Tirzepatide has demonstrated cardiometabolic benefits in clinical trials, but real-world cardiovascular outcomes among patients without diabetes following acute cardiovascular events or stroke remain understudied. We evaluated clinical outcomes associated with early tirzepatide use after acute myocardial infarction (AMI) or ischemic stroke in patients without diabetes. We conducted a retrospective study using the TriNetX Research Network (110 healthcare organizations). Adults ≥18 years and body mass index ≥27 kg/m² without diabetes, with AMI or ischemic stroke from June 2022 to November 2025 were included. Patients treated with tirzepatide within 14 days of AMI/stroke were compared with those not receiving tirzepatide. Propensity score matching (1:1) across 28 covariates balanced demographics, comorbidities, medications, and laboratory values, yielding 833 patients per cohort. Outcomes were assessed over 2 years and included all-cause emergency room visit or hospitalization, acute kidney injury (AKI), ischemic stroke, heart-failure (HF) hospitalization, and major adverse cardiovascular events. Cox proportional hazard models were used to estimate hazard ratios (HRs). After matching, tirzepatide use was associated with significantly lower risk of all-cause emergency room visit or hospitalization (HR 0.64, 95% CI 0.548–0.741), AKI (HR 0.65, 95% CI 0.441–0.962), ischemic stroke (HR 0.82, 95% CI 0.703–0.947), and HF hospitalization (HR 0.24, 95% CI 0.0001–0.383). Major adverse cardiovascular events hazard did not differ significantly (HR 0.91, 95% CI 0.814–1.021). In conclusion, early tirzepatide initiation after AMI/stroke in patients without diabetes was associated with fewer hospitalizations and reduced renal, HF, and stroke events. These findings support prospective trials of tirzepatide for secondary cardiovascular prevention in non-diabetic patients.
Central illustration
Survivors of acute myocardial infarction (AMI) or ischemic stroke remain at high risk for recurrent cardiovascular events, heart failure (HF), renal complications, and rehospitalization despite contemporary secondary prevention strategies. Although guideline-directed medical therapy has substantially improved outcomes, residual cardiometabolic risk persists, particularly among overweight or obese patients. Incretin-based therapies have emerged as effective cardiometabolic agents with benefits extending beyond glycemic control. Glucagon-like peptide1 (GLP-1) receptor agonists reduce major adverse cardiovascular events (MACE) in patients with type 2 diabetes, and tirzepatide, a dual glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 receptor agonist, produces greater weight loss and improvements in blood pressure, inflammation, and metabolic parameters than prior agents. ,,, These effects suggest potential cardiovascular benefit independent of diabetes status. However, evidence supporting the use of tirzepatide in patients without diabetes, particularly in the early period following AMI or ischemic stroke, is limited. Patients in the postevent setting represent a high-risk population in whom early intervention may modify long-term cardiovascular and cardiorenal outcomes, yet randomized data evaluating tirzepatide for secondary prevention in this context are lacking. Therefore, we conducted a large real-world, propensity-matched cohort study to evaluate clinical outcomes associated with early tirzepatide initiation following AMI or ischemic stroke in patients without diabetes to better define the potential role of tirzepatide in secondary cardiovascular prevention among this patient population.
Methods
This retrospective cohort study was conducted using TriNetX, a global federated health research network that aggregates de-identified electronic medical record (EMR) data from participating healthcare organizations (HCOs). The analysis was performed within the Research Network, which includes data from approximately 110 HCOs and provides access to patient demographics, diagnoses, procedures, medication exposures, clinical encounters, and laboratory measurements. Data within TriNetX is refreshed regularly and analyzed in real time using built-in analytic tools. Our study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines and followed the TriNetX publication standards. Clinical codes used for cohort definition and outcomes are provided in the supplementary table .
