined medication: combined using five medication including aspirin, Clopidogrel, Beta-blockers, ACEI/ARBs, and Statins Invasive procedures during hospitalization including PCI or coronary artery bypass grafting (CABG) were strongly associated with discharged prescription of aspirin. In-hospital revascularization was strongly associated with clopidogrel discharge prescription, as well as higher level of estimated glomerular filtration rate (eGFR) and hemoglobin during hospitalization and lower standard Killip-class (I or II). Presenting with NSTEMI and having a medical history of hypertension (HT) were associated with a higher likelihood to be discharged on beta-blockers, whereas having congestive heart failure (CHF) on admission was surprisingly a block to its use. Presenting with higher systolic blood pressure and diabetes mellitus (DM) were predictors of ACEI/ARBs prescription in eligible patients. In those diagnosed as STEMI, higher albumin level during hospitalization predicted use of statins on discharge, while lower peak creatinine level during index hospitalization was more likely to be prescribed with statins. Patients who underwent revascularization during index hospitalization were more likely to be prescribed with combined therapy on discharge (Table 2 ). Patients who were not on a given medication before admission were less likely to be prescribed it on discharge and this was consistent through the four medications, except clopidogrel. Clopidogrel was highly influenced by invasive interventions like PCI or CABG. Taking a specific medication before admission was still the strongest independent predictor for it to be taken on discharge of other four drugs; aspirin before admission (OR = 4.84; 95% CI = 1.90–12.30; P = 0.001) for aspirin on discharge; beta-blockers before admission (OR = 2.50; 95% CI = 1.83–3.42; P < 0.001) for beta-blockers on discharge; ACE/ARBs before admission (OR = 2.93; 95% CI = 1.97–4.34; P < 0.001) for ACE/ARBs on discharge; statins before admission (OR = 8.27; 95% CI = 0.35–15.71; P < 0.001) for statins on discharge. And for combination guideline prescription, ACEI/ARBs used before admission played a non-ignorable role in the medical part (OR = 1.92; 95% CI = 1.26–2.92; P = 0.003) (Table 2 ). 3.2.2 Six-month prescription Table 2 shows the attributes of the disparate 6-month utilization of individual recommendation and composited treatment pattern and adherence in a multivariable model. Predictors of losing prescription at 6-month were different for each drug. For aspirin, less in-hospital revascularization including PCI or CABG and not prescribed with aspirin on discharge were found to be independent predictors. For clopidogrel, the strongest predictors associated with lower continuous use were no history of revascularization, decreasing level of albumin, no index procedure of PCI or CABG, and without clopidogrel prescription on discharge. As for beta-blockers, current smoker, less heart rate beats, lower in-hospital laboratory level of albumin, and no prescription of beta-blockers contributed to inconstant use. In terms of ACEI/ARBs, independent predictors of withheld prescription were presence of AF, absence of CHF and hypertension, presentation with NSTEMI, and not prescribed ACEI/ARBs on discharge. Inconsistent use of statins was the result of no prescription on discharge. No revascularization before admission or during hospitalization and no statin therapy on discharge were considered to be two independent factors for low prescription rate of combined medication (Table 2 ). 3.3 Impact of passive prescription According to Table 3 , the patients who received the prescription on discharge and did not get the same medication before admission (active prescription pattern) had the lower risk in 6-month and 1-year mortality compared with the patients who adhered to discharge guideline recommendation and already treated with the same therapy before admitted to hospital (passive prescription pattern). Specifically, for 6-month mortality post discharge, active prescription compared with passive prescription of aspirin (2.9% vs. 7.5%, P < 0.001), beta-blockers (2.3% vs. 6.8%, P = 0.005), statins (2.4% vs.5.9%, P = 0.014); for one-year mortality post discharge, active prescription comparing with passive prescription of aspirin (5.7% vs. 13.7%, P < 0.001), beta-blockers (5.6% vs. 12.9%, P = 0.001), statins (4.6% vs.11.0%, P = 0.001). Even after adjustment for age, gender, smoking status, cardiovascular disease histories, diabetes, hypertension, hyperlipidemia, and discharge diagnosis, active prescription still demonstrated survival benefit compared to passive prescription: for 6-month mortality, aspirin (OR = 0.436, 95% CI = 0.225–0.845, P = 0.014), beta-blockers (OR = 0.374, 95% CI = 0.163–0.861, P = 0.021); for 1-year mortality, aspirin (OR = 0.538, 95% CI = 0.326–0.887, P = 0.015), beta-blockers (OR = 0.481, 95% CI = 0.260–0.892, P = 0. 020), statins (OR = 0.514, 95% CI = 0.277–0.956, P = 0.036). Table 3 Impact of passive prescription on 6-month &1-year mortality post discharge Variables Prescription Pattern 6-month mortality Adjusted # OR of 6-month mortality 1-year mortality Adjusted # OR of 1-year mortality No.% P value OR 95%CI P value No.% P value OR 95%CI P value Aspirin Active 2.9% < 0.001 0.436 0.225–0.845 0.014 5.7% < 0.001 0.538 0.326–0.887 0.015 Passive 7.5% 1.000 Reference 13.7% 1.000 Reference Clopidogrel Active 0.0% 0.730 ------- ------- ------- 0.0% 0.547 ------- ------- ------- Passive 0.7% ------- ------- ------- 2.2% ------- ------- ------- Beta-Blockers Active 2.3% 0.005 0.374 0.163–0.861 0.021 5.6% 0.001 0.481 0.260–0.892 0.020 Passive 6.8% 1.000 Reference 12.9% 1.000 Reference ACEI/ ARBs Active 4.8% 0.919 ------- ------- ------- 6.9% 0.283 ------- ------- ------- Passive 4.7% ------- ------- ------- 9.3% ------- ------- ------- Statins Active 2.4% 0.014 0.538 0.326–0.887 0.125 4.6% 0.001 0.514 0.277–0.956 0.036 Passive 5.9% 1.000 Reference 11.0% 1.000 Reference ACEI/ARBs, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blockers (ARB), odds ratio (OR) *All the data used in analyzing were after adjusted for age, gender, cardiovascular medical histories, diabetes, hypertension, hyperlipidemia, smoking status, discharge diagnosis. In Kaplan–Meier survival analysis, active prescription of aspirin had the better one year survival rate (Log-rank χ2 = 17.8, P < 0.001), active prescription of beta-blockers also gave significant benefit in one year survival rate (Log-rank χ2 = 10.3, P = 0.001), as well as the active use of statins (Log-rank χ2 = 10.7, P = 0.001) (Fig. 1 ). After adjustment with age, gender, smoking status, cardiovascular disease histories, diabetes, hypertension, hyperlipidemia and, discharge diagnosis, the hazard ratio (HR) of active prescription of aspirin was [HR = 1.750, 95% CI = 1.091–2.805, P = 0.020], of beta-blockers was [HR = 1.955, 95% CI = 1.099–3.477, P = 0.022], of statins was [HR = 1.891, 95% CI = 1.056–3.388, P = 0.032]. 4. Discussion With the increasing realization of the treatment gap, more attention has been paid to the possible reasons of withholding such important medications[ 7 , 12 – 14 ]. Our study results are consistent with other publications, which have identified that elder group[ 7 ], and traditional high-risk group with relevant medical histories and comorbidities were the significant negative predictors of physician adherence to the various performance measures after AMI[ 14 ]. However, we have found a novel reason that in our regression model prior medication is a strong independent predictor for prescription of the same discharge drug so that patients who were taking some standard medication were less likely to receive any new additional medication on discharge. This pattern was persistent for all four medications (aspirin, beta-blockers, ACEI/ARBs and statins). And for 6-month prescription, the pattern was similar to the discharge prescription’s predictors. Six-month prescription was also highly dependent on the previous medications (discharge time point). However, those patients who are not on any therapy before admission, the pattern of active prescription, who tended to be younger and lower risk patients were treated more aggressively with PCI and secondary prevention on discharge and therefore had better outcomes. Another potential explanation for this phenomenon could be human behavior. The physician may have assumed that the doctor before him/her already had prescribed the right medications and no further dose titration was necessary, or it may be due to the lack of awareness of the guidelines and the importance of adequate dosage of preventive medications post discharge to reduce later mortality. Another plausible reason is that the patients on previous medication were generally older and sicker and perhaps the doctors were unwilling to use the standard recommended doses. Relevant to this was the interesting finding in our study that low albumin level is a strong predictor of withheld discharge prescription and non-continuous use of secondary prevention. This may relate worse general health condition and more comorbidities. Albumin is one of the hepatic proteins, and its plasma concentration is usually affected by several factors, like the rate of albumin synthesis, exogenous