A real-world study of clopidogrel therapy in patients with acute coronary syndrome undergoing percutaneous coronary intervention guided by individualized metabolic types

A real-world study of clopidogrel therapy in patients with acute coronary syndrome undergoing percutaneous coronary intervention guided by individualized metabolic types | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A real-world study of clopidogrel therapy in patients with acute coronary syndrome undergoing percutaneous coronary intervention guided by individualized metabolic types Zhilei Li, Yanpeng Li, Huan Dong, Haodong Cui, Dongmei He, Ziyuan Zhou, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4836948/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To explore the relationship between adopting the recommendation for clopidogrel use based on genotype guidance in Acute Coronary Syndrome (ACS) patients undergoing Percutaneous Coronary Intervention (PCI) and the incidence of later cardiovascular ischemic and bleeding events. Methods: A retrospective study was conducted on 3, 004 ACS patients treated with clopidogrel. Patients were grouped based on CYP2C19 genotype and followed for one year to record cardiovascular adverse and bleeding events. Results: Adopting the recommendation for clopidogrel use can reduce the risk of total ischemic events in the intermediate metabolic group (Odds Ratio [OR], 0.676; P = 0.041). In the poor metabolic group, the recommendations could reduce the risk of in-stent stenosis/thrombosis (OR, 0.150; P = 0.035), revascularization (OR, 0.252; P = 0.048), and total ischemic events (OR, 0.350; P = 0.006). Individualized guidance based on the CYP2C19 genotype did not increase bleeding outcomes. Conclusion: Individualized clopidogrel guidance based on genotype can reduce the ischemic risk in patients with intermediate and poor metabolizers, and the poor metabolic group benefits more. Individualized guidance did not increase bleeding outcomes in patients with intermediate or poor metabolizers. Clopidogrel CYP2C19 Genotype Metabolic Types Individualized medication Acute Coronary Syndrome Percutaneous Coronary Intervention Figures Figure 1 Figure 2 1. Introduction Acute Coronary Syndrome (ACS) is a cardiovascular disease that seriously threatens human health. Percutaneous Coronary Intervention (PCI) is one of the important methods of treatment [1] . Clopidogrel, a commonly used antiplatelet drug, plays a key role in preventing thrombosis and reducing the risk of cardiovascular events [2] . Clopidogrel is a prodrug that is mediated by P-glycoprotein during intestinal absorption. A portion of it is metabolized by the cytochrome CYP 450 enzyme system in the liver into an active metabolite, which selectively and irreversibly inhibits the adenosine diphosphate (ADP) receptor (P2Y12), thereby preventing platelet aggregation [3] . However, only about 15% of clopidogrel is converted into an active form in the liver, and the remaining 85% is hydrolyzed by esterase and loses its activity [4] . Clopidogrel is mainly used to treat patients with ACS and after PCI, and can reduce the mortality rate and other cardiovascular events in ACS patients without revascularization [5] . However, studies have found that after using clopidogrel, there are a variety of poor prognosis situations such as myocardial infarction, stent thrombosis, ischemic stroke, and revascularization [6] . The risk of poor prognosis situations varies among individuals, and the influencing factors mainly include race, age, genetic polymorphism, drug interactions, and patient compliance [7] . Among these, the genetic polymorphism of CYP2C19 plays a key role in the metabolism of clopidogrel [8] . Patients carrying the CYP2C192 and CYP2C193 genes have lower sensitivity to clopidogrel, and their antiplatelet effect is not as pronounced as that of wild-type gene patients, which may lead to the occurrence of cardiovascular clinical events [9] . In recent years, there have been continuous studies on the relationship between the CYP2C19 genotype and the efficacy of clopidogrel. Some studies have shown that the genetic polymorphism of CYP2C19 is related to clopidogrel resistance, which is a high-risk factor for adverse cardiovascular events [10, 11] . However, meta-analyses have also reported a lack of effect of CYP2C19 no-function alleles on adverse cardiovascular outcomes among patients receiving clopidogrel for non-PCI cardiovascular indications, possibly due to lower clinical benefit from treatment with clopidogrel in these patient populations [12] . In addition to the CYP2C19 gene, the polymorphisms of other genes such as ABCB1, CES1, CYP1A2, CYP2B6, CYP3A4, CYP3A5, and CYP2C9 , as well as drug interactions, patients' comorbidities, physiological conditions at different ages, living habits, and patient compliance, may also affect the efficacy of clopidogrel [13, 14] . Taken together, this study aims to explore the relationship between the adoption of clopidogrel medication recommendations based on genotype guidance in ACS patients undergoing PCI (especially in patients with intermediate metabolic genotypes) and the incidence of later cardiovascular ischemic and bleeding events, to provide a reference for clinical rational use of drugs. 2. Materials and Methods 2.1 General Information Table 1 Individualized advice based on the CYP2C19 genotype of clopidogrel Gene Phenotype Diplotypes Individualized advice CYP2C19 Normal metabolizer *1/*1 Use the standard dose of clopidogrel 75mg qd Intermediate metabolizer *1/*2 It is recommended to increase the platelet function test ADP (LTA method) to determine the efficacy. ≥ 30% use the standard dose of 75mg. < 30% It is recommended to increase the dosage of clopidogrel to 150mg/d or switch to other antiplatelet drugs such as ticagrelor. *1/*3 Poor metabolizer *2/*2 It is recommended to switch to ticagrelor In our retrospective study, the 3,004 patients diagnosed with ACS and treated with clopidogrel were selected and admitted to Guangdong Provincial People's Hospital (Guangzhou, China) from January 2016 to March 2024, using the following inclusion criteria diagnosed with coronary atherosclerotic heart disease (including ischemic cardiomyopathy, angina pectoris, and myocardial infarction) by coronary arteriography (coronary arteriography, CAG). The patients/subjects received the advice for clopidogrel medication proposed by clinical pharmacists based on the results of CYP2C19 genotyping. The advice for clopidogrel medication is shown in Table 1 . Normal metabolizers only had the effect of studying the differences between metabolic groups and were not grouped into the adopted group or the unadopted group, due to unchanged recommended standard dosage of clopidogrel and without other advice given. The exclusion criteria are listed below: 1. Patients who have contraindications to clopidogrel or do not take clopidogrel 2. Patients with incomplete medical records 3. Patients with a previous history of ischemic or hemorrhagic diseases, hematological diseases or bleeding diathesis, and platelet count > 450×10^9 or < 100×10^9 4. Patients with combined malignant diseases such as tumors 5. Patients with severe liver or kidney diseases, coagulation disorders, or anemia [hemoglobin (Hb) level < 100g/L] 6. Non-Han population 2.2 Methods 2.2.1 Data Collection The complete clinical data of the selected patients was reviewed through the hospital's electronic medical recording system: General conditions: gender, age, height, weight, and body mass index (BMI). Risk factors of ACS: hypertension, diabetes, hyperlipidemia, smoking, and drinking. Coronary intervention conditions: the number of stent implants. Laboratory test results: platelet count, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, and serum creatinine. Drug compliance score MORISKY score (Definition: MORISKY score ≥ 6, that is, good and moderate compliance, belongs to regular medication). 2.2.2 Grouping of Research Subjects According to the genotyping results of the CYP2C19 , patients were divided into the normal metabolism group and the abnormal metabolism group. The abnormal metabolism group was further divided into the intermediate metabolism group and the poor metabolism group. The grouping was mainly distinguished based on the different metabolic capabilities of CYP2C19 . Normal metabolizer type is with the genotype of CYP2C19*1/*1 . Intermediate metabolizer type is CYP2C19*1/*2 or CYP2C19*1/*3 . The poor metabolizer type is CYP2C19*2/*2, CYP2C19*2/*3 , or CYP2C19*3/*3 . 2.2.3 Clinical Follow-up A follow-up plan was formulated to obtain the data of the follow-up patients. The selected patients were followed up by rehospitalization or telephone calls to understand and record the occurrence of various cardiovascular adverse events and bleeding events within one year of taking clopidogrel. Cardiovascular adverse events include cardiogenic death, non-fatal myocardial infarction, unstable angina pectoris, in-stent stenosis or thrombosis, and subsequent revascularization. Bleeding events include mild to moderate bleeding events like gingival bleeding, subcutaneous ecchymosis, epistaxis, conjunctival hemorrhage, gross hematuria, and fatal major bleeding including intracranial hemorrhage, gastrointestinal bleeding, and so on. The definitions of cardiovascular adverse events are as follows: Cardiogenic death: Any definite death due to cardiovascular causes or death that is not attributed to non-cardiovascular causes. Non-fatal myocardial infarction: New ischemic symptoms occur, the ST segment of the electrocardiogram is significantly depressed or elevated, and troponin is significantly increased. Unstable angina pectoris: It occurs at rest and lasts for more than 20 minutes, or the degree of angina pectoris is more severe, lasts longer, or is more frequent than before, and is confirmed by myocardial enzymes or electrocardiogram. 2.2.4 Statistical Methods Data processing was performed using SPSS 27.0 statistical software. Measurement data that obeyed a normal distribution or approximately normal distribution were expressed as the mean ± standard deviation (x ± s). The t-test was used for the comparison of means between two groups, and one-way analysis of variance (ANOVA) was used for the comparison of means among multiple groups. Measurement data that did not follow a normal distribution were expressed as the median (interquartile range), and non-parametric tests were used for comparison between groups. Count data were expressed as frequency/ percentage, and the chi-square test was used for comparison between groups. p < 0.05 indicated a statistically significant difference. 3. Results 3.1. Baseline Characteristics The follow-up of 1,943 patients was completed. Among them, 1,161 cases (59.75%) were with hypertension, 634 cases (32.63%) were with diabetes, 319 cases (16.42%) were with hyperlipidemia, 635 cases (32.68%) were with a smoking history, 363 cases (18.68%) were with a drinking history, and 1,858 cases (95.63%) were regular medication users. There was no statistically significant difference between the baseline characteristics of normal metabolism, intermediate metabolism, and poor metabolism groups, respectively ( Table 2 ). There was also no statistically significant difference, between the baseline characteristics of the abnormal metabolism adopted group and the abnormal metabolism unadopted group ( Table 3 ). Table 2 The Baseline Characteristics of Metabolic Group Item/Group Normal metabolic Intermediate metabolic Poor metabolic p-value Age 63.39±10.83 63.63 ± 10.57 63.12 ± 10.87 0.060 BMI 24.18±5.65 24.13 ± 6.57 24.26 ± 7.38 0.848 Biochemical indicators PLT (×10^9/L) 226.29±59.20 225.68 ± 59.58 226.53 ± 60.29 0.322 ALT (U/L) 28.97±24.42 28.67 ± 22.93 29.15 ± 22.98 0.868 AST (U/L) 34.02±36.63 33.48 ± 34.04 33.54 ± 34.05 0.081 BUN 6.51±5.30 6.58 ± 5.81 6.43 ± 6.25 0.733 CREA 93.78±54.99 94.29 ± 55.60 94.94 ± 60.70 0.343 Interventional situation Average number of implanted stents 2.07±1.62 2.02 ± 1.55 2.03 ± 1.58 0.400 Gender (Male n (%) ) 575 (78.12) 741 (79.33) 210 (76.92) 0.654 Gender (Female n (%) ) 161 (21.88) 193 (20.67) 63 (23.08) Previous history Hypertension n (%) 440 (59.78) 554 (59.31) 167 (61.17) 0.859 Diabetes n (%) 244 (33.15) 304 (32.55) 86 (31.54) 0.882 Hyperlipidemia n (%) 129 (17.53) 146 (15.63) 44 (16.12) 0.577 Smoking history n (%) 246 (33.42) 297 (31.80) 92 (33.70) 0.725 Drinking history n (%) 126 (17.12) 184 (19.70) 53 (19.41) 0.384 Medication compliance: Regular medication n (%) 703 (95.52) 892 (95.50) 263 (96.34) 0.825 Table 3 The Baseline Characteristics of the Abnormal Metabolic Groups Item/ group Adopted Unadopted p-value Intermediate Metabolic a (n=196) Poor Metabolic b (n=31) Intermediate Metabolic c (n=738) Poor Metabolic d (n=242) Age 62.97±11.05 63.80±10.49 63.80±10.44 63.03±10.92 0.348 BMI 23.89±4.80 23.96±5.22 24.20±6.96 24.30±7.61 0.239 Biochemical indicators PLT (×10^9/L) 225.32±57.44 226.44±57.48 225.78±60.13 226.54±60.63 0.291 ALT (U/L) 28.80±26.19 29.58±27.46 28.64±21.99 29.10±22.36 0.216 AST (U/L) 33.99±38.77 34.20±40.43 33.34±32.68 33.45±33.17 0.751 BUN 6.65±4.34 6.47±4.34 6.56±6.14 6.43±6.45 0.178 CREA 94.97±56.48 96.09±63.46 94.11±55.36 94.79±60.35 0.089 Interventional situation Average number of implanted stents 1.99±1.54 1.99±1.58 2.03±1.55 2.03±1.58 0.693 p-value (a+c/ b+d) p-value (a+b/ c+d) Gender (Male n (%) ) 155 (79.08) 23 (74.91) 586 (79.40) 187 (77.27) 0.391 0.878 Gender (Female n (%) ) 41 (20.92) 8 (25.81) 152 (20.60) 55 (22.73) Previous history Hypertension n (%) 117 (59.69) 20 (64.52) 437 (59.21) 147 (60.74) 0.582 0.975 Diabetes n (%) 64 (32.65) 10 (32.26) 240 (32.52) 76 (31.40) 0.745 0.999 Hyperlipidemia n (%) 29 (14.80) 5 (16.13) 117 (15.85) 39 (16.12) 0.846 0.680 Smoking history n (%) 61 (31.12) 11 (35.48) 236 (31.98) 81 (33.47) 0.554 0.777 Drinking history n (%) 39 (19.90) 6 (19.35) 145 (19.65) 47 (19.42) 0.917 0.995 Medication compliance Regular medication n (%) 187 (95.41) 31 (100%) 705 (95.53) 231 (95.45) 0.551 0.961 BMI: Body Mass Index; PLT: Platelet Count; ALT: Alanine Aminotransferase; AST: Aspartate Aminotransferase; BUN: Blood Urea Nitrogen; CREA: Serum Creatinine. 