THE CORRELATION BETWEEN SPECIALTY CHOICE AND THE QUALITY OF LIFE OF LEBANESE PHYSICIANS

Doctors suffer a stressful life and are less satisfied than individuals in other careers. A trend has been observed among medical students in USA showing a change of specialty choice to alleviate their quality of life. Even though most medical students choose their career path based on the field they are most pleased with, it sounds reasonable to get an idea about the quality of life in the specialty they will elect to do. The objective of this study is to evaluate the correlation between specialty choice and the quality of life of Lebanese physicians, to see which specialties have the most favorable quality of life and present their personal level of satisfaction regarding their lifestyle. This study conducted an anonymous modified short form survey (SF-36) questionnaire and some demographic data among Lebanese physicians practicing in Lebanon. Data was collected via emails using Lime Survey then entered and analyzed on SPSS software version 23.1. P value less than 0.05 was considered significant. 470 complete responses were retrieved in this research by email via Lime Survey. Specialty choice had a significant effect only on three scales; physical functioning (p \u3c .001), social functioning (p \u3c .001) and role limitations due to emotional problems (p = .25), with no significant effect on energy and fatigue, emotional well-being, role limitations due to physical health, general health and pain. It was also found that specialty had significant effect on personal satisfaction (p =.016). The study concluded that Lebanese physicians who practice laboratory medicine, family medicine, and pathology specialties having the most favorable quality of life based on the scales assessed in the SF-36 and that those practicing pediatrics had lower levels of personal satisfaction compared to those with pathology specialty

دور الثقافة التنظيمية في تحقيق التوجّه الريادي للمنظمات دراسة ميدانية على الشركة العامة للصناعات التحويلية " كنار"

هدفت هذه الدراسة إلى تقييم الثقافة التنظيمية السائدة في الشركة محل الدراسة من خلال الأبعاد الآتية: (القيم، والمعتقدات، والأعراف والتوقعات)، وتقييم مستوى التوجّه الريادي المتوافر فيها، ودراسة دور الثقافة التنظيمية في تحقيق التوجه الريادي، واعتمدت الدراسة المنهج الوصفي التحليلي، وعلى أداة الاستبانة لجمع البيانات من عينة الدراسة التي شملت 75 موظفاً فيها من مختلف المستويات الإدارية. ولتحقيق ذلك تمّ صياغة فرضية رئيسية واحد تتفرع عنها أربعة فرضيات فرعية، وقد توصلت الباحثة إلى عدّة نتائج أهمّها: لا تتمتع الشركة محل الدراسة بالثقافة التنظيمية اللازمة لتعزيز ولاء الموظف وانتمائه إلى عمله، ولا تتبنى الشركة محل الدراسة التوجه الريادي الذي يعزز قدرتها على إيجاد حلول بديلة للمشكلات التي واجهتها بأسرع وقت، حيث لم تتأقلم الشركة محل الدراسة بمرونة مع التغييرات الطارئة مما أثر ذلك على نتائج أعمالها، ولا توجد علاقة ذات دلالة إحصائية بين كل من القيم  والمعتقدات والأعراف التنظيمية والتوجه الريادي في الشركة محل الدراسة، بينما توجد علاقة ذات دلالة إحصائية بين التوقعات التنظيمية والتوجه الريادي في الشركة محل الدراسة، ولكنها علاقة ضعيفة جداً. وتوجد علاقة ذات دلالة إحصائية بين الثقافة التنظيمية والتوجه الريادي في الشركة محل الدراسة، ولكنها علاقة ضعيفة جداً

Supervoxel based 3D diseased lung segmentation

Computer-Aided Diagnosis relies on accurate tumor volume and heterogeneity assessment through CT-scans. Precise lesion segmentation is essential for patient diagnosis, therefore the development of automatic tools for lesion segmentation is needed. To improve lung nodule segmentation performance, lung segmentation masks serve as valuable priors, narrowing the focus to lung regions. Current methods suffer from the exclusion of pathological areas, especially in oncology patients, since tumor tissue differ in voxel density from other structures in the lung. Consequently, ensuring accurate lung segmentation encompassing all lesions is crucial. We developed a method based on supervoxels to fully segment the lung while encompassing nodules if present using a propagation algorithm based on geometrical properties. We compared our method to a morphology based method and neural networks trained to segment the lungs. Our method had the best performance in the inclusion of lung lesions, while retaining an adequate level of precision

3D lung nodule segmentation from 2D annotations using morphological operations

International audienceTumor volume and heterogeneity are important for patient diagnosis, and automatic lesion segmentation is needed to compute this information from routine CT-Scans. Training a supervised neural network to solve these tasks demands good quality annotations on a large quantity of fully annotated scans, which are difficult and time-consuming to obtain. We propose a fast automatic method using morphological operators to create 3D masks from hand drawn contours of the lesions on their largest axial slice. This type of annotation leads to more precise 3D masks than points or ellipses. Thus, the obtained mask may be used to train end-to-end neural networks for detection and semantic segmentation of lesions on CT-Scans in 3D. We tested this methodology on the LIDC-LUNA dataset to produce the 3D masks from automatically selected 2D annotations. We also produced 3D masks of 115 lung lesions from their 2D contours, and compared them to ground truth 3D masks on an in-house dataset. The results are promising, and the method could be adapted to other organs

