90 research outputs found
Recurrent Urinary Tract Infections: A Red Herring for Primary Appendiceal Carcinoma
No full textRecurrent Urinary Tract Infections (UTIs) are a common issue in females owing mostly to the anatomy of their urinary tract. It can also hint at a pathology pertaining to the pelvic organs like tumors or infections that infiltrate the urinary bladder. We report the case of a 45-year-old woman who initially presented to her GP with recurrent UTI’s worsening after the insertion of a Mirena coil for contraception. Primary appendiceal carcinomas invading the urinary bladder are very infrequent presentations in general practice. A low threshold for diagnosis should be kept in individuals with chronic symptoms pertaining to the urinary tract and adequate treatment started early to prevent spread
Laparoscopic Repair of Perforated Marginal Ulcer After Roux-en-Y Gastric Bypass: A Case Report and Review of Literature
No full textA Cutting-Edge Hybrid Approach for Precise COVID-19 Detection using Deep Learning
No full textThe early detection of COVID-19 is essential for decision-makers to develop effective containment and treatment plans. Traditionally, researchers interpret computer tomography (CT) scans or X-ray images in order to diagnose this disease. This study aims to demonstrate that deep learning models can be applied to three common medical imaging modes: X-rays, ultrasounds, and CT scans. This study employs and enhances four convolutional neural networks for coronavirus detection, including DenseNet121, ResNet101V2, NASNetMobile, and MobileNetV2. In this study, two main experiments were carried out. In the first experiment, a model was developed by combining imagery data to detect this virus. In order to determine which model performed the best, separate models were trained using different datasets in the second experiment. Because there were only so many photos accessible, data augmentation techniques were used to enhance the amount artificially. The results indicate that the proposed models effectively accomplished the task of classifying COVID-19. The accuracy rates achieved by the combined model, utilizing DenseNet121, ResNet101V2, NASNetMobile, and MobileNetV2, were 88.21%, 93.02%, and 88.89% respectively. When using the combined imaging dataset, the CNN model employing ResNet101v2 exhibited superior accuracy compared to NASNetMobile, DenseNet121, and MobileNetV2 models
A Cutting-Edge Hybrid Approach for Precise COVID-19 Detection using Deep Learning
No full textThe early detection of COVID-19 is essential for decision-makers to develop effective containment and treatment plans. Traditionally, researchers interpret computer tomography (CT) scans or X-ray images in order to diagnose this disease. This study aims to demonstrate that deep learning models can be applied to three common medical imaging modes: X-rays, ultrasounds, and CT scans. This study employs and enhances four convolutional neural networks for coronavirus detection, including DenseNet121, ResNet101V2, NASNetMobile, and MobileNetV2. In this study, two main experiments were carried out. In the first experiment, a model was developed by combining imagery data to detect this virus. In order to determine which model performed the best, separate models were trained using different datasets in the second experiment. Because there were only so many photos accessible, data augmentation techniques were used to enhance the amount artificially. The results indicate that the proposed models effectively accomplished the task of classifying COVID-19. The accuracy rates achieved by the combined model, utilizing DenseNet121, ResNet101V2, NASNetMobile, and MobileNetV2, were 88.21%, 93.02%, and 88.89% respectively. When using the combined imaging dataset, the CNN model employing ResNet101v2 exhibited superior accuracy compared to NASNetMobile, DenseNet121, and MobileNetV2 models.
Manuscript received: 23 Jan 2024 | Revised: 26 Feb 2024 | Accepted: 25 Mar 2024 | Published: : 30 Apr 202
CROSS CULTURAL ADAPTION, VALIDITY AND RELIABILITY OF URDU VERSIONS OF WOMAC INDEX FOR KNEE OSTEOARTHRITIS INDEX
No full textObjective: The aim of this study was to translate and cross culturally adapt Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) from source language, English to target language, Urdu. Moreover, to establish its internal consistency, test-retest reliability and validity among knee osteoarthritis patients.
Methods: WOMAC was first translated from English to Urdu as per international standardized guidelines. The synthesized version of WOMAC Urdu was initially tested in 12 patients. Final established WOMAC Urdu was administered to 120 knee osteoarthritis patients two times with a 48-hour gap between. IBM Statistics Software SPSS 20.0 was used to analyze scores.
Results: Results showed an excellent internal consistency Cronbach’s Alpha ranging from 0.816 to 0.920 for subscales of pain, stiffness and physical function. Intraclass coefficient was ranging from 0.769 to 0.945, Spearman Correlation 0.841 to 0.844 with significant correlation 0.027. There was no ceiling or floor effect with 100% kappa agreement. An excellent content validity was exhibited by significant difference of score with changing severity of knee osteoarthritis.
Conclusion: The findings conclude that WOMAC Urdu cross culturally adapted and found to be valid and reliable outcome measure for knee osteoarthritis in Urdu speaking patients.