3.2. Loss to Follow-up Situation Figure 2 Loss to follow-up situation of the metabolic groups. As shown in Figure 1 and Figure 2 , the number of loss to follow-up cases in the normal metabolic group was 247 (53.70%), 164 (35.65%) in the intermediate metabolic group, and 49 (10.65%) in the poor metabolic group. Among 2,403 selected patients, 460 patients were not included in the analysis due to reasons such as changing contact information and refusing to follow up, but 1,943 patients were enrolled. There was a significant difference in the total loss to follow-up situation among patients in three metabolic groups (P < 0.001). We further conducted a comparison between the two metabolic groups and found that there were statistically significant differences mainly between the normal metabolic group and the intermediate metabolic group/poor metabolic group (P < 0.001/P < 0.001). While there was no loss to follow-up difference between the intermediate metabolic group and the poor metabolic group (P = 0.901) in Table 4 . It can explained that the recommendations of the normal metabolic group did not change the dosage or type of clopidogrel taken by the patients. Therefore, the emphasis of patients from the normal metabolic group on the content of the study and follow-up was different from that of the intermediate and poor metabolic groups. Table 4 Comparison of Loss to Follow-up Cases between Metabolic Groups Metabolic Groups Comparison p-value Normal Metabolic Intermediate Metabolic ＜0.001 Normal Metabolic Poor Metabolic ＜0.001 Intermediate Metabolic Poor Metabolic 0.901 3.3. Distribution of CYP2C19 Genotypes and Adoption of Clopidogrel Medication Recommendations The distribution ratios of different detected CYP2C19 genotypes in ACS patients are different, which is shown in Table 5 . Normal metabolizer type (*1/*1) accounts for 37.88% of the total number of cases included. Intermediate metabolizer type (*1/*2 and *1/*3) is detected more frequently, totaling 48.07%, among which *1/*2 is the main intermediate metabolizer type. While the Poor metabolizer type (*2/*2, *2/*3, and *3/*3) is 14.05% in total. Table 5 The D istribution of CYP2C19 Metabolic T ypes Metabolic type Normal metabolizer Intermediate metabolizer Poor metabolizer Genotype *1/*1 *1/*2 *1/*3 *2/*2 *2/*3 *3/*3 Number of genotype cases 736 804 130 193 72 8 Proportion of genotype 37.88% 41.38% 6.69% 9.93% 3.71% 0.41% Number of cases (adopted + unadopted) / 174+630 22+108 20+173 11+61 0+8 Adoption proportion / 21.64% 16.92% 10.36% 15.28% 0.00% Total number of cases (n) 736 934 273 Adopted cases (n％) / 196 (20.99) 31 (11.36) Unadopted cases (n％) / 738 (79.01) 242 (88.64) It shows the adoption of clopidogrel medication recommendations based on CYP2C19 genotypes for enrolled patients ( Table 5 ). For patients with the intermediate metabolic type, 20.99% adopted the medication recommendations, indicating that some doctors and patients are aware that the intermediate metabolic rate may affect the drug efficacy and thus made adjustments. However, 79.01% of the patients did not adopt the recommendations, possibly due to insufficient awareness of the impact of drug metabolism by physicians or patients, or their belief that the standard treatment plan is still effective. Among Poor metabolizer-type patients, only 11.52% adopted the medication recommendations, and 88.64% did not adopt them. Since Poor metabolizer-type patients have a slower rate of metabolizing the drug and need to choose ticagrelor, the proportion of not adopting the recommendations is relatively high. This indicates that in clinical practice, both doctors and patients are still insufficiently aware of the influence of genotypes on drug metabolism. It is challenging for them to accept the recommendation to change the drug treatment plan. Some physicians also reported concerns that ticagrelor may relatively increase the risk of bleeding and it is difficult to balance the risk of ischemia and bleeding, so they did not accept the recommendation. In conclusion, our data pointed out that the attention to the impact of CYP2C19 genotypes on clopidogrel metabolism and the actual adoption of medication adjustments still need to be improved in clinical practice. Future work should strengthen the publicity and education on the impact of Intermediate metabolizer type and Poor metabolizer type genotypes on drug efficacy, and promote the implementation of individualized medication plans guided by genotypes. 3.4. Relationship between Clopidogrel Metabolic Types- Adoption of Medication Recommendations and Incidence of Ischemic Events Table 6 The Occurrence of Ischemic Events Ischemic events/Group Normal Metabolic Intermediate Metabolic Poor Metabolic Total number of cases p-value Unstable angina pectoris 32 (4.35) 48 (5.14) 33 (12.09) 113 (5.82) 0.405 Non-fatal myocardial infarction 11 (1.49) 18 (1.93) 13 (4.76) 42 (2.16) 0.902 Cardiogenic and vascular death 6 (0.82) 9 (0.96) 6 (2.20) 21 (1.08) 0.843 In-stent stenosis/thrombosis 32 (4.35) 67 (7.17) 45 (16.48) 144 (7.41) 0.908 Revascularization 30 (4.08) 72 (7.71) 54 (19.78) 156 (8.03) 0.389 Total ischemic events 111 (15.08) 214 (22.91) 151 (55.31) 476 (24.50) ＜0.001 In this study, we analyzed the data of different types of ischemic events in ACS patients with different CYP2C19 metabolic genotypes undergoing PCI, including unstable angina pectoris, nonfatal myocardial infarction, cardiogenic and vascular death, in-stent stenosis/thrombosis, and revascularization cases. We analyzed the occurrence of ischemic events in patients of the metabolic groups. It showed no significance was found in the occurrence of ischemic events among different metabolic groups, but there was a statistically significant difference in the total ischemic events (p < 0.001), and the incidence of each event increased as the metabolism slowed ( Table 6 ). Based on whether the medication recommendations were adopted or not, we conducted the intermediate metabolic group, the adoption of recommendations, and the occurrence of unstable angina pectoris, nonfatal myocardial infarction, cardiogenic and vascular death, in-stent stenosis/thrombosis, and revascularization, p > 0.05, with no statistically significant difference. However, there was a statistically significant difference in the total ischemic events, p = 0.041. Therefore, the results suggest that whether the recommendations are Adopted or not in the intermediate metabolic group may indicate that it does not affect the occurrence of specific ischemic events in the statistics but will increase the occurrence of total ischemic events. Adopting the recommendations can reduce the risk of total ischemic events by approximately 32.6% (Table 7). Table 7 The Comparison of Ischemic Events in the Intermediate Metabolic Group Group Occurrence of events No occurrence of events p-value Odds ratio (OR) Adopted situation Adopted Unadopted Adopted Unadopted Unstable angina pectoris 10 38 186 700 0.979 0.990 Non-fatal myocardial infarction 3 15 193 723 0.650 0.749 Cardiogenic and vascular death 1 8 195 730 0.465 0.468 In-stent stenosis/thrombosis 9 58 187 680 0.115 0.564 Revascularization 10 62 186 676 0.124 0.586 Total ischemic events 33 181 947 3509 0.041 0.676 Table 8 The Comparison of Ischemic Events in the Poor Metabolic Group Group Occurrence of events No occurrence of events p-value Odds ratio (OR) Adopted situation Adopted Unadopted Adopted Unadopted Unstable angina pectoris 2 31 29 211 0.307 0.469 Non-fatal myocardial infarction 1 12 30 230 0.647 0.639 Cardiogenic and vascular death 1 5 30 237 0.678 1.580 In-stent stenosis/thrombosis 1 44 30 198 0.035 0.150 Revascularization 2 52 29 190 0.048 0.252 Total ischemic events 7 144 148 1066 0.006 0.350 For the poor metabolic group, the adoption of recommendations and the occurrence of unstable angina pectoris, non-fatal myocardial infarction, and cardiogenic and vascular death, p > 0.05, showing no statistically significant difference. However, it significantly affects in-stent stenosis/thrombosis (p= 0.035), revascularization (p= 0.048), and total ischemic events (p= 0.006). Therefore, the recommendations that are unadopted in the poor metabolic group may suggest an increased situation of in-stent stenosis/thrombosis and revascularization in ACS patients undergoing PCI, and not adopting the relevant opinions may increase the result of total ischemic events. Adopting the recommendations can reduce the risk of in-stent stenosis, thrombosis, revascularization, and total ischemic events by approximately 85.0%, 74.8%, and 65.0%, respectively (Table 8). 3.5. Relationship between the Adoption of Clopidogrel Metabolic Types- Medication Recommendations and the Incidence of Bleeding Events Here we show the relationship between the adoption or unadoption of clopidogrel medication recommendations and the incidence of bleeding events (mild to moderate bleeding and fatal major bleeding) in patients of different CYP2C19 metabolic types (normal metabolic groups, intermediate metabolic groups, and poor metabolic Group) (Table 9). We include the number of cases of bleeding events in each group, the p-value, the total number of bleeding cases, and the odds ratio (OR) value. normal metabolic group: There were 43 cases of mild to moderate bleeding and 17 cases of fatal major bleeding. Table 9 The Relationship between CYP2C19 Metabolic Types and Bleeding Events Metabolic group Normal metabolic Abnormal metabolic Total Intermediate metabolic Intermediate metabolic Poor metabolic Poor metabolic Adopted situation Adopted Unadopted Adopted Unadopted Mild to moderate bleeding 43 78 10 48 2 18 Fatal major bleeding 17 22 1 13 1 7 p-value 0.366 0.346 0.847 Total number of bleeding cases 11 61 3 25 Number of non-bleeding cases 185 611 28 217 p-value 0.122 0.910 Total number of bleeding cases odds ratio (OR) 0.60 0.93 In the intermediate metabolic group, among the adopted patients, there were 10 cases of mild to moderate bleeding and 1 case of fatal major bleeding, while among the unadopted patients, there were 48 cases and 7 cases, respectively. The results of the chi-square test showed that the p-value for mild to moderate bleeding and fatal major bleeding caused by adoption or not is 0.346, and there is no statistically significant difference in their occurrence (p > 0.05). The total number of bleeding and non-bleeding events in adopted and unadopted patients of the intermediate metabolic group indicates that the adoption of recommendations does not lead to the occurrence of bleeding events, with no statistically significant difference (p > 0.05). The odds ratio (OR) of the total number of bleeding cases is 0.60, suggesting that the adoption of medication recommendations in the intermediate metabolic group may slightly reduce the risk of bleeding, but it does not reach statistical significance. In the poor metabolic group, there were 2 cases of mild to moderate bleeding, while among the unadopted patients, there were 18 cases of mild to moderate bleeding and 5 cases of fatal major bleeding. The p-value for mild to moderate bleeding and fatal major bleeding with or without adoption is 0.847, indicating no statistically significant difference in their occurrence (p > 0.05). The total number of bleeding and non-bleeding events in the adopted and unadopted groups of the poor metabolic group indicates that adoption does not lead to the occurrence of bleeding events, with no statistically significant difference (p > 0.05). The odds ratio (OR) of the total number of bleeding cases is 0.93, suggesting that the adoption of medication recommendations in the poor metabolic group may slightly reduce the risk of bleeding, but it does not reach statistical significance. According to the results of bleeding events, it can be concluded that individualized guidance based on the CYP2C19 genotype for clopidogrel does not increase bleeding outcomes in patients with intermediate or poor metabolizers. 4. Discussion 4.1. Disadvantages of this study This study is a single-center sample with a small number of follow-up visits, which may make it difficult to predict the overall situation. The loss to follow-up rate is high, and the analysis results may be biased. The individualized use of clopidogrel is mainly recommended for ACS patients undergoing PCI. However, a small number of patients who planned to undergo PCI canceled the procedure for some reasons, which may have a certain impact on the results. The situation of patients taking other drugs in combination is not clear, and drug interactions may have a certain impact on the results. 