Study cohorts
Two cohorts of adults aged 18 years or older with a documented AMI or ischemic stroke were constructed within TriNetX. Patients were required to have no prior diagnosis of diabetes mellitus, defined by the absence of the corresponding ICD-10 code and no documented use of glucose-lowering therapies before initiating tirzepatide. To align with contemporary indications for incretin-based therapies and inclusion criteria used in the SURMOUNT-1 trial, patients were additionally required to have a body mass index (BMI) ≥ 27 kg/m².
The exposed cohort consisted of patients who received tirzepatide within 14 days of AMI or ischemic stroke. The comparator cohort met identical inclusion criteria but had no documented exposure to tirzepatide during the same time window. The index date was defined as the date of AMI or ischemic stroke for both cohorts. All inclusion criteria were required to be met on or before the index date.
Outcomes
Outcomes were assessed beginning 1 day after the index event and continued through 2 years of follow-up. The primary outcome was a composite of all-cause emergency department visits or hospitalization. Secondary outcomes included acute kidney injury (AKI), ischemic stroke, HF hospitalization, and MACE. For time-to-event analyses, patients with a documented history of the outcome of interest before the index date were excluded from the corresponding analysis to evaluate incident events. Follow-up was censored at death, the last recorded clinical encounter, or completion of the 2-year observation window.
Propensity matching
To minimize confounding, 1:1 propensity score matching (PSM) was performed using logistic regression with greedy nearest-neighbor matching and a fixed caliper. Matching variables included demographic characteristics (age, sex, race), cardiovascular and noncardiovascular comorbidities, baseline medication exposures, and available laboratory parameters. Data rows were randomized within the TriNetX platform before matching to reduce potential ordering bias inherent to nearest-neighbor algorithms. Covariates were selected a priori based on clinical relevance, prior cardiovascular outcomes literature, and known associations with post-AMI prognosis, rather than through automated or data-driven selection. Covariate balance between cohorts was assessed using standardized mean differences, with values <0.1 indicating adequate balance. A list of covariates utilized in the creation of cohorts can be found in the supplemental table .
Statistical analyses
All analyses were conducted within the TriNetX Compare Outcomes framework. This platform provides multiple analytic approaches, including measures of association (risk, risk difference, risk ratio, and odds ratio), time-to-event analyses (Kaplan-Meier survival curves, log-rank testing, and hazard ratios), number-of-instances analyses for recurrent events, and laboratory value distribution analyses. Comparisons were performed before and after PSM. A two-sided p-value ≤ 0.05 was considered significant. For interpretability, hazard ratios are reported with tirzepatide as the reference exposure throughout the manuscript.
IRB statement
This study used deidentified data provided by TriNetX and was determined to be exempt from institutional review board oversight by the University of Texas Medical Branch (UTMB). The UTMB IRB determined that the study did not involve interaction with human subjects and met the deidentification standards outlined in Section §164.514(a) of the HIPAA Privacy Rule.
Results
Cohort identification and matching
Prior to matching, baseline demographic and clinical differences were observed between patients who received tirzepatide and those who did not. After PSM, 833 patients remained in each cohort ( Figure 1 ). postmatching balance was achieved across demographic characteristics, cardiovascular and noncardiovascular comorbidities, baseline medication exposures, and available laboratory parameters, with standardized mean differences below accepted thresholds, indicating adequate covariate balance ( Table 1 ).
Cohort selection and propensity score–matched design comparing tirzepatide versus no tirzepatide after AMI or ischemic stroke. Abbreviations: CKD, chronic kidney disease; ER, emergency room.
