52 research outputs found
Supplemental Material - Injury Patterns of Electric Scooter-Related Trauma: A Systematic Review With Proportion Meta-Analysis
No full textSupplemental Material for Injury Patterns of Electric Scooter-Related Trauma: A Systematic Review With Proportion Meta-Analysis by Andrea Spota, MD, Stefano Granieri, MD, Luca Ferrario, MD, Beatrice Zamburlini, MD, Simone Frassini, MD, Elisa Reitano, MD, Stefano PB Cioffi, MD, Michele Altomare, MD, Roberto Bini, MD, Francesco Virdis, MD, Osvaldo Chiara, MD, and Stefania Cimbanassi, MD in The American Surgeon™.</p
Intraperitoneal chemotherapy in the management of pancreatic adenocarcinoma: A systematic review and meta-analysis
No full textPancreatic cancer represents one of the leading causes of cancer-related death worldwide. Cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC), normothermic intraperitoneal chemotherapy (NIPEC), and pressurized intraperitoneal aerosol chemotherapy (PIPAC) has been proven with curative intent mainly for other tumors and there is a lack of consensus regarding possible benefits also in pancreatic cancer. The present systematic review and meta-analysis aim to provide an up-to-date overview of the effectiveness and safety of intraperitoneal treatments in the management of pancreatic cancer
Prophylactic mesh augmentation after laparotomy for elective and emergency surgery: meta-analysis
No full textBackground: Incisional hernia is a common short- and long-term complication of laparotomy and can lead to significant morbidity. The aim of this systematic review and meta-analysis is to provide an up-to-date overview of the laparotomy closure method in elective and emergency settings with the prophylactic mesh augmentation technique. Methods: The Scopus, PubMed, and Web of Science databases were screened without time restrictions up to 21 June 2022 using the keywords 'laparotomy closure', 'mesh', 'mesh positioning', and 'prophylactic mesh', and including medical subject headings terms. Only RCTs reporting the incidence of incisional hernia and other wound complications after elective or emergency midline laparotomy, where patients were treated with prophylactic mesh augmentation or without mesh positioning, were included. The primary endpoint was to explore the risk of incisional hernia at different follow-up time points. The secondary endpoint was the risk of wound complications. The risk of bias for individual studies was assessed according to the Revised Cochrane risk-of-bias tools for randomized trials. Results: Eighteen RCTs, including 2659 patients, were retrieved. A reduction in the risk of incisional hernia at every time point was highlighted in the prophylactic mesh augmentation group (1 year, risk ratio 0.31, P = 0.0011; 2 years, risk ratio 0.44, P < 0.0001; 3 years, risk ratio 0.38, P = 0.0026; 4 years, risk ratio 0.38, P = 0.0257). An increased risk of wound complications was highlighted for patients undergoing mesh augmentation, although this was not significant. Conclusions: Midline laparotomy closure with prophylactic mesh augmentation can be considered safe and effective in reducing the incidence of incisional hernia. Further trials are needed to identify the ideal type of mesh and technique for mesh positioning, but surgeons should consider prophylactic mesh augmentation to decrease incisional hernia rate, especially in high-risk patients for fascial dehiscence and even in emergency settings. Prospero registration id: CRD42022336242 (https://www.crd.york.ac.uk/prospero/record_email.php)
Functional analysis of a process line aimed at supporting the risk analysis with the ALBA methodology : the use case of MAPEI
No full textLAUREA SPECIALISTICALa tesi in oggetto è stata svolta con lo scopo ultimo di permettere a qualsiasi analista di rendere riproducibile e sistematica l’analisi funzionale attraverso l’identificazione di quei passaggi reputati fondamentali per la buona riuscita dell’analisi di un processo.
Passaggi o momenti fondamentali della nostra analisi sono stati: l’identificazione del materiale necessario alla base del nostro percorso, l’estrapolazione delle informazioni dai dati fornitici dall’azienda insieme cui è stato sviluppato il progetto, la resa sistematica della scelta dei dati, il trattamento dei dati stessi e infine lo sviluppo dell’analisi finale relativa alle possibili problematiche di uno dei macchinari oggetto di analisi.