albumin loss, and dilution. Synthesis of albumin is highly influenced by nutritional intake, colloid oncotic pressure variations, and liver function[ 15 ]. Some papers published have indicated that albumin is a bio-marker of chronic illness, including heart failure, renal failure and so on[ 16 ]. Liu et al. found that Hypoalbuminemia is common in HF patients and is associated with increased risk of death[ 17 ]. Prenner et al. also found that serum albumin is associated with myocardial fibrosis, adverse pulsatile aortic hemodynamics, and prognosis in HF[ 18 ]. Hirata et al. pointed out low albumin is associated with high mortality[ 19 ]. These previous studies have linked low serum albumin to general ill health of patients and worse clinical outcomes. Based on that, it probably reflects the reason why treatment is not optimally used in these patients with Hypoalbuminemia. This may explain continuation of insufficient doses from admission to discharge and follow-up with passive prescription. However, further studies of doctors’ awareness of guidelines seem to be essential and urgent although this may have improved over the intervening years since our study. Another strategy to increase prescription rate and consequently improve the clinical outcome could be to set up a formal discharge checking system with the recommended discharge medications for all AMI patients before discharge. This reminder system could ensure that patients leave hospital on the most optimal medication for them. More importantly, given the incomplete physician adherence and the potential source we found from this study, relying on an informal educational system does not seem to be adequate. In addition, our results also showed that patients who had the lower mortality at 6-month and 1-year were the ones who had the greater likelihood to be in active prescription group. In particular, the active prescription of medications of aspirin, beta-blockers and statins could account for the statically significant survival benefit to AMI patients after recovery although it was clear that this group had better general health and were younger. Therefore, our findings indicated that substantial support and encouragement of prescription of secondary prevention medications with dose titration if necessary needs to be highlighted to maximize the survival benefit and minimize the mortality risk especially in those who are older and in poorer general condition. Our results support the hypothesis that discharge on secondary preventive medications alone may not be enough but that the discharge dosage or subsequent dose titration may have an important impact on clinical outcomes and should be assessed to improve the quality of care for acute myocardial infarction patients. 5. Conclusions Despite advances in cardiovascular care and the establishment of management guidelines, there remained gaps in the application of the best treatments and strategies for AMI patients in Hong Kong. Our findings, that previous medication influenced discharged medication and discharge prescription highly affected 6-month prescription, indicated a potential reason for non-adherence that physicians or patients prefer the continuation of prior medication rather than initiating new secondary preventive therapies and that in these patients treatment was sub-optimal. Better understanding and narrowing these gaps between guideline and practice will contribute to improving quality of care and clinical outcomes of AMI patients. Abbreviations AMI: Acute myocardial infarction; ACEI/ARBs: Angiotensin-converting enzyme inhibitor or angiotensin II receptor blockers; UA: Unstable angina; STEMI: ST-elevation myocardial infarction; NSTEMI: Non ST-elevation myocardial infarction; ACC: American College of Cardiology; AHA: American Heart Association; LVSD: Left ventricular systolic dysfunction; LVEF: Left ventricular ejection fraction; SD: Standard deviation; IQR: Interquartile range; OR: Odds ratio; HR: Hazard ratio; PCI: Percutaneous coronary intervention; CABG: Coronary artery bypass grafting; eGFR: Estimated glomerular filtration rate; HT: Hypertension; CHF: Congestive heart failure; DM: Diabetes mellitus; Declarations Acknowledgments Authors would like to acknowledge the Chinese University of Hong Kong and the patients who participated in this study. Authors’ contributions Conceptualization: N.XR.H, B.P.Y, and CM.Y; Methodology: N.XR.H,J.E.S, and F.F; Statistical analysis: N.XR.H; Supervision: B.P.Y,YZ.X,JY.H; Writing - original draft: N.XR.H; Writing - review & editing: N.XR.H, J.E.S, F.F, and B.P.Y. All authors read and approved the final manuscript. Funding Not applicable. Availability of data and materials All data used and/or analyzed during this study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate The study protocol was approved by the ethics committee of the joint Chinese University of Hong Kong-New Territories East Cluster and was performed in accordance with the Declaration of Helsinki and Good Clinical Practice. All subjects provided written informed consent to participate. Consent for publication Not applicable. Competing interests All authors declare that they have no competing interests related to the submission of this manuscript. 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Makam RC, Erskine N, McManus DD, Lessard D, Gore JM, Yarzebski J, Goldberg RJ: Decade-Long Trends (2001 to 2011) in the Use of Evidence-Based Medical Therapies at the Time of Hospital Discharge for Patients Surviving Acute Myocardial Infarction. Am J Cardiol 2016;118(12):1792-1797. Shore S, Jones PG, Maddox TM, Bradley SM, Stolker JM, Arnold SV, Parashar S, Peterson P, Bhatt DL, Spertus J et al : Longitudinal persistence with secondary prevention therapies relative to patient risk after myocardial infarction. Heart 2015;101(10):800-807. Al-Khadra S, Meisinger C, Amann U, Holle R, Kuch B, Seidl H, Kirchberger I: Secondary prevention medication after myocardial infarction: persistence in elderly people over the course of 1 year. Drugs Aging 2014;31(7):513-525. Brilakis ES, Hernandez AF, Dai D, Peterson ED, Banerjee S, Fonarow GC, Cannon CP, Bhatt DL: Quality of care for acute coronary syndrome patients with known atherosclerotic disease: results from the Get With the Guidelines Program. Circulation 2009;120(7):560-567. Lai EJ, Grubisic M, Palepu A, Quan H, King KM, Khan NA: Cardiac medication prescribing and adherence after acute myocardial infarction in Chinese and South Asian Canadian patients. BMC Cardiovasc Disord 2011;11:56. Huynh LT, Chew DPB, Sladek RM, Phillips PA, Brieger DB, Zeitz CJ: Unperceived treatment gaps in acute coronary syndromes. International Journal of Clinical Practice 2009;63(10):1456-1464. Krumholz HM, Anderson JL, Bachelder BL, Fesmire FM, Fihn SD, Foody JM, Ho PM, Kosiborod MN, Masoudi FA, Nallamothu BK: ACC/AHA 2008 performance measures for adults with ST-elevation and non-ST-elevation myocardial infarction: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures (Writing Committee to develop performance measures for ST-elevation and non-ST-elevation myocardial infarction): developed in collaboration with the American Academy of Family Physicians and the American College of Emergency Physicians: endorsed by the American Association of Cardiovascular and Pulmonary Rehabilitation, Society for Cardiovascular Angiography and Interventions, and Society of Hospital Medicine. Circulation 2008;118(24):2596-2648. Astley CM, Macdougall CJ, Davidson PM, Chew DP: Lost in translation: health resource variability in the achievement of optimal performance and clinical outcome. Circ Cardiovasc Qual Outcomes 2011;4(5):512-520. Shang P, Liu GG, Zheng X, Ho PM, Hu S, Li J, Jiang Z, Li X, Bai X, Gao Y et al : Association Between Medication Adherence and 1-Year Major Cardiovascular Adverse Events After Acute Myocardial Infarction in China. J Am Heart Assoc 2019;8(9):e011793. Yan AT, Yan RT, Tan M, Huynh T, Soghrati K, Brunner LJ, DeYoung P, Fitchett DH, Langer A, Goodman SG et al : Optimal medical therapy at discharge in patients with acute coronary syndromes: temporal changes, characteristics, and 1-year outcome. Am Heart J 2007;154(6):1108-1115. Fuhrman MP, Charney P, Mueller CM: Hepatic proteins and nutrition assessment. J Am Diet Assoc 2004;104(8):1258-1264. Arques S, Ambrosi P: Human serum albumin in the clinical syndrome of heart failure. J Card Fail 2011;17(6):451-458. Liu M, Chan CP, Yan BP, Zhang Q, Lam YY, Li RJ, Sanderson JE, Coats AJ, Sun JP, Yip GW et al : Albumin levels predict survival in patients with heart failure and preserved ejection fraction. Eur J Heart Fail 2012;14(1):39-44. Prenner SB, Pillutla R, Yenigalla S, Gaddam S, Lee J, Obeid MJ, Ans AH, Jehangir Q, Kim J, Zamani P et al : Serum Albumin Is a Marker of Myocardial Fibrosis, Adverse Pulsatile Aortic Hemodynamics, and Prognosis in Heart Failure With Preserved Ejection Fraction. J Am Heart Assoc 2020;9(3):e014716. Hirata T, Arai Y, Yuasa S, Abe Y, Takayama M, Sasaki T, Kunitomi A, Inagaki H, Endo M, Morinaga J et al : Associations of cardiovascular biomarkers and plasma albumin with exceptional survival to the highest ages. Nat Commun 2020;11(1):3820. Cite Share Download PDF Status: Published Journal Publication published 01 Mar, 2014 Read the published version in Global