Citations

Abstract Introduction With severe burn injury, there is systemic fluid loss due to inflammatory responses in damaged tissue, leading to disruption of cellular processes. Patient fluid levels are restored with the calculation of total body surface area (TBSA). Clinically used TBSA equations are often outdated and inaccurate with error up to 20%, resulting in misinformed treatment and subsequent sequelae including prolonged hospital length of stay and increased mortality. Our objective, therefore, was to create a point-of-care (POC) system employing 3D imaging technology to accurately calculate TBSA for all patient population varieties. Methods Our team employed an iPad attachable, infrared scanner to create 3D models of the human body. From these models, TBSA can be extrapolated using scan processing software. Subject scans were collected on our device and on a gold standard scanner for comparison of TBSA output. Clinical testing on burn patients is occurring at present to establish scanning precision of TBSA in the burn care environment. Results Non-clinical verification tests of the 3D scanned TBSA revealed a 4.05% error when compared to the gold standard, and precision error of 3.8%. Additionally, we introduced the device into the burn unit for preliminary testing with a physician user and non-patient subjects. The subjects were scanned in a prone position to mimic burn care workflow. Clinician scanning error was 1.41% when compared to the gold standard scan of the same subject. Clinical precision study results are on-going in collection. Conclusions Our device introduces an improved method of TBSA estimation to assist clinicians in making accurate burn care decisions and further precision medicine with greater anthropomteric data, notably for children. This device is one of the first POC-3D scanning technologies to be used in a burn setting and may also be employed at outlying medical facilities. Destructive wildfires and combat burn injuries highlight the need for such a device to standardize the triage of burn victims with and away from experienced medical staff. Applicability of Research to Practice 3D body mapping points to an enhanced method of TBSA calculation and minimally disruptive to the burn workflow. Future developments of 3D scanning include deep learning algorithms to identify and better assess burned surface area. Additionally, further automation of TBSA scan processing to reduce user error in calculation and improve burn injury outcomes.

Abstract Eating disorders and substance use disorders frequently co‐occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [ r g ], twin‐based = 0.23‐0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome‐wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance‐use‐related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism‐based genetic correlations between eating disorder‐ and substance‐use‐related phenotypes. Significant positive genetic associations emerged between AUD and AN ( r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN ( r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating ( r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating ( r gs = −0.19 to −0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co‐varying for major depressive disorder loci. The patterns of association between eating disorder‐ and substance‐use‐related phenotypes highlights the potentially complex and substance‐specific relationships among these behaviors.

Abstract Purpose Transgender patients face considerable healthcare disparities. Improved means of recognizing transgender patients and understanding their medical needs is important to provide optimal care. The electronic medical record (EMR) of our health system allows for differentiation of gender identity, legal sex, and sex at birth. With EMR recognition of transgender patients, a recommendation for estimating creatinine clearance (CLcr) and ideal body weight (IBW) was needed to standardize medication dosing. Summary The literature was reviewed for evidence on the effect of gender-affirming hormone therapy on serum creatinine concentration and lean body mass. Findings informed a recommendation for drug dosing based on CLcr and IBW in transgender patients. Four studies that reported the effect of hormone therapy on biometric laboratory values were found. Three studies reported that values of transgender patients more closely resembled the standard values of their gender identity vs sex at birth after hormone therapy; 1 study reported a range of values that more closely resembled those associated with sex at birth while still overlapping with values associated with gender identity. Consequently, it was recommended that pharmacists dose medications based on CLcr and IBW calculations consistent with gender identity after a patient has been on hormone therapy for 6 months or longer. Conclusion Providing optimal care to transgender patients includes considering the effect of gender-affirming hormone therapy on overall physiology. Consistently using the appropriate CLcr and IBW calculations for each patient ensures safe and effective care. Additional studies are needed to confirm the effect of hormone therapy on renal clearance and lean body mass.

Major depressive disorder (MDD) is the leading cause of disability worldwide and is associated with high rates of suicide and medical comorbidities. Current antidepressant medications are suboptimal, as most MDD patients fail to achieve complete remission from symptoms. At present, clinicians are unable to predict which antidepressant is most effective for a particular patient, exposing patients to multiple medication trials and side effects. Since MDD’s etiology includes interactions between genes and environment, the epigenome is of interest for predictive utility and treatment monitoring. Epigenetic mechanisms of antidepressant medications are incompletely understood. Differences in epigenetic profiles may impact treatment response. A systematic literature search yielded 24 studies reporting the interaction between antidepressants and eight genes (BDNF, MAOA, SLC6A2, SLC6A4, HTR1A, HTR1B, IL6, IL11) and whole genome methylation. Methylation of certain sites within BDNF, SLC6A4, HTR1A, HTR1B, IL11, and the whole genome was predictive of antidepressant response. Comparing DNA methylation in patients during depressive episodes, during treatment, in remission, and after antidepressant cessation would help clarify the influence of antidepressant medications on DNA methylation. Individuals’ unique methylation profiles may be used clinically for personalization of antidepressant choice in the future.

The field of abdominal organ transplantation is multifaceted, with the clinician balancing recipient comorbidities, risks of the surgical procedure, and the pathophysiology of immunosuppression to ensure optimal outcomes. An underappreciated element throughout this process is acute pain management related to the surgical procedure. As the opioid epidemic continues to grow with increasing numbers of transplant candidates on opioids as well the increase in the development of enhanced recovery after surgery protocols, there is a need for greater focus on optimal postoperative pain control to minimize opioid use and improve outcomes. This review will summarize the physiology of acute pain in transplant recipients, assess the impact of opioid use on post-transplant outcomes, present evidence supporting nonopioid analgesia in transplant surgery, and briefly address the perioperative approach to the pretransplant recipient on opioids.

Abstract The American Society of Hematology (ASH) convened 5 guideline panels to develop clinical practice recommendations addressing 5 management areas of highest importance to individuals living with sickle cell disease: pain, cerebrovascular complications, pulmonary and kidney complications, transfusion, and hematopoietic stem cell transplant. Panels were multidisciplinary and consisted of patient representatives, content experts, and methodologists. The Mayo Clinic Evidence-Based Practice Center conducted systematic reviews based on a priori selected questions. In this exposition, we describe the process used by ASH, including the GRADE approach (Grades of Recommendations, Assessment, Development and Evaluation) for rating certainty of the evidence and the GRADE Evidence to Decision Framework. We also describe several unique challenges faced by the guideline panels and the specific innovations and solutions used to address them, including a curriculum to train patients to engage in guideline development, dealing with the opioid crisis, and working with indirect and noncomparative evidence.

Smokers are at increased risk for surgical complications. Despite the known benefits of smoking cessation, many perioperative health care providers do not routinely provide smoking cessation interventions. The variation in delivery of perioperative smoking cessation interventions may be due to limited high-level evidence for whether smoking cessation interventions used in the general population are effective and feasible in the surgical population, as well as the challenges and barriers to implementation of interventions. Yet smoking is a potentially modifiable risk factor for improving short- and long-term patient outcomes. The purpose of the Society for Perioperative Assessment and Quality Improvement (SPAQI) Consensus Statement on Perioperative Smoking Cessation is to present recommendations based on current scientific evidence in surgical patients. These statements address questions regarding the timing and intensity of interventions, roles of perioperative health care providers, and behavioral and pharmacological interventions. Barriers and strategies to overcome challenges surrounding implementation of interventions and future areas of research are identified. These statements are based on the current state of knowledge and its interpretation by a multidisciplinary group of experts at the time of publication.