L’analisi funzionale al centro del nostro progetto è stata identificata come la valutazione di tutte quelle azioni che permettono al processo di “passare di livello” senza perdere dati fondamentali ed eliminando inutili passaggi tramite l’utilizzo della logica che governa il processo stesso.
I dati analizzati sono stati valutati ed inseriti nel software A.L.B.A. (Artificial Logic Bayesian Algorithm) a partire dalle variabili stabilite nella suddivisione tra i suoi elementi primari selezionati per la nostra valutazione.
Il software permette di estrarre dati da un input di struttura binaria ed è in grado di identificare i cammini critici presenti, restituendo inoltre tutte le combinazioni possibili e gli eventi più interessanti per la valutazione del decisore in relazione all’importanza della manutenzione degli interventi da eseguire.
La nostra analisi è stata fatta partendo dalla produzione di un collante a base alcolica per l’edilizia, identificando elementi di criticità anche sotto il profilo della sicurezza degli operatori, possibili altri sviluppi possono essere ampliati al re-design del processo o a qualsiasi altro processo con il solo cambiamento delle variabili di riferimento.The thesis I’m proposing has been developed with the idea to provide to any analyst the opportunity to have a reproducible and systematic approach to the functional analysis thanks to an efficient identification of all that passages that must be fundamental for the correct analysis of the project.
The fundamental passages of the analysis have been: the identification of the necessary graphs and diagrams, the extrapolation of the information from the data given us by the company with whom we worked together, let the approach becoming systematic, the treatment of the data and the development of the final analysis concerning the possible problems of one of the equipment of the line under analysis.
The heart of this thesis has been represented by the functional analysis, intended as evaluation of all of the actions that permit the process to go further without losing any fundamental data and deleting useless passages, just using the governing logic of the process.
The data analyzed has been valued and thanks to the A.L.B.A. Software (Artificial Logic Bayesian Algorithm) we insert the inputs and the variables defined by the division of the process in its primary elements selected for the evaluation.
The software provides the possibility to extract from a binary input the critical path in the input, giving also the possible combinations and the identification of the most interesting events for the evaluation of the person that is determining, for example, the priority in the maintenance of the process.
The analysis has been done starting from the production of an alcoholic base adhesive used in the construction sector. We then identify the criticality of the production and of the operators’ security, some other possible development can be extended in the redesign or to any other process with just the changing of the reference variables
Prognostic impact of cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) in gastric cancer patients: A meta-analysis of randomized controlled trials
No full textgastric cancer patients frequently develop peritoneal metastases (PM) with a poor long-term prognosis. A solid body of evidence underlines the beneficial role of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) on survival, but to date, there is a lack of consensus regarding the optimal strategy in the treatment of locally advanced primary tumors with or without peritoneal metastasis. The present meta-analysis aims to assess the impact of CRS + HIPEC on survival analyzing the results of randomized studies only
Prediction of the clinical outcome of NMIBC using Artificial Intelligence
No full textIn our research, we have made a significant advancement in predicting the clinical outcome of high-risk non-muscle invasive bladder cancer (HR-NMIBC) by combining clinicopathological data with image-related features. This integrated approach has shown remarkable improvements in the accuracy of artificial intelligence techniques for outcome prediction.We developed a novel methodology that effectively combines information from cell nuclei per patient, resulting in enhanced classification accuracy. By integrating clinicopathological data with image-related features extracted from medical imaging, we demonstrated the power of AI in more accurately predicting clinical outcomes for HR-NMIBC.Our study provides a comprehensive view of the disease, taking into account both macroscopic characteristics and microscopic details observed at the cellular level. By aggregating information from thousands of cell nuclei for each patient, we transformed raw data into a format suitable for machine learning algorithms, improving the performance of AI techniques in clinical outcome prediction.However, it is essential to address the potential biases and imbalanced variables present in the dataset. We noticed gender imbalance, differences in tumor size, and uneven grading levels, which may affect the generalizability of our conclusions.To enhance our analysis, we retrained a convolutional neural network (CNN) using our image dataset, achieving high accuracy in segmenting hematoxylin and eosin stained images and accurately identifying cell nuclei boundaries. Additionally, we implemented an innovative clustering technique called FlowSOM, enabling us to group and classify millions of cell nuclei based on their characteristics, providing valuable insights into cellular heterogeneity.Our AI models exhibited high performance metrics, particularly the random forest algorithm, which proved most suitable for the task. We also conducted a variable importance analysis, revealing specific cell clusters with significant impact on predicting clinical outcomes, emphasizing the relevance of cellular size and shape in disease progression and treatment response.Applied Mathematic
Prospective validation of the Israeli Score for the prediction of common bile duct stones in patients with acute calculous cholecystitis
No full textBackground
Existing guidelines for predicting common bile duct stones (CBDS) are not specific for acute calculous cholecystitis (ACC). This paper is a posthoc analysis of the S.P.Ri.M.A.C.C study aiming to prospectively validate on a large independent cohort of patients the Israeli Score (IS) in predicting CBDS in patients with ACC.