Heart → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-59605","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":1492345,"identity":"f4e4fcaa-dde1-483f-8419-12bf3a33a59f","order_by":0,"name":"Nancy Xu-Rui Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYLCCBDDJfODAhwrStLAlHpxxhjS7eIwP87YQoc7gRu4ziYc77PL4Z+R8OMDbwCDPL3YAvxbJGelmEolnkoslbuRuOCC5g8Fw5uwE/Fr4JdLYJBLbmBM3SAC1GJ5hSDC4TUALG0RLPVBLzoMDiW1EaIHachikheHAQWK0SPY8Y7ZIbDueOOPMM4ODDWckCPvF4Hga482fbdWJ/e3Jjz//qbCR55cmoAUBBMAqJYhVDgL8B0hRPQpGwSgYBSMJAABt00Z7A8yCugAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-6944-844X","institution":"hangzhou first hopital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Nancy","middleName":"Xu-Rui","lastName":"Huang","suffix":""},{"id":1492346,"identity":"f1e34a7c-1e0d-4d0d-88b4-5a913d069e43","order_by":1,"name":"Fang Fang","email":"","orcid":"","institution":"Capital Medical University Affiliated Anzhen Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"Fang","suffix":""},{"id":1492347,"identity":"0a2fc41a-a7ec-40da-864e-49c2fe9716c1","order_by":2,"name":"Yizhou Xu","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yizhou","middleName":"","lastName":"Xu","suffix":""},{"id":1492348,"identity":"a2367098-d1c6-4fa2-acc2-02d4bc9b3c17","order_by":3,"name":"Jinyu Huang","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jinyu","middleName":"","lastName":"Huang","suffix":""},{"id":1492349,"identity":"f91645fb-585e-4834-9850-8ae00c0c20dd","order_by":4,"name":"John E. Sanderson","email":"","orcid":"","institution":"Chinese University of Hong Kong","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"John","middleName":"E.","lastName":"Sanderson","suffix":""},{"id":1492350,"identity":"41b796e0-3891-44bd-8f36-d28aab03c768","order_by":5,"name":"Bryan P. Yan","email":"","orcid":"","institution":"Chinese University of Hong Kong","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bryan","middleName":"P.","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2020-08-14 11:56:55","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-59605/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-59605/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1016/j.gheart.2014.03.1944","type":"published","date":"2014-03-01T19:57:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":1976492,"identity":"4dba448d-2275-470f-9ad1-797af933911f","added_by":"auto","created_at":"2020-08-18 17:36:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":109821,"visible":true,"origin":"","legend":"Kaplan–Meier survival curve: A) one-year mortality in 2 prescription patterns of aspirin; B) one-year mortality in 2 prescription patterns of beta-blockers; C) one-year mortality in the 2 prescription patterns of statins","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-59605/v1/Figure1.jpg"},{"id":13579942,"identity":"350f9121-4887-4f4a-856d-4f1b70877588","added_by":"auto","created_at":"2021-09-17 04:21:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":506418,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-59605/v1/59b0cd6f-0052-4d68-aa77-d9b598c6eac5.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003ePassive Prescription of Secondary Prevention Medical Therapy During Index Hospitalization for Acute Myocardial Infarction is Prevalent and Associated with Adverse Clinical Outcomes\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":" \u003cp\u003eAMI has become one of the most common causes for hospital admission and is associated with significant risk of mortality and morbidity in the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], especially in China [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Despite that guideline recommendations are well-established, many AMI patients still do not receive optimal care resulting in suboptimal clinical outcomes[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Multiple studies have been performed to explore the factors associated with non-adherence in order to improve quality of care. Many factors have been reported to be associated with this gap including patient\u0026rsquo;s risk status[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], age[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], relevant medical history [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], ethnicity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the type of institution and clinician [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, the reasons for this treatment gap in Asia especially the Chinese population still remain unknown. Moreover, most of the investigations were mainly focused on the inpatient quality of care during the acute period of disease and discharge time point, while the potential factors related to 6-month prescriptions are still unclear.\u003c/p\u003e \u003cp\u003eIn this study, we mainly sought to 1) analyze the potential reasons for the therapeutic gap by discharge and 6-month physician adherence, 2) estimate the clinical impact of these gaps for patients with AMI, in particular of the comparison between passive prescription and active prescription.\u003c/p\u003e "},{"header":"2. Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study population and definition\u003c/h2\u003e \u003cp\u003eWe analyzed consecutive patients presenting with AMI to a tertiary referral hospital in Hong Kong from February 2006 to March 2012. Besides unstable angina (UA), our registry consecutively recruited 1083 patients with AMI (ST-elevation and non ST-elevation myocardial infarction (STEMI/NSTEMI)), involving all causes of AMI in our health institution. And UA patients were excluded from analysis because of the AMI performance measures we used. The study protocol was approved by the ethics committee of the joint Chinese University of Hong Kong-New Territories East Cluster and was performed in accordance with the Declaration of Helsinki and Good Clinical Practice. All subjects provided written informed consent to participate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Adherence to clinical guidelines\u003c/h2\u003e \u003cp\u003eWe selected five of secondary prevention therapies recommended by American College of Cardiology (ACC) and American Heart Association (AHA), and classified as performance measures by ACC/AHA (aspirin, clopidogrel, beta-blockers, and ACEI/ARBs for patients with left ventricular systolic dysfunction (LVSD) is defined as chart documentation of an left ventricular ejection fraction (LVEF) less than 40% or narrative description of LVEF consistent with moderate or severe systolic dysfunction), and statins (if serum LDL-cholesterol\u0026thinsp;\u0026gt;\u0026thinsp;100\u0026nbsp;mg/dL)). In order to measure the physician adherence rate more accurately, we analyzed their use in patients without known contra-indications that was clearly defined in ACC/AHA 2008 performance measures for AMI [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thus, those patients with contra-indications and who were not prescribed according to the guideline recommendations, we did not regard it as non-adherence and these patients were excluded.\u003c/p\u003e \u003cp\u003eThe prescription of evidence-based therapies at two time points, discharge and six-month, was assessed. The use of medications on discharge was examined in patients who survived to hospital discharge, and the rate of 6-month prescription was assessed among patients who had survived up to 6-month post discharge.\u003c/p\u003e \u003cp\u003eTwo prescription patterns emerged in our preliminary analysis, active and passive prescription patterns. Active prescription was defined as patients who received the prescription on discharge and but were not taking any of the same medications before admission (active prescription pattern). And the passive pattern was the patients who received guideline recommended treatment but were already treated with the same therapy before admission to hospital (passive prescription pattern).