Automatic detection of ventilatory modes during invasive mechanical ventilation.
Background: Expert systems can help alleviate problems related to the shortage of human resources in critical care, offering expert advice in complex situations. Expert systems use contextual information to provide advice to staff. In mechanical ventilation, it is crucial for an expert system to be...
| Published in: | Critical Care Vol. 20; pp. 1 - 8 |
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| Main Authors: | , , , , , , , , , , , , |
| Format: | equations & formulas pictorial research tables/charts Journal Article |
| Published: |
BioMed Central
8/14/2016
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117524343&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117524343 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13648535 65OP jtl: Critical Care issn: 13648535 maglogo: N pubinfo: dt: 8/14/2016 vid: 20 pid: 24147 pub: BioMed Central artinfo: ui: 117524343 117524343 NLM27522580 117524343 10.1186/s13054-016-1436-9 NLM27522580 PMC4983761 117524343 ppf: 1 ppct: 7 formats: tig: atl: Automatic detection of ventilatory modes during invasive mechanical ventilation. aug: au: Murias, Gastón Montanyà, Jaume Chacón, Encarna Estruga, Anna Subirà, Carles Fernández, Rafael Sales, Bernat de Haro, Candelaria López-Aguilar, Josefina Lucangelo, Umberto Villar, Jesús Kacmarek, Robert M. Blanch, Lluís affil: Clínica Bazterrica y Clínica Santa Isabel, Departamento de Ciencias Fisiológicas, Farmacológicas y Bioquímicas, Facultad de Medicina, Universidad Favaloro, Buenos Aires, Argentina sug: subj: Respiration, Artificial Methods Equipment Design Respiration, Artificial Equipment and Supplies Ventilators, Mechanical Trends Decision Support Systems, Clinical Standards Decision Support Systems, Clinical Equipment and Supplies Intensive Care Units Administration Automation Equipment and Supplies Decision Support Systems, Clinical Trends Automation Methods Intensive Care Units Labor Supply Spain Respiration, Artificial Nursing Equipment Design Trends Algorithms Human ab: Background: Expert systems can help alleviate problems related to the shortage of human resources in critical care, offering expert advice in complex situations. Expert systems use contextual information to provide advice to staff. In mechanical ventilation, it is crucial for an expert system to be able to determine the ventilatory mode in use. Different manufacturers have assigned different names to similar or even identical ventilatory modes so an expert system should be able to detect the ventilatory mode. The aim of this study is to evaluate the accuracy of an algorithm to detect the ventilatory mode in use.Methods: We compared the results of a two-step algorithm designed to identify seven ventilatory modes. The algorithm was built into a software platform (BetterCare® system, Better Care SL; Barcelona, Spain) that acquires ventilatory signals through the data port of mechanical ventilators. The sample analyzed compared data from consecutive adult patients who underwent >24 h of mechanical ventilation in intensive care units (ICUs) at two hospitals. We used Cohen's kappa statistics to analyze the agreement between the results obtained with the algorithm and those recorded by ICU staff.Results: We analyzed 486 records from 73 patients. The algorithm correctly labeled the ventilatory mode in 433 (89 %). We found an unweighted Cohen's kappa index of 84.5 % [CI (95 %) = (80.5 %: 88.4 %)].Conclusions: The computerized algorithm can reliably identify ventilatory mode. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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