4.2. Analysis of the research results Through the statistical analysis of ACS patients with different CYP2C19 metabolic genotypes, it is found that there is no difference in the occurrence of ischemic events among different metabolic groups, but there is a statistically significant difference in the total ischemic events, and the incidence of each event increases as the metabolism slows down. For the intermediate metabolic group, whether the recommendation is adopted or not has no statistically significant impact on the occurrence of specific ischemic events, but it will increase the occurrence of total ischemic events. Adopting the recommendation can reduce the risk of total ischemic events by approximately 32.6%. For the poor metabolic group, whether the recommendation is adopted or not has no statistically significant impact on the occurrence of unstable angina pectoris, non-fatal myocardial infarction, and cardiogenic and vascular death, but it has an impact on in-stent stenosis/thrombosis, revascularization, and total ischemic events, with statistically significant differences. Adopting the recommendation can reduce the risk of in-stent stenosis/thrombosis, revascularization, and total ischemic events by approximately 85.0%, 74.8%, and 65.0%, respectively. Based on the results of bleeding events, it can be concluded that the individualized guidance suggestions based on the CYP2C19 genotype of clopidogrel do not increase the bleeding outcomes in patients with intermediate metabolizers or poor metabolizers. 4.3. Implications for clinical practice These data reflect that in clinical practice, the attention to the impact of CYP2C19 genotypes on clopidogrel metabolism and the actual adoption of medication adjustments still need to be improved. Future work should strengthen the publicity and education on the impact of intermediate metabolizer type and poor metabolizer type genotypes on drug efficacy and promote the implementation of individualized medication plans guided by genotypes. In conclusion, this study guides the clinical rational use of drugs, but further expansion of the sample size and improvement of the research design still need to evaluate more accurately the role of genotype-guided clopidogrel antiplatelet therapy in ACS patients undergoing PCI. 5. Conclusions This real-world study investigated the relationship between the adoption of clopidogrel medication recommendations based on genotype guidance in ACS patients undergoing PCI and the incidence of later cardiovascular ischemic and bleeding events. The main findings are as follows: In the intermediate metabolic group, adopting the clopidogrel medication recommendation can reduce the risk of total ischemic events by approximately 32.6%. In the poor metabolic group, adopting the recommendation can reduce the risk of in-stent stenosis/thrombosis, revascularization, and total ischemic events by approximately 85.0%, 74.8%, and 65.0%, respectively. Individualized guidance based on the CYP2C19 genotype for clopidogrel did not increase bleeding outcomes in patients with intermediate or poor metabolizers. This study highlights the importance of considering CYP2C19 genotypes in clopidogrel therapy. However, it also has several limitations, including being a single-center sample with a small number of follow-up visits, a high loss to follow-up rate, and uncertainties regarding patients taking other drugs. Future work should expand the sample size, improve the research design, and strengthen publicity and education on the impact of genotype-guided individualized medication plans to better evaluate the role of genotype-guided clopidogrel antiplatelet therapy in ACS patients undergoing PCI. Declarations Author Contributions Yanpeng Li and Zhilei Li are co-first authors and contributed equally to this work. All authors contributed to the study's conception and design. Clinical data review was primarily performed by Zhilei Li, Haodong Cui, and Huan Dong, with additional contributions from Zhilei Li, Dongmei He, and Ziyuan Zhou. Data processing and statistical analysis were mainly conducted by Zhilei Li and Yanpeng Li. The first draft of the manuscript was written by Zhilei Li and Yanpeng Li, and subsequent editing and proofreading of the article manuscript were carried out by Yanpeng Li, Xiujuan Yang, and Xiaojuan Zhang. All authors provided valuable comments on previous versions of the manuscript, and all read and approved the final manuscript. Funding This paper is funded by the outstanding young fund project for district-university cooperation in major projects of the health system in Nanshan district, Shenzhen (NSZD2023062)and the National Natural Science Foundation of China (No.82073805). Data Availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Code Availability Not applicable. Ethics approval This study was approved by the Ethics Committee of Guangdong Provincial People's Hospital. The ethics approval number is KY2024-5 14-01. The study was conducted by the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Consent for participate This study was exempted from the informed consent process as approved by the Ethics Committee of Guangdong Provincial People's Hospital. The research has de-identified information of identifiable individuals, removing personal and private information such as names, addresses, and occupations. This has no impact on the research content. Consent for Publication The authors affirm that human research participants provided informed consent for the publication of the images in Figure 1-2, Table1-9, These contents are only used for scientific research and statistics and do not involve the personal privacy of the participating patients. Conflicts of Interest The authors have no relevant financial or non-financial interests to disclose. References Cavallari LH, Lee CR, Beitelshees AL, Cooper-DeHoff RM, Duarte JD, Voora D, et al. Multisite Investigation of Outcomes With Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention. JACC Cardiovasc Interv. 2018 Jan 22;11 (2):181-191. doi: 10.1016/j.jcin.2017.07.022. Epub 2017 Nov 1. PMID: 29102571; PMCID: PMC5775044. Scott SA, Sangkuhl K, Stein CM, Hulot JS, Mega JL, Roden DM, et al. Clinical Pharmacogenetics Implementation Consortium. Clinical Pharmacogenetics Implementation Consortium guidelines for CYP2C19 genotype and clopidogrel therapy: 2013 update. Clin Pharmacol Ther. 2013 Sep;94 (3):317-23. doi: 10.1038/clpt.2013.105. Epub 2013 May 22. PMID: 23698643; PMCID: PMC3748366. Kazui M, Nishiya Y, Ishizuka T, Hagihara K, Farid NA, Okazaki O, et al. Identification of the human cytochrome P450 enzymes involved in the two oxidative steps in the bioactivation of clopidogrel to its pharmacologically active metabolite. Drug Metab Dispos. 2010 Jan;38 (1):92-9. doi: 10.1124/dmd.109.029132. PMID: 19812348. Shuldiner AR, O'Connell JR, Bliden KP, Gandhi A, Ryan K, Horenstein RB, et al. Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA. 2009 Aug 26;302 (8):849-57. doi: 10.1001/jama.2009.1232. PMID: 19706858; PMCID: PMC3641569. Pereira NL, Farkouh ME, So D, Lennon R, Geller N, Mathew V, et al. Effect of Genotype-Guided Oral P2Y12 Inhibitor Selection vs Conventional Clopidogrel Therapy on Ischemic Outcomes After Percutaneous Coronary Intervention: The TAILOR-PCI Randomized Clinical Trial. JAMA. 2020 Aug 25;324 (8):761-771. doi: 10.1001/jama.2020.12443. PMID: 32840598; PMCID: PMC7448831. Mega JL, Simon T, Collet JP, Anderson JL, Antman EM, Bliden K, et al. Reduced-function CYP2C19 genotype and risk of adverse clinical outcomes among patients treated with clopidogrel predominantly for PCI: a meta-analysis. JAMA. 2010 Oct 27;304 (16):1821-30. doi: 10.1001/jama.2010.1543. PMID: 20978260; PMCID: PMC3048820. Verma SS, Bergmeijer TO, Gong L, Reny JL, Lewis JP, Mitchell BD, Alexopoulos D, et al. Genomewide Association Study of Platelet Reactivity and Cardiovascular Response in Patients Treated With Clopidogrel: A Study by the International Clopidogrel Pharmacogenomics Consortium. Clin Pharmacol Ther. 2020 Nov;108 (5):1067-1077. doi: 10.1002/cpt.1911. Epub 2020 Jul 9. PMID: 32472697; PMCID: PMC7689744. Sibbing D, Gebhard D, Koch W, Braun S, Stegherr J, Morath T, et al. Isolated and interactive impact of common CYP2C19 genetic variants on the antiplatelet effect of chronic clopidogrel therapy. J Thromb Haemost. 2010 Aug;8 (8):1685-93. doi: 10.1111/j.1538-7836.2010.03921.x. Epub 2010 May 21. PMID: 20492469. Sibbing D, Koch W, Gebhard D, Schuster T, Braun S, Stegherr J, et al. Cytochrome 2C19*17 allelic variant, platelet aggregation, bleeding events, and stent thrombosis in clopidogrel-treated patients with coronary stent placement. Circulation. 2010 Feb 2;121 (4):512-8. doi: 10.1161/CIRCULATIONAHA.109.885194. Epub 2010 Jan 18. PMID: 20083681. Pan Y, Chen W, Xu Y, Yi X, Han Y, Yang Q, et al. Genetic Polymorphisms and Clopidogrel Efficacy for Acute Ischemic Stroke or Transient Ischemic Attack: A Systematic Review and Meta-Analysis. Circulation. 2017 Jan 3;135 (1):21-33. doi: 10.1161/CIRCULATIONAHA.116.024913. Epub 2016 Nov 2. PMID: 27806998. Collet JP, Thiele H, Barbato E, Barthélémy O, Bauersachs J, Bhatt DL, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021 Apr 7;42 (14):1289-1367. doi: 10.1093/eurheartj/ehaa575. PMID: 32860058. Sorich MJ, Rowland A, McKinnon RA, Wiese MD. CYP2C19 genotype has a greater effect on adverse cardiovascular outcomes following percutaneous coronary intervention and in Asian populations treated with clopidogrel: a meta-analysis. Circ Cardiovasc Genet. 2014 Dec;7 (6):895-902. doi: 10.1161/CIRCGENETICS.114.000669. Epub 2014 Sep 25. PMID: 25258374. Botton MR, Whirl-Carrillo M, Del Tredici AL, Sangkuhl K, Cavallari LH, Agúndez JAG, et al. PharmVar GeneFocus: CYP2C19. Clin Pharmacol Ther. 2021 Feb;109 (2):352-366. doi: 10.1002/cpt.1973. Epub 2020 Jul 22. PMID: 32602114; PMCID: PMC7769975. Angiolillo DJ, Capodanno D, Danchin N, Simon T, Bergmeijer TO, Ten Berg JM, et al. Derivation, Validation, and Prognostic Utility of a Prediction Rule for Nonresponse to Clopidogrel: The ABCD-GENE Score. JACC Cardiovasc Interv. 2020 Mar 9;13 (5):606-617. doi: 10.1016/j.jcin.2020.01.226. PMID: 32139218. 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Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIie3QwUqEQBjA8W8RxsuQ11lc6hW+GPBU7qsogl0khCA8dBAWvHrtPXqARgS7CF097hbsWfDSYak+LahgDLp1mD8ygzP8BkcAk+kfdmQBgyAF7nwuBCDGCWlrhrCJIPBlTm/qiyCtz5DpoTNR/SDwC7Ht/XaLZyv52Mqhz/xLcDf1kKaHEwbW7qnTftgFBhhzr0s8odroClZN7N4inhbApEy0pBEB1kS4B1WhwnuyFkdcFMCZqyWLgsgbl2Ur++pVhblI5EBkPU8sRkRxhARFlU8EXSLhPGEjibjo4mvRNhGReLyLjApLfxfHedgvXzJ/7ZT1XZ/d+EQi+mOH4/PS3uyeNUSf9W38EzGZTCbTR++USVeT8P6ibAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-3439-0986","institution":"Southern University of Science and Technology Hospital","correspondingAuthor":true,"prefix":"","firstName":"Zhilei","middleName":"","lastName":"Li","suffix":""},{"id":342888044,"identity":"46a0944e-2c00-4130-9ecd-29e1beb97172","order_by":1,"name":"Yanpeng Li","email":"","orcid":"","institution":"Shenzhen University Medical School, Shenzhen University","correspondingAuthor":false,"prefix":"","firstName":"Yanpeng","middleName":"","lastName":"Li","suffix":""},{"id":342888045,"identity":"63a3af58-5635-4ef8-b7b7-25c896772db9","order_by":2,"name":"Huan Dong","email":"","orcid":"","institution":"Inner Mongolia Medical College Affiliated Hospital: The Affiliated Hospital of Inner Mongolia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Dong","suffix":""},{"id":342888046,"identity":"25168877-e161-4d1b-b9cb-c1bb9a917f17","order_by":3,"name":"Haodong Cui","email":"","orcid":"","institution":"China-Japan Union Hospital of Jilin University Department of Gastrointestinal and Colorectal Surgery","correspondingAuthor":false,"prefix":"","firstName":"Haodong","middleName":"","lastName":"Cui","suffix":""},{"id":342888047,"identity":"1130497d-f5ad-4c0a-a258-7627aff93a05","order_by":4,"name":"Dongmei He","email":"","orcid":"","institution":"The Fifth Affiliated Hospital of Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dongmei","middleName":"","lastName":"He","suffix":""},{"id":342888048,"identity":"437370c0-75c2-4688-ae89-7b00bfde0b40","order_by":5,"name":"Ziyuan Zhou","email":"","orcid":"","institution":"zhongguo yixue kexueyuan zhongliu yiyuan shenzhen yiyuan: Cancer Hospital Chinese Academy of Medical Sciences Shenzhen Center","correspondingAuthor":false,"prefix":"","firstName":"Ziyuan","middleName":"","lastName":"Zhou","suffix":""},{"id":342888049,"identity":"da30161f-9782-4771-9d70-482ef1d0c20e","order_by":6,"name":"Xiujuan Yang","email":"","orcid":"","institution":"Zhujiang Hospital: Zhujiang Hospital of Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiujuan","middleName":"","lastName":"Yang","suffix":""},{"id":342888050,"identity":"bb0f96c0-ec01-441d-b085-c2cc7d172e93","order_by":7,"name":"Xiaojuan Zhang","email":"","orcid":"https://orcid.org/0000-0002-3985-4738","institution":"Guangdong Provincial People's Hospital Affiliated to Southern Medical University: Guangdong Provincial People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaojuan","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-07-31 16:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4836948/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4836948/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66629985,"identity":"a1494f5b-3c7b-4351-817a-dc5ecda1f403","added_by":"auto","created_at":"2024-10-15 04:43:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":86966,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInclusion and Exclusion Criteria.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4836948/v1/0b4b8e43897f286d55e7906a.png"},{"id":66629983,"identity":"30ded4d6-f672-4f2e-b8b3-bd1a86d9f5eb","added_by":"auto","created_at":"2024-10-15 04:43:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15474,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLoss to follow-up situation of the metabolic groups.