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Follow-up (outcomes)\u003c/h2\u003e \u003cp\u003eThe clinical impact was calculated at two time-points: six-month post discharge, and one-year post discharge. Clinical outcome was defined as event (including death, recurrent myocardial infarction, cardiac hospitalization, bleeding). Mortality involved the death caused by all reasons. Outside-hospital clinical events of 6-month and 1-year were obtained from the record of patient\u0026rsquo;s primary care system or through phone call follow-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eBaseline information were summarized using continuous or categorical data depending the characteristics of the variables. Shapiro\u0026ndash;Wilks test was done to test the normality of the data. Continuous data with normal distributions were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD),otherwise they were showed as median with interquartile range (IQR). For categorical data, they were showed as frequency and percentage (%). Patients who received complete guidelines recommended secondary prevention treatments were compared with those who received partial guideline recommended treatments. Further comparisons were also done between the two-prescription pattern groups (i.e. active and passive prescription) for each evidence-based medical therapy. Independent t-test and Chi-square test (fisher exact test if one cell has the count below 5) were performed to establish the difference of baseline informal between the two-prescription pattern groups. Logistic regression was conducted to explore the potential mechanism of adherence and influence of adherence on clinical outcomes. Univariate regression model including the following variables (baseline characteristics, medical histories, medication before admission, presentation of AMI, laboratory results during hospitalization, and procedures during index admission). And variables with P values of \u0026lt;\u0026thinsp;0.05 on univariate analysis were entered into multivariate logistic regression model. A multivariate regression model was performed to determine the predictors of adherence. The effect of prescription patterns of all five drugs on the clinical outcomes including 6-month mortality and 1-year mortality rate were explored after controlling for the following variables: age, gender, cardiovascular medical histories, diabetes, hypertension, hyperlipidemia, smoking status, and discharge diagnosis. Survival was evaluated by Kaplan\u0026ndash;Meier survival curve, and differences in survival between two prescription patterns (active prescription and passive prescription) were calculated by the log-rank test. A two-sided p-value below 0.05 were considered statistically significant. Statistical analysis was performed using SPSS version 22.0 (SPSS Inc., Chicago, IL, USA).\u003c/p\u003e \u003c/div\u003e "},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Patient population and Performance measure (Quality of care)\u003c/h2\u003e\n\u003cp\u003eDuring the whole study period, a total of 1083 AMI patients with 459 of STEMI (42.4%) or 624 of NSTEMI (57.6%) were enrolled. 54 patients died before discharge, therefore, the analysis of prescription of discharge guideline recommended medications were estimated with 1029 patients. 108 AMI patients died within six months after admission, so 975 patients were taken into account for 6-month physician adherence assessment. Finally, totally 149 patients cumulatively died during the one-year period post admission as AMI in our registry.\u003c/p\u003e\n\u003cp\u003eOverall, physician adherence rates for the key performance measures (discharge medication)were: 94.8% for aspirin, 54.2% for clopidogrel, 64.5% for beta-blockers, 61.4% for ACEI/ARBs use in patients with LVSD, 83.5% for statins.\u003c/p\u003e\n\u003cp\u003eFor secondary prevention adherence at 6-month: calculated by the type of AMI, the STEMI population had a significantly higher usage than NSTEMI of aspirin (94.8% vs. 91.4%, P\u0026thinsp;=\u0026thinsp;0.042), ACEI/ARBs (67.6% vs. 58.8%, P\u0026thinsp;=\u0026thinsp;0.006), statins (90.3% vs. 81.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and all 5 medications (21.1% vs.14.4%, P\u0026thinsp;=\u0026thinsp;0.012).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e showed the baseline clinical characteristics of two different discharge prescription patterns (active vs. passive). Additionally, this pattern of active prescription was seen in those lower risk patients (who were younger, with less comorbidities, had better LVEF value) and who were treated more aggressively with secondary prevention on discharge. However, for clopidogrel, the discharge medication pattern was highly associated with the patients\u0026rsquo; vascular histories and in-hospital percutaneous coronary intervention (PCI) treatment.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBaseline characteristics \u0026amp; intervention therapy of active and passive prescription patterns\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAspirin\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eClopidogrel\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eBeta-blocker\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eACEI/ARBs\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eStatins\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003ePrescription Pattern\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eNumber\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e652\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e307\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e542\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e392\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e249\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e393\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e215\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e545\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e219\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eDemographics\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge, mean(SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66.0\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.657\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e67.8\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale, no.%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e71.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e61.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e87.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.268\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e60.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e63.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.008\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e63.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmoker, no.%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e54.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.862\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.045\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eMedical histories\u003c/span\u003e, no.%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePVD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.008\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.729\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.645\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStroke\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.0-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.095\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes mellitus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e58.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e52.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e54.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.390\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e54.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e54.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e71.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHyperlipidemia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.553\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e57.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCRF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.875\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCHF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003ePhysical characteristics at admission\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeart rate (bpm), mean(SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e79.7\u0026thinsp;\u0026plusmn;\u0026thinsp;20.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85.6\u0026thinsp;\u0026plusmn;\u0026thinsp;21.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e79.1\u0026thinsp;\u0026plusmn;\u0026thinsp;19.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e96.2\u0026thinsp;\u0026plusmn;\u0026thinsp;23.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84.2\u0026thinsp;\u0026plusmn;\u0026thinsp;20.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81.9\u0026thinsp;\u0026plusmn;\u0026thinsp;21.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.186\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e82.4\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e83.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.486\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80.6\u0026thinsp;\u0026plusmn;\u0026thinsp;20.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e83.1\u0026thinsp;\u0026plusmn;\u0026thinsp;21.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.139\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSBP (mmHg), mean(SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e141.6\u0026thinsp;\u0026plusmn;\u0026thinsp;30.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e148.5\u0026thinsp;\u0026plusmn;\u0026thinsp;33.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.580\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e147.3\u0026thinsp;\u0026plusmn;\u0026thinsp;28.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e150.6\u0026thinsp;\u0026plusmn;\u0026thinsp;33.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.196\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e145.1\u0026thinsp;\u0026plusmn;\u0026thinsp;30.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e151.4\u0026thinsp;\u0026plusmn;\u0026thinsp;33.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e144.3\u0026thinsp;\u0026plusmn;\u0026thinsp;29.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e145.7\u0026thinsp;\u0026plusmn;\u0026thinsp;35.