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iRhythm Technologies Announces Publication of Large-Scale Study in Heart Rhythm and New Data Presented at AHA Scientific Sessions 2025

1. Zio LTCM monitoring detects more arrhythmias than traditional methods. 2. Home application of Zio devices shows high compliance and data quality. 3. Real-world data emphasizes early arrhythmia detection in at-risk populations. 4. Cardiovascular risks escalate in CKM syndrome, warranting proactive monitoring. 5. iRhythm's solutions aim to prevent serious outcomes through early detection.

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Why Bullish?

The article highlights the superiority of iRhythm's monitoring products, indicating potential increased demand for Zio LTCM. Historical examples show that advances in medical technology often lead to market growth for companies like IRTC.

How important is it?

The findings and innovations discussed position iRhythm strongly in a growing market, increasing its relevance to investors. The potential for higher adoption rates can significantly impact share price due to expected improvements in financial performance.

Why Long Term?

As iRhythm continues to demonstrate the effectiveness of Zio LTCM, it is likely to establish itself as a standard in arrhythmia detection, hence improving future revenues. A similar trend was observed with other healthcare innovators in chronic disease management.

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November 11, 2025 08:05 ET  | Source: iRhythm Real-world data across more than 1 million patients published in Heart Rhythm show that 24–48-hour monitoring can miss actionable arrhythmias and highlights the value of iRhythm’s Zio® long-term continuous monitoring (LTCM)– even in patients with frequent (i.e., daily) symptoms1Data from more than 742,000 patients presented at the American Heart Association (AHA) Scientific Sessions 2025 confirm that at-home self-application and activation of Zio 14-day patch-based LTCM devices achieve high compliance, strong engagement, and data quality comparable to in-clinic application2Additional large-scale real-world analyses also presented at AHA 2025 provide expanded insights into CKM/CKD risk and reveal earlier arrhythmia detection supporting proactive monitoring in at-risk populations3,4,5 SAN FRANCISCO, Nov. 11, 2025 (GLOBE NEWSWIRE) --  iRhythm Technologies, Inc. (NASDAQ: IRTC) announced the publication of “Relationship of Symptom Frequency and Symptom-Rhythm Correlation to Arrhythmia Type and Time to Detection: Insights from Ambulatory ECG Monitoring in Over 1 Million Patients,”1 in Heart Rhythm, the journal of the Heart Rhythm Society, featuring real-world insights from more than one million patients monitored with iRhythm’s Zio® long-term continuous monitoring (LTCM) service. The study examined how symptom frequency influences time to arrhythmia detection and the correlation between symptoms and arrhythmia events, underscoring the advantages of long-term continuous monitoring with the Zio LTCM service. Separately, new data presented at the American Heart Association (AHA) Scientific Sessions 2025 include real-world evidence demonstrating successful at-home patient application and activation of the Zio LTCM device,2 and independent large-scale analyses across cardio-kidney-metabolic (CKM) and chronic kidney disease (CKD) populations highlighting earlier arrhythmia detection and risk emergence across the disease continuum.3-5 Real-World Evidence Published in Heart Rhythm Journal The newly published findings in Heart Rhythm draws on data from more than 1.1 million patients who used iRhythm’s Zio LTCM and revealed that short-term (24–48-hour) monitoring, such as with Holter, can miss actionable arrhythmias—even in patients reporting daily symptoms—and that patient-reported symptoms were infrequently associated with arrhythmia events.1 Although prior studies including CAMELOT6 and AVALON7 have shown that LTCM yields greater arrhythmia diagnosis and less retesting, 24-48-hour Holter monitoring is often preferred by clinicians and payors for frequent symptoms despite limited evidence linking symptom frequency to optimal monitoring duration. In this new retrospective cohort study of 1.1 million patients who used iRhythm’s Zio LTCM, 20.8% had reported symptoms more than once per day. Nearly two-thirds (64%) of daily-symptom patients with actionable arrhythmias were undetected in the first 48 hours, and the mean time to first detected arrhythmia exceeded 48 hours for all arrhythmia types, regardless of symptom