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4836948/v1/b2c9639c6cf63007624534d2.png"},{"id":66632482,"identity":"73c37575-0651-4472-b75e-f5170bae2397","added_by":"auto","created_at":"2024-10-15 04:59:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1094086,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4836948/v1/71ef7cdd-9a79-42ed-8454-5f336749e721.pdf"}],"financialInterests":"","formattedTitle":"A real-world study of clopidogrel therapy in patients with acute coronary syndrome undergoing percutaneous coronary intervention guided by individualized metabolic types","fulltext":[{"header":"1.\tIntroduction","content":"\u003cp\u003eAcute Coronary Syndrome (ACS) is a cardiovascular disease that seriously threatens human health. Percutaneous Coronary Intervention (PCI) is one of the important methods of treatment\u003csup\u003e\u0026nbsp;[1]\u003c/sup\u003e. Clopidogrel, a commonly used antiplatelet drug, plays a key role in preventing thrombosis and reducing the risk of cardiovascular events\u003csup\u003e\u0026nbsp;[2]\u003c/sup\u003e. Clopidogrel is a prodrug that is mediated by P-glycoprotein during intestinal absorption. A portion of it is metabolized by the cytochrome CYP 450 enzyme system in the liver into an active metabolite, which selectively and irreversibly inhibits the adenosine diphosphate (ADP) receptor (P2Y12), thereby preventing platelet aggregation \u003csup\u003e[3]\u003c/sup\u003e. However, only about 15% of clopidogrel is converted into an active form in the liver, and the remaining 85% is hydrolyzed by esterase and loses its activity \u003csup\u003e[4]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eClopidogrel is mainly used to treat patients with ACS and after PCI, and can reduce the mortality rate and other cardiovascular events in ACS patients without revascularization \u003csup\u003e[5]\u003c/sup\u003e. However, studies have found that after using clopidogrel, there are a variety of poor prognosis situations such as myocardial infarction, stent thrombosis, ischemic stroke, and revascularization \u003csup\u003e[6]\u003c/sup\u003e. The risk of poor prognosis situations varies among individuals, and the influencing factors mainly include race, age, genetic polymorphism, drug interactions, and patient compliance \u003csup\u003e[7]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAmong these, the genetic polymorphism of \u003cem\u003eCYP2C19\u003c/em\u003e plays a key role in the metabolism of clopidogrel \u003csup\u003e[8]\u003c/sup\u003e. Patients carrying the \u003cem\u003eCYP2C192\u003c/em\u003e and \u003cem\u003eCYP2C193\u0026nbsp;\u003c/em\u003egenes have lower sensitivity to clopidogrel, and their antiplatelet effect is not as pronounced as that of wild-type gene patients, which may lead to the occurrence of cardiovascular clinical events \u003csup\u003e[9]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn recent years, there have been continuous studies on the relationship between the\u003cem\u003e\u0026nbsp;CYP2C19\u0026nbsp;\u003c/em\u003egenotype and the efficacy of clopidogrel. Some studies have shown that the genetic polymorphism of \u003cem\u003eCYP2C19\u003c/em\u003e is related to clopidogrel resistance, which is a high-risk factor for adverse cardiovascular events \u003csup\u003e[10, 11]\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, meta-analyses have also reported a lack of effect of CYP2C19 no-function alleles on adverse cardiovascular outcomes among patients receiving clopidogrel for non-PCI cardiovascular indications, possibly due to lower clinical benefit from treatment with clopidogrel in these patient populations \u003csup\u003e[12]\u003c/sup\u003e. In addition to the \u003cem\u003eCYP2C19\u0026nbsp;\u003c/em\u003egene, the polymorphisms of other genes such as \u003cem\u003eABCB1, CES1, CYP1A2, CYP2B6, CYP3A4, CYP3A5,\u0026nbsp;\u003c/em\u003eand \u003cem\u003eCYP2C9\u003c/em\u003e, as well as drug interactions, patients' comorbidities, physiological conditions at different ages, living habits, and patient compliance, may also affect the efficacy of clopidogrel\u003csup\u003e[13, 14]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTaken together, this study aims to explore the relationship between the adoption of clopidogrel medication recommendations based on genotype guidance in ACS patients undergoing PCI (especially in patients with intermediate metabolic genotypes) and the incidence of later cardiovascular ischemic and bleeding events, to provide a reference for clinical rational use of drugs.\u003c/p\u003e"},{"header":"2.\tMaterials and Methods","content":"\u003ch3\u003e2.1 General Information\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 Individualized advice based on the \u003cem\u003eCYP2C19\u003c/em\u003e genotype of clopidogrel\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003ePhenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\" valign=\"top\"\u003e\n \u003cp\u003eDiplotypes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"56.70103092783505%\" valign=\"top\"\u003e\n \u003cp\u003eIndividualized advice\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.371134020618557%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eCYP2C19\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\" valign=\"top\"\u003e\n \u003cp\u003eNormal metabolizer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e*1/*1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"56.70103092783505%\" valign=\"top\"\u003e\n \u003cp\u003eUse the standard dose of clopidogrel 75mg qd\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.176470588235293%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eIntermediate metabolizer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.117647058823529%\"\u003e\n \u003cp\u003e*1/*2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.70588235294117%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eIt is recommended to increase the platelet function test ADP (LTA method) to determine the efficacy.\u003c/p\u003e\n \u003col\u003e\n \u003cli\u003e\u0026ge; 30% use the standard dose of 75mg.\u003c/li\u003e\n \u003cli\u003e\u0026lt; 30% It is recommended to increase the dosage of clopidogrel to 150mg/d or switch to other antiplatelet drugs such as ticagrelor.\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e*1/*3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003ePoor metabolizer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.117647058823529%\"\u003e\n \u003cp\u003e*2/*2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.70588235294117%\" valign=\"top\"\u003e\n \u003cp\u003eIt is recommended to switch to ticagrelor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn our retrospective study, the 3,004 patients diagnosed with ACS and treated with clopidogrel were selected and admitted to Guangdong Provincial People\u0026apos;s Hospital (Guangzhou, China) from January 2016 to March 2024, using the following inclusion criteria diagnosed with coronary atherosclerotic heart disease (including ischemic cardiomyopathy, angina pectoris, and myocardial infarction) by coronary arteriography (coronary arteriography, CAG). The patients/subjects received the advice for clopidogrel medication proposed by clinical pharmacists based on the results of \u003cem\u003eCYP2C19\u0026nbsp;\u003c/em\u003egenotyping. The advice for clopidogrel medication is shown in \u003cstrong\u003eTable 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eNormal metabolizers only had the effect of studying the differences between metabolic groups and were not grouped into the adopted group or the unadopted group, due to unchanged recommended standard dosage of clopidogrel and without other advice given. The exclusion criteria are listed below:\u003c/p\u003e\n\u003cp\u003e1. Patients who have contraindications to clopidogrel or do not take clopidogrel\u003c/p\u003e\n\u003cp\u003e2. Patients with incomplete medical records\u003c/p\u003e\n\u003cp\u003e3. Patients with a previous history of ischemic or hemorrhagic diseases, hematological diseases or bleeding diathesis, and platelet count \u0026gt; 450\u0026times;10^9 or \u0026lt; 100\u0026times;10^9\u003c/p\u003e\n\u003cp\u003e4. Patients with combined malignant diseases such as tumors\u003c/p\u003e\n\u003cp\u003e5. Patients with severe liver or kidney diseases, coagulation disorders, or anemia [hemoglobin (Hb) level \u0026lt; 100g/L]\u003c/p\u003e\n\u003cp\u003e6. Non-Han population\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.2 Methods\u003c/h2\u003e\n\u003ch3\u003e2.2.1 Data Collection\u003c/h3\u003e\n\u003cp\u003eThe complete clinical data of the selected patients was reviewed through the hospital\u0026apos;s electronic medical recording system:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eGeneral conditions: gender, age, height, weight, and body mass index (BMI).\u003c/li\u003e\n \u003cli\u003eRisk factors of ACS: hypertension, diabetes, hyperlipidemia, smoking, and drinking.\u003c/li\u003e\n \u003cli\u003eCoronary intervention conditions: the number of stent implants.\u003c/li\u003e\n \u003cli\u003eLaboratory test results: platelet count, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, and serum creatinine.\u003c/li\u003e\n \u003cli\u003eDrug compliance score MORISKY score (Definition: MORISKY score \u0026ge; 6, that is, good and moderate compliance, belongs to regular medication).\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch3\u003e2.2.2 Grouping of Research Subjects\u003c/h3\u003e\n\u003cp\u003eAccording to the genotyping results of the\u003cem\u003e\u0026nbsp;CYP2C19\u003c/em\u003e, patients were divided into the normal metabolism group and the abnormal metabolism group. The abnormal metabolism group was further divided into the intermediate metabolism group and the poor metabolism group. The grouping was mainly distinguished based on the different metabolic capabilities of \u003cem\u003eCYP2C19\u003c/em\u003e. Normal metabolizer type is with the genotype of \u003cem\u003eCYP2C19*1/*1\u003c/em\u003e. Intermediate metabolizer type is \u003cem\u003eCYP2C19*1/*2 or CYP2C19*1/*3\u003c/em\u003e. The poor metabolizer type is \u003cem\u003eCYP2C19*2/*2, CYP2C19*2/*3\u003c/em\u003e, or \u003cem\u003eCYP2C19*3/*3\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003e2.2.3 Clinical Follow-up\u003c/h3\u003e\n\u003cp\u003eA follow-up plan was formulated to obtain the data of the follow-up patients. The selected patients were followed up by rehospitalization or telephone calls to understand and record the occurrence of various cardiovascular adverse events and bleeding events within one year of taking clopidogrel.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCardiovascular adverse events include cardiogenic death, non-fatal myocardial infarction, unstable angina pectoris, in-stent stenosis or thrombosis, and subsequent revascularization.\u003c/p\u003e\n\u003cp\u003eBleeding events include mild to moderate bleeding events like gingival bleeding, subcutaneous ecchymosis, epistaxis, conjunctival hemorrhage, gross hematuria, and fatal major bleeding including intracranial hemorrhage, gastrointestinal bleeding, and so on.\u003c/p\u003e\n\u003cp\u003eThe definitions of cardiovascular adverse events are as follows:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eCardiogenic death: Any definite death due to cardiovascular causes or death that is not attributed to non-cardiovascular causes.\u003c/li\u003e\n \u003cli\u003eNon-fatal myocardial infarction: New ischemic symptoms occur, the ST segment of the electrocardiogram is significantly depressed or elevated, and troponin is significantly increased.\u003c/li\u003e\n \u003cli\u003eUnstable angina pectoris: It occurs at rest and lasts for more than 20 minutes, or the degree of angina pectoris is more severe, lasts longer, or is more frequent than before, and is confirmed by myocardial enzymes or electrocardiogram.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch3\u003e2.2.4 Statistical Methods\u003c/h3\u003e\n\u003cp\u003eData processing was performed using SPSS 27.0 statistical software. Measurement data that obeyed a normal distribution or approximately normal distribution were expressed as the mean \u0026plusmn; standard deviation (x \u0026plusmn; s). The t-test was used for the comparison of means between two groups, and one-way analysis of variance (ANOVA) was used for the comparison of means among multiple groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMeasurement data that did not follow a normal distribution were expressed as the median (interquartile range), and non-parametric tests were used for comparison between groups. Count data were expressed as frequency/ percentage, and the chi-square test was used for comparison between groups. p \u0026lt; 0.05 indicated a statistically significant difference.\u0026nbsp;\u003c/p\u003e"},{"header":"3.\tResults","content":"\u003ch3\u003e3.1. Baseline Characteristics\u003c/h3\u003e\n\u003cp\u003eThe follow-up of 1,943 patients was completed. Among them, 1,161 cases (59.75%) were with hypertension, 634 cases (32.63%) were with diabetes, 319 cases (16.42%) were with hyperlipidemia, 635 cases (32.68%) were with a smoking history, 363 cases (18.68%) were with a drinking history, and 1,858 cases (95.63%) were regular medication users. There was no statistically significant difference between the baseline characteristics of normal metabolism, intermediate metabolism, and poor metabolism groups, respectively (\u003cstrong\u003eTable 2\u003c/strong\u003e). There was also no statistically significant difference, between the baseline characteristics of the abnormal metabolism adopted group and the abnormal metabolism unadopted group (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 The Baseline Characteristics of Metabolic Group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eItem/Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003eNormal metabolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003eIntermediate metabolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003ePoor metabolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e63.39\u0026plusmn;10.