32 research outputs found
Air Quality and Bioclimatic Conditions within the Greater Athens Area, Greece - Development and Applications of Artificial Neural Networks
Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station
© 2018, ISB. The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature
Early myocardial injury is an integral component of experimental acute liver failure – a study in two porcine models
Transportation and air quality perspectives and projections in a Mediterranean country, the case of Greece
This study provides a thorough review and analysis of the evolution of the Greek vehicle fleet over the last ~30 years, which is next used for the generation of high granularity fleet projections, the assessment of associated air pollution and the estimation of relevant environmental benefits by 2030. The integrated methodology developed takes also into account vehicle clustering and the Brown’s Double Simple Exponential Smoothing technique that, together with the adoption of COPERT-based emission factors, allow for the estimation of the anticipated emissions in 2030. Expected 2030 emissions levels suggest a reduction across all pollutants compared to 2018, ranging from 3.7% for PM10 to 54.5% for NMVOC (and 46% for CO, 14% for SO2, 28% for NOX and 21% for CO2). We find that Greece is on track with national goals concerning the reduction of air pollution from the transportation sector, which designates the positive contribution anticipated by EVs and new, “greener” vehicles, and sets new challenges for the further improvement of the sector beyond the 2030 outlook
Beyond Preconditioning: Postconditioning as an Alternative Technique in the Prevention of Liver Ischemia-Reperfusion Injury
Liver ischemia/reperfusion injury may significantly compromise hepatic postoperative function. Various hepatoprotective methods have been improvised, aiming at attenuating IR injury. With ischemic preconditioning (IPC), the liver is conditioned with a brief ischemic period followed by reperfusion, prior to sustained ischemia. Ischemic postconditioning (IPostC), consisting of intermittent sequential interruptions of blood flow in the early phase of reperfusion, seems to be a more feasible alternative than IPC, since the onset of reperfusion is more predictable. Regarding the potential mechanisms involved, it has been postulated that the slow intermittent oxygenation through controlled reperfusion decreases the burst production of oxygen free radicals, increases antioxidant activity, suppresses neutrophil accumulation, and modulates the apoptotic cascade. Additionally, favorable effects on mitochondrial ultrastructure and function, and upregulation of the cytoprotective properties of nitric oxide, leading to preservation of sinusoidal structure and maintenance of blood flow through the hepatic circulation could also underlie the protection afforded by postconditioning. Clinical studies are required to show whether biochemical and histological improvements afforded by the reperfusion/reocclusion cycles of postconditioning during early reperfusion can be translated to a substantial clinical benefit in liver resection and transplantation settings or to highlight more aspects of its molecular mechanisms
Global Consequences of Liver Ischemia/Reperfusion Injury
Liver ischemia/reperfusion injury has been extensively studied during the last decades and has been implicated in the pathophysiology of many clinical entities following hepatic surgery and transplantation. Apart from its pivotal role in the pathogenesis of the organ’s post reperfusion injury, it has also been proposed as an underlying mechanism responsible for the dysfunction and injury of other organs as well. It seems that liver ischemia and reperfusion represent an event with “global” consequences that influence the function of many remote organs including the lung, kidney, intestine, pancreas, adrenals, and myocardium among others. The molecular and clinical manifestation of these remote organs injury may lead to the multiple organ dysfunction syndrome, frequently encountered in these patients. Remote organ injury seems to be in part the result of the oxidative burst and the inflammatory response following reperfusion. The present paper aims to review the existing literature regarding the proposed mechanisms of remote organ injury after liver ischemia and reperfusion
Radial Basis Function Artificial Neural Network for the Investigation of Thyroid Cytological Lesions
