Interrupted inferior vena cava syndrome discovered incidentally after minimally invasive mitral valve repair in a 31-year-old female patient: A case report.

INTRODUCTION: Femoral cannulation is a technique used in minimally invasive cardiac surgery (MICS) for accessing the heart through the femoral artery and vein. However, the presence of an interruption in the inferior vena cava (IVC) can pose challenges during the procedure. Understanding the patient's venous anatomy is crucial to ensure successful cannulation. PRESENTATION OF CASE: We present the case of a 31-year-old female patient scheduled for minimally invasive mitral valve repair. During the procedure, femoral vein cannulation was unsuccessful. Subsequent diagnostic Computed Tomography (CT) revealed an interrupted IVC with azygos continuation. DISCUSSION: The interruption of the IVC can make cannulation through the femoral vein difficult or impossible due to the absence of the femoral vein or the presence of a collateral, necessitating alternative approaches. Preoperative imaging, such as CT, plays a significant role in identifying IVC interruptions and guiding surgical planning. CONCLUSION: Our case highlights the challenges associated with IVC interruptions during femoral cannulation in MICS. Preoperative imaging is essential for identifying anatomical variations and determining the most appropriate cannulation approach.

Enteral Sedation in Patients Requiring Mechanical Ventilation During an Intravenous Analgesic and Sedative Shortage.

Background: There is a paucity of data evaluating the use of enteral sedation in mechanical ventilation. A sedative shortage resulted in the use of this approach. Purpose: To evaluate the feasibility of using enteral sedatives to decrease intravenous (IV) analgesia and sedative requirements. Materials/Methods: This single-center, retrospective, observational study compared two groups of patients admitted to the ICU who were mechanically ventilated. One group received a combination of enteral and IV sedatives and the second group received IV monotherapy. Linear mixed model (LMM) analyses were performed to assess the impact of enteral sedatives on IV fentanyl equivalents, IV midazolam equivalents, and propofol. Mann-Whitney U tests were performed on percent of days at goal for Richmond Agitation and Sedation Scale (RASS) and critical care pain observation tool (CPOT) scores. Results: One hundred and four patients were included. The average cohort age was 62 years and 58.7% were male. The median length of mechanical ventilation was 7.1 days and the median length of stay was 11.9 days. The LMM estimated that enteral sedatives reduced IV fentanyl equivalents received per patient by an average of 305.6 mcg/day (P = .04), although did not significantly decrease midazolam equivalents or propofol. There was no statistically significant difference in CPOT scores (P = .57 and P = .46 respectively), however RASS scores in the enteral sedation group were more often at goal (P = .03); oversedation occurred more in the non-enteral sedation group (P = .018). Conclusion: Enteral sedation may be a possible way to decrease IV analgesia requirements during periods of shortage.

New Trends in Melanoma Detection Using Neural Networks: A Systematic Review.

Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease today. The high mortality rate associated with melanoma makes it necessary to detect the early stages to be treated urgently and properly. This is the reason why many researchers in this domain wanted to obtain accurate computer-aided diagnosis systems to assist in the early detection and diagnosis of such diseases. The paper presents a systematic review of recent advances in an area of increased interest for cancer prediction, with a focus on a comparative perspective of melanoma detection using artificial intelligence, especially neural network-based systems. Such structures can be considered intelligent support systems for dermatologists. Theoretical and applied contributions were investigated in the new development trends of multiple neural network architecture, based on decision fusion. The most representative articles covering the area of melanoma detection based on neural networks, published in journals and impact conferences, were investigated between 2015 and 2021, focusing on the interval 2018-2021 as new trends. Additionally presented are the main databases and trends in their use in teaching neural networks to detect melanomas. Finally, a research agenda was highlighted to advance the field towards the new trends.

Using Artificial Neural Networks to Predict Intra-Abdominal Abscess Risk Post-Appendectomy.

Objective: To determine if artificial neural networks (ANN) could predict the risk of intra-abdominal abscess (IAA) development post-appendectomy. Background: IAA formation occurs in 13.6% to 14.6% of appendicitis cases with "complicated" appendicitis as the most common cause of IAA. There remains inconsistency in describing the severity of appendicitis with variation in treatment with respect to perforated appendicitis. Methods: Two "reproducible" ANN with different architectures were developed on demographic, clinical, and surgical information from a retrospective surgical dataset of 1574 patients less than 19 years old classified as either negative (n = 1,328) or positive (n = 246) for IAA post-appendectomy for appendicitis. Of 34 independent variables initially, 12 variables with the highest influence on the outcome selected for the final dataset for ANN model training and testing. Results: A total of 1574 patients were used for training and test sets (80%/20% split). Model 1 achieved accuracy of 89.84%, sensitivity of 70%, and specificity of 93.61% on the test set. Model 2 achieved accuracy of 84.13%, sensitivity of 81.63%, and specificity of 84.6%. Conclusions: ANN applied to selected variables can accurately predict patients who will have IAA post-appendectomy. Our reproducible and explainable ANNs potentially represent a state-of-the-art method for optimizing post-appendectomy care.

Deep Learning-Based Methods for Automatic Diagnosis of Skin Lesions.