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e63.63 \u0026plusmn; 10.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e63.12 \u0026plusmn; 10.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e24.18\u0026plusmn;5.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e24.13 \u0026plusmn; 6.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e24.26 \u0026plusmn; 7.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003eBiochemical indicators\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003ePLT (\u0026times;10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e226.29\u0026plusmn;59.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e225.68 \u0026plusmn; 59.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e226.53 \u0026plusmn; 60.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eALT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e28.97\u0026plusmn;24.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e28.67 \u0026plusmn; 22.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e29.15 \u0026plusmn; 22.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.868\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eAST (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e34.02\u0026plusmn;36.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e33.48 \u0026plusmn; 34.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e33.54 \u0026plusmn; 34.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eBUN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e6.51\u0026plusmn;5.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e6.58 \u0026plusmn; 5.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e6.43 \u0026plusmn; 6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eCREA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e93.78\u0026plusmn;54.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e94.29 \u0026plusmn; 55.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e94.94 \u0026plusmn; 60.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003eInterventional situation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eAverage number of implanted stents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e2.07\u0026plusmn;1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e2.02 \u0026plusmn; 1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e2.03 \u0026plusmn; 1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.400\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eGender (Male n (%) )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e575 (78.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e741 (79.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e210 (76.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.654\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.681818181818183%\"\u003e\n \u003cp\u003eGender (Female n (%) )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.727272727272727%\"\u003e\n \u003cp\u003e161 (21.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.272727272727273%\"\u003e\n \u003cp\u003e193 (20.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.318181818181817%\"\u003e\n \u003cp\u003e63 (23.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003ePrevious history\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eHypertension n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e440 (59.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e554 (59.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e167 (61.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eDiabetes n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e244 (33.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e304 (32.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e86 (31.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eHyperlipidemia n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e129 (17.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e146 (15.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e44 (16.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eSmoking history n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e246 (33.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e297 (31.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e92 (33.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eDrinking history n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e126 (17.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e184 (19.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e53 (19.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eMedication compliance:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003eRegular medication n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e703 (95.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e892 (95.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\"\u003e\n \u003cp\u003e263 (96.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 The Baseline Characteristics of the Abnormal Metabolic Groups\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\" rowspan=\"2\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eItem/\u003c/p\u003e\n \u003cp\u003egroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" colspan=\"2\" style=\"width: 26.1468%;\"\u003e\n \u003cp\u003eAdopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.282828282828284%\" colspan=\"2\" style=\"width: 14.2239%;\"\u003e\n \u003cp\u003eUnadopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" colspan=\"2\" rowspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.728813559322035%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003eIntermediate Metabolic\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e(n=196)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.423728813559322%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003ePoor Metabolic\u003csup\u003eb\u0026nbsp;\u003c/sup\u003e(n=31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.423728813559322%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003eIntermediate Metabolic\u003csup\u003ec\u0026nbsp;\u003c/sup\u003e(n=738)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.423728813559322%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003ePoor Metabolic\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(n=242)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e62.97\u0026plusmn;11.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e63.80\u0026plusmn;10.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e63.80\u0026plusmn;10.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e63.03\u0026plusmn;10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e23.89\u0026plusmn;4.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e23.96\u0026plusmn;5.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e24.20\u0026plusmn;6.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e24.30\u0026plusmn;7.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"79.79797979797979%\" colspan=\"5\" style=\"width: 54.3854%;\"\u003e\n \u003cp\u003eBiochemical indicators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003ePLT\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(\u0026times;10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e225.32\u0026plusmn;57.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e226.44\u0026plusmn;57.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e225.78\u0026plusmn;60.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e226.54\u0026plusmn;60.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eALT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e28.80\u0026plusmn;26.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e29.58\u0026plusmn;27.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e28.64\u0026plusmn;21.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e29.10\u0026plusmn;22.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eAST (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e33.99\u0026plusmn;38.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e34.20\u0026plusmn;40.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e33.34\u0026plusmn;32.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e33.45\u0026plusmn;33.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eBUN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e6.65\u0026plusmn;4.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e6.47\u0026plusmn;4.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e6.56\u0026plusmn;6.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e6.43\u0026plusmn;6.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eCREA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e94.97\u0026plusmn;56.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e96.09\u0026plusmn;63.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e94.11\u0026plusmn;55.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e94.79\u0026plusmn;60.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"80.61224489795919%\" colspan=\"5\" style=\"width: 54.3854%;\"\u003e\n \u003cp\u003eInterventional situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\" style=\"width: 2.6495%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\" style=\"width: 2.7193%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.556701030927837%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eAverage number of implanted stents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e1.99\u0026plusmn;1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e1.99\u0026plusmn;1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e2.03\u0026plusmn;1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e2.03\u0026plusmn;1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.61855670103093%\" colspan=\"2\" style=\"width: 5.3688%;\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003ep-value \u0026nbsp;(a+c/\u003c/p\u003e\n \u003cp\u003eb+d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003ep-value \u0026nbsp;(a+b/\u003c/p\u003e\n \u003cp\u003ec+d)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eGender \u0026nbsp;(Male n (%) )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e155 (79.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e23 (74.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e586 (79.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e187 (77.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" rowspan=\"2\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003e0.391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" rowspan=\"2\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003e0.878\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.376623376623378%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eGender (Female n (%) )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.181818181818183%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e41 (20.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e8 (25.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e152 (20.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e55 (22.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"80.61224489795919%\" colspan=\"5\" style=\"width: 54.3854%;\"\u003e\n \u003cp\u003ePrevious history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\" style=\"width: 2.6495%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\" style=\"width: 2.7193%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eHypertension n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e117 (59.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e20 (64.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e437 (59.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e147 (60.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eDiabetes n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e64 (32.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e10 (32.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e240 (32.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e76 (31.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003e0.745\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eHyperlipidemia n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e29 (14.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e5 (16.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e117 (15.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e39 (16.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003e0.680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eSmoking history n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e61 (31.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e11 (35.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e236 (31.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e81 (33.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eDrinking history n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e39 (19.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e6 (19.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e145 (19.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e47 (19.