Objective. This study investigates the potential of an artificial intelligence (AI) methodology, the radial basis function (RBF) artificial neural network (ANN), in the evaluation of thyroid lesions. Study Design. The study was performed on 447 patients who had both cytological and histological evaluation in agreement. Cytological specimens were prepared using liquid-based cytology, and the histological result was based on subsequent surgical samples. Each specimen was digitized; on these images, nuclear morphology features were measured by the use of an image analysis system. The extracted measurements (41,324 nuclei) were separated into two sets: the training set that was used to create the RBF ANN and the test set that was used to evaluate the RBF performance. The system aimed to predict the histological status as benign or malignant. Results. The RBF ANN obtained in the training set has sensitivity 82.5%, specificity 94.6%, and overall accuracy 90.3%, while in the test set, these indices were 81.4%, 90.0%, and 86.9%, respectively. Algorithm was used to classify patients on the basis of the RBF ANN, the overall sensitivity was 95.0%, the specificity was 95.5%, and no statistically significant difference was observed. Conclusion. AI techniques and especially ANNs, only in the recent years, have been studied extensively. The proposed approach is promising to avoid misdiagnoses and assists the everyday practice of the cytopathology. The major drawback in this approach is the automation of a procedure to accurately detect and measure cell nuclei from the digitized images
Correction to: Two years later: Is the SARS-CoV-2 pandemic still having an impact on emergency surgery? An international cross-sectional survey among WSES members
Background: The SARS-CoV-2 pandemic is still ongoing and a major challenge for health care services worldwide. In the first WSES COVID-19 emergency surgery survey, a strong negative impact on emergency surgery (ES) had been described already early in the pandemic situation. However, the knowledge is limited about current effects of the pandemic on patient flow through emergency rooms, daily routine and decision making in ES as well as their changes over time during the last two pandemic years. This second WSES COVID-19 emergency surgery survey investigates the impact of the SARS-CoV-2 pandemic on ES during the course of the pandemic.
Methods: A web survey had been distributed to medical specialists in ES during a four-week period from January 2022, investigating the impact of the pandemic on patients and septic diseases both requiring ES, structural problems due to the pandemic and time-to-intervention in ES routine.
Results: 367 collaborators from 59 countries responded to the survey. The majority indicated that the pandemic still significantly impacts on treatment and outcome of surgical emergency patients (83.1% and 78.5%, respectively). As reasons, the collaborators reported decreased case load in ES (44.7%), but patients presenting with more prolonged and severe diseases, especially concerning perforated appendicitis (62.1%) and diverticulitis (57.5%). Otherwise, approximately 50% of the participants still observe a delay in time-to-intervention in ES compared with the situation before the pandemic. Relevant causes leading to enlarged time-to-intervention in ES during the pandemic are persistent problems with in-hospital logistics, lacks in medical staff as well as operating room and intensive care capacities during the pandemic. This leads not only to the need for triage or transferring of ES patients to other hospitals, reported by 64.0% and 48.8% of the collaborators, respectively, but also to paradigm shifts in treatment modalities to non-operative approaches reported by 67.3% of the participants, especially in uncomplicated appendicitis, cholecystitis and multiple-recurrent diverticulitis.
Conclusions: The SARS-CoV-2 pandemic still significantly impacts on care and outcome of patients in ES. Well-known problems with in-hospital logistics are not sufficiently resolved by now; however, medical staff shortages and reduced capacities have been dramatically aggravated over last two pandemic years
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
Gut mucosa dysfunction in a porcine model of hepatectomy combined with liver ischemia/reperfusion: the role of desferrioxamine and bioartificial liver support
Background: This study aims to evaluate whether injury of gut mucosa in a porcine model of post-hepatectomy liver dysfunction can be prevented using antioxidant treatment with desferrioxamine and bioartificial liver support.
Methods: Post-hepatectomy liver failure was induced in pigs combining major (70%) liver resection and ischemia/reperfusion injury. An ischemic period of 150 minutes, was followed by reperfusion for 24 hours. Animals were randomly divided into a control group (n=6), a desferrioxamine group (DFX, n=6) and a bioartificial liver support group (Hepat, n=6). DFX animals were treated with continuous IV infusion of desferrioxamine 100 mg/kg. Hepat group animals were subjected to a 6 hour extracorporeal session with bioartificial liver, starting from 6 hours after reperfusion. Intestinal mucosal injury (IMI), bacterial and endotoxin translocation (BT) were evaluated in all animals. Intestinal mucosa was also evaluated for oxidative markers.
Results: Both therapeutic groups had improvement of liver function and hepatic encephalopathy, significantly lower IMI scores, decreased BT and endotoxinaemia in the portal and systemic circulation and improved oxidative stress markers.
Conclusion: Desferrioxamine as well as bioartificial liver support therapy seems to attenuate mucosal injury and bacterial translocation from post-hepatectomy liver dysfunction following major hepatectomy under vascular control