Performance of an automated electronic acute lung injury screening system in intensive care unit patients.
OBJECTIVE
Lung protective ventilation reduces mortality in patients with acute lung injury, but underrecognition of acute lung injury has limited its use. We recently validated an automated electronic acute lung injury surveillance system in patients with major trauma in a single intensive care unit. In this study, we assessed the system's performance as a prospective acute lung injury screening tool in a diverse population of intensive care unit patients.


METHODS
Patients were screened prospectively for acute lung injury over 21 wks by the automated system and by an experienced research coordinator who manually screened subjects for enrollment in Acute Respiratory Distress Syndrome Clinical Trials Network (ARDSNet) trials. Performance of the automated system was assessed by comparing its results with the manual screening process. Discordant results were adjudicated blindly by two physician reviewers. In addition, a sensitivity analysis using a range of assumptions was conducted to better estimate the system's performance.


METHODS
The Hospital of the University of Pennsylvania, an academic medical center and ARDSNet center (1994-2006).


METHODS
Intubated patients in medical and surgical intensive care units.


METHODS
None.


RESULTS
Of 1270 patients screened, 84 were identified with acute lung injury (incidence of 6.6%). The automated screening system had a sensitivity of 97.6% (95% confidence interval, 96.8-98.4%) and a specificity of 97.6% (95% confidence interval, 96.8-98.4%). The manual screening algorithm had a sensitivity of 57.1% (95% confidence interval, 54.5-59.8%) and a specificity of 99.7% (95% confidence interval, 99.4-100%). Sensitivity analysis demonstrated a range for sensitivity of 75.0-97.6% of the automated system under varying assumptions. Under all assumptions, the automated system demonstrated higher sensitivity than and comparable specificity to the manual screening method.


CONCLUSIONS
An automated electronic system identified patients with acute lung injury with high sensitivity and specificity in diverse intensive care units of a large academic medical center. Further studies are needed to evaluate the effect of automated prompts that such a system can initiate on the use of lung protective ventilation in patients with acute lung injury.
Koenig
Helen C
HC
Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Finkel
Barbara B
BB
Khalsa
Satjeet S
SS
Lanken
Paul N
PN
Prasad
Meeta
M
Urbani
Richard
R
Fuchs
Barry D
BD
D000046:Academic Medical Centers; D055371:Acute Lung Injury / Q000175:diagnosis* / Q000401:mortality / Q000628:therapy; D001331:Automation; D015331:Cohort Studies; D016001:Confidence Intervals; D003422:Critical Care / Q000379:methods*; D016638:Critical Illness / Q000401:mortality / Q000628:therapy; D042241:Early Diagnosis; D004582:Electronics, Medical / Q000295:instrumentation; D005260:Female; D017052:Hospital Mortality / Q000639:trends; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D011446:Prospective Studies; D015272:Pulmonary Medicine / Q000295:instrumentation*; D012121:Respiration, Artificial / Q000009:adverse effects / Q000379:methods; D012128:Respiratory Distress Syndrome / Q000175:diagnosis* / Q000401:mortality / Q000628:therapy; D012680:Sensitivity and Specificity; D016019:Survival Analysis