Introduction:The performance of tracheotomy is a common procedural request by critical care departments to the surgical services of general surgery, thoracic surgery and otolaryngology -head & neck surgery. A Canadian Society of Otolaryngology -Head & Neck Surgery (CSO-HNS) task force was convened with multi-specialty involvement from otolaryngology-head & neck surgery, general surgery, critical care and anesthesiology to develop a set of recommendations for the performance of tracheotomies during the COVID-19 pandemic. Main body: The tracheotomy procedure is highly aerosol generating and directly exposes the entire surgical team to the viral aerosol plume and secretions, thereby increasing the risk of transmission to healthcare providers. As such, we believe extended endotracheal intubation should be the standard of care for the entire duration of ventilation in the vast majority of patients. Pre-operative COVID-19 testing is highly recommended for any nonemergent procedure. Conclusion: The set of recommendations in this document highlight the importance of avoiding tracheotomy procedures in patients who are COVID-19 positive if at all possible. Recommendations for appropriate PPE and environment are made for COVID-19 positive, negative and unknown patients requiring consideration of tracheotomy. The safety of healthcare professionals who care for ill patients and who keep critical infrastructure operating is paramount.

Vital signs historically served as the primary method to triage patients and resources for trauma and emergency care, but have failed to provide clinically-meaningful predictive information about patient clinical status. In this review, a framework is presented that focuses on potential wearable sensor technologies that can harness necessary electronic physiological signal integration with a current state-of-the-art predictive machine-learning algorithm that provides early clinical assessment of hypovolemia status to impact patient outcome. The ability to study the physiology of hemorrhage using a human model of progressive central hypovolemia led to the development of a novel machine-learning algorithm known as the compensatory reserve measurement (CRM). Greater sensitivity, specificity, and diagnostic accuracy to detect hemorrhage and onset of decompensated shock has been demonstrated by the CRM when compared to all standard vital signs and hemodynamic variables. The development of CRM revealed that continuous measurements of changes in arterial waveform features represented the most integrated signal of physiological compensation for conditions of reduced systemic oxygen delivery. In this review, detailed analysis of sensor technologies that include photoplethysmography, tonometry, ultrasound-based blood pressure, and cardiogenic vibration are identified as potential candidates for harnessing arterial waveform analog features required for real-time calculation of CRM. The integration of wearable sensors with the CRM algorithm provides a potentially powerful medical monitoring advancement to save civilian and military lives in emergency medical settings.

Background The 22‐item sino‐nasal outcome test (SNOT‐22) is a widely used and powerful patient‐reported outcomes measure for chronic rhinosinusitis (CRS). More recently; however, the SNOT‐22 has been evaluated as a predictive tool for multiple conditions. The objective of this scoping review is to investigate the extent to which SNOT‐22 is used in this manner and present this information in a way useful for clinicians. Methods A systematic search of PubMed, Scopus, Cochrane Library, and Web of Science was performed. Studies that evaluated SNOT‐22s predictive utility were considered for eligibility in this scoping review. Results A total of 39 studies met eligibility. The SNOT‐22 was found to be used as a predictive tool in three broad categories: (1) to predict a diagnosis, (2) to predict an outcome of an intervention, and (3) to predict a patient treatment preference. Thirteen studies were included in the diagnosis category, which made up ten different individual predictions. Twenty‐four studies were included in the outcomes category and investigated 17 different individual predictions. Finally, two studies were included in the patient preferences category, which together made one prediction. Conclusions The SNOT‐22 is a versatile tool that has the potential to be used in predicting various diagnoses, outcomes, and patient preferences. However, care must be taken in applying these predictions to clinical practice, as further research must be done in validating these predictions based on SNOT‐22 responses.

Summary: Since the 1960s, skin has been considered to be the most allogenic tissue in humans. This tenet has remained unquestioned in the reconstructive transplant arena, which has led to skin serving as the sole monitor for early rejection in vascularized composite allotransplantation. In this article, the authors question the validity of this belief. The authors’ hypothesis is that skin is not always an accurate monitor of rejection in the deep tissues, thus questioning the positive and negative predictive value of the punch biopsy for suspected vascularized composite allotransplantation rejection. A search was carried out identifying vascularized composite allotransplantation publications where the allogenicity of transplanted skin was evaluated. Eighteen publications claimed skin was found to be the most allogenic tissue in humans, justifying its use as a superior monitor for rejection. Eight publications demonstrated skin to be a poor monitor of rejection deeper to the skin. Two vascularized composite allotransplantation animal studies reported skin rejecting simultaneously with the deeper tissues. Finally, three publications discussed a skin and kidney allograft, transplanted simultaneously, indicating skin allogenicity was equivalent to the that of the kidney allograft. Much of the literature in human vascularized composite allotransplantation claims skin to be an excellent monitor of the deep tissues. The conclusion from this study is that skin does not always function as a good monitor for what could be rejecting in the deep tissues. The authors believe continued research is necessary to focus on expanding novel monitoring techniques and technologies to accurately diagnose vascularized composite allotransplantation rejection without tissue destruction.

Introduction The Prehospital Trauma Registry (PHTR) captures after-action reviews (AARs) as part of a continuous performance improvement cycle and to provide commanders real-time feedback of Role 1 care. We have previously described overall challenges noted within the AARs. We now performed a focused assessment of challenges with regard to hemodynamic monitoring to improve casualty monitoring systems. Materials and Methods We performed a review of AARs within the PHTR in Afghanistan from January 2013 to September 2014 as previously described. In this analysis, we focus on AARs specific to challenges with hemodynamic monitoring of combat casualties. Results Of the 705 PHTR casualties, 592 had available AAR data; 86 of those described challenges with hemodynamic monitoring. Most were identified as male (97%) and having sustained battle injuries (93%), typically from an explosion (48%). Most were urgent evacuation status (85%) and had a medical officer in their chain of care (65%). The most common vital sign mentioned in AAR comments was blood pressure (62%), and nearly one-quarter of comments stated that arterial palpation was used in place of blood pressure cuff measurements. Conclusions Our qualitative methods study highlights the challenges with obtaining vital signs—both training and equipment. We also highlight the challenges regarding ongoing monitoring to prevent hemodynamic collapse in severely injured casualties. The U.S. military needs to develop better methods for casualty monitoring for the subset of casualties that are critically injured.

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