Posture recognition to reduce the insertable cardiac monitor clinical review burden

Q: What is the clinical evidence from this study?

Study design: Observational. Population: Patients with insertable cardiac monitors (ICMs) and adjudicated true arrhythmia episodes (n=336). Intervention: Accelerometer-based posture-sensing algorithm for insertable cardiac monitors. Primary outcome: Proportion of true arrhythmia episodes (tachycardia, bradycardia, and pause) associated with steady vs. unsteady posture changes at arrhythmia onset.

Q: What does this research mean for the field?

Accelerometer-based posture sensing in insertable cardiac monitors reveals that 85.1% of tachycardia, 94.5% of bradycardia, and 95.2% of pause episodes occur during steady posture, enabling prioritization of the minority of episodes associated with unsteady posture changes. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

Rakesh Gopinathannair; Dale Yoo; Harish Manyam; Devi G. Nair; Roy S. Gardner; Nima Badie; Fujian Qu; Fady Dawoud; Dhanunjaya Lakkireddy

doi:10.1016/j.hroo.2025.04.013

May 9, 2025Heart Rhythm O2Open Access

Posture recognition to reduce the insertable cardiac monitor clinical review burden

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Key result

ICM posture sensing classifies ~85% to ~95% of arrhythmias as steady to streamline review.

n=336

Why the study?

Insertable cardiac monitors continuously record and automatically transmit detected arrhythmia clips to an online patient care network for clinician review, creating a clinical review burden that posture recognition aims to reduce.

Does an accelerometer-based posture-sensing algorithm in insertable cardiac monitors identify true arrhythmia episodes without unsteady posture changes to potentially reduce the clinical review burden in patients undergoing ambulatory arrhythmia monitoring?

Key Points

To evaluate an accelerometer-based posture-sensing algorithm in insertable cardiac monitors that classifies posture changes at arrhythmia onset to prioritize clinically urgent episodes.
Retrospectively analyzed 600 randomly selected Abbott Assert-IQ devices from the Merlin.net patient care network, including 200 with tachycardia episodes and 400 with bradycardia or pause episodes.
Tracked posture changes at arrhythmia onset using embedded 3-dimensional accelerometers to categorize events as steady or unsteady (sequential downward posture change).
Evaluated up to the first 5 manually adjudicated true episodes per patient across 336 patients (mean age 69.8 ± 14.7 years, 58.1% men).
Unsteady posture changes occurred in only 14.9% of tachycardia, 5.5% of bradycardia, and 4.8% of pause episodes, identifying high-priority clinical events.
Most episodes did not involve unsteady posture changes, including 85.1% of tachycardia, 94.5% of bradycardia, and 95.2% of pause episodes.
No significant differences in demographics or device programming were observed between unsteady and steady posture groups for tachycardia (P > .51) or bradycardia and pause episodes (P > .17).

Study Design

Type

Observational (n=336)

Structured PICO

Does an accelerometer-based posture-sensing algorithm in insertable cardiac monitors identify true arrhythmia episodes without unsteady posture changes to potentially reduce the clinical review burden in patients undergoing ambulatory arrhythmia monitoring?

P

Population

336 patients (mean age 69.8 years, 58.1% male) with Assert-IQ insertable cardiac monitors and at least one manually adjudicated true arrhythmia episode (tachycardia, bradycardia, or pause).

E

Exposure

Novel ultralow-power 3-dimensional accelerometer-based posture-sensing algorithm embedded in the Assert-IQ ICM to classify subcutaneous electrograms (EGMs) by posture changes at arrhythmia onset (steady upright, steady reclined, steady lying down, or unsteady).

O

Outcome

Distribution of posture changes (steady vs unsteady) at the onset of manually adjudicated true tachycardia, bradycardia, and pause episodes.surrogate

An accelerometer-based posture-sensing algorithm in insertable cardiac monitors identified that 85.1% to 95.2% of true arrhythmia episodes occur without unsteady posture changes, enabling prioritization of potentially dangerous unsteady episodes to streamline clinical review.

Limitations

Inability to differentiate changes between standing and sitting upright (without reclining)
Some posture measurements could not be classified (i.e., in between upright and reclined)
Retrospective evaluation requiring further studies to evaluate potential impact on patient diagnosis and clinical response
Only up to the first 5 episodes per patient adjudicated as true were included in the analysis to limit bias by large episode-volume patients
Further studies are needed to evaluate the potential impact on patient diagnosis and clinical response

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Implication

May reduce ICM alert review burden via posture sensing; leaves open need for outcome trials before adoption.

Abstract

Insertable cardiac monitors (ICMs) enable the ambulatory diagnosis of unexplained symptoms associated with cardiac arrhythmias, including tachycardia, bradycardia, and pause/asystole. ICMs continually monitor the subcutaneous electrogram (EGM) and record clips of detected arrhythmias for automatic transmission to an online patient care network (PCN) for clinician review.

Discussion

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Cite This Study

Gopinathannair et al. (2025) conducted an observational in Patients with insertable cardiac monitors (ICMs) and adjudicated true arrhythmia episodes (n=336). Accelerometer-based posture-sensing algorithm for insertable cardiac monitors was evaluated on Proportion of true arrhythmia episodes (tachycardia, bradycardia, and pause) associated with steady vs. unsteady posture changes at arrhythmia onset. Accelerometer-based posture sensing identified that 85.1% of tachycardia, 94.5% of bradycardia, and 95.2% of pause episodes had steady posture changes, allowing reduced review priority.

synapsesocial.com/papers/6ae08d42062155b7bf5fccf3 https://doi.org/10.1016/j.hroo.2025.04.013

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Posture recognition to reduce the insertable cardiac monitor clinical review burden

Key Points

Study Design

Structured PICO

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Posture recognition to reduce the insertable cardiac monitor clinical review burden

Key Points

Study Design

Structured PICO

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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