Data presented at ACC.26 further demonstrate the benefits of iRhythm’s Zio® ambulatory ECG portfolio across multiple patient populations as company launches new digital education platform

• Data presented at ACC.26 demonstrate a high prevalence of clinically actionable arrhythmias across CKM patient populations using the Zio^® ambulatory ECG portfolio.^1,2
• Chief Medical Officer Mintu Turakhia, MD, MS, delivered the 57th Annual Louis F. Bishop Keynote on scaling AI in cardiology and translating advances into clinical practice.
• iRhythm Academy launch expands access to clinician education at scale in ambulatory cardiac monitoring as the field continues to advance.

SAN FRANCISCO, March 30, 2026 (GLOBE NEWSWIRE) — iRhythm Holdings, Inc. (NASDAQ: IRTC) announced results from three retrospective analyses presented at the American College of Cardiology (ACC) 2026 Annual Scientific Sessions in New Orleans, March 28–30, 2026, that add to the growing body of clinical evidence supporting the benefits of its Zio^® ambulatory ECG monitoring service across patient populations.^1,2 The data provide insights into the timing and incidence of clinically relevant arrhythmias and highlight opportunities to improve care for patients along the cardiovascular-kidney-metabolic (CKM) continuum.

iRhythm also highlighted its leadership in advancing AI in cardiology, with Chief Medical Officer Mintu Turakhia, MD, MS, Clinical Professor of Medicine at Stanford University, delivering the 57th Annual Louis F. Bishop Keynote, titled “Scaling AI in Cardiology: Moving From Paper and Podium to Product,” and announced the launch of iRhythm Academy, a clinician education platform.

High Prevalence of Clinically Actionable Arrhythmias Across the CKM Continuum, Highlighting Increased Risk for Arrhythmias in this Patient Population

Two abstracts presented at ACC.26 reported the results of retrospective analyses of the incidence of arrhythmias in patients across the CKM disease continuum.^3,4 Each study utilized data from the iRhythm clinical data warehouse linked to commercial fee-for-service and government-sponsored plans claims data. Findings from both studies enhance the understanding of how CKM risk factors influence the incidence of arrhythmias, highlighting that clinically relevant arrhythmias are not limited to patients with more advanced comorbid conditions or disease states.

Arrhythmias in Patients with Diabetes and Chronic Kidney Disease Detected by Long-Term Ambulatory ECG Monitoring³ (Abstract #1474-105) evaluated the prevalence of arrhythmias detected in a cohort of 657,147 individuals in the U.S. who received 14-day continuous ambulatory monitoring linked to commercial fee-for-service or Medicare Advantage claims. The cohort had a mean age of 59 years and was 58% female. Clinically actionable arrhythmias were more commonly identified in patients with chronic kidney disease (CKD), with or without diabetes:

• 11% of patients had diabetes, 4% had chronic kidney disease, and 4% had both conditions—together representing nearly 20% of the overall cohort.
• After accounting for differences in age, clinically actionable arrhythmias affected 48% of patients with CKD and 47% of patients with both diabetes and CKD, compared with 39% of patients with diabetes alone and 35% of patients with neither condition.
• Arrhythmia risk increased across kidney-metabolic phenotypes, highest in CKD (with or without diabetes), with diabetes alone also increasing risk—highlighting the value of targeted rhythm monitoring in patient populations at higher risk for arrhythmia.

Incidence of Arrhythmias in Patients with Obesity Detected by Long-Term Ambulatory ECG Monitoring⁴ (Abstract # 1403-107) evaluated the prevalence of arrhythmias of arrhythmias detected 162,531 individuals in the U.S. who received 14-day long-term continuous monitoring (LTCM) with Zio and where BMI or weight-related diagnostic codes were available. The cohort had a mean age of 58 years and was 65% female. Higher body weight was associated with greater likelihood of atrial fibrillation (AF) detection:

• The prevalence of detected AF increased with weight, rising from 4.5% in normal/underweight patients to 6.5% in patients with severe obesity.
• After accounting for differences in age, sex, and comorbidities, patients with severe obesity had nearly threefold higher odds of AF detection compared with normal/underweight patients (adjusted odds ratio of 2.8).
• Nearly two-thirds of patients in this cohort had obesity or severe obesity, highlighting excess weight as a common and potentially modifiable risk factor for AF.

