Laparoscopic Treatment of a Huge Mesenteric Chylous Cyst

Mesenteric chylous cysts are rare. This study suggests that even large mesenteric chylous cysts may be managed with minimally invasive means

Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids

In smart electrical grids, fault detection tasks may have a high impact on society due to their economic and critical implications. In the recent years, numerous smart grid applications, such as defect detection and load forecasting, have embraced data-driven methodologies. The purpose of this study is to investigate the challenges associated with the security of machine learning (ML) applications in the smart grid scenario. Indeed, the robustness and security of these data-driven algorithms have not been extensively studied in relation to all power grid applications. We demonstrate first that the deep neural network method used in the smart grid is susceptible to adversarial perturbation. Then, we highlight how studies on fault localization and type classification illustrate the weaknesses of present ML algorithms in smart grids to various adversarial attacksComment: Accepted in AdvML@KDD'2

Direct Anterior versus Lateral Approach for Femoral Neck Fracture: Role in COVID-19 Disease

Background: During the COVID-19 emergency, the incidence of fragility fractures in elderly patients remained unchanged. The management of these patients requires a multidisciplinary approach. The study aimed to assess the best surgical approach to treat COVID-19 patients with femoral neck fracture undergoing hemiarthroplasty (HA), comparing direct lateral (DL) versus direct anterior approach (DAA). Methods: A single-center, observational retrospective study including 50 patients affected by COVID-19 infection (30 males, 20 females) who underwent HA between April 2020 to April 2021 was performed. The patients were allocated into two groups according to the surgical approach used: lateral approach and anterior approach. For each patient, the data were recorded: age, sex, BMI, comorbidity, oxygen saturation (SpO2), fraction of the inspired oxygen (FiO2), type of ventilation invasive or non-invasive, HHb, P/F ratio (PaO2/FiO2), hemoglobin level the day of surgery and 1 day post operative, surgical time, Nottingham Hip Fractures Score (NHFS) and American Society of Anesthesiologists Score (ASA). The patients were observed from one hour before surgery until 48 h post-surgery of follow-up. The patients were stratified into five groups according to Alhazzani scores. A non-COVID-19 group of patients, as the control, was finally introduced. Results: A lateral position led to a better level of oxygenation (p < 0.01), compared to the supine anterior approach. We observed a better post-operative P/F ratio and a reduced need for invasive ventilation in patients lying in the lateral position. A statistically significant reduction in the surgical time emerged in patients treated with DAA (p < 0.01). Patients within the DAA group had a significantly lower blood loss compared to direct lateral approach. Conclusions: DL approach with lateral decubitus seems to preserved respiratory function in HA surgery. Thus, the lateral position may be associated with beneficial effects on gas exchange

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules.

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs

Computer-assisted navigation for intramedullary nailing of intertrochanteric femur fractures: a preliminary result

Aim To demonstrate a reduction of risk factors ray-depending in proximal femur nailing of intertrochanteric femur fractures, comparing standard technique with computer-assisted navigation system. Methods One hundred patients hospitalised between October 2021 and June 2022 with intertrochanteric femur fractures type 31-A1 and 31-A2 were prospectively enrolled and divided randomly into two groups. A study group was treated with computer-assisted navigation system ATLAS (Masmec Biomed, Modugno, Bari, Italy) (20 patients), while a control group received the standard nailing technique. The same intertrochanteric nail was implanted by a single senior surgeon, Endovis BA 2 (EBA2, Citieffe, Calderara di Reno, Bologna, Italy). The following data were recorded: the setup time of operating room (STOR; minutes); surgical time (ST; minutes); radiation exposure time (ETIR; seconds) and dose area product (DAP; cGy·cm2). Results Patients underwent femur nailing with computer-assisted navigation system reported more set-up time of operating room (24.87±4.58; p<0.01), less surgical time (26.15±5.80; p<0.01), less time of radiant exposure (4.84±2.07; p<0.01) and lower dose area product (16.26±2.91; p<0.01). Conclusion The preliminary study demonstrated that computerassisted navigation allowed a better surgical technique standardization, significantly reduced exposure to ionizing radiation, including a reduction in surgical time. The ATLAS system could also play a key role in residents improving learning curve