Table 1
Baseline characteristics of patients with acute myocardial infarction or ischemic stroke without diabetes
| Before PSM | After PSM | ||||||
|---|---|---|---|---|---|---|---|
| No Tirzepatide ( N = 285,111) | Tirzepatide ( N = 836) | P-value | No Tirzepatide ( N = 833) | Tirzepatide ( N = 833) | P-value | SMD | |
| Demographics | |||||||
| Age at Index | 62.9 ± 14.3 | 56.5 ± 12.1 | <0.001 | 56.8 ± 15 | 56.5 ± 12.1 | 0.588 | 0.027 |
| White | 203,649 (71.4%) | 658 (78.7%) | <0.001 | 652 (78.3%) | 655 (78.6%) | 0.858 | 0.009 |
| Female | 128,992 (45.2%) | 487 (58.3%) | <0.001 | 476 (57.1%) | 485 (58.2%) | 0.655 | 0.022 |
| Hispanic or Latino | 13,190 (4.6%) | 36 (4.3%) | 0.660 | 37 (4.4%) | 36 (4.3%) | 0.905 | 0.006 |
| Black or African American | 48,310 (16.9%) | 108 (12.9%) | 0.002 | 102 (12.2%) | 108 (13.0%) | 0.658 | 0.022 |
| Diagnoses (comorbidities) | |||||||
| Essential (primary) hypertension | 121,078 (42.5%) | 529 (63.3%) | <0.001 | 517 (62.1%) | 528 (63.4%) | 0.577 | 0.027 |
| Disorders of lipoprotein metabolism and other lipidemias | 100,733 (35.3%) | 505 (60.4%) | <0.001 | 496 (59.5%) | 502 (60.3%) | 0.764 | 0.015 |
| Atrial fibrillation and flutter | 33,765 (11.8%) | 110 (13.2%) | 0.240 | 116 (13.9%) | 109 (13.1%) | 0.616 | 0.025 |
| Cerebral infarction | 39,356 (13.8%) | 384 (45.9%) | <0.001 | 365 (43.8%) | 381 (45.7%) | 0.431 | 0.039 |
| Heart failure | 31,574 (11.1%) | 113 (13.5%) | 0.025 | 113 (13.6%) | 112 (13.4%) | 0.943 | 0.004 |
| CKD | 23,311 (8.2%) | 71 (8.5%) | 0.739 | 74 (8.9%) | 71 (8.5%) | 0.794 | 0.013 |
| Overweight and obesity | 43,068 (15.1%) | 470 (56.2%) | <0.001 | 489 (58.7%) | 467 (56.1%) | 0.276 | 0.053 |
| Persons with potential health hazards related to socioeconomic and psychosocial circumstances | 7,371 (2.6%) | 40 (4.8%) | <0.001 | 38 (4.6%) | 40 (4.8%) | 0.817 | 0.011 |
| Personal history of nicotine dependence | 31,883 (11.2%) | 153 (18.3%) | <0.001 | 137 (16.4%) | 152 (18.2%) | 0.332 | 0.048 |
| Sleep apnea | 26,282 (9.2%) | 301 (36.0%) | <0.001 | 307 (36.9%) | 299 (35.9%) | 0.684 | 0.020 |
| Medications | |||||||
| Beta Blocking Agents | 80,418 (28.2%) | 343 (41.0%) | <0.001 | 319 (38.3%) | 340 (40.8%) | 0.293 | 0.052 |
| Loop Diuretics | 32,295 (11.3%) | 105 (12.6%) | 0.262 | 104 (12.5%) | 105 (12.6%) | 0.941 | 0.004 |
| Antilipemic Agents | 93,278 (32.7%) | 503 (60.2%) | <0.001 | 497 (59.7%) | 500 (60.0%) | 0.881 | 0.007 |
| ACE Inhibitors | 30,582 (10.7%) | 135 (16.1%) | <0.001 | 128 (15.4%) | 134 (16.1%) | 0.686 | 0.020 |
