Outbreak of unusualSalmonella entericaserovar Typhimurium monophasic variant 1,4 [5],12:i:-, Italy, June 2013 to September 2014

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How future surgery will benefit from SARS-COV-2-related measures: a SPIGC survey conveying the perspective of Italian surgeons

COVID-19 negatively affected surgical activity, but the potential benefits resulting from adopted measures remain unclear. The aim of this study was to evaluate the change in surgical activity and potential benefit from COVID-19 measures in perspective of Italian surgeons on behalf of SPIGC. A nationwide online survey on surgical practice before, during, and after COVID-19 pandemic was conducted in March-April 2022 (NCT:05323851). Effects of COVID-19 hospital-related measures on surgical patients' management and personal professional development across surgical specialties were explored. Data on demographics, pre-operative/peri-operative/post-operative management, and professional development were collected. Outcomes were matched with the corresponding volume. Four hundred and seventy-three respondents were included in final analysis across 14 surgical specialties. Since SARS-CoV-2 pandemic, application of telematic consultations (4.1% vs. 21.6%; p < 0.0001) and diagnostic evaluations (16.4% vs. 42.2%; p < 0.0001) increased. Elective surgical activities significantly reduced and surgeons opted more frequently for conservative management with a possible indication for elective (26.3% vs. 35.7%; p < 0.0001) or urgent (20.4% vs. 38.5%; p < 0.0001) surgery. All new COVID-related measures are perceived to be maintained in the future. Surgeons' personal education online increased from 12.6% (pre-COVID) to 86.6% (post-COVID; p < 0.0001). Online educational activities are considered a beneficial effect from COVID pandemic (56.4%). COVID-19 had a great impact on surgical specialties, with significant reduction of operation volume. However, some forced changes turned out to be benefits. Isolation measures pushed the use of telemedicine and telemetric devices for outpatient practice and favored communication for educational purposes and surgeon-patient/family communication. From the Italian surgeons' perspective, COVID-related measures will continue to influence future surgical clinical practice

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Visit-to-visit blood pressure variability in alzheimer disease

The aim of this study was to evaluate visit-to-visit blood pressure (BP) variability in a cohort of patients with Alzheimer disease (AD) and healthy controls. Patients with clinically diagnosed mild or moderate AD and cognitively normal controls matched for age and sex were recruited and followed up for 6 months. To characterize the BP status of each individual, mean, maximum and minimum values, SD, and coefficient of variation were obtained for both systolic BP (SBP) and diastolic BP (DBP). Seventy AD patients and 140 controls were enrolled. No meaningful differences were found in prevalence or treatments of various vascular risk factors. AD patients had higher maximum and lower minimum values and greater SD and coefficient of variation of both SBP and DBP. Group differences in mean values were significant only for SBP. In the multiple logistic regression analysis, adjusted for confounding variables, all the indices related to BP variability were significantly associated with AD. Our results show that AD patients have a greater variability of both SBP and DBP in comparison with age-matched cognitive normal controls, suggesting potential implication in the pathogenesis or progression of the disease.

EEG-Based Alzheimer’s Disease Recognition Using Robust-PCA and LSTM Recurrent Neural Network

The use of electroencephalography (EEG) has recently grown as a means to diagnose neurodegenerative pathologies such as Alzheimer’s disease (AD). AD recognition can benefit from machine learning methods that, compared with traditional manual diagnosis methods, have higher reliability and improved recognition accuracy, being able to manage large amounts of data. Nevertheless, machine learning methods may exhibit lower accuracies when faced with incomplete, corrupted, or otherwise missing data, so it is important do develop robust pre-processing techniques do deal with incomplete data. The aim of this paper is to develop an automatic classification method that can still work well with EEG data affected by artifacts, as can arise during the collection with, e.g., a wireless system that can lose packets. We show that a recurrent neural network (RNN) can operate successfully even in the case of significantly corrupted data, when it is pre-filtered by the robust principal component analysis (RPCA) algorithm. RPCA was selected because of its stated ability to remove outliers from the signal. To demonstrate this idea, we first develop an RNN which operates on EEG data, properly processed through traditional PCA; then, we use corrupted data as input and process them with RPCA to filter outlier components, showing that even with data corruption causing up to 20% erasures, the RPCA was able to increase the detection accuracy by about 5% with respect to the baseline PCA

Short-term memory binding is impaired in AD but not in non-AD dementias.

Binding is a cognitive function responsible for integrating features within complex stimuli (e.g., shape-colour conjunctions) or events within complex memories (e.g., face-name associations). This function operates both in short-term memory (STM) and in long-term memory (LTM) and is severely affected by Alzheimer's disease (AD). However, forming conjunctions in STM is the only binding function which is not affected by healthy ageing or chronic depression. Whether this specificity holds true across other non-AD dementias is as yet unknown. The present study investigated STM conjunctive binding in a sample of AD patients and patients with other non-AD dementias using a task which has proved sensitive to the effects of AD. The STM task assesses the free recall of objects, colours, and the bindings of objects and colours. Patients with AD, frontotemporal dementia, vascular dementia, lewy body dementia and dementia associated with Parkinson's disease showed memory, visuo-spatial, executive and attentional deficits on standard neuropsychological assessment. However, only AD patients showed STM binding deficits. This deficit was observed even when memory for single features was at a similar level across patient groups. Regression and discriminant analyses confirmed that the STM binding task accounted for the largest proportion of variance between AD and non-AD groups and held the greatest classification power to identify patients with AD. STM conjunctive binding places little demands on executive functions and appears to be subserved by components of the memory network which are targeted by AD, but not by non-AD dementias

Homocysteine, Cognitive Functions, and Degenerative Dementias: State of the Art

There is strong evidence that homocysteine is a risk factor not only for cerebrovascular diseases but also for degenerative dementias. A recent consensus statement renewed the importance and the role of high levels of homocysteine in cognitive decline in several forms of degenerative dementia, such as Alzheimer’s disease. Although the molecular mechanisms by which homocysteine causes cell dysfunction are known, both the impact of homocysteine on specific cognitive functions and the relationship between homocysteine level and non-Alzheimer dementias have been poorly investigated. Most of the studies addressing the impact of hyperhomocysteinemia on dementias have not examined the profile of performance across different cognitive domains, and have only relied on screening tests, which provide a very general and coarse-grained picture of the cognitive status of the patients. Yet, trying to understand whether hyperhomocysteinemia is associated with the impairment of specific cognitive functions would be crucial, as it would be, in parallel, learning whether some brain circuits are particularly susceptible to the damage caused by hyperhomocysteinemia. These steps would allow one to (i) understand the actual role of homocysteine in the pathogenesis of cognitive decline and (ii) improve the diagnostic accuracy, differential diagnosis and prognostic implications. This review is aimed at exploring and revising the state of the art of these two strictly related domains. Suggestions for future research are provided