Keywords: WOMAC Urdu, Knee Osteoarthritis, Cross Cultural Adaptation, Health Status, Reliabilit
Current status of liver surgery for non-colorectal non-neuroendocrine liver metastases: the NON.LI.MET. Italian Society for Endoscopic Surgery and New Technologies (SICE) and Association of Italian Surgeons in Europe (ACIE) collaborative international survey
No full textDespite the increasing trend in liver resections for non-colorectal non-neuroendocrine liver metastases (NCNNLM), the role of surgery for these liver malignancies is still debated. Registries are an essential, reliable tool for assessing epidemiology, diagnosis, and therapeutic approach in a single hub, especially when data are dispersive and inconclusive, as in our case. The dissemination of this preliminary survey would allow us to understand if the creation of an International Registry is a viable option, while still offering a snapshot on this issue, investigating clinical practices worldwide. The steering committee designed an online questionnaire with Google Forms, which consisted of 37 questions, and was open from October 5th, 2022, to November 30th, 2022. It was disseminated using social media and mailing lists of the Italian Society of Endoscopic Surgery and New Technologies (SICE), the Association of Italian Surgeons in Europe (ACIE), and the Spanish Chapter of the American College of Surgeons (ACS). Overall, 141 surgeons (approximately 18% of the total invitations sent) from 27 countries on four continents participated in the survey. Most respondents worked in general surgery units (62%), performing less than 50 liver resections/year (57%). A multidisciplinary discussion was currently performed to validate surgical indications for NCNNLM in 96% of respondents. The most commonly adopted selection criteria were liver resectability, RECIST criteria, and absence of extrahepatic disease. Primary tumors were generally of gastrointestinal (42%), breast (31%), and pancreaticobiliary origin (13%). The most common interventions were parenchymal-sparing resections (51% of respondents) of metachronous metastases with an open approach. Major post-operative complications (Clavien-Dindo > 2) occurred in up to 20% of the procedures, according to 44% of respondents. A subset analysis of data from high-volume centers (> 100 cases/year) showed lower post-operative complications and better survival. The present survey shows that NCNNLM patients are frequently treated by surgeons in low-volume hospitals for liver surgery. Selection criteria are usually based on common sense. Liver resections are performed mainly with an open approach, possibly carrying a high burden of major post-operative complications. International guidelines and a specific consensus on this field are desirable, as well as strategies for collaboration between high-volume and low-volume centers. The present study can guide the elaboration of a multi-institutional document on the optimal pathway in the management of patients with NCNNLM
Self-reported health and smoking status, and body mass index: a case-control comparison based on GEN SCRIP (GENetics of SChizophRenia In Pakistan) data
No full textIntroduction Individuals with schizophrenia are at a high risk of physical health comorbidities and premature mortality. Cardiovascular and metabolic causes are an important contributor. There are gaps in monitoring, documenting and managing these physical health comorbidities. Because of their condition, patients themselves may not be aware of these comorbidities and may not be able to follow a lifestyle that prevents and manages the complications. In many low-income and middle-income countries including Pakistan, the bulk of the burden of care for those struggling with schizophrenia falls on the families.Objectives To determine the rate of self-reported physical health disorders and risk factors, like body mass index (BMI) and smoking, associated with cardiovascular and metabolic disorders in cases of schizophrenia compared with a group of mentally healthy controls.Design A case-controlled, cross-sectional multicentre study of patients with schizophrenia in Pakistan.Settings Multiple data collection sites across the country for patients, that is, public and private psychiatric OPDs (out patient departments), specialised psychiatric care facilities, and psychiatric wards of teaching and district level hospitals. Healthy controls were enrolled from the community.Participants We report a total of 6838 participants’ data with (N 3411 (49.9%)) cases of schizophrenia compared with a group of healthy controls (N 3427 (50.1%)).Results BMI (OR 0.98 (CI 0.97 to 0.99), p=0.0025), and the rate of smoking is higher in patients with schizophrenia than in controls. Problems with vision (OR 0.13 (0.08 to 0.2), joint pain (OR 0.18 (0.07 to 0.44)) and high cholesterol (OR 0.13 (0.05 to 0.35)) have higher reported prevalence in controls. The cases describe more physical health disorders in the category ‘other’ (OR 4.65 (3.01 to 7.18)). This captures residual disorders not listed in the questionnaire.Conclusions Participants with schizophrenia in comparison with controls report more disorders. The access in the ‘other’ category may be a reflection of undiagnosed disorders
Young-IFSO Bariatric/Metabolic Surgery Training and Education Survey
No full textBackground This international Young-IFSO survey aims to address variations, trends, and obstacles in bariatric/metabolic surgery (BMS) training globally, since expectations and resources differ among young surgeons.Methods The Young-IFSO scientific team designed an online confidential questionnaire with 50 questions analyzing the individual BMS training. The survey link was sent to all IFSO/ASMBS members and was shared in social media. All Young-IFSO members (age up to 45 years) were invited to participate between 16 December 2022 and 4 February 2023.Results A total of 240 respondents from 61 countries took the survey. Most respondents (70.24%) described their current position as a consultant surgeon with an average of 5.43 years' experience working in BMS, and 55% are working in a bariatric center of excellence. More than 50% of the respondents performed none or less than 10 BMS during residency. Preparation of the stomach and stapling during sleeve gastrectomy (SG) were the first steps performed, and SG was the first BMS completed as a first operating surgeon by most of the respondents (74%). In total, 201 (84.45%) surgeons reported to perform scientific work. Most respondents (90.13%) reported that surgical mentorship had improved their surgical skills.Conclusion This international experts' survey underlines the lack of a standardized global surgical curriculum of BMS during residency. It shows that SG is the single most performed procedure by young surgeons. These data might underline the importance of advancing surgical education in BMS, and accredited fellowship programs should be offered globally to maintain and raise quality of BMS
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