3D lung nodule segmentation from 2D annotations using morphological operations

International audienceTumor volume and heterogeneity are important for patient diagnosis, and automatic lesion segmentation is needed to compute this information from routine CT-Scans. Training a supervised neural network to solve these tasks demands good quality annotations on a large quantity of fully annotated scans, which are difficult and time-consuming to obtain. We propose a fast automatic method using morphological operators to create 3D masks from hand drawn contours of the lesions on their largest axial slice. This type of annotation leads to more precise 3D masks than points or ellipses. Thus, the obtained mask may be used to train end-to-end neural networks for detection and semantic segmentation of lesions on CT-Scans in 3D. We tested this methodology on the LIDC-LUNA dataset to produce the 3D masks from automatically selected 2D annotations. We also produced 3D masks of 115 lung lesions from their 2D contours, and compared them to ground truth 3D masks on an in-house dataset. The results are promising, and the method could be adapted to other organs

Supervoxel based 3D diseased lung segmentation

Computer-Aided Diagnosis relies on accurate tumor volume and heterogeneity assessment through CT-scans. Precise lesion segmentation is essential for patient diagnosis, therefore the development of automatic tools for lesion segmentation is needed. To improve lung nodule segmentation performance, lung segmentation masks serve as valuable priors, narrowing the focus to lung regions. Current methods suffer from the exclusion of pathological areas, especially in oncology patients, since tumor tissue differ in voxel density from other structures in the lung. Consequently, ensuring accurate lung segmentation encompassing all lesions is crucial. We developed a method based on supervoxels to fully segment the lung while encompassing nodules if present using a propagation algorithm based on geometrical properties. We compared our method to a morphology based method and neural networks trained to segment the lungs. Our method had the best performance in the inclusion of lung lesions, while retaining an adequate level of precision

Establishing an ECMO program in a developing country: challenges and lessons learned.

AIM: The ECMO (extracorporeal membrane oxygenation) Program at the American University of Beirut Medical Center was established in November 2015 as the first program serving adult and pediatric population in a low-resource setting. The aim of the study is to describe the challenges faced during the establishment of the program and factors leading to its success. METHODS: The program establishment is described. The preparation phase, included the strategic, financial, and clinical planning by administration, nursing, and a multidisciplinary team of physicians. The training and education phase included all the involved nurses, perfusionists, and physicians. Concerns were heard from various stakeholders, and the challenges were analyzed and discussed. RESULTS: The preparation committee chose the adequate equipment, responded to the concerns, defined roles and responsibilities through credentialing and privileging, wrote policies and protocols, and established a strategy to decide for the ECMO indication. Selected team of nurses, physicians, and perfusionists are identified and trained locally, and abroad. A full-time ECMO physician was recruited to launch the program. Twelve patients (6 adults, 3 children, and 3 neonates) were supported by ECMO, for cardiac and respiratory indications. Eleven patients were supported by veno-arterial ECMO, and 1 patient (a neonate) with veno-venous ECMO. Overall, 75% survived to decannulation and 41% survived to discharge. CONCLUSION: With limited human and financial resources, new ECMO centers need to carefully establish selection criteria that may differ from those used in developed countries. Indications should be discussed on a case by case basis, taking into account clinical, social, and financial issues. This experience might help other institutions in developing countries to build their own program despite financial and human limitations

Better than RECIST and Faster than iRECIST: Defining the Immunotherapy Progression Decision Score to Better Manage Progressive Tumors on Immunotherapy

International audienceAbstract Purpose: The objective of the study is to propose the immunotherapy progression decision (iPD) score, a practical tool based on patient features that are available at the first evaluation of immunotherapy treatment, to help oncologists decide whether to continue the treatment or switch rapidly to another therapeutic line when facing a progressive disease patient at the first evaluation. Experimental Design: This retrospective study included 107 patients with progressive disease at first evaluation according to RECIST 1.1. Clinical, radiological, and biological data at baseline and first evaluation were analyzed. An external validation set consisting of 31 patients with similar baseline characteristics was used for the validation of the score. Results: Variables were analyzed in a univariate study. The iPD score was constructed using only independent variables, each considered as a worsening factor for the survival of patients. The patients were stratified in three groups: good prognosis (GP), poor prognosis (PP), and critical prognosis (CP). Each group showed significantly different survivals (GP: 11.4, PP: 4.4, CP: 2.3 months median overall survival, P < 0.001, log-rank test). Moreover, the iPD score was able to detect the pseudoprogressors better than other scores. On the validation set, CP patients had significantly worse survival than PP and GP patients (P < 0.05, log-rank test). Conclusions: The iPD score provides oncologists with a new evaluation, computable at first progression, to decide whether treatment should be continued (for the GP group), or immediately changed for the PP and CP groups. Further validation on larger cohorts is needed to prove its efficacy in clinical practice