Details

Autor(en) / Beteiligte

• Muñoz-Bonet, Juan Ignacio
• Posadas-Blázquez, Vicente
• González-Galindo, Laura
• Sánchez-Zahonero, Julia
• Vázquez-Martínez, José Luis
• Castillo, Andrés
• Brines, Juan

Titel

Exploring the clinical relevance of vital signs statistical calculations from a new-generation clinical information system

Ist Teil von

• Scientific reports, 2023-09, Vol.13 (1), p.15068-10, Article 15068

Ort / Verlag

London: Nature Publishing Group

Erscheinungsjahr

2023

Quelle

Electronic Journals Library

Beschreibungen/Notizen

• Abstract New information on the intensive care applications of new generation ‘high-density data clinical information systems’ (HDDCIS) is increasingly being published in the academic literature. HDDCIS avoid data loss from bedside equipment and some provide vital signs statistical calculations to promote quick and easy evaluation of patient information. Our objective was to study whether manual records of continuously monitored vital signs in the Paediatric Intensive Care Unit could be replaced by these statistical calculations. Here we conducted a prospective observational clinical study in paediatric patients with severe diabetic ketoacidosis, using a Medlinecare ® HDDCIS, which collects information from bedside equipment (1 data point per parameter, every 3–5 s) and automatically provides hourly statistical calculations of the central trend and sample dispersion. These calculations were compared with manual hourly nursing records for patient heart and respiratory rates and oxygen saturation. The central tendency calculations showed identical or remarkably similar values and strong correlations with manual nursing records. The sample dispersion calculations differed from the manual references and showed weaker correlations. We concluded that vital signs calculations of central tendency can replace manual records, thereby reducing the bureaucratic burden of staff. The significant sample dispersion calculations variability revealed that automatic random measurements must be supervised by healthcare personnel, making them inefficient.