Early detection of deterioration in COVID-19 patients by continuous ward respiratory rate monitoring: a pilot prospective cohort study.

COVID-19 continuous monitoring hospitalization ward respiratory failure respiratory rate

Journal

Frontiers in medicine
ISSN: 2296-858X
Titre abrégé: Front Med (Lausanne)
Pays: Switzerland
ID NLM: 101648047

Informations de publication

Date de publication:
2023
Historique:
received: 20 06 2023
accepted: 12 10 2023
medline: 29 11 2023
pubmed: 29 11 2023
entrez: 29 11 2023
Statut: epublish

Résumé

Tachypnea is among the earliest signs of pulmonary decompensation. Contactless continuous 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. Single-center pilot prospective cohort study in COVID-19 patients who were cared for in routine wards. COVID-19 patients who had at least one escalation of pulmonary management were matched to three 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. Clinicians were blinded to respiratory rate data from the continuous monitor. The exposures were respiratory features over rolling periods of 30 min, 24 h, and 72 h before respiratory care escalation. The primary outcome was a subsequent escalation in ventilatory support beyond a Venturi mask. Among 125 included patients, 13 exhibited at least one escalation and were each matched to three 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 escalation events. Our overall model, based on continuous data, had a moderate accuracy with an AUC 0.81 (95%CI: 0.73, 0.88) and a good specificity 0.93 (95%CI: 0.87, 0.99). Our pilot observational study suggests that respiratory rate variability as detected with continuous monitoring is associated with subsequent care escalation during the following 24 h. Continuous respiratory monitoring thus appears to be a valuable increment over intermittent monitoring. Our study was the initial evaluation of Circadia contactless respiratory monitoring in COVID-19 patients who are at special risk of pulmonary deterioration. The major limitation is that the analysis was largely

Sections du résumé

Background UNASSIGNED
Tachypnea is among the earliest signs of pulmonary decompensation. Contactless continuous 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 UNASSIGNED
Single-center pilot prospective cohort study in COVID-19 patients who were cared for in routine wards. COVID-19 patients who had at least one escalation of pulmonary management were matched to three 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. Clinicians were blinded to respiratory rate data from the continuous monitor. The exposures were respiratory features over rolling periods of 30 min, 24 h, and 72 h before respiratory care escalation. The primary outcome was a subsequent escalation in ventilatory support beyond a Venturi mask.
Results UNASSIGNED
Among 125 included patients, 13 exhibited at least one escalation and were each matched to three 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 escalation events. Our overall model, based on continuous data, had a moderate accuracy with an AUC 0.81 (95%CI: 0.73, 0.88) and a good specificity 0.93 (95%CI: 0.87, 0.99).
Conclusion UNASSIGNED
Our pilot observational study suggests that respiratory rate variability as detected with continuous monitoring is associated with subsequent care escalation during the following 24 h. Continuous respiratory monitoring thus appears to be a valuable increment over intermittent monitoring.
Strengths and limitations UNASSIGNED
Our study was the initial evaluation of Circadia contactless respiratory monitoring in COVID-19 patients who are at special risk of pulmonary deterioration. The major limitation is that the analysis was largely

Identifiants

pubmed: 38020176
doi: 10.3389/fmed.2023.1243050
pmc: PMC10645134
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1243050

Informations de copyright

Copyright © 2023 Rivas, López-Baamonde, Sanahuja, Del Rio, Ramis, Recasens, López, Arias, Kampakis, Lauteslager, Awara, Mascha, Soriano, Badía, Castro and Sessler.

Déclaration de conflit d'intérêts

SK, TL, and OA were employed by Circadia Technologies, Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare that this study received funding from Circadia Technologies, Ltd. The funder had the following involvement in the study: SK is a Circadia employee and did the statistical analysis. TL is also a Circadia employee and helped interpret the data and reviewed and revised the manuscript.

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Auteurs

Eva Rivas (E)

Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.
Department of Outcomes Research, Cleveland Clinic, Cleveland, OH, United States.

Manuel López-Baamonde (M)

Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.

Josep Sanahuja (J)

Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.

Elena Del Rio (E)

Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.

Tomeu Ramis (T)

Department of Anesthesiology and Critical Care, Hosptial Universitary Son Espases, Mallorca, Spain.

Anna Recasens (A)

Department of Anesthesiology, Hospital del Mar. Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Universitat Autònoma de Barcelona, Barcelona, Spain.

Antonio López (A)

Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.

Marilyn Arias (M)

Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.

Stylianos Kampakis (S)

Circadia Technologies, Ltd., London, United Kingdom.

Timo Lauteslager (T)

Circadia Technologies, Ltd., London, United Kingdom.

Osama Awara (O)

Circadia Technologies, Ltd., London, United Kingdom.

Edward J Mascha (EJ)

Department of Outcomes Research, Cleveland Clinic, Cleveland, OH, United States.
Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, United States.

Alex Soriano (A)

Department of Infectious Disease, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, CIBERINF, Barcelona, Spain.

Joan Ramon Badía (JR)

Department of Pneumology, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.

Pedro Castro (P)

Medical Intensive Care Unit, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain.

Daniel I Sessler (DI)

Department of Outcomes Research, Cleveland Clinic, Cleveland, OH, United States.

Classifications MeSH