These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Detecting ineffective triggering in the expiratory phase in mechanically ventilated patients based on airway flow and pressure deflection: feasibility of using a computer algorithm.
    Author: Chen CW, Lin WC, Hsu CH, Cheng KS, Lo CS.
    Journal: Crit Care Med; 2008 Feb; 36(2):455-61. PubMed ID: 18091543.
    Abstract:
    OBJECTIVE: Ineffective triggering (IT) is the most common manifestation of patient-ventilator asynchrony in mechanically ventilated patients. IT in the expiratory phase (ITE) accounts for the majority of IT and is associated with characteristic features of flow and airway pressure deflection, caused by ineffective effort from the patient. The purpose of this study was to quantify the characteristics of flow and airway pressure deflections of ITE and, using a computerized algorithm, to evaluate their usefulness in the detection of ITEs. DESIGN: Prospective, clinical study. SETTING: Medical intensive care unit in a 1,000-bed university hospital. PATIENTS: A total of 14 mechanically ventilated adult patients with patient-ventilator asynchrony. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed 5,899 breaths and found that 1,831 were ITEs. The average values for maximum flow deflection (F(def)) and maximum airway pressure deflection (P(def)) in ITEs were 13.94 +/- 8.0 L/min and 1.91 +/- 0.97 cm H2O. With a starting value of 0.1 L/min for F(def) and 0.01 cm H2O for P(def), the area under the receiver operating characteristics curve of F(def) and P(def) for the detection of ITEs was 0.98 and 0.97, respectively. Sensitivity and specificity for the detection of ITEs were 91.5% and 96.2% for F(def), respectively, for a cutoff value of 5.45 L/min, and 93.3% and 92.9% for Pdef, for a cutoff value of 0.45 cm H2O. CONCLUSION: We conclude that accurately detecting and quantifying ITEs is feasible using a computerized algorithm based on F(def) and P(def). Such a computerized estimation of patient-ventilator interaction might be helpful for adjusting ventilator settings in an intensive care unit.
    [Abstract] [Full Text] [Related] [New Search]