Development and validation of a score to predict postoperative respiratory failure in a multicentre European cohort : A prospective, observational study

BACKGROUND Postoperative respiratory failure (PRF) is the most frequent respiratory complication following surgery. OBJECTIVE The objective of this study was to build a clinically useful predictive model for the development of PRF. DESIGN A prospective observational study of a multicentre cohort. SETTING Sixty-three hospitals across Europe. PATIENTS Patients undergoing any surgical procedure under general or regional anaesthesia during 7-day recruitment periods. MAIN OUTCOME MEASURES Development of PRF within 5 days of surgery. PRF was defined by a partial pressure of oxygen in arterial blood (PaO2) less than 8 kPa or new onset oxyhaemoglobin saturation measured by pulse oximetry (SpO(2)) less than 90% whilst breathing room air that required conventional oxygen therapy, noninvasive or invasive mechanical ventilation. RESULTS PRF developed in 224 patients (4.2% of the 5384 patients studied). In-hospital mortality [95% confidence interval (95% CI)] was higher in patients who developed PRF [10.3% (6.3 to 14.3) vs. 0.4% (0.2 to 0.6)]. Regression modelling identified a predictive PRF score that includes seven independent risk factors: low preoperative SpO(2); at least one preoperative respiratory symptom; preoperative chronic liver disease; history of congestive heart failure; open intrathoracic or upper abdominal surgery; surgical procedure lasting at least 2 h; and emergency surgery. The area under the receiver operating characteristic curve (c-statistic) was 0.82 (95% CI 0.79 to 0.85) and the Hosmer-Lemeshow goodness-of-fit statistic was 7.08 (P = 0.253). CONCLUSION A risk score based on seven objective, easily assessed factors was able to predict which patients would develop PRF. The score could potentially facilitate preoperative risk assessment and management and provide a basis for testing interventions to improve outcomes. The study was registered at ClinicalTrials.gov (identifier NCT01346709)

Development of a prediction model for postoperative pneumonia A multicentre prospective observational study

BACKGROUND Postoperative pneumonia is associated with increased morbidity, mortality and costs. Prediction models of pneumonia that are currently available are based on retrospectively collected data and administrative coding systems. OBJECTIVE To identify independent variables associated with the occurrence of postoperative pneumonia. DESIGN A prospective observational study of a multicentre cohort (Prospective Evaluation of a RIsk Score for postoperative pulmonary COmPlications in Europe database). SETTING Sixty-three hospitals in Europe. PATIENTS Patients undergoing surgery under general and/or regional anaesthesia during a 7-day recruitment period. MAIN OUTCOME MEASURE The primary outcome was postoperative pneumonia. Definition: the need for treatment with antibiotics for a respiratory infection and at least one of the following criteria: new or changed sputum; new or changed lung opacities on a clinically indicated chest radiograph; temperature more than 38.3 degrees C; leucocyte count more than 12 000 mu l(-1). RESULTS Postoperative pneumonia occurred in 120 out of 5094 patients (2.4%). Eighty-two of the 120 (68.3%) patients with pneumonia required ICU admission, compared with 399 of the 4974 (8.0%) without pneumonia (P < 0.001). We identified five variables independently associated with postoperative pneumonia: functional status [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.58 to 3.12], pre-operative SpO(2) values while breathing room air (OR 0.83, 95% CI 0.78 to 0.84), intra-operative colloid administration (OR 2.97, 95% CI 1.94 to 3.99), intra-operative blood transfusion (OR 2.19, 95% CI 1.41 to 4.71) and surgical site (open upper abdominal surgery OR 3.98, 95% CI 2.19 to 7.59). The model had good discrimination (c-statistic 0.89) and calibration (Hosmer-Lemeshow P = 0.572). CONCLUSION We identified five variables independently associated with postoperative pneumonia. The model performed well and after external validation may be used for risk stratification and management of patients at risk of postoperative pneumonia