BackgroundA common postoperative complication found among patients who are critically ill is delirium, which has a high mortality rate. A predictive model is needed to identify high-risk patients in order to apply strategies which will prevent and/or reduce adverse outcomes.ObjectivesTo identify the incidence of, and the risk factors for, postoperative delirium (POD) in surgical intensive care unit (SICU) patients, and to determine predictive scores for the development of POD.MethodsThis study enrolled adults aged over 18 years who had undergone an operation within the preceding week and who had been admitted to a SICU for a period that was expected to be longer than 24 h. The CAM − ICU score was used to determine the occurrence of delirium.ResultsOf the 250 patients enrolled, delirium was found in 61 (24.4%). The independent risk factors for delirium that were identified by a multivariate analysis comprised age, diabetes mellitus, severity of disease (SOFA score), perioperative use of benzodiazepine, and mechanical ventilation. A predictive score (age + (5 × SOFA) + (15 × Benzodiazepine use) + (20 × DM) + (20 × mechanical ventilation) + (20 × modified IQCODE > 3.42)) was created. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 (95% CI: 0.786 to 0.897). The cut point of 125 demonstrated a sensitivity of 72.13% and a specificity of 80.95%, and the hospital mortality rate was significantly greater among the delirious than the non-delirious patients (25% vs. 6%, p < 0.01).ConclusionsPOD was experienced postoperatively by a quarter of the surgical patients who were critically ill. A risk score utilizing 6 variables was able to predict which patients would develop POD. The identification of high-risk patients following SICU admission can provide a basis for intervention strategies to improve outcomes.Trial registrationThai Clinical Trials Registry TCTR20181204006. Date registered on December 4, 2018. Retrospectively registered.Electronic supplementary materialThe online version of this article (10.1186/s12871-019-0694-x) contains supplementary material, which is available to authorized users.

Background Sarcopenia is defined as decreased skeletal muscle mass and muscle functions (strength and physical performance). Muscle mass is measured by specific methods, such as bioelectrical impedance analysis and dual-energy X-ray absorptiometry. However, the devices used for these methods are costly and are usually not portable. A simple tool to screen for sarcopenia without measuring muscle mass might be practical, especially in developing countries. The aim of this study was to design a simple screening tool and to validate its performance in screening for sarcopenia in older adult cancer patients scheduled for elective surgery. Methods Cancer surgical patients aged >60 years were enrolled. Their nutritional statuses were evaluated using the Mini Nutrition Assessment-Short Form. Sarcopenia was assessed using Asian Working Group for Sarcopenia (AWGS) criteria. Appendicular skeletal muscle mass was measured by bioelectrical impedance analysis. Four screening formulas with differing combinations of factors (muscle strength, physical performance, and nutritional status) were assessed. The validities of the formulas, compared with the AWGS definition, are presented as sensitivity, specificity, accuracy, and area under a receiver operating characteristic curve. Results Of 251 enrolled surgical patients, 84 (34%) were diagnosed with sarcopenia. Malnutrition (odds ratio [OR]: 2.89, 95% CI: 1.40–5.93); underweight status (OR: 2.80, 95% CI: 1.06–7.43); and age increments of 5 years (OR: 1.78, 95% CI: 1.41–2.24) were independent predictors of preoperative sarcopenia. The combination of low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition had the highest sensitivity, specificity, and accuracy (81.0%, 78.4%, and 79.3%, respectively). This screening formula estimated the probability of sarcopenia with a positive predictive value of 65.4% and a negative predictive value of 89.1%. Conclusion Sarcopenia screening can be performed using a simple tool. The combination of low muscle strength and/or abnormal physical performance, plus malnutrition/risk of malnutrition, has the highest screening performance.

BackgroundA predictive model of scores of difficult intubation (DI) may help physicians screen for airway difficulty to reduce morbidity and mortality in obese patients. The present study aimed to set up and evaluate the predictive performance of a newly developed, practical, multivariate DI model for obese patients.MethodsA prospective multi-center study was undertaken on adults with a body mass index (BMI) of 30 kg/m2 or more who were undergoing conventional endotracheal intubation. The BMI and 10 preoperative airway tests (namely, malformation of the teeth in the upper jaw, the modified Mallampati test [MMT], the upper lip bite test, neck mobility testing, the neck circumference [NC], the length of the neck, the interincisor gap, the hyomental distance, the thyromental distance [TM] and the sternomental distance) were examined. A DI was defined as one with an intubation difficulty scale (IDS) score ≥ 5.ResultsThe 1,015 patients recruited for the study had a mean BMI of 34.2 (standard deviation: 4.3 kg/m2). The proportions for easy intubation, slight DI and DI were 81%, 15.8% and 3.2%, respectively. Drawing on the results of a multivariate analysis, clinically meaningful variables related to obesity (namely, BMI, MMT, and the ratio of NC to TM) were used to build a predictive model for DI. Nevertheless, the best model only had a fair predictive performance. The area under the receiver operating characteristic curve (AUC) was 0.71 (95% confidence interval 0.68–0.84).ConclusionsThe predictive performance of the selected model showed limited benefit for preoperative screening to predict DI among obese patients.