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.
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.
  
  
  METHODS
  Prospective, clinical study.
  
  
  METHODS
  Medical intensive care unit in a 1,000-bed university hospital.
  
  
  METHODS
  A total of 14 mechanically ventilated adult patients with patient-ventilator asynchrony.
  
  
  METHODS
  None.
  
  
  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.
  
  
  CONCLUSIONS
  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.
authors: Medical Intensive Care Unit, Department of Internal Medicine, National Cheng Kung University Medical Center, Tainan, Taiwan.
authors: Chang-Wen
authors: CW
authors: Chen
authors: Wei-Chieh
authors: WC
authors: Lin
authors: Chih-Hsin
authors: CH
authors: Hsu
authors: Kuo-Sheng
authors: KS
authors: Cheng
authors: Chien-Shun
authors: CS
authors: Lo
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000403:Airway Resistance / Q000502:physiology*; D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D004868:Equipment Failure; D045853:Exhalation / Q000502:physiology*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012123:Pulmonary Ventilation / Q000502:physiology*; D012121:Respiration, Artificial / Q000009:adverse effects* / Q000295:instrumentation; D012131:Respiratory Insufficiency / Q000175:diagnosis / Q000503:physiopathology* / Q000628:therapy; D012122:Ventilators, Mechanical