Rationale: Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies. Objectives: To determine the frequency and outcome of ALI development in patients at risk and validate a lung injury prediction score (LIPS). Methods: In this prospective multicenter observational cohort study, predisposing conditions and risk modifiers predictive of ALI development were identified from routine clinical data available during initial evaluation. The discrimination of the model was assessed with area under receiver operating curve (AUC). The risk of death from ALI was determined after adjustment for severity of illness and predisposing conditions. Measurements and Main Results: Twenty-two hospitals enrolled 5,584 patients at risk. ALI developed a median of 2 (interquartile range 1-4) days after initial evaluation in 377 (6.8%; 148 ALI-only, 229 adult respiratory distress syndrome) patients. The frequency of ALI varied according to predisposing conditions (from 3% in pancreatitis to 26% after smoke inhalation). LIPS discriminated patients who developed ALI from those who did not with an AUC of 0.80 (95% confidence interval, 0.78-0.82). When adjusted for severity of illness and predisposing conditions, development of ALI increased the risk of in-hospital death (odds ratio, 4.1; 95% confidence interval, 2.9-5.7). Conclusions: ALI occurrence varies according to predisposing conditions and carries an independently poor prognosis. Using routinely available clinical data, LIPS identifies patients at high risk for ALI early in the course of their illness. This model will alert clinicians about the risk of ALI and facilitate testing and implementation of ALI prevention strategies. Clinical trial registered with www.clinicaltrials.gov (NCT00889772).

Sirtuins (SIRT), first discovered in yeast as NAD+ dependent epigenetic and metabolic regulators, have comparable activities in human physiology and disease. Mounting evidence supports that the seven-member mammalian sirtuin family (SIRT1–7) guard homeostasis by sensing bioenergy needs and responding by making alterations in the cell nutrients. Sirtuins play a critical role in restoring homeostasis during stress responses. Inflammation is designed to “defend and mend” against the invading organisms. Emerging evidence supports that metabolism and bioenergy reprogramming direct the sequential course of inflammation; failure of homeostasis retrieval results in many chronic and acute inflammatory diseases. Anabolic glycolysis quickly induced (compared to oxidative phosphorylation) for ROS and ATP generation is needed for immune activation to “defend” against invading microorganisms. Lipolysis/fatty acid oxidation, essential for cellular protection/hibernation and cell survival in order to “mend,” leads to immune repression. Acute/chronic inflammations are linked to altered glycolysis and fatty acid oxidation, at least in part, by NAD+ dependent function of sirtuins. Therapeutically targeting sirtuins may provide a new class of inflammation and immune regulators. This review discusses how sirtuins integrate metabolism, bioenergetics, and immunity during inflammation and how sirtuin-directed treatment improves outcome in chronic inflammatory diseases and in the extreme stress response of sepsis.

Severe injury and shock are frequently associated with abnormalities in patient body temperature. Substantial increases in mortality have been associated with profound hypothermia, especially below 35 degrees C. The purpose of this study was to further characterize the impact of hypothermia in a large dataset of trauma patients. This study was a retrospective analysis of the 2004 version of the National Trauma Data Bank (NTDB), which contains approximately 1.1 million patients from over 400 trauma centers. Admission temperature was analyzed with respect to mortality, injury severity score (ISS), base deficit (BD), Glasgow Coma Score (GCS), and hospital outcomes. The NTDB contained 701,491 patients with temperatures recorded upon trauma center admission. Of these, 11,026 patients had admission temperatures <35 degrees C, and 802 had temperatures <32 degrees C. Comparison of core temperature versus mortality revealed that as temperature decreased, the mortality rate increased, reaching approximately 39% at 32 degrees C, and remained constant at lower temperatures. Surprisingly, 477 patients (59.5%) survived with temperatures <32 degrees C. Similarly, BD increased as hypothermia worsened until body temperature reached 31 degrees C, below which there was little further increase. Patients with admission temperatures less than 35 degrees C had significantly greater mortality (25.5% vs. 3.0%, P < 0.001) and BD (7.8 vs. 3.7, P < 0.001) when compared with patients with temperatures >or=35 degrees C. In survivors, average ventilator days and intensive care unit (ICU) days were 14.4 and 12.8, respectively, for patients with temperatures <35 degrees C as opposed to more normothermic patients who demonstrated an average of 9.5 ventilator days and 9.1 ICU days (P < 0.001). When grouped by individual ISS, BD level, and GCS motor score, mortality was significantly greater when admission temperature was below 35 degrees C (ISS mean difference = 11.4%, BD mean difference = 22.8%, and GCS motor mean difference = 9.85%). Logistic regression revealed that hypothermia remains an independent determinant of mortality after correction for confounding variables (odds ratio = 1.54, 95% confidence interval 1.40-1.71). Admission hypothermia is associated with greater mortality, increased injury severity, more profound acidosis, and prolonged ICU/ventilator courses. However, although mortality at <32 degrees C is high, patients with temperatures this low do survive. As temperatures drop below 32 degrees C, mortality rates remain constant, which may indicate a threshold below which physiologic mechanisms are unable to correct body temperature regardless of injury severity. Although shock severity is highly indicative of outcome, hypothermia independently contributes to the substantial mortality associated with severe injury.

No abstract

Background Acute respiratory distress syndrome (ARDS) remains a serious postoperative complication. Although ARDS prevention is a priority, our inability to identify patients at risk for ARDS remains a barrier to progress. We tested and refined the previously reported surgical lung injury prediction (SLIP) model in a multicenter cohort of at-risk surgical patients. Methods This is a secondary analysis of a multicenter, prospective cohort investigation evaluating high-risk patients undergoing surgery. Preoperative ARDS risk factors and risk modifiers were evaluated for inclusion in a parsimonious risk-prediction model. Multiple imputation and domain analysis were used to facilitate development of a refined model, designated SLIP-2. Area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model performance. Results Among 1,562 at-risk patients, ARDS developed in 117 (7.5%). Nine independent predictors of ARDS were identified: sepsis, high-risk aortic vascular surgery, high-risk cardiac surgery, emergency surgery, cirrhosis, admission location other than home, increased respiratory rate (20-29 and >30 breaths/min), FIO2 greater than 35%, and SpO2 less than 95%. The original SLIP score performed poorly in this heterogeneous cohort with baseline risk factors for ARDS (AUC [95% CI], 0.56 [0.50, 0.62]). In contrast, SLIP-2 score performed well (AUC [95% CI], 0.84 [0.81, 0.88]). Internal validation indicated similar discrimination, with an AUC of 0.84. Conclusions In this multicenter cohort of patients at risk for ARDS, SLIP-2 score outperformed the original SLIP score. If validated in an independent sample, this tool may help identify surgical patients at high risk for ARDS.