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.583\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLVEF(%), mean(SD)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.039\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.224\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.418\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.416\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.639\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKillip class III\u0026ndash;IV, no.%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.073\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.928\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.252\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSTEMI, no.%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eLaboratory results, mean (SD)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum LDL (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeGFR, mL/min/1.73\u0026nbsp;m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65.2\u0026thinsp;\u0026plusmn;\u0026thinsp;25.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64.9\u0026thinsp;\u0026plusmn;\u0026thinsp;21.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72.5\u0026thinsp;\u0026plusmn;\u0026thinsp;35.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.408\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65.1\u0026thinsp;\u0026plusmn;\u0026thinsp;22.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.6\u0026thinsp;\u0026plusmn;\u0026thinsp;26.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.3\u0026thinsp;\u0026plusmn;\u0026thinsp;25.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65.4\u0026thinsp;\u0026plusmn;\u0026thinsp;25.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e52.6\u0026thinsp;\u0026plusmn;\u0026thinsp;26.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eIn-hospital Treatment\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePCI, no.%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e63.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e89.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e61.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e60.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e47.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e65.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"16\"\u003e*All the data used in analyzing were after adjusted with excluding the patients who have contraindications.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"16\"\u003eACEI/ARBs, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blockers (ARB); CI, confidence interval; OR, Odds ratio; STEMI, ST elevated myocardial infarction; eGFR, estimated glomerular filtration rate; CHF: congestive heart failure; CRF, chronic renal failure; MI, myocardial infarction; PVD, peripheral vascular disease; PCI, percutaneous coronary intervention; LDL, low-density lipoprotein; LVEF, left ventricular ejection fraction; SBP, systolic blood pressure\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Predictors of adherence to guideline therapy\u003c/h2\u003e\n\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n\u003ch2\u003e3.2.1 Discharge prescription\u003c/h2\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e increasing age was related to the lower prescription rates of aspirin (OR\u0026thinsp;=\u0026thinsp;0.94; 95% CI\u0026thinsp;=\u0026thinsp;0.91\u0026ndash;0.97; P\u0026thinsp;=\u0026thinsp;0.001, per year), beta-blockers (OR\u0026thinsp;=\u0026thinsp;0.97; 95% CI\u0026thinsp;=\u0026thinsp;0.96\u0026ndash;0.99; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, per year) and statins (OR\u0026thinsp;=\u0026thinsp;0.95; 95% CI\u0026thinsp;=\u0026thinsp;0.94\u0026ndash;0.97; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, per year) on discharge. Traditional risk features (corresponding medical histories and comorbidities) were correlated with lower usage of beta-blockers and ACEI/ARBs, but did not significantly influence the prescription rate of aspirin and statins on discharge.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003ePredictors of adherence to discharged \u0026amp;6-month medical therapy\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAdjusted OR\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95% CI\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eAspirin on discharge\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (per year)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.91\u0026ndash;0.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndex revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.13\u0026ndash;6.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.026\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAspirin before admission\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.90\u0026ndash;12.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eClopidogrel on discharge\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eeGFR( mL/min/1.73\u0026nbsp;m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00-1.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.037\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHemoglobin(g/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.05\u0026ndash;1.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKillip class (III-IV)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.23\u0026ndash;0.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.016\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndex revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e34.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22.94\u0026ndash;51.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eBeta-blockers on discharge\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (per year)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.96\u0026ndash;0.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNSTEMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.18\u0026ndash;2.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHistory of Hypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.31\u0026ndash;2.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeart Failure on admission\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.35\u0026ndash;0.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.032\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBeta-blockers before admission\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.83\u0026ndash;3.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eACEI/ARBs on discharge\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSystolic Blood Pressure\u003c/p\u003e\n\u003cp\u003e(per mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00-1.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes mellitus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.03\u0026ndash;1.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.033\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eACEI/ARBs before admission\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.97\u0026ndash;4.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eStatins on discharge\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (per year)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.94\u0026ndash;0.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSTEMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.32\u0026ndash;2.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlbumin (per g/l)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04\u0026ndash;1.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePeak Creatinine (per \u0026micro;mol/l)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.98\u0026ndash;1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStatins before admission\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.35\u0026ndash;15.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eCombined medication use on discharge\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiastolic Blood Pressure\u003c/p\u003e\n\u003cp\u003e(per mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00-1.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndex revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.60\u0026ndash;16.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eACEI/ARBs before admission\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.26\u0026ndash;2.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eAspirin at 6-month\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndex revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.08\u0026ndash;3.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.027\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAspirin on discharge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.13\u0026ndash;32.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eClopidogrel at 6-month\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlbumin during hospitalization (g/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u0026ndash;1.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHistory of revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.15\u0026ndash;3.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndex revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.45\u0026ndash;4.