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003e0.995\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"80.61224489795919%\" colspan=\"5\" style=\"width: 54.3854%;\"\u003e\n \u003cp\u003eMedication compliance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.204081632653061%\" style=\"width: 2.6495%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\" style=\"width: 2.7193%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\" style=\"width: 12.1321%;\"\u003e\n \u003cp\u003eRegular medication n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\" style=\"width: 12.7597%;\"\u003e\n \u003cp\u003e187 (95.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 13.3872%;\"\u003e\n \u003cp\u003e31 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 9.3431%;\"\u003e\n \u003cp\u003e705 (95.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\" style=\"width: 6.7633%;\"\u003e\n \u003cp\u003e231 (95.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.416666666666666%\" style=\"width: 2.6495%;\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 2.7193%;\"\u003e\n \u003cp\u003e0.961\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI: Body Mass Index; PLT: Platelet Count; ALT: Alanine Aminotransferase; AST: Aspartate Aminotransferase; BUN: Blood Urea Nitrogen; CREA: Serum Creatinine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Loss to Follow-up Situation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2 Loss to follow-up situation of the metabolic groups.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in \u003cstrong\u003eFigure 1\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003eFigure 2\u003c/strong\u003e, the number of loss to follow-up cases in the normal metabolic group was 247 (53.70%), 164 (35.65%) in the intermediate metabolic group, and 49 (10.65%) in the poor metabolic group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong 2,403 selected patients, 460 patients were not included in the analysis due to reasons such as changing contact information and refusing to follow up, but 1,943 patients were enrolled.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was a significant difference in the total loss to follow-up situation among patients in three metabolic groups (P \u0026lt; 0.001). We further conducted a comparison between the two metabolic groups and found that there were statistically significant differences mainly between the normal metabolic group and the intermediate metabolic group/poor metabolic group (P \u0026lt; 0.001/P \u0026lt; 0.001). While there was no loss to follow-up difference between the intermediate metabolic group and the poor metabolic group (P = 0.901) in \u003cstrong\u003eTable 4\u003c/strong\u003e. It can explained that the recommendations of the normal metabolic group did not change the dosage or type of clopidogrel taken by the patients. Therefore, the emphasis of patients from the normal metabolic group on the content of the study and follow-up was different from that of the intermediate and poor metabolic groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Comparison of Loss to Follow-up Cases between Metabolic Groups\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"82.82828282828282%\" colspan=\"2\"\u003e\n \u003cp\u003eMetabolic Groups\u0026nbsp;Comparison\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.41414141414141%\" valign=\"top\"\u003e\n \u003cp\u003eNormal Metabolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.41414141414141%\" valign=\"top\"\u003e\n \u003cp\u003eIntermediate Metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.41414141414141%\" valign=\"top\"\u003e\n \u003cp\u003eNormal Metabolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.41414141414141%\" valign=\"top\"\u003e\n \u003cp\u003ePoor Metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.41414141414141%\" valign=\"top\"\u003e\n \u003cp\u003eIntermediate Metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.41414141414141%\" valign=\"top\"\u003e\n \u003cp\u003ePoor Metabolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch3\u003e3.3. Distribution of \u003cem\u003eCYP2C19\u003c/em\u003e Genotypes and Adoption of Clopidogrel Medication Recommendations\u003c/h3\u003e\n\u003cp\u003eThe distribution ratios of different detected \u003cem\u003eCYP2C19\u0026nbsp;\u003c/em\u003egenotypes in ACS patients are different, which is shown in \u003cstrong\u003eTable 5\u003c/strong\u003e. Normal metabolizer type (*1/*1) accounts for 37.88% of the total number of cases included. Intermediate metabolizer type (*1/*2 and *1/*3) is detected more frequently, totaling 48.07%, among which *1/*2 is the main intermediate metabolizer type. While the Poor metabolizer type (*2/*2, *2/*3, and *3/*3) is 14.05% in total.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe D\u003c/strong\u003e\u003cstrong\u003eistribution of \u003cem\u003eCYP2C19\u003c/em\u003e Metabolic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003cstrong\u003eypes\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\"\u003e\n \u003cp\u003eMetabolic type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003eNormal metabolizer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" colspan=\"2\"\u003e\n \u003cp\u003eIntermediate metabolizer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.571428571428573%\" colspan=\"3\"\u003e\n \u003cp\u003ePoor\u0026nbsp;\u003c/p\u003e\n \u003cp\u003emetabolizer\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003eGenotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003e*1/*1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e*1/*2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e*1/*3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e*2/*2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e*2/*3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e*3/*3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003eNumber of genotype cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003e736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e804\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003eProportion of genotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003e37.88%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e41.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e6.69%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e9.93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e3.71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.41%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003eNumber of cases\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(adopted + unadopted)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e174+630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e22+108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e20+173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e11+61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0+8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003eAdoption proportion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.556701030927837%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.371134020618557%\"\u003e\n \u003cp\u003e21.64%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e16.92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e10.36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e15.28%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\"\u003e\n \u003cp\u003eTotal number of cases (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" colspan=\"2\"\u003e\n \u003cp\u003e934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.571428571428573%\" colspan=\"3\"\u003e\n \u003cp\u003e273\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\"\u003e\n \u003cp\u003eAdopted cases (n％)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" colspan=\"2\"\u003e\n \u003cp\u003e196 (20.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.571428571428573%\" colspan=\"3\"\u003e\n \u003cp\u003e31 (11.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.571428571428573%\"\u003e\n \u003cp\u003eUnadopted cases (n％)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" colspan=\"2\"\u003e\n \u003cp\u003e738 (79.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.571428571428573%\" colspan=\"3\"\u003e\n \u003cp\u003e242 (88.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIt shows the adoption of clopidogrel medication recommendations based on\u003cem\u003e\u0026nbsp;CYP2C19\u0026nbsp;\u003c/em\u003egenotypes for enrolled patients (\u003cstrong\u003eTable 5\u003c/strong\u003e). For patients with the intermediate metabolic type, 20.99% adopted the medication recommendations, indicating that some doctors and patients are aware that the intermediate metabolic rate may affect the drug efficacy and thus made adjustments. However, 79.01% of the patients did not adopt the recommendations, possibly due to insufficient awareness of the impact of drug metabolism by physicians or patients, or their belief that the standard treatment plan is still effective.\u003c/p\u003e\n\u003cp\u003eAmong Poor metabolizer-type patients, only 11.52% adopted the medication recommendations, and 88.64% did not adopt them. Since Poor metabolizer-type patients have a slower rate of metabolizing the drug and need to choose ticagrelor, the proportion of not adopting the recommendations is relatively high. This indicates that in clinical practice, both doctors and patients are still insufficiently aware of the influence of genotypes on drug metabolism. It is challenging for them to accept the recommendation to change the drug treatment plan. Some physicians also reported concerns that ticagrelor may relatively increase the risk of bleeding and it is difficult to balance the risk of ischemia and bleeding, so they did not accept the recommendation.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our data pointed out that the attention to the impact of \u003cem\u003eCYP2C19\u0026nbsp;\u003c/em\u003egenotypes on clopidogrel metabolism and the actual adoption of medication adjustments still need to be improved in clinical practice. Future work should strengthen the publicity and education on the impact of Intermediate metabolizer type and Poor metabolizer type genotypes on drug efficacy, and promote the implementation of individualized medication plans guided by genotypes.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e3.4. Relationship between Clopidogrel Metabolic Types- Adoption of Medication Recommendations and Incidence of Ischemic Events\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6 The Occurrence of Ischemic Events\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.760563380281692%\"\u003e\n \u003cp\u003eIschemic events/Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003eNormal Metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\"\u003e\n \u003cp\u003eIntermediate Metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.316901408450704%\"\u003e\n \u003cp\u003ePoor Metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003eTotal number of cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.091549295774648%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.760563380281692%\"\u003e\n \u003cp\u003eUnstable angina pectoris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e32 (4.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\"\u003e\n \u003cp\u003e48 (5.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.316901408450704%\"\u003e\n \u003cp\u003e33 (12.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e113 (5.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.091549295774648%\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.760563380281692%\"\u003e\n \u003cp\u003eNon-fatal myocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e11 (1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\"\u003e\n \u003cp\u003e18 (1.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.316901408450704%\"\u003e\n \u003cp\u003e13 (4.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e42 (2.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.091549295774648%\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.760563380281692%\"\u003e\n \u003cp\u003eCardiogenic and vascular death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e6 (0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\"\u003e\n \u003cp\u003e9 (0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.316901408450704%\"\u003e\n \u003cp\u003e6 (2.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e21 (1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.091549295774648%\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.760563380281692%\"\u003e\n \u003cp\u003eIn-stent stenosis/thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e32 (4.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\"\u003e\n \u003cp\u003e67 (7.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.316901408450704%\"\u003e\n \u003cp\u003e45 (16.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e144 (7.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.091549295774648%\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.760563380281692%\"\u003e\n \u003cp\u003eRevascularization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e30 (4.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\"\u003e\n \u003cp\u003e72 (7.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.316901408450704%\"\u003e\n \u003cp\u003e54 (19.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e156 (8.