| ARBs | 38,975 (13.7%) | 226 (27.0%) | <0.001 | 226 (27.1%) | 225 (27.0%) | 0.956 | 0.003 |
| SGLT2 Inhibitors | 5,407 (1.9%) | 52 (6.2%) | <0.001 | 52 (6.2%) | 50 (6.0%) | 0.838 | 0.010 |
| Anticoagulants | 78,828 (27.6%) | 319 (38.2%) | <0.001 | 310 (37.2%) | 316 (37.9%) | 0.761 | 0.015 |
| Antiarrhythmics | 74,220 (26.0%) | 293 (35.0%) | <0.001 | 282 (33.9%) | 293 (35.2%) | 0.571 | 0.028 |
| Laboratory | |||||||
| BMI | 32.3 ± 5.8 | 38.1 ± 7.6 | <0.001 | 36.8 ± 7.3 | 38.1 ± 7.6 | 0.002 | 0.166 |
| 27–30 kg/m 2, n (%) | 63,886 (22.4) | 96 (11.5) | <0.001 | 80 (9.6) | 96 (11.5) | 0.202 | 0.063 |
| 30–35 kg/m 2, n (%) | 81,121 (28.5) | 315 (37.7) | <0.001 | 284 (34.1) | 315 (37.8) | 0.113 | 0.078 |
| 35–40 kg/m 2, n (%) | 38,308 (13.4) | 288 (34.4) | <0.001 | 299 (35.9) | 285 (34.2) | 0.472 | 0.035 |
| ≥ 40 kg/m 2, n (%) | 21,734 (7.6) | 287 (34.3) | <0.001 | 301 (36.1) | 284 (34.1) | 0.383 | 0.043 |
| Cholesterol in LDL [Mass/volume] in Serum or Plasma | 95.7 ± 39.5 | 86.8 ± 36.7 | <0.001 | 96.0 ± 36.0 | 86.7 ± 36.6 | <0.001 | 0.256 |
| <190 mg/dL, n (%) | 87,742 (30.8) | 523 (62.6) | <0.001 | 524 (62.9) | 520 (62.4) | 0.839 | 0.010 |
| ≥190 mg/dL, n (%) | 2,256 (0.8) | 10 (1.2) | 0.187 | 10 (1.2) | 10 (1.2) | 1 | <0.001 |
| NT-proBNP [Mass/volume] in Serum, Plasma or Blood | 2481.4 ± 6089.6 | 660.0 ± 1154.4 | 0.021 | 584.3 ± 791.5 | 680.6 ± 1168.9 | 0.585 | 0.096 |
| 0–300 pg/mL, n (%) | 6.412 (2.2) | 36 (4.3) | <0.001 | 45 (5.4) | 34 (4.1) | 0.205 | 0.062 |
| 300–600 pg/mL, n (%) | 2,938 (1.0) | 10 (1.2) | 0.636 | 10 (1.2) | 10 (1.2) | 1 | <0.001 |
| 600–900 pg/mL, n (%) | 1,771 (0.6) | 10 (1.2) | 0.035 | 10 (1.2) | 10 (1.2) | 1 | <0.001 |
| 900–1200 pg/mL, n (%) | 1,312 (0.5) | 10 (1.2) | 0.002 | 10 (1.2) | 10 (1.2) | 1 | <0.001 |
| ≥ 1200 pg/mL, n (%) | 6,258 (2.2) | 10 (1.2) | 0.049 | 15 (1.8%) | 10 (1.2) | 0.314 | 0.049 |
| Creatinine [Mass/volume] in Serum, Plasma or Blood | 1.2 ± 4.7 | 1.0 ± 0.6 | 0.122 | 1.2 ± 5.6 | 1.0 ± 0.6 | 0.249 | 0.064 |
| 0–1.30 mg/dL, n (%) | 141,640 (49.7) | 611 (73.1) | <0.001 | 603 (72.4) | 608 (73.0) | 0.783 | 0.013 |
| ≥ 1.30 mg/dL, n (%) | 38,402 (13.5) | 100 (12.0) | 0.202 | 106 (12.7) | 99 (11.9) | 0.602 | 0.026 |
| Hemoglobin A1c/Hemoglobin total in Blood | 5.6 ± 0.6 | 5.6 ± 0.6 | 0.718 | 5.6 ± 0.5 | 5.6 ± 0.6 | 0.052 | 0.129 |
| 0–3 %, n (%) | 14 (0.0) | 0 (0) | 0.839 | 0 (0) | 0 (0) | – | – |
| ≥ 3 %, n (%) | 65,768 (23.1) | 458 (54.8) | <0.001 | 452 (54.3) | 455 (54.6) | 0.883 | 0.007 |
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