Predicting the result of noninvasive ventilation in severe acute exacerbations of patients with chronic airflow limitation

Objective: To analyze prospectively the factors related to the success of n oninvasive ventilation (NIV) in the treatment of acute exacerbations of chr onic airflow limitation (CAFL) and to generate a multiple regression model in order to detect which patients can be successfully treated by this metho d. Setting: A respiratory medicine ward of a referral hospital. Methods and principal results: Initially, we examined 44 episodes of acute respiratory failure in 30 patients with CAFL in whom mechanical ventilation was advisable. In 34 of 44 episodes (77%), NIV was used successfully. Pati ents in whom NIV succeeded had a lower FEV1 prior to admission, a higher le vel of consciousness (LC), and significant improvements in PaCO2, pH, and L C after 1 h of NIV, A logistic regression model consisting of baseline FEV1 and PaCO2 values, initial PaCO2, pH, and LC values on admission, and Pace, values after 1 h of NIV allowed us to correctly classify > 95% of the 44 e pisodes in which the outcome was successful. In the second part of the stud y, we prospectively validated the equation in another 15 consecutive CAFL p atients with acute hypercapnic respiratory failure. NIV successfully treate d 12 patients (80%), and the model correctly classified 14 patients (93%). Conclusion: Good LC at the beginning of NIV and improvements in pH, PaCO2, and LC values after 1 h of NIV are associated with successful responses to NIV in COPD patients with acute hypercapnic respiratory failure. Our valida ted multiple I egression model confirms that these variables predict the re sult of NIV in acute hypercapnic failure in CAFL patients.