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClopidogrel on discharge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.42\u0026ndash;10.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eBeta-blockers at 6-month\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCurrent smoker\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.34\u0026ndash;0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.008\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeart rate during hospitalization (bpm)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00-1.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.029\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlbumin during hospitalization (g/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u0026ndash;1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.047\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBeta-blockers on discharge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.00-29.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eACEI/ARBs at 6-month\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u0026ndash;2.26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.044\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCHF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.32\u0026ndash;3.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.09\u0026ndash;0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.029\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePresented with STEMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.28\u0026ndash;2.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eACEI/ARBs on discharge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.36\u0026ndash;22.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eStatins at 6-month\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStatins on discharge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.90-43.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eCombined medication use\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalicUnderline\"\u003eat 6-month\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHistory of revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.09\u0026ndash;3.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.024\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIndex revascularization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.59\u0026ndash;4.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStatins on discharge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.35\u0026ndash;12.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\"\u003e*All the data used in analyzing were after adjusted with excluding the patients who have contraindications.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\"\u003e+Analysis performed using multivariable logistic regression, variables in the model including baseline characteristics, medical histories, medication before admission, presentation of AMI, laboratory results during hospitalization, and procedures during index admission.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\"\u003eACEI/ARBs, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blockers (ARB); CI, confidence interval; OR, Odds ratio; STEMI, ST elevated myocardial infarction; NSTEMI, non- ST elevated myocardial infarction; eGFR, estimated glomerular filtration rate; CHF: congestive heart failure; AF: atrial fibrillation; Combined medication: combined using five medication including aspirin, Clopidogrel, Beta-blockers, ACEI/ARBs, and Statins\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInvasive procedures during hospitalization including PCI or coronary artery bypass grafting (CABG) were strongly associated with discharged prescription of aspirin. In-hospital revascularization was strongly associated with clopidogrel discharge prescription, as well as higher level of estimated glomerular filtration rate (eGFR) and hemoglobin during hospitalization and lower standard Killip-class (I or II). Presenting with NSTEMI and having a medical history of hypertension (HT) were associated with a higher likelihood to be discharged on beta-blockers, whereas having congestive heart failure (CHF) on admission was surprisingly a block to its use. Presenting with higher systolic blood pressure and diabetes mellitus (DM) were predictors of ACEI/ARBs prescription in eligible patients. In those diagnosed as STEMI, higher albumin level during hospitalization predicted use of statins on discharge, while lower peak creatinine level during index hospitalization was more likely to be prescribed with statins. Patients who underwent revascularization during index hospitalization were more likely to be prescribed with combined therapy on discharge (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePatients who were not on a given medication before admission were less likely to be prescribed it on discharge and this was consistent through the four medications, except clopidogrel. Clopidogrel was highly influenced by invasive interventions like PCI or CABG. Taking a specific medication before admission was still the strongest independent predictor for it to be taken on discharge of other four drugs; aspirin before admission (OR\u0026thinsp;=\u0026thinsp;4.84; 95% CI\u0026thinsp;=\u0026thinsp;1.90\u0026ndash;12.30; P\u0026thinsp;=\u0026thinsp;0.001) for aspirin on discharge; beta-blockers before admission (OR\u0026thinsp;=\u0026thinsp;2.50; 95% CI\u0026thinsp;=\u0026thinsp;1.83\u0026ndash;3.42; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for beta-blockers on discharge; ACE/ARBs before admission (OR\u0026thinsp;=\u0026thinsp;2.93; 95% CI\u0026thinsp;=\u0026thinsp;1.97\u0026ndash;4.34; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for ACE/ARBs on discharge; statins before admission (OR\u0026thinsp;=\u0026thinsp;8.27; 95% CI\u0026thinsp;=\u0026thinsp;0.35\u0026ndash;15.71; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for statins on discharge. And for combination guideline prescription, ACEI/ARBs used before admission played a non-ignorable role in the medical part (OR\u0026thinsp;=\u0026thinsp;1.92; 95% CI\u0026thinsp;=\u0026thinsp;1.26\u0026ndash;2.92; P\u0026thinsp;=\u0026thinsp;0.003) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2.2 Six-month prescription\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the attributes of the disparate 6-month utilization of individual recommendation and composited treatment pattern and adherence in a multivariable model.\u003c/p\u003e\n\u003cp\u003ePredictors of losing prescription at 6-month were different for each drug. For aspirin, less in-hospital revascularization including PCI or CABG and not prescribed with aspirin on discharge were found to be independent predictors. For clopidogrel, the strongest predictors associated with lower continuous use were no history of revascularization, decreasing level of albumin, no index procedure of PCI or CABG, and without clopidogrel prescription on discharge. As for beta-blockers, current smoker, less heart rate beats, lower in-hospital laboratory level of albumin, and no prescription of beta-blockers contributed to inconstant use. In terms of ACEI/ARBs, independent predictors of withheld prescription were presence of AF, absence of CHF and hypertension, presentation with NSTEMI, and not prescribed ACEI/ARBs on discharge. Inconsistent use of statins was the result of no prescription on discharge. No revascularization before admission or during hospitalization and no statin therapy on discharge were considered to be two independent factors for low prescription rate of combined medication (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Impact of passive prescription\u003c/h2\u003e\n\u003cp\u003eAccording to Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the patients who received the prescription on discharge and did not get the same medication before admission (active prescription pattern) had the lower risk in 6-month and 1-year mortality compared with the patients who adhered to discharge guideline recommendation and already treated with the same therapy before admitted to hospital (passive prescription pattern). Specifically, for 6-month mortality post discharge, active prescription compared with passive prescription of aspirin (2.9% vs. 7.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), beta-blockers (2.3% vs. 6.8%, P\u0026thinsp;=\u0026thinsp;0.005), statins (2.4% vs.5.9%, P\u0026thinsp;=\u0026thinsp;0.014); for one-year mortality post discharge, active prescription comparing with passive prescription of aspirin (5.7% vs. 13.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), beta-blockers (5.6% vs. 12.9%, P\u0026thinsp;=\u0026thinsp;0.001), statins (4.6% vs.11.0%, P\u0026thinsp;=\u0026thinsp;0.001). Even after adjustment for age, gender, smoking status, cardiovascular disease histories, diabetes, hypertension, hyperlipidemia, and discharge diagnosis, active prescription still demonstrated survival benefit compared to passive prescription: for 6-month mortality, aspirin (OR\u0026thinsp;=\u0026thinsp;0.436, 95% CI\u0026thinsp;=\u0026thinsp;0.225\u0026ndash;0.845, P\u0026thinsp;=\u0026thinsp;0.014), beta-blockers (OR\u0026thinsp;=\u0026thinsp;0.374, 95% CI\u0026thinsp;=\u0026thinsp;0.163\u0026ndash;0.861, P\u0026thinsp;=\u0026thinsp;0.021); for 1-year mortality, aspirin (OR\u0026thinsp;=\u0026thinsp;0.538, 95% CI\u0026thinsp;=\u0026thinsp;0.326\u0026ndash;0.887, P\u0026thinsp;=\u0026thinsp;0.015), beta-blockers (OR\u0026thinsp;=\u0026thinsp;0.481, 95% CI\u0026thinsp;=\u0026thinsp;0.260\u0026ndash;0.892, P\u0026thinsp;=\u0026thinsp;0. 