Conflict medicine is an age-old branch of medicine which focuses on delivering healthcare services to the injured in the setting of conflicts, wars, disasters, and/or other calamities. The course in its purest form has been traditionally given only in military medical schools while civilian medical students are usually taught parts of the course in other overlapping subjects like surgery, infectious diseases, etc. However, in a crisis situation, civilian doctors are expected to double up as military doctors, which leads to emotional, mental, and physical stress for the civilian doctors along with logistical and organizational challenges. The current Covid-19 pandemic and the Russo-Ukrainian conflict have highlighted once again the emergent need for the implementation of conflict medicine courses in regular medical curricula, so as to make the medical students situation-ready. With our present discussion, we aim to provide a brief overview of the course, its core modules, challenges to its implementation, and possible solutions. We believe that the complex management skills gained by this course are not only useful in conflict scenario but are also valuable in managing day-to-day medical emergencies.
Life-threatening complications (LTCs) and negative results of surgical treatments often go unreported. Minimally invasive repair of pectus excavatum (MIRPE) represents a procedure with a low incidence of adverse outcomes. However, 15 potentially fatal cases of MIRPE-related heart injury have been published. We report a case of cardiac perforation (CP) during MIRPE. A 12-year-old female was admitted for elective repair of a severe asymmetric pectus excavatum. Preoperative computed tomography showed a Haller index of 4.9. MIRPE was performed under bilateral video-assisted thoracoscopy. After the placement of the pectus bar, cardiac arrhythmias, hypotension and bilateral hemothorax occurred. Emergency thoracotomy without pectus bar removal showed CP. The wound sites were repaired and the pectus bar was eventually successfully implanted. The patient was discharged on postoperative day 11. After 10 months, she remains asymptomatic. Reporting rare complications is essential for accurate calculations of the true prevalence of LTCs, maintaining high alertness in pediatric surgeons.
Gut microbiota are defined as the microbial population of the intestines. They include various types of bacteria which can influence and predict the existence or onset of some specific diseases. Therefore, it is a common practice in medicine to analyze the gut microbiota for diagnostic purposes by analyzing certain measurable biochemical features associated with the disease under investigation. However, the evaluation of all the data collected from the gut microbiota is a labor-intensive process. Machine learning algorithms may be a helpful tool to identify the hidden patterns in gut microbiota for the detection of disease and other classification problems. In this study, we propose a deep neural model based on 1D-CNN to detect cardiovascular disease using bacterial taxonomy and OTU (Operational Taxonomic Unit) table data. The developed method is compared to classical machine learning algorithms, regression, boosting algorithm and a deep model, TabNet, developed for tabular data and obtained outperforming classification results. The proposed method is robust and well adapted to taxonomy data in tabular form. It can be easily adapted to detect other diseases by using taxonomy data.
Background and Objectives. The aim of this study is to determine the prevailing microbiota in samples from pediatric patients with acute appendicitis, as well as evaluate the antibacterial sensitivity of the isolated microorganisms, comparing the data obtained with the clinic’s antibacterial therapy guidelines. Materials and Methods. The study group consisted of 93 patients between the ages of 7 and 18. All patients underwent a laparoscopic or conventional appendectomy. The children were hospitalized with signs and symptoms suggestive of acute appendicitis. Microbiological cultures from the appendix and abdominal cavity were collected intraoperatively. Results. E. coli was identified in most cases irrespective of the clinical presentation of acute appendicitis. Most strains were susceptible to ampicillin and amoxicillin/clavulanic acid. Five strains of E. coli produced extended spectrum beta-lactamase (ESBL). Pseudomonas aeruginosa (P. aeruginosa) was the second most commonly isolated causative agent. Furthermore, it was common in cases of acute complex appendicitis. Most strains of P. aeruginosa were resistant to amoxicillin/clavulanic acid, ertapenem, ampicillin and cefotaxime, yet were susceptible to ceftazidime. Regardless of the clinical presentation, the samples yielded mixed isolates. Conclusion. E. coli is the main causative agent of acute appendicitis in the pediatric population displaying susceptibility to various antibiotics. P. aeruginosa was more prevalent in cases of acute complex appendicitis. P. aeruginosa isolates were susceptible to ceftazidime; however, they were resistant to cefotaxime, which should, therefore, be removed from guidelines for empirical antibacterial treatment of acute appendicitis due to phenotypic resistance of P. aeruginosa. We recommend antibiotics with distinct implementation to avoid antibiotic resistance.
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