frequency. Symptom–Rhythm Correlation (SRC) was notably low for most arrhythmias, with less than 20% of patients documenting a symptom coinciding with an arrhythmic episode. These findings highlight the clinical value of Zio LTCM up to 14 days for identification of arrhythmias, challenging the limitations of short-duration Holter monitoring still prevalent in clinical practice and payer policy. “These findings challenge the long-held clinical assumptions and payor guidelines that frequent symptoms justify short-duration monitoring,” said Mintu Turakhia, MD, Chief Medical and Scientific Officer and EVP of Advanced Technologies at iRhythm. “They reinforce the limitations of 24–48-hour Holter monitoring, even if patients report symptoms multiple times a day during wear, and highlight the value of Zio long-term continuous monitoring up to 14 days. iRhythm’s real-world data are contributing evidence that can help guide both clinical practice and payer policy.” Data Presented at AHA 2025 Patient Home Enrollment Pathway for Ambulatory Cardiac Monitoring (“Compliance, ECG Quality, and Engagement With a Smartphone App in Patients With In-Clinic Compared With Home-Based, Self-Applied Long-Term Continuous ECG Patch Monitors” 2 study) Presented at the American Heart Association (AHA) Scientific Sessions 2025, this analysis evaluated iRhythm’s patient home enrollment pathway for its Zio® monitoring service, demonstrating that patients can successfully self-apply and activate the Zio 14-day patch-based LTCM device shipped directly to their home, achieving high compliance with the prescribed wear duration and data quality comparable to in-clinic application. Among the analysis of 742,268 Zio LTCM devices, researchers compared in-clinic and home-based applications using iRhythm’s home enrollment (HE) pathway where monitoring devices are shipped directly to their home. Median wear time and percent analyzable ECG time were high and comparable across groups (>13.8 days and >98%, respectively), and early wear terminations were infrequent (≤2% for both groups). MyZio mobile app use was more common among HE patients (52% vs. 17%) and associated with fewer early terminations, greater analyzable time, and higher rate of compliance with return of devices for analysis within 45 days (93% vs. 80%). Earlier Arrhythmia Risk Across the CKM Syndrome Continuum In 2023, the AHA introduced the cardiovascular-kidney-metabolic (CKM) framework to describe how metabolic dysfunction, kidney disease, and cardiovascular disease interact as stages of a single syndrome, emphasizing early intervention to prevent progression to advanced organ failure.8 Three large-scale real-world analyses presented at AHA 2025 provide new insights and reveal arrhythmia risk emerging earlier across the CKM syndrome continuum.3-5 The analyses, encompassing data from more than 10 million patients, provide new insights into how and when arrhythmias develop across the CKM syndrome continuum. The data show that arrhythmias can occur before or during early CKM syndrome stages, with risk accelerating as metabolic or kidney disease progresses. While arrhythmias including atrial fibrillation are well recognized as complications after development or progression to advanced CKD,9 these findings identify arrhythmias as a clinically measurable signal of elevated CKM syndrome risk and strengthen the case for earlier rhythm assessment to identify at-risk patients before advanced complications occur. Arrhythmias as Early Predictors of Chronic Kidney Disease (CKD) (“Arrhythmias as Early Predictors of CKD: Real-World Evidence from a National Cardio-Kidney-Metabolic Cohort”5 study)Among more than 8 million CKD patients, arrhythmias—primarily atrial fibrillation (AF)—occurred before CKD diagnosis in 58 percent of patients, on the same day in 14 percent, and after diagnosis in 28 percent. AF was the most common arrhythmia (75–83 percent). Patients with AF before CKD showed high cardiometabolic burden: 68 percent had hypertension, 45 percent had a major adverse cardiovascular event (MACE), and 94 percent had at least one metabolic comorbidity. These findings suggest that arrhythmias may serve as early indicators of CKD progression. CKD and CKM Syndrome: Accelerated Progression to Arrhythmias(“CKD and CKM Syndrome: Accelerated Progression to Arrhythmias in a National Cohort”4 study)In a cohort of 3.5 million adults with obesity, 26,478 (0.8 percent) progressed to CKD; within four months of CKD onset, 4 percent developed a major arrhythmia, most commonly atrial fibrillation (65 percent) and supraventricular tachycardia (14 percent). Seventy percent of arrhythmias occurred in CKD Stage 3, identifying kidney dysfunction as a potential inflection point in arrhythmia risk and highlighting the value of enhanced rhythm surveillance as kidney function declines. Onset of Arrhythmias Across the CKM Continuum (“Onset of Arrhythmias in the CKM Continuum: Real-World Insights from a National Cohort”3 study)Across CKM stages, arrhythmia incidence increased from 6.3 percent after Stage 1 to 9.2 percent after Stage 2 and 12.5 percent after Stage 3. Younger patients (ages 18–34) accounted for 41% of arrhythmia cases identified after Stage 1, suggesting earlier onset in this population. These findings underscore the potential value of early arrhythmia monitoring among individuals at risk of CKM progression. These findings expand understanding of how arrhythmias evolve within the CKM syndrome continuum and strengthen the case for earlier rhythm assessment in at-risk populations. Consistent with these findings, other published data7 in patients with Type 2 diabetes—a key metabolic condition within the CKM syndrome continuum—show that arrhythmias are often first detected in acute care settings, contributing to higher healthcare costs, and may be mitigated through early detection using ambulatory cardiac monitoring. Redefining Cardiac Care Through Proactive Detection and Predictive Insight With an estimated 27 million people in the U.S. at risk for undiagnosed arrhythmias,10 iRhythm remains committed to reaching these patients sooner through scalable, clinically validated solutions. The company is advancing a new standard of proactive, data-driven cardiac monitoring designed to identify arrhythmias before they lead to stroke, hospitalization, or other serious outcomes. iRhythm’s collaboration with Lucem Health, announced earlier this year, represents the next step in that evolution—combining iRhythm’s proactive efforts with its proven ECG monitoring service with Lucem’s AI-powered risk stratification to more precisely identify individuals at risk. Early pilot testing conducted by iRhythm, in collaboration with Lucem Health, suggests promising improvement in targeting patient populations with elevated arrhythmia risk and enabling earlier clinical engagement with greater precision.11 Together, the data published in Heart Rhythm and those presented at AHA 2025 build on iRhythm’s comprehensive clinical evidence program, encompassing more than 125 original research manuscripts,12 insights derived from over 2 billion hours of curated heartbeat data13 and nearly 12 million patient reports posted since the company’s inception—underscoring the company’s ongoing commitment to expanding evidence that supports improved patient outcomes. About iRhythm TechnologiesiRhythm 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. Media Contact:Kassandra Perrymediarelations@irhythmtech.com Investor Contact:Stephanie Zhadkevichinvestors@irhythmtech.com 1 Battisti AJ, et al. Relationship of Symptom Frequency and Symptom-Rhythm Correlation to Arrhythmia Type and Time to Detection: Insights from Ambulatory ECG Monitoring in Over 1 Million Patients. Heart Rhythm. 2025 Nov 6:S1547-5271(25)03049-8. doi: 10.1016/j.hrthm.2025.11.007. Epub ahead of print.2 Ashburner JM et al. Compliance, ECG Quality, and Engagement With a Smartphone App in Patients With In-Clinic Compared With Home-Based, Self-Applied Long-Term Continuous ECG Patch Monitors. American Heart Association Scientific Sessions, November 10, 2025; New Orleans, Louisiana.3 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.4 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.5 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.6 Reynolds MR, et al. Comparative effectiveness and healthcare utilization for ambulatory cardiac monitoring strategies in Medicare beneficiaries. Am Heart J. 2024 Mar;269:25-347 Russo P et al. Clinical and Economic Burden of Cardiac Arrhythmias in Patients with Type 2 Diabetes. J Health Med Econ Vol. 11 No. 1:151    8 Khan SS et al. AHA Presidential Advisory on Cardiovascular-Kidney-Metabolic Health and Disease. Circulation. 2023;148:e202–e221. 9 Turakhia MP et al. Chronic kidney disease and arrhythmias: conclusions from a KDIGO Controversies Conference. European Heart Journal, 2018; 39(24): 2314–2325.10 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 The predictive-AI solution does not represent the functionality of any Zio branded medical device.12 Data on file. iRhythm Technologies, 2025.13 Data on file. iRhythm Technologies, 2024.

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