Factors related to post-operative delirium in middle-aged and elderly patients in intensive care unit and risk prediction model / 中国康复理论与实践

@#Objective To analyze the influencing factors of post-operative delirium (POD) in middle-aged and elderly patients in intensive care unit (ICU) and construct risk prediction model for it.Methods A total of 112 middle-aged and elderly postoperative patients in the ICU of Lu'an Hospital of Anhui Medical University from January, 2018 to February, 2021 were selected. On the second day after the operation, they were transferred to ICU, and assessed with the Confusion AssessmentMethod for Intensive Care Unit (CAM-ICU). The patients were divided into delirium group (n = 52) and non-delirium group (n = 60) according to assessment. Univariate analysis was used to compare the differences in clinical data between the two groups, and multivariate Logistic regression analysis was used to screen the independent influencing factors to construct risk prediction model. Receiver operating characteristic (ROC) curve was used to evaluate prediction performance. Results Multivariate logistic regression analysis showed Acute Physiology and Chronic Health Evaluation II score (APACHE II score) (OR = 1.424, 95%CI 1.204 to 1.685, P < 0.001), ICU sleep quality score (OR = 1.432, 95%CI 1.159 to 1.770, P < 0.001), and postoperative oxygenation index ≤ 300 (OR = 4.485, 95%CI 1.644 to 12.240, P = 0.001) were independent influencing factors of postoperative delirium in ICU. The prediction model was: logit(P) = -11.381+0.354X1 (APACHE II score, cut-off value 16)+0.359X2 (ICU sleep quality score, cut-off value 13)+1.501X3 (postoperative oxygenation index ≤ 300), with the sensitivity and specificity of 79.2% and 79.7% respectively. The area under the ROC curve was 0.866 (95%CI 0.801 to 0.930), more than those of the factors alone (P < 0.05). Conclusion The prediction model based on Logistic regression can predict the occurrence of postoperative delirium in middle-aged and elderly patients in ICU.

Dynamic matching algorithm for viral structure prediction

Most viruses have RNA genomes, their biological functions are expressed more by folded architecture than by sequence

Among the various RNA structures, pseudoknots are the most typical. In general, RNA secondary structures prediction doesn't contain pseudoknots because of its difficulty in modeling

Here we present an algorithm of dynamic matching to predict RNA secondary structures with pseudoknots by combining the merits of comparative and thermodynamic approaches

We have tested and verified our algorithm on some viral RNA

Comparisons show that our algorithm and loop matching method has similar accuracy and time complexity, and are more sensitive than the maximum weighted matching method and Rivas algorithm. Among the four methods, our algorithm has the best prediction specificity. The results show that our algorithm is more reliable and efficient than the other methods

EFFECT OF GLUTAMINE SUPPLEMENTATION ON GLUTAMINE METABOLISM IN EXERCISING MICE / 营养学报

Objective: To approach the effects of glutamine supplementation on plasma and muscle levels of glutamine, and the activities of tissue glutamine synthetase and glutaminase after high intensity exercise. Methods: BAL/C mice were randomly divided into high intensity exercise(2% body weight load) and control groups to swim 2 hours per day for 8 weeks. Results: To compare with control group, high intensity exercise reduced glutamine levels in plasma and muscle by 74% (P