Unlabelled: The aim of this study was trying to create a new instrument able to evaluate the final gravity prognostic of acute pancreatitis, taking note that none of used scores has proved to have a complete efficiency in such kind of appreciations.
Method: The study has been made on 437 patients treated in the Surgical Clinic of St Pantelimon Hospital between 1996-2000. There have been analyzed all clinical, biochemical, imagistic and operative elements and there were selected those semnificatively correlated with the results.
Results: We obtained a four-degree classification of potential gravity of the disease in aim to know how aggressive the therapy should be, even in delusive forms of the disease.
Conclusions: We so propose to analyze this new classification that offered us to our patient's results able to reduce mortality.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Rates and Predictors of Malignancy in Bethesda III and IV Thyroid Nodules: A Prospective Study.
Cureus
December 2024
Internal Medicine, University of Alexandria, Alexandria, EGY.
Aim: Thyroid nodules, based on high-resolution ultrasonography (HRUS), are among the most common endocrine abnormalities that affect the general population because of their high estimated prevalence rates. Fine needle aspiration cytology (FNAC) is a safe, cost-effective modality to differentiate between benign and malignant thyroid nodules based on the Bethesda System for Reporting Thyroid Cytopathology (BSRTC), thus avoiding unnecessary surgery. However, categories III and IV of BSRTC remain a controversial issue in clinical practice, encompassing a wide range of risks of malignancy.
View Article and Find Full Text PDFDFMA: an improved DeepLabv3+ based on FasterNet, multi-receptive field, and attention mechanism for high-throughput phenotyping of seedlings.
Front Plant Sci
January 2025
Institute of Crop Science, Huzhou Academy of Agriculture Sciences, Huzhou, China.
With the rapid advancement of plant phenotyping research, understanding plant genetic information and growth trends has become crucial. Measuring seedling length is a key criterion for assessing seed viability, but traditional ruler-based methods are time-consuming and labor-intensive. To address these limitations, we propose an efficient deep learning approach to enhance plant seedling phenotyping analysis.
View Article and Find Full Text PDFCan a mechanical circulatory support comprehensive approach to cardiogenic shock at referral centers reduce 30-day mortality?
Front Cardiovasc Med
January 2025
School of Medicine, Vita-Salute San Raffaele University, Milan, Italy.
Although mortality risk prediction in cardiogenic shock (CS) is possible, assessing the impact of the multitude of therapeutic efforts on outcomes is not straightforward. We assessed whether a temporary mechanical circulatory support comprehensive approach to the treatment of CS may reduce 30-day mortality as compared to expected mortality predicted by the recently proposed Cardiogenic Shock Score (CSS). Consecutive CS patients supported by pVAD Impella (Abiomed, Danvers, MA) at two national referral centers were included.
View Article and Find Full Text PDFImproving equity through barrier-free transportation: an evaluation of Shanghai metro stations.
Front Public Health
January 2025
School of Design, Shanghai Jiao Tong University, Shanghai, China.
Introduction: As urbanization progresses and vulnerable populations increase, equitable accessibility remains a critical issue. This study evaluates the accessibility of transit-oriented development (TOD) in Shanghai, focusing on barrier-free facilities in metro stations.
Methods: A comprehensive evaluation framework combining the Analytic Hierarchy Process (AHP) and the System Usability Scale (SUS) was developed to assess metro station accessibility.
From prediction to practice: mitigating bias and data shift in machine-learning models for chemotherapy-induced organ dysfunction across unseen cancers.
BMJ Oncol
November 2024
Department of Computer Science, Durham University, Durham, UK.
Objectives: Routine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. This study aims to develop models that could support individualised decisions on the timing of renal and hepatic monitoring while exploring the effect of data shift on model performance.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!