Expanding Evidence Highlights the Opportunity for Earlier Detection and Diagnosis

Data presented at ACC.26 build on prior real-world evidence demonstrating that arrhythmias are common, early, and often silent across cardiometabolic patient populations. Findings from two large-scale, real-world studies^5,6 presented at the American Diabetes Association’s 85th Scientific Sessions in June 2025 (ADA 2025) demonstrated that arrhythmias preceded 43% of diabetes and 59% of CKD cases in the study population. Many patients in one study subsequently developed clinically actionable arrhythmia or major cardiovascular events. Three large-scale real-world analyses presented at the American Heart Association Scientific Sessions 2025 (AHA 2025)^7-9 similarly revealed arrhythmia risk emerging earlier across the CKM syndrome continuum. These findings are extended by ACC.26 data demonstrating that the Zio ambulatory ECG service has a high diagnostic yield in these patient populations,^3,4 enabling earlier identification of clinically actionable arrhythmias.

With an estimated 27 million people in the U.S. at risk for undiagnosed arrhythmias each year,¹⁰ iRhythm is committed to reaching patients sooner and has been advancing a data-driven, proactive cardiac monitoring approach deployed with healthcare systems focused on population health management and value-based care goals. Building on this foundation, in 2025, iRhythm announced a collaboration with Lucem Health to apply predictive AI¹¹ to flag patients at elevated risk for arrhythmias, including those with diabetes and CKD, enabling more targeted selection of patients for proactive monitoring and more timely diagnosis and clinical decision-making.

Scaling AI in Cardiology and Expanding Education at Scale

In addition to the data presentations at ACC.26, Mintu Turakhia, MD, MS, Chief Medical and Scientific Officer and EVP, Advanced Technologies at iRhythm, and Clinical Professor of Medicine at Stanford University, delivered the 57th Annual Louis F. Bishop Keynote, titled “Scaling AI in Cardiology: Moving From Paper and Podium to Product.” The keynote addressed the gap between advances in artificial intelligence and their translation into routine cardiovascular care.

Drawing on iRhythm’s platform, its application of advanced AI in cardiac monitoring, and 20-year history, Dr. Turakhia emphasized how AI must function as an infrastructural backbone—integrating multiple streams of data, extending AI to new clinical domains, operationalized within clinical workflows, and accountable for real-world outcomes.

“The primary barrier to impact is no longer technical development or model performance — most AI across diagnostics, clinical decision support, and other domains work well. We need to think of these tools not as point solutions or standalone tests, but rather as critical clinical infrastructure and integrated systems that are safely and responsibly deployed,” said Dr. Turakhia.

iRhythm also launched iRhythm Academy, an education platform offering interactive courses, webinars, publications, and micro-learning modules for healthcare professionals focused on ambulatory cardiac monitoring, extending access to education at scale as the field continues to advance.

iRhythm also announced an upcoming update to the MyZio^® mobile app, which supports patients throughout their ECG monitoring journey with Zio, with the addition of Spanish-language functionality to support patient accessibility.¹²

Data presented at ACC.26 build on iRhythm’s comprehensive clinical evidence program, encompassing more than 135 original research manuscripts, insights derived from over 3 billion hours of curated heartbeat data, and nearly 12 million patient reports since the company’s inception¹³—underscoring its ongoing commitment to expanding evidence that supports improved patient outcomes.

About iRhythm Holdings
iRhythm is a leading digital health care company that creates trusted solutions that detect, predict, and prevent disease. Combining wearable biosensors and cloud-based data analytics with powerful proprietary algorithms, iRhythm distills data from millions of heartbeats into clinically actionable information. Through a relentless focus on patient care, iRhythm’s vision is to deliver better data, better insights, and better health for all.

