Search Results (6)

Landslides are among the most relevant and potentially damaging natural risks, causing material and human losses. The department of Aube in France is well known for several major landslide occurrences. This study focuses on the assessment of Landslide Susceptibility (LS) using the Frequency Ratio (FR) as a statistical method, the Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) method, and Random Forest (RF) and k-Nearest Neighbor (kNN) as machine learning methods in the Aube department, northeast of France. Subsequently, the thematic layers of eight landslide causative factors, including distance to hydrography, density of quarries, elevation, slope, lithology, distance to roads, distance to faults, and rainfall, were generated in the geographic information system (GIS) environment. The thematic layers were integrated and processed to map landslide susceptibility in the study area. On the other hand, an inventory of landslides was carried out based on the database created by the French Geological Survey (BRGM), where 157 landslide occurrences were selected, and then RF and kNN models were trained to generate landslide maps (LSMs) of the study area. The generated maps were assessed by using the Area Under the Receiver Operating Characteristic Curve (ROC AUC). Subsequently, the accuracy assessment of the FR model revealed more accurate results (AUC = 66.0%) than AHP, outperforming the latter by 6%, while machine learning models results showed that RF gave better results than kNN (<7.3%) with AUC = 95%. Following the analysis of LS mapping results, lithology, distance to the hydrographic network, distance to roads, and elevation were the four main factors controlling landslide susceptibility in the study area. Future mitigation and protection activities within the Aube department can benefit from the present study mapping results, implicating an optimized land management for decision-makers. Full article

Background: General practitioners (GPs) played a decisive role during the COVID-19 epidemic, particularly in the identification and care of patients at home. This study aimed to describe the primary care physicians’ perceptions of the COVID-19 crisis and to guide future decisions regarding measures to prolong, abrogate, or improve upon methods for crisis management. Methods: This is a cross-sectional study based on a 30-item questionnaire aiming to investigate how primary care physicians (GPs) working in the rural Aube Department experienced the COVID-19 crisis. Results: Among the 152 respondents, 60.5% were not satisfied with the level of information from authorities during the crisis. By multivariate analysis, a feeling of having been adequately informed (OR 21.87, 95%CI 4.14–115.53) and a feeling that non-COVID-19-related diseases were adequately managed (OR 6.42, 95%CI 1.07–38.51) were both significantly associated with an overall satisfaction with the management of the crisis. Conclusion: This study about rural primary care physicians in Eastern France highlights some of the weaknesses of the French healthcare system in terms of the provision of primary care during the epidemic. A leading cause of dissatisfaction was that the information relayed by the health authorities about the disease and its management largely overlooked the primary care providers, many of whom had to rely on traditional media to obtain information. Full article

Abnormal uterine bleeding (AUB) is a condition defined as all uterine bleeding that differs from physiological menstruation. The etiology of AUB has been classified by the International Federation of Gynecology and Obstetrics (FIGO). It includes structural categories, such as endometrial polyps, adenomyosis, leiomyomas, hyperplasia, and malignant neoplasms, and non-structural categories, i.e., hemorrhages due to congenital and acquired coagulopathies, ovarian dysfunction, disorders of the local endometrial hemostasis mechanism with normal organ structure, iatrogenic causes, and due to other poorly defined causes. This is a retrospective study based on the medical data of a group of 543 women aged 21–88 years (52.81 ± 11.79) (p < 0.01) hospitalized at the Gynecology and Obstetrics Department in Biała Podlaska, Poland. These patients underwent an hysteroscopy procedure due to excessive uterine bleeding of varied, FIGO-divided etiology. The results show the dependence of postoperative hemoglobin and platelet count on the etiology of bleeding and the age of the women. The majority of patients had normal hemoglobin and platelet counts after the procedure, while moderate anemia was the most common disorder. It occurred most frequently in patients undergoing hysteroscopy due to heavy menstrual bleeding. Full article

Background. Abnormal uterine bleeding (AUB) is a common gynecologic condition, and proper management is based on the histological evaluation of an adequate endometrial sample obtained via biopsy. The aims of this study were to evaluate factors influencing the reliability and success rate of Pipelle endometrial sampling for histopathological diagnosis. Methods. One hundred and eighty patients with AUB underwent endometrial sampling using both Pipelle and dilatation and curettage (D&C) procedures at the Clinical Academic Department of Women’s Health, University Medical Center between January 2019 and April 2021. We analyzed the effects of age, menopausal status, ethnicity, body mass index (BMI), provider experience, and procedure indication on the success and reliability of each procedure. Results. Pipelle sampling was successful in 144 (80.56%) women, while D&C was successful in 164 (91.11%) women. Analysis using Fisher’s exact test showed that age, menopausal status, and biopsy indication were factors affecting the success rate of both methods, while ethnicity, BMI, and physician experience had no influence. Overall concordance in the histopathological results between Pipelle and D&C was 91.72%. Conclusion. Pipelle sampling was found to be reliable for the detection of endometrial carcinoma and endometrial hyperplasia, while its reliability was low in cases of endometrial polyps. The endometrial sampling approach should be personalized in daily clinical practice for women with AUB, and Pipelle sampling is not suitable for all patients. If an endometrial polyp is suspected, the physician should consider other diagnostic tools, bearing in mind all of the factors influencing endometrial sampling success and reliability rates. Full article

Assessing the health profiles of populations is a crucial task to create a coherent healthcare offer. Emergency Departments (EDs) are at the core of the healthcare system and could benefit from this evaluation via an improved understanding of the healthcare needs of their population. This paper proposes a novel hierarchical agglomerative clustering algorithm based on multimorbidity analysis. The proposed approach constructs the clustering dendrogram by introducing new quality indicators based on the relative risk of co-occurrences of patient diagnoses. This algorithm enables the detection of multimorbidity patterns by merging similar patient profiles according to their common diagnoses. The multimorbidity approach has been applied to the data of the largest ED of the Aube Department (Eastern France) to cluster its patient visits. Among the 120,718 visits identified during a 24-month period, 16 clusters were identified, accounting for 94.8% of the visits, with the five most prevalent clusters representing 63.0% of them. The new quality indicators show a coherent and good clustering solution with a cluster membership of 1.81 based on a cluster compactness of 1.40 and a cluster separation of 0.77. Compared to the literature, the proposed approach is appropriate for the discovery of multimorbidity patterns and could help to develop better clustering algorithms for more diverse healthcare datasets. Full article

In recent years, the competition of uses for scarce and highly valuable natural resources, and the frequency and severity of natural and technological disasters have increased, and this trend is likely to worsen in the years to come. In the Mediterranean area, especially in its Eastern part, the high human exploitation driven by different economic sectors and interests is resulting in intensive use of the land and its resources. Tourism intensification, rapid growth of urban settlement and related sprawl, movement and displacement of populations, rural abandonment, and adoption of different agricultural techniques are profoundly and rapidly changing the landscape character of the East Mediterranean. In view of the risks to cultural and natural heritage, a Landscape Risk Assessment Model (LRA) and Decision Support System (LDSS) were developed through the MedScapes-ENPI project. This paper reports the experience conducted at the Landscape Design and Ecosystem Management Department (LDEM) in the American University of Beirut (AUB) in developing the two tools, LRA and LDSS. It aims to provide insight into the methodology designed and tested during the length of the project to take into account the protection of landscapes of particular interest as well as the rational planning of all the landscapes with special emphasis on the use of natural resources. The assessment was applied in the study area of each partner country of the ENPI project, allowing for a better understanding of the implications in land-use and conservation decision-making. Full article