From Risk Assessment to Intervention: A Systematic Review of Thrombosis in Plastic Surgery.

Thromboembolism is a feared complication in plastic surgery and is linked to higher rates of morbidity and mortality. Despite extensive research, there is a lack of consistency between recommendations and clinical protocols to be implemented pre and post-surgery to reduce the incidence of thromboembolism. A systematic literature review was conducted using Pubmed and Scopus databases to determine the risk factors, screening methods, and existing treatment models for thromboembolism prevention. Articles in non-English languages were excluded. Analysis indicated that predominant risk factors include age (>35), elevated body mass index, coagulation disorders, smoking, estrogen therapies, genetic predisposition, vascular endothelium damage, stasis, and use of general anesthesia in patients with a history of cancer. Implementation of a proper prophylactic protocol is dependent on understanding the interplay between the aforementioned risk factors and the utilization of well-defined, evidence-based guidelines, such as the 2005 Caprini Risk Assessment Model and ultrasound surveillance. The literature review revealed that mechanical prophylaxis is the primary prevention method, followed by thromboprophylaxis for patients with higher Caprini scores. Plastic surgeons often underestimate the present risk stratification tools available for the prophylactic intervention of thromboembolism due to the fear of bleeding or hematoma complications postoperatively. In summary, this literature review emphasizes the importance of plastic surgeons selecting protocols that is inclusive of the patient's risk profile to yield a reduced risk of thromboembolism.

The African cancer burden: what is the potential role of modern oncology innovation in reducing the continent's rapidly rising mortality?

With increasing prevalence and an expected rise in disease burden, cancer is a cause of concern for African healthcare. The cancer burden in Africa is expected to rise to 2.1 million new cases per year and 1.4 million deaths annually by the year 2040. Even though efforts are being made to improve the standard of oncology service delivery in Africa, the current state of cancer care is not yet on par with the rise in the cancer burden. Cutting-edge technologies and innovations are being developed across the globe to augment the battle against cancer; however, many of them are beyond the reach of African countries. Modern oncology innovations targeted to ward Africa would be promising to address the high cancer mortality rates. The innovations should be cost-effective and widely accessible to tackle the rapidly rising mortality rate on the African continent. Though it may seem promising, a multidisciplinary approach is required to overcome the challenges associated with the development and implementation of modern oncology innovations in Africa.

Prospects of evolution-based artificial intelligence models in genome-wide studies to stratify genetic risk variants in nonalcoholic fatty liver disease.

The emergence of genome-wide association studies (GWAS) has identified genetic traits and polymorphisms that are associated with the progression of nonalcoholic fatty liver disease (NAFLD). Phospholipase domain-containing 3 and transmembrane 6 superfamily member 2 are genes commonly associated with NAFLD phenotypes. However, there are fewer studies and replicability in lesser-known genes such as LYPLAL1 and glucokinase regulator (GCKR). With the advent of artificial intelligence (AI) in clinical genetics, studies have utilized AI algorithms to identify phenotypes through electronic health records and utilize convolution neural networks to improve the accuracy of variant identification, predict the deleterious effects of variants, and conduct phenotype-to-genotype mapping. Natural language processing (NLP) and machine-learning (ML) algorithms are popular tools in GWAS studies and connect electronic health record phenotypes to genetic diagnoses using a combination of international classification disease (ICD)-based approaches. However, there are still limitations to machine-learning - and NLP-based models, such as the lack of replicability in larger cohorts and underpowered sample sizes, which prevent the accurate prediction of genetic variants that may increase the risk of NAFLD and its progression to advanced-stage liver fibrosis. This may be largely due to the lack of understanding of the clinical consequence in the majority of pathogenic variants. Though the concept of evolution-based AI models and evolutionary algorithms is relatively new, combining current international classification disease -based NLP models with phylogenetic and evolutionary data can improve prediction accuracy and create valuable connections between variants and their pathogenicity in NAFLD. Such developments can improve risk stratification within clinical genetics and research while overcoming limitations in GWAS studies that prevent community-wide interpretations.

A critical appraisal on the treatment of acute appendicitis in pediatric population during the COVID-19 pandemic.

Acute appendicitis is one of the most common causes of abdominal pain in children. During the coronavirus disease 2019 (COVID-19) pandemic, a delay in presentation to the emergency department and a higher rate of complicated appendicitis were observed. Traditionally, operative management (laparoscopic or open appendectomy) was thought to be the best treatment strategy for acute appendicitis. However, nonoperative management with antibiotics has gained popularity in managing pediatric appendicitis during the COVID-19 era. The pandemic has posed significant challenges in the management of acute appendicitis. Cancellation of elective appendectomies, delay in seeking care due to fear of contracting COVID-19 infection, and impact of COVID-19 infection in the pediatric population have resulted in higher rates of complications. Furthermore, multiple studies have reported multisystem inflammatory syndrome in children mimicking acute appendicitis, subjecting patients to unnecessary surgery. Therefore, it is imperative to update the treatment guidelines for the management of acute appendicitis in the pediatric population during and after COVID-19 times.