Forward-Looking Statements
This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended, and the Private Securities Litigation Reform Act of 1995. These statements can be identified by words such as “anticipate,” “estimate,” “expect,” “intend,” “will,” “may,” “project,” “plan,” “believe,” “target,” and similar expressions that relate to future events or outcomes.

Forward-looking statements in this press release include, but are not limited to, statements regarding the significance and potential impact of the data presented; the clinical utility and performance of iRhythm’s Zio® ambulatory ECG monitoring service; the potential to enable earlier detection and diagnosis of arrhythmias; the application of artificial intelligence and predictive analytics to identify patients at elevated risk for arrhythmias; and the ability to expand access to clinician education and improve patient care through initiatives such as iRhythm Academy.

These statements are based on current assumptions and expectations and are subject to risks and uncertainties that could cause actual results to differ materially. These risks and uncertainties include, among others, the timing, interpretation, and acceptance of clinical data; the ability to translate findings into clinical practice; regulatory and reimbursement developments; market adoption of iRhythm’s products and services; and the risks described in the section entitled “Risk Factors” in iRhythm’s most recent filings with the Securities and Exchange Commission, including its Forms 10-K and 10-Q.

These forward-looking statements speak only as of the date of this press release, and iRhythm undertakes no obligation to update them, except as required by law.

Media Contact:
Kassandra Perry
mediarelations@irhythmtech.com

Investor Contact:
Stephanie Zhadkevich
investors@irhythmtech.com

1. The Zio AT device is not intended for use in critical care patients because the reporting timeliness is not consistent with life-threatening arrhythmias such as ventricular fibrillation. Refer to Zio AT Clinical Reference Manual for additional information.
2. Do not use Zio AT for patients with symptomatic episodes where variations in cardiac performance could result in immediate danger to the patient or when real-time or in-patient monitoring should be prescribed.
3. Ashburner JM et al. “Arrhythmias in Patients with Diabetes and Chronic Kidney Disease Detected by Long-Term Ambulatory ECG Monitoring.” American College of Cardiology 2026 Annual Scientific Session & Expo, 2026. New Orleans, Louisiana.
4. Battisti AJ. “Incidence of Arrhythmias in Patients with Obesity Detected by Long-Term Ambulatory ECG Monitoring.” American College of Cardiology 2026 Annual Scientific Session & Expo, 2026. New Orleans, Louisiana.
5. “Incidence of Cardiac Arrhythmias in Patients with Diabetes: a Real-World Study.” American Diabetes Scientific Sessions, 2025; Chicago, Illinois.
6. Russo P et al. “Incidence and Timing of Major Arrhythmias in T2D and CKD:A Real-World Analysis.” American Diabetes Scientific Sessions, 2025; Chicago, Illinois.
7. Russo P et al. “Onset of Arrhythmias in the CKM Continuum: Real-World Insights From a National Cohort.” American Heart Association Scientific Sessions, 2025; New Orleans, Louisiana.
8. Russo P et al. “CKD and CKM Syndrome: Accelerated Progression to Arrhythmias in a National Cohort.” American Heart Association Scientific Sessions, 2025; New Orleans, Louisiana.
9. Russo P et al. “Arrhythmias as Early Predictors of Chronic Kidney Disease: Real-World Evidence From a National Cardio-Kidney-Metabolic Cohort.” American Heart Association Scientific Sessions, 2025; New Orleans, Louisiana.https://www.jacc.org/doi/10.1016/S0735-1097%2823%2902786 9 https://www.ajmc.com/view/assessment-of-variation-in-ambulatory-cardiac-monitoring-among-commercially-insured-patients
10. iRhythm internal estimate based on analysis of public and proprietary sources, including U.S. Census Bureau data, CDC healthcare utilization data, Medicare Public Use Files, IQVIA, Komodo Health, Definitive Healthcare, and peer-reviewed literature on arrhythmia prevalence, symptom presentation, and diagnostic pathways. Full source list available upon request.
11. Predictive Arrhythmia Solutions does not represent functionality of any Zio branded medical device.
12. The MyZio^® mobile app for patients is not a medical device and is not intended to diagnose, treat, cure, or prevent any disease.
13. Data on file. iRhythm Technologies, 2025.