 at the 5 year follow-up by using a real-world data from Taiwan's NHI Research Database (NHIRD).

Data Source
This study was approved by the Institutional Review Board of MacKay Memorial Hospital (MMH-IRB; approval no. 20MMHIS351e). NHIRD is a database that contains the claims data of 99% of Taiwan's residents covered by NHI. Because individual identifiers in the NHIRD have been encrypted and cannot be recognized, the need for informed consent was waived under the full review process of the MMH-IRB. The NHIRD includes data on inpatient, outpatient, and prescription drug claims. The prescribed medications can be classified using the Anatomical Therapeutic Chemical (ATC) system; disease diagnoses are coded according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) until 2016 and according to the International Classification of Diseases, Tenth Revision (ICD-10), subsequently. Death records from the National Death Registry are linked to the NHIRD on the basis of patients' encrypted identifiers [9].

Study Cohort
In the retrospective cohort, we included patients who were admitted for a primary diagnosis of MI (ICD-9-CM 410 and ICD-10 I21.0-I21.4, I22.0-I22.2, I22.8, and I22.9) between 2007 and 2016. The date of the first MI admission was considered the index date of MI. We excluded patients who were aged <20 years, were not Taiwanese citizens, had died during admission, had a previous MI or HF diagnosis, had received ivabradine or angiotensin receptor/neprilysin inhibitor (the recommended medications for chronic HF with systolic dysfunction) [10], had received PCI before admission, did not receive PCI or stent implantation, or had received polymer-free drug-coating stent or combined DES and BMS implantation at index MI admission. We also excluded patients who received first-generation DES implantation, which is associated with an increased stent thrombosis risk [11], and in turn, raises safety concerns and leads to a considerably decreased use in Taiwan. Moreover, patients with high HF risk, including those who received coronary artery bypass grafting [12], ventricular assist device support [13], valvular surgery [14], or heart transplantation [15] during the study period were excluded. Finally, patients who received a non-STEMI diagnosis were excluded. Figure 1 illustrates the patient selection process. [11], and in turn, raises safety concerns and leads to a considerably decreased use in T wan. Moreover, patients with high HF risk, including those who received coronary arte bypass grafting [12], ventricular assist device support [13], valvular surgery [14], or he transplantation [15] during the study period were excluded. Finally, patients who ceived a non-STEMI diagnosis were excluded. Figure 1 illustrates the patient selecti process.

Propensity Score Matching
To reduce potential bias in patient selection, we used propensity score matchi (PSM) to select pairs of patients with similar baseline characteristics but different i planted stent types (i.e., NG-DES or BMS). PSM is being increasingly used in studies es mating the treatment effects by employing observational data [16]. In the present stud pairs of patients were matched on the basis of the logit of the propensity score by usi calipers of widths equal to 0.2 of the standard deviation.
Covariates used to calculate the propensity score are listed in Table 1: age, sex, ind MI admission year, comorbidities, prescribed medications, multivessel PCI use, intraa tic balloon pump (IABP) use, CHA2DS2-VASc score (including congestive HF, hyperte sion, age ≥75 years, diabetes, stroke/transient ischemic attack, vascular disease, age = 6 74 years, female sex) [17], ORBIT score (including age ≥75 years, insufficient kidney fun tion, treatment with any antiplatelet, a positive clinical history of bleeding, and anemia abnormal hemoglobin) [18], and Academic Research Consortium (ARC)-defined ma (including history of malignancy, use of anticoagulants, end-stage chronic kidney disea and intracranial hemorrhage) and minor (including age ≥75 years, history of ischem stroke, and history of bleeding events requiring hospitalization or transfusion) bleedi risk criteria [19].

