Early detection of deterioration in COVID-19 patients by continuous ward respiratory rate monitoring: a pilot prospective cohort study - Rivas, Eva; López-Baamonde, Manuel; Sanahuja, Josep; Del Rio, Elena; Ramis, Tomeu; Recasens, Anna; López, Antonio; Arias, Marilyn; Kampakis, Stylianos; Lauteslager, Timo; Awara, Osama; Mascha, Edward J.; et al. (Frontiers in Medicine, 2023)
Background: Tachypnea is among the earliest signs of pulmonary decompensation.Contactless continuously respiratory rate monitoring might be useful in isolated COVID-19 patients admitted in wards. We therefore aimed to determine whether continuous monitoring of respiratory patterns in hospitalized patients with COVID-19 predicts subsequent need for increased respiratory support.Methods: Single-center pilot prospective cohort study in COVID-19 patients who were cared for in routine wards. COVID-19 patients who have at least one escalation of pulmonary management were matched to 3 non-escalated patients. Contactless respiratory monitoring was instituted after patients enrolled, and continued for 15 days unless hospital discharge, initiation of invasive mechanical ventilation, or death occurred.Respiratory rate data from the continuous monitor was not available to clinicians. The exposures were respiratory features over rolling periods of 30 minutes, 24 hours, and 72 hours before respiratory care escalation. The primary outcome was a subsequent escalation in ventilatory support beyond a Venturi mask.Results: Among 125 included patients, 13 exhibited at least one escalation and were each matched to 3 non-escalated patients. A total of 28 escalation events were matched to 84 non-escalation episodes. The 30-min mean respiratory rate in escalated patients was 23 breaths per minute (bpm) ranging from 13 to 40 bpm, similar to the 22 bpm in non-escalated patients, although with less variability (range 14 to 31 bpm). However, higher respiratory rate variability, especially skewness over 1 day, was associated with higher incidence of an escalation event. Our overall model, based on continuous data,