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.091549295774648%\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.760563380281692%\"\u003e\n \u003cp\u003eTotal ischemic events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e111 (15.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.492957746478874%\"\u003e\n \u003cp\u003e214 (22.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.316901408450704%\"\u003e\n \u003cp\u003e151 (55.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.669014084507042%\"\u003e\n \u003cp\u003e476 (24.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.091549295774648%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn this study, we analyzed the data of different types of ischemic events in ACS patients with different \u003cem\u003eCYP2C19\u003c/em\u003e metabolic genotypes undergoing PCI, including unstable angina pectoris, nonfatal myocardial infarction, cardiogenic and vascular death, in-stent stenosis/thrombosis, and revascularization cases. We analyzed the occurrence of ischemic events in patients of the metabolic groups. It showed no significance was found in the occurrence of ischemic events among different metabolic groups, but there was a statistically significant difference in the total ischemic events (p \u0026lt; 0.001), and the incidence of each event increased as the metabolism slowed (\u003cstrong\u003eTable 6\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eBased on whether the medication recommendations were adopted or not, we conducted the intermediate metabolic group, the adoption of recommendations, and the occurrence of unstable angina pectoris, nonfatal myocardial infarction, cardiogenic and vascular death, in-stent stenosis/thrombosis, and revascularization, p \u0026gt; 0.05, with no statistically significant difference. However, there was a statistically significant difference in the total ischemic events, p = 0.041. Therefore, the results suggest that whether the recommendations are Adopted or not in the intermediate metabolic group may indicate that it does not affect the occurrence of specific ischemic events in the statistics but will increase the occurrence of total ischemic events. Adopting the recommendations can reduce the risk of total ischemic events by approximately 32.6% (Table 7).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7 The Comparison of Ischemic Events in the Intermediate Metabolic Group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"2\"\u003e\n \u003cp\u003eOccurrence of\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eevents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"2\"\u003e\n \u003cp\u003eNo occurrence of events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\" rowspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\" rowspan=\"2\"\u003e\n \u003cp\u003eOdds\u0026nbsp;ratio\u0026nbsp;(OR)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40%\"\u003e\n \u003cp\u003eAdopted situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.75%\"\u003e\n \u003cp\u003eAdopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.25%\"\u003e\n \u003cp\u003eUnadopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.75%\"\u003e\n \u003cp\u003eAdopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.25%\"\u003e\n \u003cp\u003eUnadopted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eUnstable angina pectoris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eNon-fatal myocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e723\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eCardiogenic and vascular death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eIn-stent stenosis/thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e680\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eRevascularization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.586\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eTotal ischemic events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e3509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.216494845360825%\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8 The Comparison of Ischemic Events in the Poor Metabolic Group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.6530612244898%\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\" colspan=\"2\"\u003e\n \u003cp\u003eOccurrence of\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eevents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" colspan=\"2\"\u003e\n \u003cp\u003eNo occurrence of events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.16326530612245%\" rowspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\" rowspan=\"2\"\u003e\n \u003cp\u003eOdds ratio (OR)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40%\"\u003e\n \u003cp\u003eAdopted situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.75%\"\u003e\n \u003cp\u003eAdopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.25%\"\u003e\n \u003cp\u003eUnadopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.75%\"\u003e\n \u003cp\u003eAdopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.25%\"\u003e\n \u003cp\u003eUnadopted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eUnstable angina pectoris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.469\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eNon-fatal myocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eCardiogenic and vascular death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e1.580\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eIn-stent stenosis/thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eRevascularization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.98969072164948%\"\u003e\n \u003cp\u003eTotal ischemic events\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFor the poor metabolic group, the adoption of recommendations and the occurrence of unstable angina pectoris, non-fatal myocardial infarction, and cardiogenic and vascular death, p \u0026gt; 0.05, showing no statistically significant difference. However, it significantly affects in-stent stenosis/thrombosis (p= 0.035), revascularization (p= 0.048), and total ischemic events (p= 0.006). Therefore, the recommendations that are unadopted in the poor metabolic group may suggest an increased situation of in-stent stenosis/thrombosis and revascularization in ACS patients undergoing PCI, and not adopting the relevant opinions may increase the result of total ischemic events. Adopting the recommendations can reduce the risk of in-stent stenosis, thrombosis, revascularization, and total ischemic events by approximately 85.0%, 74.8%, and 65.0%, respectively (Table 8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. Relationship between the Adoption of Clopidogrel Metabolic Types- Medication Recommendations and the Incidence of Bleeding Events\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHere we show the relationship between the adoption or unadoption of clopidogrel medication recommendations and the incidence of bleeding events (mild to moderate bleeding and fatal major bleeding) in patients of different \u003cem\u003eCYP2C19\u0026nbsp;\u003c/em\u003emetabolic types (normal metabolic groups, intermediate metabolic groups, and poor metabolic Group) (Table 9). We include the number of cases of bleeding events in each group, the p-value, the total number of bleeding cases, and the odds ratio (OR) value. normal metabolic group: There were 43 cases of mild to moderate bleeding and 17 cases of fatal major bleeding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9 The Relationship between \u003cem\u003eCYP2C19\u003c/em\u003e Metabolic Types and Bleeding Events \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.252525252525253%\" rowspan=\"2\"\u003e\n \u003cp\u003eMetabolic group \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.121212121212121%\" rowspan=\"2\"\u003e\n \u003cp\u003eNormal metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"62.62626262626262%\" colspan=\"5\"\u003e\n \u003cp\u003eAbnormal metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.864406779661017%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.728813559322035%\"\u003e\n \u003cp\u003eIntermediate metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.728813559322035%\"\u003e\n \u003cp\u003eIntermediate metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.338983050847457%\"\u003e\n \u003cp\u003ePoor metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.338983050847457%\"\u003e\n \u003cp\u003ePoor metabolic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.041666666666668%\"\u003e\n \u003cp\u003eAdopted situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003eAdopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003eUnadopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003eAdopted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003eUnadopted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.041666666666668%\"\u003e\n \u003cp\u003eMild to moderate bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.041666666666668%\"\u003e\n \u003cp\u003eFatal major bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.510204081632654%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.387755102040817%\" colspan=\"2\"\u003e\n \u003cp\u003e0.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" colspan=\"2\"\u003e\n \u003cp\u003e0.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" colspan=\"2\"\u003e\n \u003cp\u003e0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.041666666666668%\"\u003e\n \u003cp\u003eTotal number of bleeding cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.041666666666668%\"\u003e\n \u003cp\u003eNumber of non-bleeding cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.291666666666667%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.583333333333334%\"\u003e\n \u003cp\u003e611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.510204081632654%\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.142857142857143%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" colspan=\"2\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" colspan=\"2\"\u003e\n \u003cp\u003e0.910\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.510204081632654%\"\u003e\n \u003cp\u003eTotal number of bleeding cases odds ratio (OR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.244897959183673%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.142857142857143%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" colspan=\"2\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.510204081632654%\" colspan=\"2\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn the intermediate metabolic group, among the adopted patients, there were 10 cases of mild to moderate bleeding and 1 case of fatal major bleeding, while among the unadopted patients, there were 48 cases and 7 cases, respectively. The results of the chi-square test showed that the p-value for mild to moderate bleeding and fatal major bleeding caused by adoption or not is 0.346, and there is no statistically significant difference in their occurrence (p \u0026gt; 0.05). The total number of bleeding and non-bleeding events in adopted and unadopted patients of the intermediate metabolic group indicates that the adoption of recommendations does not lead to the occurrence of bleeding events, with no statistically significant difference (p \u0026gt; 0.05). The odds ratio (OR) of the total number of bleeding cases is 0.60, suggesting that the adoption of medication recommendations in the intermediate metabolic group may slightly reduce the risk of bleeding, but it does not reach statistical significance.\u003c/p\u003e\n\u003cp\u003eIn the poor metabolic group, there were 2 cases of mild to moderate bleeding, while among the unadopted patients, there were 18 cases of mild to moderate bleeding and 5 cases of fatal major bleeding. The p-value for mild to moderate bleeding and fatal major bleeding with or without adoption is 0.847, indicating no statistically significant difference in their occurrence (p \u0026gt; 0.05). The total number of bleeding and non-bleeding events in the adopted and unadopted groups of the poor metabolic group indicates that adoption does not lead to the occurrence of bleeding events, with no statistically significant difference (p \u0026gt; 0.05). The odds ratio (OR) of the total number of bleeding cases is 0.93, suggesting that the adoption of medication recommendations in the poor metabolic group may slightly reduce the risk of bleeding, but it does not reach statistical significance.\u003c/p\u003e\n\u003cp\u003eAccording to the results of bleeding events, it can be concluded that individualized guidance based on the \u003cem\u003eCYP2C19\u003c/em\u003e genotype for clopidogrel does not increase bleeding outcomes in patients with intermediate or poor metabolizers.\u003c/p\u003e"},{"header":"4.\tDiscussion","content":"\u003ch3\u003e4.1. Disadvantages of this study\u003c/h3\u003e\n\u003col\u003e\n \u003cli\u003eThis study is a single-center sample with a small number of follow-up visits, which may make it difficult to predict the overall situation.\u003c/li\u003e\n \u003cli\u003eThe loss to follow-up rate is high, and the analysis results may be biased.\u003c/li\u003e\n \u003cli\u003eThe individualized use of clopidogrel is mainly recommended for ACS patients undergoing PCI. However, a small number of patients who planned to undergo PCI canceled the procedure for some reasons, which may have a certain impact on the results.\u003c/li\u003e\n \u003cli\u003eThe situation of patients taking other drugs in combination is not clear, and drug interactions may have a certain impact on the results.