Propensity Score Matching
To reduce potential bias in patient selection, we used propensity score matching (PSM) to select pairs of patients with similar baseline characteristics but different implanted stent types (i.e., NG-DES or BMS). PSM is being increasingly used in studies estimating the treatment effects by employing observational data [16]. In the present study, pairs of patients were matched on the basis of the logit of the propensity score by using calipers of widths equal to 0.2 of the standard deviation.
Covariates used to calculate the propensity score are listed in Table 1: age, sex, index MI admission year, comorbidities, prescribed medications, multivessel PCI use, intraaortic balloon pump (IABP) use, CHA 2 DS 2 -VASc score (including congestive HF, hypertension, age ≥75 years, diabetes, stroke/transient ischemic attack, vascular disease, age = 65-74 years, female sex) [17], ORBIT score (including age ≥75 years, insufficient kidney function, treatment with any antiplatelet, a positive clinical history of bleeding, and anemia or abnormal hemoglobin) [18], and Academic Research Consortium (ARC)-defined major (including history of malignancy, use of anticoagulants, end-stage chronic kidney disease, and intracranial hemorrhage) and minor (including age ≥75 years, history of ischemic stroke, and history of bleeding events requiring hospitalization or transfusion) bleeding risk criteria [19].  Comorbidities were defined if patients had two or more diagnostic claims within 1 year prior to the index MI admission. Prescribed medications included angiotensinconverting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs), betablockers, nitrates, aspirin, P2Y 12 inhibitors, statins, proton pump inhibitors (PPIs), steroids, and nonsteroidal anti-inflammatory drugs (NSAIDs). The diagnostic codes for diseases and the ATC codes for medications are listed in Table S1.
We used multivessel PCI and CHA 2 DS 2 -VASc scores as indicators to represent the severity of coronary artery disease (CAD) [20]. To consider the potential risk of bleeding complications, we referred to patients who had at least one major or two minor ARC criteria for bleeding risk as patients with ARC-HBR according to the ARC's definition [19]. We also used the ORBIT score to assist the assessment of patients' bleeding risk, in which patients with ORBIT scores of 0-2 were classified as low risk, whereas those with ORBIT scores of ≥3 were classified as medium to high risk [18].

Study Outcomes
The main study outcome was the occurrence of HHF (ICD-9-CM code 428 and ICD-10 code I50) after stent implantation. The study patients were followed up for 5 years. Those who died before developing HF during the follow-up period were considered to have competing risks.

Statistical Methods
Primary analysis was performed to examine the risk of HHF associated with the use of the two stent types (i.e., NG-DES and BMS) in patients with STEMI. The consistency of the treatment effect was evaluated among eight prespecified subgroups stratified by age, sex, number of treated vessels, number of implanted stents, use of an IABP, CHA 2 DS 2 -VASc scores, ORBIT scores, and whether the patients were at ARC-HBR [19]. We used a competing risk model in which death was considered a competing risk and reported the adjusted subdistribution hazard ratio (SHR) to account for the possibility that patients might have died before HHF occurrence. The variables listed in Table 1 were used in the competing risk model when examining the association between implanted stent types and the occurrence of HHF. To further examine the abovementioned association in patients with STEMI who were compliant with guideline-recommended duration of DAPT [2,3], we also performed a separate analysis of patients who received DAPT for an undefined duration of >6 months after the index MI admission. All analyses were performed using SAS/STAT 9.4 (SAS Institute, Cary, NC, USA) and STATA 14 software (Stata Corp, College Station, TX, USA). A standardized mean difference (SMD) >0.1 indicated imbalance between the two groups, and a p of <0.05 indicated a significant association between risk of HHF and type of stent used.

Results
Of the 25,194 patients with STEMI who received PCI and stent implantation included in this study, 7291 (28.9%) received NG-DES implantation. The patients who were aged ≥75 years had less frequently received NG-DES implantation than those patients who were <75 years. Overall, the use of NG-DESs gradually increased over time. Compared with patients in the BMS group, those in the NG-DES group had a higher prevalence of dyslipidemia; had a lower prevalence of cerebrovascular disease; had more frequently used beta-blockers and statins; had less frequently used PPIs, steroids, and NSAIDs; had less frequently used IABP; and had lower ORBIT scores (Table 1). Using PSM, we selected 6831 patient pairs, and the baseline characteristics in the NG-DES and BMS groups were highly similar ( Table 1).
The rates of cumulative incidence competing risk (CICR) of HHF after stent implantation at the 1, 2,