020), statins (OR\u0026thinsp;=\u0026thinsp;0.514, 95% CI\u0026thinsp;=\u0026thinsp;0.277\u0026ndash;0.956, P\u0026thinsp;=\u0026thinsp;0.036).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eImpact of passive prescription on 6-month \u0026amp;1-year mortality post discharge\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePrescription\u003c/p\u003e\n\u003cp\u003ePattern\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e6-month\u003c/p\u003e\n\u003cp\u003emortality\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eAdjusted\u003csup\u003e#\u003c/sup\u003e OR of 6-month\u003c/p\u003e\n\u003cp\u003emortality\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1-year\u003c/p\u003e\n\u003cp\u003emortality\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eAdjusted\u003csup\u003e#\u003c/sup\u003e OR of 1-year\u003c/p\u003e\n\u003cp\u003emortality\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNo.%\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNo.%\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAspirin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.9%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.436\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.225\u0026ndash;0.845\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.538\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.326\u0026ndash;0.887\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.5%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClopidogrel\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.730\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.547\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBeta-Blockers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.374\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.163\u0026ndash;0.861\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.481\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.260\u0026ndash;0.892\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.020\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.8%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.9%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eACEI/ ARBs\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.8%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.919\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.9%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.283\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e-------\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStatins\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eActive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.4%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.014\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.538\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.326\u0026ndash;0.887\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.6%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.514\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.277\u0026ndash;0.956\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePassive\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.9%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"15\"\u003eACEI/ARBs, angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blockers (ARB), odds ratio (OR)\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"15\"\u003e*All the data used in analyzing were after adjusted for age, gender, cardiovascular medical histories, diabetes, hypertension, hyperlipidemia, smoking status, discharge diagnosis.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn Kaplan\u0026ndash;Meier survival analysis, active prescription of aspirin had the better one year survival rate (Log-rank \u0026chi;2\u0026thinsp;=\u0026thinsp;17.8, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), active prescription of beta-blockers also gave significant benefit in one year survival rate (Log-rank \u0026chi;2\u0026thinsp;=\u0026thinsp;10.3, P\u0026thinsp;=\u0026thinsp;0.001), as well as the active use of statins (Log-rank \u0026chi;2\u0026thinsp;=\u0026thinsp;10.7, P\u0026thinsp;=\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). After adjustment with age, gender, smoking status, cardiovascular disease histories, diabetes, hypertension, hyperlipidemia and, discharge diagnosis, the hazard ratio (HR) of active prescription of aspirin was [HR\u0026thinsp;=\u0026thinsp;1.750, 95% CI\u0026thinsp;=\u0026thinsp;1.091\u0026ndash;2.805, P\u0026thinsp;=\u0026thinsp;0.020], of beta-blockers was [HR\u0026thinsp;=\u0026thinsp;1.955, 95% CI\u0026thinsp;=\u0026thinsp;1.099\u0026ndash;3.477, P\u0026thinsp;=\u0026thinsp;0.022], of statins was [HR\u0026thinsp;=\u0026thinsp;1.891, 95% CI\u0026thinsp;=\u0026thinsp;1.056\u0026ndash;3.388, P\u0026thinsp;=\u0026thinsp;0.032].\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":" \u003cp\u003eWith the increasing realization of the treatment gap, more attention has been paid to the possible reasons of withholding such important medications[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our study results are consistent with other publications, which have identified that elder group[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and traditional high-risk group with relevant medical histories and comorbidities were the significant negative predictors of physician adherence to the various performance measures after AMI[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, we have found a novel reason that in our regression model prior medication is a strong independent predictor for prescription of the same discharge drug so that patients who were taking some standard medication were less likely to receive any new additional medication on discharge. This pattern was persistent for all four medications (aspirin, beta-blockers, ACEI/ARBs and statins). And for 6-month prescription, the pattern was similar to the discharge prescription\u0026rsquo;s predictors. Six-month prescription was also highly dependent on the previous medications (discharge time point). However, those patients who are not on any therapy before admission, the pattern of active prescription, who tended to be younger and lower risk patients were treated more aggressively with PCI and secondary prevention on discharge and therefore had better outcomes.\u003c/p\u003e \u003cp\u003eAnother potential explanation for this phenomenon could be human behavior. The physician may have assumed that the doctor before him/her already had prescribed the right medications and no further dose titration was necessary, or it may be due to the lack of awareness of the guidelines and the importance of adequate dosage of preventive medications post discharge to reduce later mortality. Another plausible reason is that the patients on previous medication were generally older and sicker and perhaps the doctors were unwilling to use the standard recommended doses. Relevant to this was the interesting finding in our study that low albumin level is a strong predictor of withheld discharge prescription and non-continuous use of secondary prevention. This may relate worse general health condition and more comorbidities. Albumin is one of the hepatic proteins, and its plasma concentration is usually affected by several factors, like the rate of albumin synthesis, exogenous albumin loss, and dilution. Synthesis of albumin is highly influenced by nutritional intake, colloid oncotic pressure variations, and liver function[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Some papers published have indicated that albumin is a bio-marker of chronic illness, including heart failure, renal failure and so on[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Liu et al. found that Hypoalbuminemia is common in HF patients and is associated with increased risk of death[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Prenner et al. also found that serum albumin is associated with myocardial fibrosis, adverse pulsatile aortic hemodynamics, and prognosis in HF[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Hirata et al. pointed out low albumin is associated with high mortality[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These previous studies have linked low serum albumin to general ill health of patients and worse clinical outcomes. Based on that, it probably reflects the reason why treatment is not optimally used in these patients with Hypoalbuminemia. This may explain continuation of insufficient doses from admission to discharge and follow-up with passive prescription.\u003c/p\u003e \u003cp\u003eHowever, further studies of doctors\u0026rsquo; awareness of guidelines seem to be essential and urgent although this may have improved over the intervening years since our study. Another strategy to increase prescription rate and consequently improve the clinical outcome could be to set up a formal discharge checking system with the recommended discharge medications for all AMI patients before discharge. This reminder system could ensure that patients leave hospital on the most optimal medication for them. More importantly, given the incomplete physician adherence and the potential source we found from this study, relying on an informal educational system does not seem to be adequate.