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch3\u003e4.2. Analysis of the research results\u003c/h3\u003e\n\u003cp\u003eThrough the statistical analysis of ACS patients with different \u003cem\u003eCYP2C19\u0026nbsp;\u003c/em\u003emetabolic genotypes, it is found that there is no difference in the occurrence of ischemic events among different metabolic groups, but there is a statistically significant difference in the total ischemic events, and the incidence of each event increases as the metabolism slows down.\u003c/p\u003e\n\u003cp\u003eFor the intermediate metabolic group, whether the recommendation is adopted or not has no statistically significant impact on the occurrence of specific ischemic events, but it will increase the occurrence of total ischemic events. Adopting the recommendation can reduce the risk of total ischemic events by approximately 32.6%. For the poor metabolic group, whether the recommendation is adopted or not has no statistically significant impact on the occurrence of unstable angina pectoris, non-fatal myocardial infarction, and cardiogenic and vascular death, but it has an impact on in-stent stenosis/thrombosis, revascularization, and total ischemic events, with statistically significant differences. Adopting the recommendation can reduce the risk of in-stent stenosis/thrombosis, revascularization, and total ischemic events by approximately 85.0%, 74.8%, and 65.0%, respectively.\u003c/p\u003e\n\u003cp\u003eBased on the results of bleeding events, it can be concluded that the individualized guidance suggestions based on the \u003cem\u003eCYP2C19\u003c/em\u003e genotype of clopidogrel do not increase the bleeding outcomes in patients with intermediate metabolizers or poor metabolizers.\u003c/p\u003e\n\u003ch3\u003e4.3. Implications for clinical practice\u003c/h3\u003e\n\u003cp\u003eThese data reflect that in clinical practice, the attention to the impact of \u003cem\u003eCYP2C19\u0026nbsp;\u003c/em\u003egenotypes on clopidogrel metabolism and the actual adoption of medication adjustments still need to be improved.\u003c/p\u003e\n\u003cp\u003eFuture work should strengthen the publicity and education on the impact of intermediate metabolizer type and poor metabolizer type genotypes on drug efficacy and promote the implementation of individualized medication plans guided by genotypes.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this study guides the clinical rational use of drugs, but further expansion of the sample size and improvement of the research design still need to evaluate more accurately the role of genotype-guided clopidogrel antiplatelet therapy in ACS patients undergoing PCI.\u003c/p\u003e"},{"header":"5.\tConclusions","content":"\u003cp\u003eThis real-world study investigated the relationship between the adoption of clopidogrel medication recommendations based on genotype guidance in ACS patients undergoing PCI and the incidence of later cardiovascular ischemic and bleeding events. The main findings are as follows:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eIn the intermediate metabolic group, adopting the clopidogrel medication recommendation can reduce the risk of total ischemic events by approximately 32.6%.\u003c/li\u003e\n \u003cli\u003eIn the poor metabolic group, adopting the recommendation can reduce the risk of in-stent stenosis/thrombosis, revascularization, and total ischemic events by approximately 85.0%, 74.8%, and 65.0%, respectively.\u003c/li\u003e\n \u003cli\u003eIndividualized guidance based on the CYP2C19 genotype for clopidogrel did not increase bleeding outcomes in patients with intermediate or poor metabolizers.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThis study highlights the importance of considering CYP2C19 genotypes in clopidogrel therapy. However, it also has several limitations, including being a single-center sample with a small number of follow-up visits, a high loss to follow-up rate, and uncertainties regarding patients taking other drugs. Future work should expand the sample size, improve the research design, and strengthen publicity and education on the impact of genotype-guided individualized medication plans to better evaluate the role of genotype-guided clopidogrel antiplatelet therapy in ACS patients undergoing PCI.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYanpeng Li and Zhilei Li are co-first authors and contributed equally to this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study's conception and design. Clinical data review was primarily performed by Zhilei Li, Haodong Cui, and Huan Dong, with additional contributions from Zhilei Li, Dongmei He, and Ziyuan Zhou. Data processing and statistical analysis were mainly conducted by Zhilei Li and Yanpeng Li. The first draft of the manuscript was written by Zhilei Li and Yanpeng Li, and subsequent editing and proofreading of the article manuscript were carried out by Yanpeng Li, Xiujuan Yang, and Xiaojuan Zhang. All authors provided valuable comments on previous versions of the manuscript, and all read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis paper is funded by the outstanding young fund project for district-university cooperation in major projects of the health system in Nanshan district, Shenzhen (NSZD2023062)and the National Natural Science Foundation of China (No.82073805).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Guangdong Provincial People's Hospital. The ethics approval number is KY2024-5 14-01. The study was conducted by the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was exempted from the informed consent process as approved by the Ethics Committee of Guangdong Provincial People's Hospital. The research has de-identified information of identifiable individuals, removing personal and private information such as names, addresses, and occupations. This has no impact on the research content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that human research participants provided informed consent for the publication of the images in Figure 1-2, Table1-9, These contents are only used for scientific research and statistics and do not involve the personal privacy of the participating patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCavallari LH, Lee CR, Beitelshees AL, Cooper-DeHoff RM, Duarte JD, Voora D, et al. Multisite Investigation of Outcomes With Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention. JACC Cardiovasc Interv. 2018 Jan 22;11 (2):181-191. doi: 10.1016/j.jcin.2017.07.022. Epub 2017 Nov 1. PMID: 29102571; PMCID: PMC5775044.\u003c/li\u003e\n\u003cli\u003eScott SA, Sangkuhl K, Stein CM, Hulot JS, Mega JL, Roden DM, et al. Clinical Pharmacogenetics Implementation Consortium. Clinical Pharmacogenetics Implementation Consortium guidelines for CYP2C19 genotype and clopidogrel therapy: 2013 update. Clin Pharmacol Ther. 2013 Sep;94 (3):317-23. doi: 10.1038/clpt.2013.105. Epub 2013 May 22. PMID: 23698643; PMCID: PMC3748366.\u003c/li\u003e\n\u003cli\u003eKazui M, Nishiya Y, Ishizuka T, Hagihara K, Farid NA, Okazaki O, et al. Identification of the human cytochrome P450 enzymes involved in the two oxidative steps in the bioactivation of clopidogrel to its pharmacologically active metabolite. Drug Metab Dispos. 2010 Jan;38 (1):92-9. doi: 10.1124/dmd.109.029132. PMID: 19812348.\u003c/li\u003e\n\u003cli\u003eShuldiner AR, O\u0026apos;Connell JR, Bliden KP, Gandhi A, Ryan K, Horenstein RB, et al. Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA. 2009 Aug 26;302 (8):849-57. doi: 10.1001/jama.2009.1232. PMID: 19706858; PMCID: PMC3641569.\u003c/li\u003e\n\u003cli\u003ePereira NL, Farkouh ME, So D, Lennon R, Geller N, Mathew V, et al. Effect of Genotype-Guided Oral P2Y12 Inhibitor Selection vs Conventional Clopidogrel Therapy on Ischemic Outcomes After Percutaneous Coronary Intervention: The TAILOR-PCI Randomized Clinical Trial. JAMA. 2020 Aug 25;324 (8):761-771. doi: 10.1001/jama.2020.12443. PMID: 32840598; PMCID: PMC7448831.\u003c/li\u003e\n\u003cli\u003eMega JL, Simon T, Collet JP, Anderson JL, Antman EM, Bliden K, et al. Reduced-function CYP2C19 genotype and risk of adverse clinical outcomes among patients treated with clopidogrel predominantly for PCI: a meta-analysis. JAMA. 2010 Oct 27;304 (16):1821-30. doi: 10.1001/jama.2010.1543. PMID: 20978260; PMCID: PMC3048820.\u003c/li\u003e\n\u003cli\u003eVerma SS, Bergmeijer TO, Gong L, Reny JL, Lewis JP, Mitchell BD, Alexopoulos D, et al. Genomewide Association Study of Platelet Reactivity and Cardiovascular Response in Patients Treated With Clopidogrel: A Study by the International Clopidogrel Pharmacogenomics Consortium. Clin Pharmacol Ther. 2020 Nov;108 (5):1067-1077. doi: 10.1002/cpt.1911. Epub 2020 Jul 9. PMID: 32472697; PMCID: PMC7689744.\u003c/li\u003e\n\u003cli\u003eSibbing D, Gebhard D, Koch W, Braun S, Stegherr J, Morath T, et al. Isolated and interactive impact of common CYP2C19 genetic variants on the antiplatelet effect of chronic clopidogrel therapy. J Thromb Haemost. 2010 Aug;8 (8):1685-93. doi: 10.1111/j.1538-7836.2010.03921.x. Epub 2010 May 21. PMID: 20492469.\u003c/li\u003e\n\u003cli\u003eSibbing D, Koch W, Gebhard D, Schuster T, Braun S, Stegherr J, et al. Cytochrome 2C19*17 allelic variant, platelet aggregation, bleeding events, and stent thrombosis in clopidogrel-treated patients with coronary stent placement. Circulation. 2010 Feb 2;121 (4):512-8. doi: 10.1161/CIRCULATIONAHA.109.885194. Epub 2010 Jan 18. PMID: 20083681.\u003c/li\u003e\n\u003cli\u003ePan Y, Chen W, Xu Y, Yi X, Han Y, Yang Q, et al. Genetic Polymorphisms and Clopidogrel Efficacy for Acute Ischemic Stroke or Transient Ischemic Attack: A Systematic Review and Meta-Analysis. Circulation. 2017 Jan 3;135 (1):21-33. doi: 10.1161/CIRCULATIONAHA.116.024913. Epub 2016 Nov 2. PMID: 27806998.\u003c/li\u003e\n\u003cli\u003eCollet JP, Thiele H, Barbato E, Barth\u0026eacute;l\u0026eacute;my O, Bauersachs J, Bhatt DL, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021 Apr 7;42 (14):1289-1367. doi: 10.1093/eurheartj/ehaa575. PMID: 32860058.\u003c/li\u003e\n\u003cli\u003eSorich MJ, Rowland A, McKinnon RA, Wiese MD. CYP2C19 genotype has a greater effect on adverse cardiovascular outcomes following percutaneous coronary intervention and in Asian populations treated with clopidogrel: a meta-analysis. Circ Cardiovasc Genet. 2014 Dec;7 (6):895-902. doi: 10.1161/CIRCGENETICS.114.000669. Epub 2014 Sep 25. PMID: 25258374.\u003c/li\u003e\n\u003cli\u003eBotton MR, Whirl-Carrillo M, Del Tredici AL, Sangkuhl K, Cavallari LH, Ag\u0026uacute;ndez JAG, et al. PharmVar GeneFocus: CYP2C19. Clin Pharmacol Ther. 2021 Feb;109 (2):352-366. doi: 10.1002/cpt.1973. Epub 2020 Jul 22. PMID: 32602114; PMCID: PMC7769975.\u003c/li\u003e\n\u003cli\u003eAngiolillo DJ, Capodanno D, Danchin N, Simon T, Bergmeijer TO, Ten Berg JM, et al. Derivation, Validation, and Prognostic Utility of a Prediction Rule for Nonresponse to Clopidogrel: The ABCD-GENE Score. JACC Cardiovasc Interv. 2020 Mar 9;13 (5):606-617. doi: 10.1016/j.jcin.2020.01.226. PMID: 32139218.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Clopidogrel, CYP2C19 Genotype, Metabolic Types, Individualized medication, Acute Coronary Syndrome, Percutaneous Coronary Intervention ","lastPublishedDoi":"10.21203/rs.3.rs-4836948/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4836948/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eTo explore the relationship between adopting the recommendation for clopidogrel use based on genotype guidance in Acute Coronary Syndrome (ACS) patients undergoing Percutaneous Coronary Intervention (PCI) and the incidence of later cardiovascular ischemic and bleeding events.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA retrospective study was conducted on 3, 004 ACS patients treated with clopidogrel. Patients were grouped based on CYP2C19 genotype and followed for one year to record cardiovascular adverse and bleeding events.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAdopting the recommendation for clopidogrel use can reduce the risk of total ischemic events in the intermediate metabolic group (Odds Ratio [OR], 0.676; P = 0.041). In the poor metabolic group, the recommendations could reduce the risk of in-stent stenosis/thrombosis (OR, 0.150; P = 0.035), revascularization (OR, 0.252; P = 0.048), and total ischemic events (OR, 0.350; P = 0.006). Individualized guidance based on the CYP2C19 genotype did not increase bleeding outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eIndividualized clopidogrel guidance based on genotype can reduce the ischemic risk in patients with intermediate and poor metabolizers, and the poor metabolic group benefits more. Individualized guidance did not increase bleeding outcomes in patients with intermediate or poor metabolizers.\u003c/p\u003e","manuscriptTitle":"A real-world study of clopidogrel therapy in patients with acute coronary syndrome undergoing percutaneous coronary intervention guided by individualized metabolic types","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-15 04:43:38","doi":"10.21203/rs.3.rs-4836948/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":"ef9c79ff-ed39-43c4-ba5f-5fd13f7b095c","owner":[],"postedDate":"October 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-15T04:43:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-15 04:43:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4836948","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4836948","identity":"rs-4836948","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}