Methods
The S.P.Ri.M.A.C.C. study is an observational multicenter prospective study endorsed by the World Society of Emergency Surgery (WSES). Between September 1st, 2021, and September 1st, 2022, 1201 participants were included. The Chi-Square test was used to compare categorical data. A Cochran-Armitage test was run to determine whether a linear trend existed between the IS and the presence of CBDS. To assess the accuracy of the prediction model, the receiver operating characteristic (ROC) curve was generated, and the area under the ROC curve (AUC) was calculated. Logistic regression was run to obtain Odds Ratio (OR). A two-tailed p < 0.05 was considered statistically significant.
Results
The rate of CBDS was 1.8% in patients with an IS of 0, 4.2% in patients with an IS of 1, 24.5% in patients with 2 and 56.3% in patients with 3 (p < 0.001). The Cochran-Armitage test of trend showed a statistically significant linear trend, p < 0.001. Patients with an IS of 3 had 64.4 times (95% CI 24.8–166.9) higher odds of having associated CBDS than patients with an IS of 0. The AUC of the ROC curve of IS for the prediction of CBDS was 0.809 (95% CI 0.752–0.865, p < 0.001). By applying the highest cut-off point (3), the specificity reached 99%, while using the lowest cut-off value (0), the sensitivity reached 100%.
Conclusion
The IS is a reliable tool to predict CBDS associated with ACC. The algorithm derived from the IS could optimize the management of patients with ACC
Prospective validation of the Israeli Score for the prediction of common bile duct stones in patients with acute calculous cholecystitis
No full textBACKGROUND: Existing guidelines for predicting common bile duct
stones (CBDS) are not specific for acute calculous cholecystitis
(ACC). This paper is a posthoc analysis of the S.P.Ri.M.A.C.C
study aiming to prospectively validate on a large independent
cohort of patients the Israeli Score (IS) in predicting CBDS in
patients with ACC. METHODS: The S.P.Ri.M.A.C.C. study is an
observational multicenter prospective study endorsed by the World
Society of Emergency Surgery (WSES). Between September 1st, 2021,
and September 1st, 2022, 1201 participants were included. The
Chi-Square test was used to compare categorical data. A
Cochran-Armitage test was run to determine whether a linear trend
existed between the IS and the presence of CBDS. To assess the
accuracy of the prediction model, the receiver operating
characteristic (ROC) curve was generated, and the area under the
ROC curve (AUC) was calculated. Logistic regression was run to
obtain Odds Ratio (OR). A two-tailed p < 0.05 was considered
statistically significant. RESULTS: The rate of CBDS was 1.8\% in
patients with an IS of 0, 4.2\% in patients with an IS of 1,
24.5\% in patients with 2 and 56.3\% in patients with 3 (p <
0.001). The Cochran-Armitage test of trend showed a statistically
significant linear trend, p < 0.001. Patients with an IS of 3 had
64.4 times (95\% CI 24.8-166.9) higher odds of having associated
CBDS than patients with an IS of 0. The AUC of the ROC curve of
IS for the prediction of CBDS was 0.809 (95\% CI 0.752-0.865, p <
0.001). By applying the highest cut-off point (3), the
specificity reached 99\%, while using the lowest cut-off value
(0), the sensitivity reached 100\%. CONCLUSION: The IS is a
reliable tool to predict CBDS associated with ACC. The algorithm
derived from the IS could optimize the management of patients
with ACC
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