Multilevel Pharmacological Effects of Antipsychotics in Potential Glioblastoma Treatment.

Glioblastoma Multiforme (GBM) is a debilitating type of brain cancer with a high mortality rate. Despite current treatment options such as surgery, radiotherapy, and the use of temozolomide and bevacizumab, it is considered incurable. Various methods, such as drug repositioning, have been used to increase the number of available treatments. Drug repositioning is the use of FDA-approved drugs to treat other diseases. This is possible because the drugs used for this purpose have polypharmacological effects. This means that these medications can bind to multiple targets, resulting in multiple mechanisms of action. Antipsychotics are one type of drug used to treat GBM. Antipsychotics are a broad class of drugs that can be further subdivided into typical and atypical classes. Typical antipsychotics include chlorpromazine, trifluoperazine, and pimozide. This class of antipsychotics was developed early on and primarily works on dopamine D2 receptors, though it can also work on others. Olanzapine and Quetiapine are examples of atypical antipsychotics, a category that was created later. These medications have a high affinity for serotonin receptors such as 5- HT2, but they can also act on dopamine and H1 receptors. Antipsychotic medications, in the case of GBM, also have other effects that can affect multiple pathways due to their polypharmacological effects. These include NF-B suppression, cyclin deregulation, and -catenin phosphorylation, among others. This review will delve deeper into the polypharmacological, the multiple effects of antipsychotics in the treatment of GBM, and an outlook for the field's future progression.

Embracing robotic surgery in low- and middle-income countries: Potential benefits, challenges, and scope in the future.

Robotic surgery has applications in many medical specialties, including urology, general surgery, and surgical oncology. In the context of a widespread resource and personnel shortage in Low- and Middle-Income Countries (LMICs), the use of robotics in surgery may help to reduce physician burnout, surgical site infections, and hospital stays. However, a lack of haptic feedback and potential socioeconomic factors such as high implementation costs and a lack of trained personnel may limit its accessibility and application. Specific improvements focused on improved financial and technical support to LMICs can help improve access and have the potential to transform the surgical experience for both surgeons and patients in LMICs. This review focuses on the evolution of robotic surgery, with an emphasis on challenges and recommendations to facilitate wider implementation and improved patient outcomes.

Investigating thyroid dysfunction in the context of COVID-19 infection.

COVID-19 is a contagious viral infection caused by severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2). One of the key features of COVID-19 infection is inflammation. There is increasing evidence pointing to an association between cytokine storm and autoimmunity. One autoimmune disease of interest in connection to COVID-19 is hyperthyroidism. COVID-19 has been shown to decrease TSH levels and induce thyrotoxicosis, destructive thyroiditis, and de novo Graves' disease. It has also been suggested that the immune response against SARS-CoV-2 antigens following vaccination can cross-react through a mechanism called molecular mimicry which can elicit autoimmune reactivity, potentially leading to potential thyroid disease post vaccine. However, if the COVID-19 vaccine is linked to reduced COVID-19 related serious disease, it could potentially play a protective role against post COVID-19 hyperthyroidism (de novo disease and exacerbations). Further studies investigating the complex interplay between COVID-19 or COVID-19 vaccine and thyroid dysfunction can help provide substantial evidence and potential therapeutic targets that can alter prognosis and improve COVID-19 related outcomes in individuals with or without preexisting thyroid disease.

Investigating discrepancies in demand and access for bariatric surgery across different demographics in the COVID-19 era.

Obesity affects over 650 million adults worldwide and increases the risk of cardiovascular events, diabetes, and hypertension. While lifestyle recommendations are popular management options, bariatric surgery has emerged as a standard of care in refractory cases, reported to cause at least a 30% reduction in mortality. In addition, it mitigates obesity-related complications leading to a significant improvement in the quality of life for morbidly obese patients (BMI >40). Despite the numerous benefits, demand and access to bariatric surgery vary across different demographics such as age, gender, and socioeconomic status. This demand and access were further reduced due to the COVID-19 pandemic. This has resulted in cancellations of elective surgeries such as weight loss procedures and promotes a sedentary lifestyle which has short-term and long-term detrimental consequences on the health of obese patients. In the context of the prevalent epidemiological trends, this reduction in bariatric services will disproportionately affect the elderly, males, low SES, and African Americans. This editorial highlights the prevalent discrepancies in demand and access to bariatric surgery amidst the COVID-19 pandemic, and possible recommendations to improve overall access and utilization of bariatric services in morbidly obese patients belonging to all demographics.