\u003c/p\u003e \u003cp\u003eIn addition, our results also showed that patients who had the lower mortality at 6-month and 1-year were the ones who had the greater likelihood to be in active prescription group. In particular, the active prescription of medications of aspirin, beta-blockers and statins could account for the statically significant survival benefit to AMI patients after recovery although it was clear that this group had better general health and were younger. Therefore, our findings indicated that substantial support and encouragement of prescription of secondary prevention medications with dose titration if necessary needs to be highlighted to maximize the survival benefit and minimize the mortality risk especially in those who are older and in poorer general condition.\u003c/p\u003e \u003cp\u003eOur results support the hypothesis that discharge on secondary preventive medications alone may not be enough but that the discharge dosage or subsequent dose titration may have an important impact on clinical outcomes and should be assessed to improve the quality of care for acute myocardial infarction patients.\u003c/p\u003e "},{"header":"5. Conclusions","content":" \u003cp\u003eDespite advances in cardiovascular care and the establishment of management guidelines, there remained gaps in the application of the best treatments and strategies for AMI patients in Hong Kong. Our findings, that previous medication influenced discharged medication and discharge prescription highly affected 6-month prescription, indicated a potential reason for non-adherence that physicians or patients prefer the continuation of prior medication rather than initiating new secondary preventive therapies and that in these patients treatment was sub-optimal. Better understanding and narrowing these gaps between guideline and practice will contribute to improving quality of care and clinical outcomes of AMI patients.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eAMI: Acute myocardial infarction; ACEI/ARBs: Angiotensin-converting enzyme inhibitor or angiotensin II receptor blockers; UA: Unstable angina; STEMI: ST-elevation myocardial infarction; NSTEMI: Non ST-elevation myocardial infarction; ACC: American College of Cardiology; AHA: American Heart Association; LVSD: Left ventricular systolic dysfunction; LVEF: Left ventricular ejection fraction; SD: Standard deviation; IQR: Interquartile range; OR: Odds ratio; HR: Hazard ratio; PCI: Percutaneous coronary intervention; CABG: Coronary artery bypass grafting; eGFR: Estimated glomerular filtration rate; HT: Hypertension; CHF: Congestive heart failure; DM: Diabetes mellitus;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors would like to acknowledge the Chinese University of Hong Kong and the patients who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: N.XR.H, B.P.Y, and CM.Y; Methodology: N.XR.H,J.E.S, and F.F; Statistical analysis: N.XR.H; Supervision: B.P.Y,YZ.X,JY.H; Writing - original draft: N.XR.H; Writing - review \u0026amp; editing: N.XR.H, J.E.S, F.F, and B.P.Y. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used and/or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the ethics committee of the joint Chinese University of Hong Kong-New Territories East Cluster and was performed in accordance with the Declaration of Helsinki and Good Clinical Practice. All subjects provided written informed consent to participate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no competing interests related to the submission of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization Cardiovascular disease: Fact sheet number 317 [\u003ca href=\"http://www.who.int/mediacentre/factsheets/fs317/en/index.html\"\u003ehttp://www.who.int/mediacentre/factsheets/fs317/en/index.html\u003c/a\u003e]\u003c/li\u003e\n\u003cli\u003eJiang He DG, Kristi Reynolds, Xiufang Duan,Chonghua Yao, Jialiang Wang, Chung-Shiuan Chen,Jing Chen, Rachel P. Wildman,\u0026nbsp; Michael J. Klag, and Paul K. 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failure and preserved ejection fraction. \u003cem\u003eEur J Heart Fail \u003c/em\u003e2012;14(1):39-44.\u003c/li\u003e\n\u003cli\u003ePrenner SB, Pillutla R, Yenigalla S, Gaddam S, Lee J, Obeid MJ, Ans AH, Jehangir Q, Kim J, Zamani P\u003cem\u003e et al\u003c/em\u003e: Serum Albumin Is a Marker of Myocardial Fibrosis, Adverse Pulsatile Aortic Hemodynamics, and Prognosis in Heart Failure With Preserved Ejection Fraction. \u003cem\u003eJ Am Heart Assoc \u003c/em\u003e2020;9(3):e014716.\u003c/li\u003e\n\u003cli\u003eHirata T, Arai Y, Yuasa S, Abe Y, Takayama M, Sasaki T, Kunitomi A, Inagaki H, Endo M, Morinaga J\u003cem\u003e et al\u003c/em\u003e: Associations of cardiovascular biomarkers and plasma albumin with exceptional survival to the highest ages. \u003cem\u003eNat Commun \u003c/em\u003e2020;11(1):3820.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Secondary Prevention, Acute Myocardial Infarction, Quality of Care","lastPublishedDoi":"10.21203/rs.3.rs-59605/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-59605/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Secondary prevention therapy reduces death and re-infarction after acute myocardial infarction (AMI) but is under-utilized in clinical practice. Mechanisms for this therapeutic gap are not well established. We aimed to evaluate the impact of passive continuation compared to active initiation of secondary prevention therapy for AMI patients during index hospitalization. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We analyzed 1083 consecutive patients with AMI to a tertiary referral hospital in Hong Kong and assessed discharge prescription rates of secondary prevention therapies (aspirin, clopidogrel, beta-blockers, statins, angiotensin-converting enzyme inhibitor or angiotensin II receptor blockers (ACEI/ARBs)). Multivariate analysis was used to identify independent predictors of discharge and 6-month medication, Kaplan-Meier survival curve was used to evaluate 12-month survival. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Overall prescription rates of aspirin, clopidogrel, beta-blockers, statins, ACEI/ARBs on discharge was 94.8%, 54.2%, 64.5%, 83.5% and 61.4%, respectively. Multivariate analysis showed that prior use of each therapy, except clopidogrel, was an independent predictor of prescription of the same therapy on discharge: aspirin [Odds ratio (OR) =4.8, 95% CI =1.9-12.3, P\u0026lt;0.01]; beta-blockers (OR=2.5, 95%CI =1.8-3.4, P\u0026lt;0.01); statins (OR=8.3, 95%CI =0.4-15.7, P\u0026lt;0.01) and ACEI/ARBs (OR=2.9, 95%CI =2.0-4.3, P\u0026lt;0.01). Passive continuation of prior medication was associated with higher 1-year mortality rates than active initiation in treatment naïve patient [aspirin (13.7% vs. 5.7%), beta-blockers (12.9% vs. 5.6%), statins (11.0% vs. 4.6%), all P\u0026lt;0.01].Active prescription was more common in lower risk patients (who were younger, with less co-morbidity, and with higher left ventricular ejection fraction) who were treated more aggressively with secondary prevention medication on discharge. Also patients who were not on a given medication before admission were less likely to be prescribed it on discharge.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Overall use of secondary prevention medication for AMI was suboptimal compared to guideline recommendations. Our findings suggested the practice of passive continuation of prior medication was prevalent and associated with adverse clinical outcomes compared to those who received secondary preventive medication for the first time during index hospitalization. Failure to start additional medication and possible inadequate dose titration in the passive continuation group may be in part the reason for the poorer clinical outcome in this group.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Passive Prescription of Secondary Prevention Medical Therapy During Index Hospitalization for Acute Myocardial Infarction is Prevalent and Associated with Adverse Clinical Outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-08-18 17:35:23","doi":"10.21203/rs.3.rs-59605/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2ed1c57d-191f-4edf-96fa-fdeb5273bb6a","owner":[],"postedDate":"August 18th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":314181,"name":"Cardiac \u0026 Cardiovascular Systems"},{"id":314182,"name":"Cardiothoracic Surgery"}],"tags":[],"updatedAt":"2021-07-22T19:57:07+00:00","versionOfRecord":{"articleIdentity":"rs-59605","link":"https://doi.org/10.1016/j.gheart.2014.03.1944","journal":{"identity":"global-heart","isVorOnly":true,"title":"Global Heart"},"publishedOn":"2014-03-01 19:57:07","publishedOnDateReadable":"March 1st, 2014"},"versionCreatedAt":"2020-08-18 17:35:23","video":"","vorDoi":"10.1016/j.gheart.2014.03.1944","vorDoiUrl":"https://doi.org/10.1016/j.gheart.2014.03.1944","workflowStages":[]},"version":"v1","identity":"rs-59605","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-59605","identity":"rs-59605","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}