The optimal duration of continuous respiratory rate monitoring to predict in-hospital mortality within seven days of admission - A pilot study in a low resource setting.

Acute medicine Patient monitoring Physiology Respiratory rate Technology

Journal

Resuscitation plus
ISSN: 2666-5204
Titre abrégé: Resusc Plus
Pays: Netherlands
ID NLM: 101774410

Informations de publication

Date de publication:
Dec 2024
Historique:
received: 28 07 2024
revised: 25 08 2024
accepted: 31 08 2024
medline: 24 9 2024
pubmed: 24 9 2024
entrez: 24 9 2024
Statut: epublish

Résumé

Currently there are no established benefits from the continuous monitoring of vital signs, and the optimal time period for respiratory rate measurement is unknown. Low resource Ugandan hospital. Prospective observational study. Respiratory rates of acutely ill patients were continuously measured by a piezoelectric device for up to seven hours after admission to hospital. 22 (5.5%) out of 402 patients died within 7 days of hospital admission. The highest c-statistic of discrimination for 7-day mortality (0.737 SE 0.078) was obtained after four hours of continuously measured respiratory rates transformed into a weighted respiratory rate score (wRRS). After seven hours of measurement the c-statistic of the wRRS fell to 0.535 SE 0.078. 20% the patients who died within seven days did not have an elevated National Early Warning Score (NEWS) on admission but were identified by the 4-hour wRRS. None of the 88 patients whose average respiratory rate remained between 12 and 20 bpm throughout four hours of observation died within 7 days of admission. A simple predictive model that included the four-hour wRRS, Shock Index and altered mental status had a c-statistic for 7-day in-hospital mortality of 0.843 SE. 0.057. Four hours of continuously measured respiratory rates was the observation period that best predicted 7-day in-hospital mortality. After four hours the discrimination of a weighted respiratory rate score deteriorated rapidly.

Sections du résumé

Background UNASSIGNED
Currently there are no established benefits from the continuous monitoring of vital signs, and the optimal time period for respiratory rate measurement is unknown.
Setting UNASSIGNED
Low resource Ugandan hospital.
Methods UNASSIGNED
Prospective observational study. Respiratory rates of acutely ill patients were continuously measured by a piezoelectric device for up to seven hours after admission to hospital.
Results UNASSIGNED
22 (5.5%) out of 402 patients died within 7 days of hospital admission. The highest c-statistic of discrimination for 7-day mortality (0.737 SE 0.078) was obtained after four hours of continuously measured respiratory rates transformed into a weighted respiratory rate score (wRRS). After seven hours of measurement the c-statistic of the wRRS fell to 0.535 SE 0.078. 20% the patients who died within seven days did not have an elevated National Early Warning Score (NEWS) on admission but were identified by the 4-hour wRRS. None of the 88 patients whose average respiratory rate remained between 12 and 20 bpm throughout four hours of observation died within 7 days of admission. A simple predictive model that included the four-hour wRRS, Shock Index and altered mental status had a c-statistic for 7-day in-hospital mortality of 0.843 SE. 0.057.
Conclusion UNASSIGNED
Four hours of continuously measured respiratory rates was the observation period that best predicted 7-day in-hospital mortality. After four hours the discrimination of a weighted respiratory rate score deteriorated rapidly.

Identifiants

pubmed: 39314254
doi: 10.1016/j.resplu.2024.100768
pii: S2666-5204(24)00219-4
pmc: PMC11417511
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100768

Informations de copyright

© 2024 The Author(s).

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Franck Katembo Sikakulya (FK)

Faculty of Clinical Medicine and Dentistry, Department of Surgery, Kampala International University Western Campus, Ishaka-Bushenyi, Uganda.
Faculty of Medicine, Université Catholique du Graben, Butembo, Democratic Republic of the Congo.

Immaculate Nakitende (I)

Enrolled Nurse (EN), Emergency and Out-patient Department, Kitovu Hospital, Masaka, Uganda.

Joan Nabiryo (J)

Enrolled Nurse (EN), Emergency and Out-patient Department, Kitovu Hospital, Masaka, Uganda.

Rezvan Pakdel (R)

Software Engineer, PMD Solutions, Cork, Ireland.

Sylivia Namuleme (S)

Director of Nursing, Diplomate Nursing (DN) Kitovu Hospital, Masaka, Uganda.

Alfred Lumala (A)

Medical Director, Kitouv Hospital, Masaka, Uganda.

John Kellett (J)

School of Clinical and Biomedical Sciences, University of Bolton, United Kingdom.

Classifications MeSH