Introduction: Delirium is an acute disturbance of consciousness and cognition that has been shown to be associated with poor outcomes, including increased mortality. We aimed to evaluate outcome after postoperative delirium in a cohort of surgical intensive care unit (SICU) patients. Methods: This prospective study was conducted over a 10-month period in a SICU. Postoperative delirium was diagnosed in accordance with the Intensive Care Delirium Screening Checklist (ICDSC). The primary outcome was mortality at 6-month follow-up. Hospital mortality and becoming dependent were considered as secondary outcomes, on the basis of the evaluation of the patient’s ability to undertake both personal and instrumental activities of daily living (ADL) before surgery and 6 months after discharge from the SICU. For each dichotomous outcome - hospital mortality, mortality at 6-month follow-up, and becoming dependent - a separate multiple logistic regression analysis was performed, which included delirium as an independent variable. Another outcome analyzed was changes in health-related quality of life, as determined using short-form 36 (SF-36), which was administered before and 6 months after discharge from the SICU. Additionally, for each SF-36 domain, a separate multiple linear regression model was used for each SF-36 domain, with changes in the SF-36 domain as a dependent variable and delirium as an independent variable. Results: Of 775 SICU-admitted adults, 562 were enrolled in the study, of which 89 (16%) experienced postoperative delirium. Delirium was an independent risk factor for mortality at the 6-month follow-up (OR = 2.562, P <0.001) and also for hospital mortality (OR = 2.673, P <0.001). Delirium was also an independent risk factor for becoming dependent for personal ADL (P-ADL) after SICU discharge (OR = 2.188, P <0.046). Moreover, patients who experienced postoperative delirium showed a greater decline in SF-36 domains after discharge, particularly in physical function, vitality, and social function, as compared to patients without postoperative delirium. Conclusions: Postoperative delirium was an independent risk factor for 6-month follow-up mortality, hospital mortality, and becoming independent in P-ADL after SICU discharge. It was also significantly associated with a worsening in the quality of life after surgery.

The heart-rate dynamics are one of the most analyzed physiological interactions. Many mathematical methods were proposed to evaluate heart-rate variability. These methods have been successfully applied in research to expand knowledge concerning the cardiovascular dynamics in healthy as well as in pathological conditions. Notwithstanding, they are still far from clinical practice. In this paper, we aim to review the nonlinear methods most used to assess heart-rate dynamics. We focused on methods based on concepts of chaos, fractality, and complexity: Poincaré plot, recurrence plot analysis, fractal dimension (and the correlation dimension), detrended fluctuation analysis, Hurst exponent, Lyapunov exponent entropies (Shannon, conditional, approximate, sample entropy, and multiscale entropy), and symbolic dynamics. We present the description of the methods along with their most notable applications.

Background and study aim: The reliability and external validity of narrow band imaging (NBI) in the stomach have not been described consistently. The aim of the current study was to describe and estimate the accuracy and reliability of a simplified classification system for NBI in the diagnosis of gastric lesions. Methods: Consecutive patients undergoing NBI endoscopy at two reference centers (n = 85, 33 % with dysplasia) were included in two studies. In total, 224 different areas were biopsied and recorded onto video. In the derivation study, previously described NBI features were analyzed in order to develop a simplified classification. In the validation study the accuracy and reliability of this classification were estimated among three groups of endoscopists with different levels of expertise in NBI. Results: The reliability/accuracy results from the derivation study allowed the creation of a simplified NBI classification. In the validation study, “regular vessels with circular mucosa” (pattern A) was associated with normal histology (accuracy 83 %; 95 % confidence interval [CI] 75 % – 90 %); “tubulo-villous mucosa” (pattern B) was associated with intestinal metaplasia (accuracy 84 %; 95CI 77 % – 91 %; positive likelihood ratio [LR + ] = 4.75); and “irregular vessels and mucosa” (pattern C) was associated with dysplasia (accuracy 95 %; 95CI 90 % – 99 %; LR + = 44.33). The reproducibility of these patterns was high (k = 0.62). “Light-blue crest” was moderately reliable (k = 0.49) but specific (87 %) for intestinal metaplasia. A variable vascular density (additional pattern + ) was the best feature for Helicobacter pylori gastritis (accuracy 70 %; 95CI 59 % – 80 %) but showed only fair reliability (k = 0.38). Non-experienced endoscopists presented lower agreement (k = 0.6 vs. k = 0.75) and accuracy (74 % vs. 86 %) than international experts/experienced endoscopists. Conclusion: A simplified NBI classification is accurate and reliable for the diagnosis of intestinal metaplasia and dysplasia. The classification should be further assessed and validated on a per-patient assessment of NBI, and by comparing NBI with other imaging technologies. ^* The authors contributed equally to this study and should be considered joint first authors.

About 160 years ago, the concept of entropy was introduced in thermodynamics by Rudolf Clausius. Since then, it has been continually extended, interpreted, and applied by researchers in many scientific fields, such as general physics, information theory, chaos theory, data mining, and mathematical linguistics. This paper presents The Entropy Universe, which aims to review the many variants of entropies applied to time-series. The purpose is to answer research questions such as: How did each entropy emerge? What is the mathematical definition of each variant of entropy? How are entropies related to each other? What are the most applied scientific fields for each entropy? We describe in-depth the relationship between the most applied entropies in time-series for different scientific fields, establishing bases for researchers to properly choose the variant of entropy most suitable for their data. The number of citations over the past sixteen years of each paper proposing a new entropy was also accessed. The Shannon/differential, the Tsallis, the sample, the permutation, and the approximate entropies were the most cited ones. Based on the ten research areas with the most significant number of records obtained in the Web of Science and Scopus, the areas in which the entropies are more applied are computer science, physics, mathematics, and engineering. The universe of entropies is growing each day, either due to the introducing new variants either due to novel applications. Knowing each entropy’s strengths and of limitations is essential to ensure the proper improvement of this research field.