Use of electronic critical care flow sheet data to predict unplanned extubation in ICUs

This study utilized critical care flow sheet data to develop prediction models for unplanned extubation. A total of 5180 patients with 5412 cases of endotracheal tube extubation treated in a tertiary care teaching hospital were evaluated. A total of 60 extubation cases were classified as unplanned, and 5352 as planned. Features documented in the critical care flow sheet for the 24 h prior to extubation were grouped into those with recording frequencies ≤3 and >3. The nearest values to the extubation were identified for all features. For features recorded >3 times, the maximum, minimum, mean, and recording frequencies were calculated. Univariate analyses were performed to select features for inclusion in multivariate analyses. Three multivariate logistic regression models were compared. Model 1 contained only the nearest value, Model 2 added a recording frequency, and Model 3 replaced the nearest value with the maximum, minimum, or mean that had the highest effect size for each feature recorded >3 times. Univariate analyses showed that 18 features differed significantly between the unplanned extubation and control groups. These included vital signs (e.g., pulse and respiration rates, body temperature), ventilator parameters (e.g., minute volume, peak pressure), and consciousness indicators (e.g., Glasgow coma scale score, Richmond agitation sedation scale score, motor power). On all three multivariate analyses, the Glasgow coma scale score, pulse rate, and peak pressure were statistically significant. The frequency of patient positioning (Model 2) and the minimum respiration rate (Model 3) were also significant. Area under the curve, sensitivity, and positive and negative predictive values improved slightly from Model 1 to Model 2 and from Model 2 to Model 3. This study found that minute volume, peak pressure, and motor power are significant risk factors for unplanned extubation that have not been previously reported. Recording frequency, which reflects how often nursing activities were provided, was also a useful predictor. The indicators identified in this study may help to predict and prevent unplanned extubation in clinical settings.