Blood serum amyloid A as potential biomarker of pembrolizumab efficacy for patients affected by advanced non-small cell lung cancer overexpressing PD-L1: results of the exploratory "FoRECATT" study

Background: Identifying the patients who may benefit the most from immune checkpoints inhibitors remains a great challenge for clinicians. Here we investigate on blood serum amyloid A (SAA) as biomarker of response to upfront pembrolizumab in patients with advanced non-small-cell lung cancer (NSCLC). Methods: Patients with PD-L1 ≥ 50% receiving upfront pembrolizumab (P cohort) and with PD-L1 0-49% treated with chemotherapy (CT cohort) were evaluated for blood SAA and radiological response at baseline and every 9&nbsp;weeks. Endpoints were response rate (RR) according to RECIST1.1, progression-free (PFS) and overall survival (OS). The most accurate SAA cut-off to predict response was established with ROC analysis in the P cohort. Results: In the P Cohort (n = 42), the overall RR was 38%. After a median follow-up of 18.5&nbsp;months (mo), baseline SAA ≤ the ROC-derived cut-off (29.9&nbsp;mg/L; n = 28/42.67%) was significantly associated with higher RR (53.6 versus 7.1%; OR15, 95% CI 1.72-130.7, p = 0.009), longer PFS (17.4 versus 2.1 mo; p &lt; 0.0001) and OS (not reached versus 7.2mo; p &lt; 0.0001) compared with SAA &gt; 29.9&nbsp;mg/L. In multivariate analysis, low SAA positively affects PFS (p = 0.001) and OS (p = 0.048) irrespective of ECOG PS, number of metastatic sites and pleural effusion. SAA monitoring (n = 40) was also significantly associated with survival endpoints: median PFS 17.4 versus 2.1 mo and median OS not reached versus 7.2 mo when SAA remained low (n = 14) and high (n = 12), respectively. In the CT Cohort (n = 30), RR was not affected by SAA level (p &gt; 0.05) while low SAA at baseline (n = 17) was associated with better PFS (HR 0.38, 95% CI 0.16-0.90, p = 0.006) and OS (HR 0.25, 95% CI 0.09-0.67, p &lt; 0.001). Conclusion: Low SAA predicts good survival outcomes irrespective of treatment for advanced NSCLC patients and higher likelihood of response to upfront pembrolizumab only. The strong prognostic value might be exploited to easily identify patients most likely to benefit from immunotherapy. A further study (FoRECATT-2) is ongoing to confirm results in a larger sample size and to investigate the effect of SAA on immune response in vitro assays

Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach

Dietary behaviour is a core element in diabetes self-management. There are no remarkable differences between nutritional guidelines for people with type 2 diabetes and healthy eating recommendations for the general public. This study aimed to evaluate dietary differences between subjects with and without diabetes and to describe any emerging dietary patterns characterizing diabetic subjects. In this cross-sectional study conducted on older adults from Southern Italy, eating habits in the “Diabetic” and “Not Diabetic” groups were assessed with FFQ, and dietary patterns were derived using an unsupervised learning algorithm: principal component analysis. Diabetic subjects (n = 187) were more likely to be male, slightly older, and with a slightly lower level of education than subjects without diabetes. The diet of diabetic subjects reflected a high-frequency intake of dairy products, eggs, vegetables and greens, fresh fruit and nuts, and olive oil. On the other hand, the consumption of sweets and sugary foods was reduced compared to non-diabetics (23.74 ± 35.81 vs. 16.52 ± 22.87; 11.08 ± 21.85 vs. 7.22 ± 15.96). The subjects without diabetes had a higher consumption of red meat, processed meat, ready-to-eat dishes, alcoholic drinks, and lower vegetable consumption. The present study demonstrated that, in areas around the Mediterranean Sea, older subjects with diabetes had a healthier diet than their non-diabetic counterparts

Preface of the 31st Italian Symposium on Advanced Database Systems

This volume contains the proceedings of the 31st Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), held in Galzinagno Terme (Padua, Italy) from 2 to 5 July 2023.</p

Preface of the 31st Italian Symposium on Advanced Database Systems

This volume contains the proceedings of the 31st Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), held in Galzinagno Terme (Padua, Italy) from 2 to 5 July 2023.</p