The current standard of care for respiratory monitoring outside of the operating room (OR) and intensive care unit (ICU) is nursing attention with pulse oximetry, and this is NOT working¹ because:
[1] Avoiding AE secondary to opioid-induced respiratory depression. JONA, Vol.46, No.2, pp 87-94
[2] Anderson LW et. al. Acute respiratory compromise on inpatient wards in the US: Incidence, outcomes and factors associated with in-hospital mortality. Resuscitation 2016; 105:123-9
[3] Sun Z, Sessler DI, Dalton JE, et al. Postoperative hypoxemia is common and persistent: a prospective blinded observational study. Anesth Analg. 2015;121:709–715.
[4] Anderson LW et. al. The prevalence and significance of vital signs prior to in-hospital cardiac arrest. Resuscitation 2016;98:112-7 and 75% of rescue events are respiratory in nature
[5] Reference: Behrendt CE. Acute respiratory failure in the United States: incidence and 31-day survival. Chest 2000;118:1100–5.18.
[6] Stefan MS, Shieh MS, Pekow PS, et al. Epidemiology and outcomes of acute respiratory failure in the United States, 2001 to 2009: a national survey. J Hosp. Med 2013;8:76–82
Linshom Medical is PREDICTIVE of respiratory decline and notifies the healthcare team when interventions are easy and inexpensive.
Linshom Medical is the first to deliver an operating room-quality respiratory profile to the patient’s bedside for continuous, predictive respiratory monitoring (CPRM). This wearable, FDA-cleared sensor provides advance notice of respiratory decline, helping to avoid costly rapid response activations, rescue events (codes), ICU transfers, and death.
Wearable, Non-Invasive, Safe. Follows current, established workflow in the post-anesthesia care unit (PACU), emergency department (ED), and on the general care floor (GCF).
Linshom Medical is the only device capable of practically delivering the trend of relative Tide Volume (rTV) to the patient’s bedside.
RR and rTV provide advance notice to the care team and help solve the current false alarm problem.
Linshom Medical is able to monitor and display respiratory rate and trend of tidal volume data in real-time and does not suffer from high cost or motion artifacts.
– Ashish K. Khanna, MD, MS, FCCP, FCCM, FASA
Wake Forest School of Medicine. Professor and Vice-Chair of Research, Director of Perioperative Outcomes and Informatics Collaborative (POIC), Department of Anesthesiology, Section on Critical Care Medicine.
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