Document Type

Poster

Publication Date

4-30-2026

Comments

Presented at the 2026 International Anesthesia Research Society (IARS) Annual Meeting.

Abstract

Introduction & Objectives

- Mortality within 30 days after major surgery is the third leading cause of death worldwide.1

- Post-operative adverse events leading to mortality include pneumonia, respiratory failure, sepsis, kidney failure, pulmonary embolism, and major cardiac events.2,3

- Early warning signs of clinical deterioration are commonly missed due to infrequent clinical assessments, delaying timely diagnosis and intervention.2,4

- On the general hospital floors, vital signs are monitored every 4 to 8 hours, suggesting patients could be unmonitored 96% of their hospital stay.1

- Changes in respiratory rate (RR) are the earliest and most sensitive indicator of clinical deterioration, yet it is often inaccurately measured.2,5,6

- Early and accurate detection of worsening respiratory function leads to timely initiation of appropriate therapy and improved clinical outcomes.1,3

- RTM Vital Signs is developing a wearable wireless acoustic RMS in collaboration with Thomas Jefferson University (TJU) to continuously measure RR, tidal volume, minute ventilation, breathing pattern, apnea duration, and pulse rate. The system uses machine learning/artificial intelligence algorithms designed to detect and predict clinical deterioration prior to a respiratory related adverse event.

- Objective: To address the clinical need for early and accurate detection of clinical deterioration by comparing RMS measurements of RR to an FDA-cleared respiratory monitoring device (ExSpiron 2xi).

Language

English

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