Rationale: Significant progress has been made in understanding the pathogenesis of acute respiratory distress syndrome (ARDS). Recent advances in hospital practice may have reduced the incidence of this lethal syndrome. Objectives: To observe incidence trends and associated outcomes of ARDS. Methods: This population-based cohort study was conducted in Olmsted County, Minnesota. Using a validated screening protocol, investigators identified intensive care patients with acute hypoxemia and bilateral pulmonary infiltrates. The presence of ARDS was independently confirmed according to American-European Consensus Conference criteria. The incidence of ARDS and associated outcomes were compared over the 8-year study period (2001–2008). Measurements and Main Results: Over the 8-year period, critically ill Olmsted County residents presented with increasing severity of acute illness, a greater number of comorbidities, and a higher prevalence of major predisposing conditions for ARDS. The ARDS incidence decreased significantly from 82.4 to 38.9 per 100,000 person-years during the study period (P < 0.001). A decline in hospital-acquired ARDS (P < 0.001) was responsible for the fall in the incidence density with no change on admission (P = 0.877). Overall, mortality and hospital and intensive care unit lengths of stay decreased over time (P < 0.001), whereas the ARDS case-fatality did not change significantly. Conclusions: Despite an increase in patients' severity of illness, number of comorbidities, and prevalence of major ARDS risk factors, the incidence of ARDS in this suburban community decreased by more than half. Correlation of the observed findings with changes in health care delivery may have important implications for the planning of acute care services in other regions.

Background. Acute kidney injury (AKI) is common in critically ill patients and is associated with high morbidity and mortality. Early identification of high-risk patients provides an opportunity to develop strategies for prevention, early diagnosis and treatment of AKI. Methods. We undertook this multicenter prospective cohort study to develop and validate a risk score for predicting AKI in patients admitted to an intensive care unit (ICU). Patients were screened for predictor variables within 48 h of ICU admission. Baseline and acute risk factors were recorded at the time of screening and serum creatinine was measured daily for up to 7 days. A risk score model for AKI was developed with multivariate regression analysis combining baseline and acute risk factors in the development cohort (573 patients) and the model was further evaluated on a test cohort (144 patients). Validation was performed on an independent prospective cohort of 1300 patients. The discriminative ability of the risk model was assessed by the area under the receiver operating characteristic curve (AUROC) and model calibration was evaluated by Hosmer–Lemeshow statistic. AKI was defined by the Kidney Disease: Improving Global Outcomes criteria (absolute change of 0.3 mg/dL or relative change of 50% from baseline serum creatinine in 48 h to 7 days, respectively). Results. AKI developed in 754 (37.2%) patients. In the multivariate model, chronic kidney disease, chronic liver disease, congestive heart failure, hypertension, atherosclerotic coronary vascular disease, pH ≤ 7.30, nephrotoxin exposure, sepsis, mechanical ventilation and anemia were identified as independent predictors of AKI and the AUROC for the model in the test cohort was 0.79 [95% confidence interval (CI) 0.70–0.89]. On the external validation cohort, the AUROC value was 0.81 (95% CI 0.78–0.83). The risk model demonstrated good calibration in both cohorts. Positive and negative predictive values for the optimal cutoff value of ≥ 5 points in test and validation cohorts were 22.7 and 96.1% and 31.8 and 95.4%, respectively. Conclusions. A risk score model integrating chronic comorbidities and acute events at ICU admission can identify patients at high risk to develop AKI. This risk assessment tool could help clinicians to stratify patients for primary prevention, surveillance and early therapeutic intervention to improve care and outcomes of ICU patients.

Background: Acute lung injury (ALI) is a serious postoperative complication with limited treatment options. A preoperative risk-prediction model would assist clinicians and scientists interested in ALI. The objective of this investigation was to develop a surgical lung injury prediction (SLIP) model to predict risk of postoperative ALI based on readily available preoperative risk factors. Methods: Secondary analysis of a prospective cohort investigation including adult patients undergoing high-risk surgery. Preoperative risk factors for postoperative ALI were identified and evaluated for inclusion in the SLIP model. Multivariate logistic regression was used to develop the model. Model performance was assessed with the area under the receiver operating characteristic curve and the Hosmer-Lemeshow goodness-of-fit test. Results: Out of 4,366 patients, 113 (2.6%) developed early postoperative ALI. Predictors of postoperative ALI in multivariate analysis that were maintained in the final SLIP model included high-risk cardiac, vascular, or thoracic surgery, diabetes mellitus, chronic obstructive pulmonary disease, gastroesophageal reflux disease, and alcohol abuse. The SLIP score distinguished patients who developed early postoperative ALI from those who did not with an area under the receiver operating characteristic curve (95% CI) of 0.82 (0.78-0.86). The model was well calibrated (Hosmer-Lemeshow, P = 0.55). Internal validation using 10-fold cross-validation noted minimal loss of diagnostic accuracy with a mean ± SD area under the receiver operating characteristic curve of 0.79 ± 0.08. Conclusions: Using readily available preoperative risk factors, we developed the SLIP scoring system to predict risk of early postoperative ALI.

BACKGROUND: Optimal titration of inspired oxygen is important to prevent hyperoxia in mechanically ventilated patients in ICUs. There is mounting evidence of the deleterious effects of hyperoxia; however, there is a paucity of data about F IO ₂ practice and oxygen exposure among patients in ICUs. We therefore sought to assess excessive F IO ₂ exposure in mechanically ventilated patients with acute lung injury and to evaluate the effect on pulmonary outcomes. METHODS: From a database of ICU patients with acute lung injury identified by prospective electronic medical record screening, we identified those who underwent invasive mechanical ventilation for > 48 hours from January 1 to December 31, 2008. Ventilator settings, including F IO ₂ and corresponding S pO ₂ , were collected from the electronic medical record at 15-min intervals for the first 48 hours. Excessive F IO ₂ was defined as F IO ₂ > 0.5 despite S pO ₂ > 92%. The association between the duration of excessive exposure and pulmonary outcomes was assessed by change in oxygenation index from baseline to 48 hours and was analyzed by univariate and multivariate linear regression analysis. RESULTS: Of 210 patients who met the inclusion criteria, 155 (74%) were exposed to excessive F IO ₂ for a median duration of 17 hours (interquartile range 7.5–33 h). Prolonged exposure to excessive F IO ₂ correlated with worse oxygenation index at 48 hours in a dose-response manner ( P < .001.). Both exposure to higher F IO ₂ and longer duration of exposure were associated with worsening oxygenation index at 48 hours ( P < .001), more days on mechanical ventilation, longer ICU stay, and longer hospital stay ( P = .004). No mortality difference was noted. CONCLUSIONS: Excessive oxygen supplementation is common in mechanically ventilated patients with ALI and may be associated with worsening lung function.