Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

A GPU-Accelerated SVD Algorithm, Based on QR Factorization and Givens Rotations, for DWI Denoising

In this work, we present a parallel implementation of the Singular Value Decomposition (SVD) method on Graphics Processing Units (GPUs) using CUDA programming model. Our approach is based on an iterative parallel version of the QR factorization by means Givens plane rotations using the Sameh and Kuck scheme. The parallel algorithm is driven by an outer loop executed on the CPU. Therefore, threads and blocks configuration is organized in order to use the shared memory and avoid multiple accesses to global memory. However, the main kernel provides coalesced accesses to global memory using contiguous indices. As case study, we consider the application of the SVD in the Overcomplete Local Principal Component Analysis (OLPCA) algorithm for the Diffusion Weighted Imaging (DWI) denoising process. Our results show significant improvements in terms of performances with respect to the CPU version that encourage its usability for this expensive application

A Parallel Implementation of the Hestenes-Jacobi-One-Sides Method Using GPU-CUDA

In this work, we present a parallel implementation of Hestenes-Jacobi-One-sided method exploiting the CUDA environment of Graphics Processing Units (GPUs). Our approach is based on a scheme which performs multiple orthogonalization processes in parallel, across multiple rows and columns. Driven by an outer loop, executed on the CPU, the algorithm configures the CUDA grid with threads and blocks in order to allow the CUDA-kernels to use the shared memory and avoid multiple accesses to global memory. We use this GPU-parallel algorithm in order to accelerate the Singular Value Decomposition (SVD) process which has a variety of applications in scientific computing, signal processing, automatic control and many other areas. Preliminar experiments show a significant improvements in terms of performances with respect to the CPU version and our previuos GPU version

On GPU-CUDA as preprocessing of fuzzy-rough data reduction by means of singular value decomposition

Data reduction algorithms often produce inaccurate results for loss of relevant information. Recently, the singular value decomposition (SVD) method has been used as preprocessing method in order to deal with high-dimensional data and achieve fuzzy-rough reduct convergence on higher dimensional datasets. Despite the well-known fact that SVD offers attractive properties, its high computational cost remains a critical issue. In this work, we present a parallel implementation of the SVD algorithm on graphics processing units using CUDA programming model. Our approach is based on an iterative parallel version of the QR factorization by means of Givens rotations using the Sameh and Kuck scheme. Our results show significant improvements in terms of performances with respect to the CPU version that encourage its usability for this expensive processing of data

The use of di-hydroxypropylphenol (Propophol) in endoscopic procedures

The authors illustrate different endoscopic procedures that may require anaesthesiological assistance through analgo-sedation procedures. Analgo- sedation is useful to the patient and to the endoscopist that can carry out the exam more rapidly and in optimal conditions. The technique employed consists in the administration of propophol, starting with an initial bolus of the drug followed by a continuous perfusion to maintain the hypnotic state. Monitoring of cardiovascular and respiratory parameters shows a great reliability of the drug and effectiveness of the method

The evolutionary ecology of fatty-acid variation : Implications for consumer adaptation and diversification

The nutritional diversity of resources can affect the adaptive evolution of consumer metabolism and consumer diversification. The omega-3 long-chain polyunsaturated fatty acids eicosapentaenoic acid (EPA; 20:5n-3) and docosahexaenoic acid (DHA; 22:6n-3) have a high potential to affect consumer fitness, through their widespread effects on reproduction, growth and survival. However, few studies consider the evolution of fatty acid metabolism within an ecological context. In this review, we first document the extensive diversity in both primary producer and consumer fatty acid distributions amongst major ecosystems, between habitats and amongst species within habitats. We highlight some of the key nutritional contrasts that can shape behavioural and/or metabolic adaptation in consumers, discussing how consumers can evolve in response to the spatial, seasonal and community-level variation of resource quality. We propose a hierarchical trait-based approach for studying the evolution of consumers' metabolic networks and review the evolutionary genetic mechanisms underpinning consumer adaptation to EPA and DHA distributions. In doing so, we consider how the metabolic traits of consumers are hierarchically structured, from cell membrane function to maternal investment, and have strongly environment-dependent expression. Finally, we conclude with an outlook on how studying the metabolic adaptation of consumers within the context of nutritional landscapes can open up new opportunities for understanding evolutionary diversification

Changes in surgicaL behaviOrs dUring the CoviD-19 pandemic. The SICE CLOUD19 Study

BACKGROUND: The spread of the SARS-CoV2 virus, which causes COVID-19 disease, profoundly impacted the surgical community. Recommendations have been published to manage patients needing surgery during the COVID-19 pandemic. This survey, under the aegis of the Italian Society of Endoscopic Surgery, aims to analyze how Italian surgeons have changed their practice during the pandemic.METHODS: The authors designed an online survey that was circulated for completion to the Italian departments of general surgery registered in the Italian Ministry of Health database in December 2020. Questions were divided into three sections: hospital organization, screening policies, and safety profile of the surgical operation. The investigation periods were divided into the Italian pandemic phases I (March-May 2020), II (June-September 2020), and III (October-December 2020).RESULTS: Of 447 invited departments, 226 answered the survey. Most hospitals were treating both COVID-19-positive and -negative patients. The reduction in effective beds dedicated to surgical activity was significant, affecting 59% of the responding units. 12.4% of the respondents in phase I, 2.6% in phase II, and 7.7% in phase III reported that their surgical unit had been closed. 51.4%, 23.5%, and 47.8% of the respondents had at least one colleague reassigned to non-surgical COVID-19 activities during the three phases. There has been a reduction in elective (>200 procedures: 2.1%, 20.6% and 9.9% in the three phases, respectively) and emergency (<20 procedures: 43.3%, 27.1%, 36.5% in the three phases, respectively) surgical activity. The use of laparoscopy also had a setback in phase I (25.8% performed less than 20% of elective procedures through laparoscopy). 60.6% of the respondents used a smoke evacuation device during laparoscopy in phase I, 61.6% in phase II, and 64.2% in phase III. Almost all responders (82.8% vs. 93.2% vs. 92.7%) in each analyzed period did not modify or reduce the use of high-energy devices.CONCLUSION: This survey offers three faithful snapshots of how the surgical community has reacted to the COVID-19 pandemic during its three phases. The significant reduction in surgical activity indicates that better health policies and more evidence-based guidelines are needed to make up for lost time and surgery not performed during the pandemic