Epidemiology, practice of ventilation and outcome for patients at increased risk of postoperative pulmonary complications

BACKGROUND Limited information exists about the epidemiology and outcome of surgical patients at increased risk of postoperative pulmonary complications (PPCs), and how intraoperative ventilation was managed in these patients. OBJECTIVES To determine the incidence of surgical patients at increased risk of PPCs, and to compare the intraoperative ventilation management and postoperative outcomes with patients at low risk of PPCs. DESIGN This was a prospective international 1-week observational study using the ‘Assess Respiratory Risk in Surgical Patients in Catalonia risk score’ (ARISCAT score) for PPC for risk stratification. PATIENTS AND SETTING Adult patients requiring intraoperative ventilation during general anaesthesia for surgery in 146 hospitals across 29 countries. MAIN OUTCOME MEASURES The primary outcome was the incidence of patients at increased risk of PPCs based on the ARISCAT score. Secondary outcomes included intraoperative ventilatory management and clinical outcomes. RESULTS A total of 9864 patients fulfilled the inclusion criteria. The incidence of patients at increased risk was 28.4%. The most frequently chosen tidal volume (VT) size was 500 ml, or 7 to 9 ml kg1 predicted body weight, slightly lower in patients at increased risk of PPCs. Levels of positive end-expiratory pressure (PEEP) were slightly higher in patients at increased risk of PPCs, with 14.3% receiving more than 5 cmH2O PEEP compared with 7.6% in patients at low risk of PPCs (P < 0.001). Patients with a predicted preoperative increased risk of PPCs developed PPCs more frequently: 19 versus 7%, relative risk (RR) 3.16 (95% confidence interval 2.76 to 3.61), P < 0.001) and had longer hospital stays. The only ventilatory factor associated with the occurrence of PPCs was the peak pressure. CONCLUSION The incidence of patients with a predicted increased risk of PPCs is high. A large proportion of patients receive high VT and low PEEP levels. PPCs occur frequently in patients at increased risk, with worse clinical outcome

Epidemiology, practice of ventilation and outcome for patients at increased risk of postoperative pulmonary complications: LAS VEGAS - An observational study in 29 countries

BACKGROUND Limited information exists about the epidemiology and outcome of surgical patients at increased risk of postoperative pulmonary complications (PPCs), and how intraoperative ventilation was managed in these patients. OBJECTIVES To determine the incidence of surgical patients at increased risk of PPCs, and to compare the intraoperative ventilation management and postoperative outcomes with patients at low risk of PPCs. DESIGN This was a prospective international 1-week observational study using the ‘Assess Respiratory Risk in Surgical Patients in Catalonia risk score’ (ARISCAT score) for PPC for risk stratification. PATIENTS AND SETTING Adult patients requiring intraoperative ventilation during general anaesthesia for surgery in 146 hospitals across 29 countries. MAIN OUTCOME MEASURES The primary outcome was the incidence of patients at increased risk of PPCs based on the ARISCAT score. Secondary outcomes included intraoperative ventilatory management and clinical outcomes. RESULTS A total of 9864 patients fulfilled the inclusion criteria. The incidence of patients at increased risk was 28.4%. The most frequently chosen tidal volume (V T) size was 500 ml, or 7 to 9 ml kg−1 predicted body weight, slightly lower in patients at increased risk of PPCs. Levels of positive end-expiratory pressure (PEEP) were slightly higher in patients at increased risk of PPCs, with 14.3% receiving more than 5 cmH2O PEEP compared with 7.6% in patients at low risk of PPCs (P ˂ 0.001). Patients with a predicted preoperative increased risk of PPCs developed PPCs more frequently: 19 versus 7%, relative risk (RR) 3.16 (95% confidence interval 2.76 to 3.61), P ˂ 0.001) and had longer hospital stays. The only ventilatory factor associated with the occurrence of PPCs was the peak pressure. CONCLUSION The incidence of patients with a predicted increased risk of PPCs is high. A large proportion of patients receive high V T and low PEEP levels. PPCs occur frequently in patients at increased risk, with worse clinical outcome.</p

Lower Emotional Complexity as a Prospective Predictor of Psychopathology in Adolescents From the General Population

Emotional complexity (EC) involves the ability to distinguish between distinct emotions (differentiation) and the experience of a large range of emotions (diversity). Lower EC has been related to psychopathology in cross-sectional studies. This study aimed to investigate (a) whether EC prospectively predicts psychopathology and (b) whether this effect is contingent on stressful life events. To further explore EC, we compared the effects of differentiation and diversity. Adolescents from the general population (N = 401) rated 8 negatively valenced emotions 10 times a day for 6 consecutive days. Further, they completed the Symptom Checklist-90 (baseline and 1-year follow-up) and a questionnaire on past year's life events at follow-up. Logistic regression analyses tested whether EC-reflected by emotion differentiation (intraclass correlation coefficient [ICC]) and diversity (diversity index [DI])-predicted prognosis (good: remitting or lacking symptoms vs. bad: worsening or persisting symptoms). EC predicted prognoses but only when based on the ICC (OREC.ICC = 1.42, p = .02). An ECICC 1 SD above average increased the probability of good prognosis from .67 to .74. This effect was not related to stressful life events (OREC × Life events = 1.03, p = .86) and disappeared when emotion intensity (mean level) was taken into account (OREC = 1.20, p = .20). Predicting future prognosis does not necessitate complex measures of emotional experience (ICC, DI) but rather might be achieved through simpler indices (mean). The discrepant effects of the ICC and DI on prognosis suggest that impaired emotion representation (ICC) plays a more important role in vulnerability to mental ill health than does low diversity of emotions (DI)

Computational Drug Repurposing: Current Trends

Biomedical discovery has been reshaped upon the exploding digitization of data which can be retrieved from a number of sources, ranging from clinical pharmacology to cheminformatics-driven databases. Now, supercomputing platforms and publicly available resources such as biological, physicochemical, and clinical data, can all be integrated to construct a detailed map of signaling pathways and drug mechanisms of action in relation to drug candidates. Recent advancements in computer-aided data mining have facilitated analyses of 'big data' approaches and the discovery of new indications for pre-existing drugs has been accelerated. Linking gene-phenotype associations to predict novel drug-disease signatures or incorporating molecular structure information of drugs and protein targets with other kinds of data derived from systems biology provide great potential to accelerate drug discovery and improve the success of drug repurposing attempts. In this review, we highlight commonly used computational drug repurposing strategies, including bioinformatics and cheminformatics tools, to integrate large-scale data emerging from the systems biology, and consider both the challenges and opportunities of using this approach. Moreover, we provide successful examples and case studies that combined various in silico drug-repurposing strategies to predict potential novel uses for known therapeutics