The main purpose of the study was to develop a high accuracy system able to diagnose skin lesions using deep learning-based methods. We propose a new decision system based on multiple classifiers like neural networks and feature-based methods. Each classifier (method) gives the final decision system a certain weight, depending on the calculated accuracy, helping the system make a better decision. First, we created a neural network (NN) that can differentiate melanoma from benign nevus. The NN architecture is analyzed by evaluating it during the training process. Some biostatistic parameters, such as accuracy, specificity, sensitivity, and Dice coefficient are calculated. Then, we developed three other methods based on convolutional neural networks (CNNs). The CNNs were pre-trained using large ImageNet and Places365 databases. GoogleNet, ResNet-101, and NasNet-Large, were used in the enumeration order. CNN architectures were fine-tuned in order to distinguish the different types of skin lesions using transfer learning. The accuracies of the classifications were determined. The last proposed method uses the classical method of image object detection, more precisely, the one in which some features are extracted from the images, followed by the classification step. In this case, the classification was done by using a support vector machine. Just as in the first method, the sensitivity, specificity, Dice similarity coefficient and accuracy are determined. A comparison of the obtained results from all the methods is then done. As mentioned above, the novelty of this paper is the integration of these methods in a global fusion-based decision system that uses the results obtained by each individual method to establish the fusion weights. The results obtained by carrying out the experiments on two different free databases shows that the proposed system offers higher accuracy results.

Arthrogryposis in a Case of Chiari Malformation II: First Case Report in a Mediterranean Population.

BACKGROUND Arthrogryposis multiplex congenita is a multifactorial syndromic or non-syndromic group of conditions consisting of multiple congenital contractures of the body, of unknown etiology. It is associated with a heterogenous group of disorders that include but are not limited to processes such as myopathic and neuropathic. Neural tube defect is a neuropathic disorder that incorporates myelomeningocele that might be either isolated or within a spectrum of multiple diseases. CASE REPORT This is a case report of a 28-day-old male born with lower limb arthrogryposis with myelomeningocele and Chiari II malformation in a Mediterranean population. CONCLUSIONS Lower extremity arthrogryposis with myelomeningocele and Chiari II malformation is a prenatal diagnosis that requires high clinical suspicion, early multidisciplinary intervention, and genetic counselling. As long as new approaches are being explored in the management of such cases, babies born now with neural tube defects can expect better quality of life.

Hawkinsinuria With Direct Hyperbilirubinemia in Egyptian-Lebanese Boy.

Tyrosinemia type III is the rarest type of tyrosinemia, because of a mutation in 4-OH-phenylpyruvate dioxygenase (HPD). This causes two different types of diseases with different modes of inheritance: tyrosinemia type III and hawkinsinuria. Hawkinsinuria is an autosomal dominant disease, which presents a failure to thrive and metabolic acidosis; however, the liver is not affected. P.A33T heterozygous mutation was reported by Tomoeda et al. to cause hawkinsinuria. This case report will present the first case of an Egyptian-Lebanese male who developed direct hyperbilirubinemia and was found to have tyrosinemia type III, due to elevated tyrosine levels in the blood and tyrosine derivatives in the urine, but genetic testing revealed a P.A33T heterozygous mutation, a cause of hawkinsinuria.

EBV Infection Unmasking a Choledochal Cyst in an Infant.

Hepatic involvement is common in acute Epstein-Barr virus (EBV) infection in children. It usually manifests as a transitory elevation of transaminases in up to 80% to 90% of patients, and they normalize by 2 to 6 weeks. A cholestatic pattern with elevated gamma-glutamyl transferase (γGT) and alkaline phosphatase (ALP) is common, in up to 60% in young adults. However, jaundice is very rare occurring in only 5% of pediatric patients. We report here an 8-month-old female with EBV infection who developed obstructive jaundice 2 weeks after the initial infection. Radiologic investigations were compatible with choledochal cyst type IVa complicated by stone formation in the common bile duct. In case of clinical exacerbation or nonamelioration of liver function tests in EVB infection, another diagnosis should be addressed. This highlights the importance of close follow-up in these patients in order not to miss a serious underlying condition such as choledochal malformation.

Case report: Guillain-Barre syndrome with pneumococcus - A new association in pediatrics.

Guillain-Barre Syndrome, an acute flaccid paralysis known to be caused by recent Gastro-intestinal infections mainly campylobacter, and Respiratory infections mainly mycoplasma pneumoniae and influenza. One reported case of severe invasive pneumococcal disease in a 68 year old female, that presented with Austrian's triad of meningitis, pneumonia and endocarditis, and progressed to develop Guillain Barre syndrome, an association never been documented before. We present a case of 13 year old male, presented with hypoactivity and inability to bare his own weight, developed septic shock due to pneumococcus with Acute Respiratory Distress Syndrome, and was found to have neurological findings of Guillain-Barre Syndrome. A new association in pediatric age group, never been reported before.

Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project.

We describe the organization of a nascent international effort, the Functional Annotation of Animal Genomes (FAANG) project, whose aim is to produce comprehensive maps of functional elements in the genomes of domesticated animal species.

The effectiveness of primary bipolar arthroplasty in treatment of unstable intertrochanteric fractures in elderly patients.

BACKGROUND: The treatment of unstable intertrochanteric fracture in the elderly patient is still controversial. Traditionally, internal fixation using a dynamic hip screw was of choice. Recently, some authors advocated the use of cemented bipolar arthroplasty or hemiarthroplasty which results in better functional outcome. AIM: The aim of this study is to find out which of these treatment options can lead to the best clinical and functional outcomes. PATIENTS AND METHODS: One hundred and two patients admitted to Makassed General Hospital between 2002 and 2007 with a diagnosis of unstable intertrochanteric fracture of femur were selected. Preoperative and operative data was retrieved from inpatient hospital files. Postoperative radio clinical data at follow up visits was collected from outpatient department files. Functional outcomes were assessed with use of Harris hip score. The main clinical measures were early postoperative full weight bearing, postoperative complications and functional outcome. RESULTS: The time to full weight bearing, the rate of postoperative complications, and the functional outcomes was significantly better in the cemented bipolar arthroplasty group. CONCLUSION: According to our results, we believe that cemented bipolar hemiarthroplasty is of choice in freely mobile elderly patients above seventy years of age with an intertrochanteric femoral fracture.