Citations

I. Executive Summary Background The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS.

Objectives: To develop and verify a digital twin model of critically ill patient using the causal artificial intelligence approach to predict the response to specific treatment during the first 24 hours of sepsis. Design: Directed acyclic graphs were used to define explicitly the causal relationship among organ systems and specific treatments used. A hybrid approach of agent-based modeling, discrete-event simulation, and Bayesian network was used to simulate treatment effect across multiple stages and interactions of major organ systems (cardiovascular, neurologic, renal, respiratory, gastrointestinal, inflammatory, and hematology). Organ systems were visualized using relevant clinical markers. The application was iteratively revised and debugged by clinical experts and engineers. Agreement statistics was used to test the performance of the model by comparing the observed patient response versus the expected response (primary and secondary) predicted by digital twin. Setting: Medical ICU of a large quaternary- care academic medical center in the United States. Patients or Subjects: Adult (> 18 year yr old), medical ICU patients were included in the study. Interventions: No additional interventions were made beyond the standard of care for this study. Measurements and Main Results: During the verification phase, model performance was prospectively tested on 145 observations in a convenience sample of 29 patients. Median age was 60 years (54–66 d) with a median Sequential Organ Failure Assessment score of 9.5 (interquartile range, 5.0–14.0). The most common source of sepsis was pneumonia, followed by hepatobiliary. The observations were made during the first 24 hours of the ICU admission with one-step interventions, comparing the output in the digital twin with the real patient response. The agreement between the observed versus and the expected response ranged from fair (kappa coefficient of 0.41) for primary response to good (kappa coefficient of 0.65) for secondary response to the intervention. The most common error detected was coding error in 50 observations (35%), followed by expert rule error in 29 observations (20%) and timing error in seven observations (5%). Conclusions: We confirmed the feasibility of development and prospective testing of causal artificial intelligence model to predict the response to treatment in early stages of critical illness. The availability of qualitative and quantitative data and a relatively short turnaround time makes the ICU an ideal environment for development and testing of digital twin patient models. An accurate digital twin model will allow the effect of an intervention to be tested in a virtual environment prior to use on real patients.

ObjectiveAdvanced practice providers (APPs) may see patients independently or assist in “collaborative” clinics in otolaryngology practices. Our goal was to redesign the collaborative physician‐APP clinic model to increase patient access, maintain financial sustainability, and optimize patient and staff experience.MethodsThe study was performed in a tertiary care academic rhinology clinic seeing adult patients. The DMAIC framework (define, measure, analyze, improve, control) was used to develop the new model. The process shift between old and new models was analyzed by utilizing a statistical process control chart. Patient and staff surveys were tracked.ResultsThe collaborative physician‐APP model was redesigned into 2 parallel and independently run (“concurrent”) physician and APP clinics. Patient access increased by 38.9% from a mean of 17.9 patients per collaborative clinic (n = 15 days, 269 patients) to 29.3 patients per concurrent clinic (n = 12 days, 352 patients). Medicare reimbursement rate modeling showed the collaborative clinic to operate at a loss of $1341.51 per day, while the concurrent clinic model operated at a $1309.88 gain (200% positive change). Patient and staff experience tracked positively.DiscussionOtolaryngology clinics can become overwhelmed by the volume of empaneled established patients. Traditional collaborative physician‐APP clinics see the same panel of patients together. However, these can be successfully redesigned to a concurrent model. Concurrent clinics improve patient access and provider satisfaction while maintaining patient satisfaction and fiscal performance.Implications for PracticeLeveraging an experienced APP to run a parallel and independent clinic alongside the physician (concurrent clinic model) may improve patient access, financial metrics, and patient/staff experience.

Abstract Purpose: The role of immune-oncologic mechanisms of racial disparities in prostate cancer remains understudied. Limited research exists to evaluate the molecular underpinnings of immune differences in African American men (AAM) and European American men (EAM) prostate tumor microenvironment (TME). Experimental Design: A total of 1,173 radiation-naïve radical prostatectomy samples with whole transcriptome data from the Decipher GRID registry were used. Transcriptomic expressions of 1,260 immune-specific genes were selected to assess immune-oncologic differences between AAM and EAM prostate tumors. Race-specific differential expression of genes was assessed using a rank test, and intergene correlational matrix and gene set enrichment was used for pathway analysis. Results: AAM prostate tumors have significant enrichment of major immune-oncologic pathways, including proinflammatory cytokines, IFNα, IFNγ, TNFα signaling, ILs, and epithelial–mesenchymal transition. AAM TME has higher total immune content score (ICSHIGH) compared with 0 (37.8% vs. 21.9%, P = 0.003). AAM tumors also have lower DNA damage repair and are genomically radiosensitive as compared with EAM. IFITM3 (IFN-inducible transmembrane protein 3) was one of the major proinflammatory genes overexpressed in AAM that predicted increased risk of biochemical recurrence selectively for AAM in both discovery [HRAAM = 2.30; 95% confidence interval (CI), 1.21–4.34; P = 0.01] and validation (HRAAM = 2.42; 95% CI, 1.52–3.86; P = 0.0001) but not in EAM. Conclusions: Prostate tumors of AAM manifest a unique immune repertoire and have significant enrichment of proinflammatory immune pathways that are associated with poorer outcomes. Observed immune-oncologic differences can aid in a genomically adaptive approach to treating prostate cancer in AAM.

The American Venous Forum (AVF) and the Society for Vascular Surgery set forth these guidelines for the management of endothermal heat-induced thrombosis (EHIT). The guidelines serve to compile the body of literature on EHIT and to put forth evidence-based recommendations. The guidelines are divided into the following categories: classification of EHIT, risk factors and prevention, and treatment of EHIT. One major feature is to standardize the reporting under one classification system. The Kabnick and Lawrence classification systems are now combined into the AVF EHIT classification system. The novel classification system affords standardization in reporting but also allows continued combined evaluation with the current body of literature. Recommendations codify the use of duplex ultrasound for the diagnosis of EHIT. Risk factor assessments and methods of prevention including mechanical prophylaxis, chemical prophylaxis, and ablation distance are discussed. Treatment guidelines are tailored to the AVF EHIT class (ie, I, II, III, IV). Reference is made to the use of surveillance, antiplatelet therapy, and anticoagulants as deemed indicated, and the recommendations incorporate the use of the novel direct oral anticoagulants. Last, EHIT management as it relates to the great and small saphenous veins is discussed.

Abstract Background: Elastomeric respirators are reusable and reliable protection from infectious aerosol particles such as SARS-CoV-2. There is a lack of safety data for use in sterile fields limiting application to operating room settings where high-risk aerosol generating procedures are performed. We hypothesized an equivalent reduction in sterile field contamination would be achieved using an elastomeric respirator covered by a surgical mask as compared to a standard surgical mask or N95.Methods: Randomized controlled crossover experiment with repeat measurement comparing microbial and aerosol contamination of operating room surfaces for elastomeric respirators, elastomeric respirators covered by a surgical mask, N95, surgical mask, and no mask. 80 experiments were performed by participants with randomized order and balanced crossover to all masking groups (n=16 per masking group). Participants executed droplet and aerosol generating procedures while wearing: (Group 1) elastomeric respirator with mask, (Group 2) elastomeric respirator only, (Group 3) N95, and (Group 4) surgical mask. Positive control was established with the participant unmasked (Group 5). Contamination was measured by microbial growth on settling plates and optical particle counters (0.2+ and 2 um+ particles).Results: There was a reduction in microbial contamination at the sterile field (p<0.001) for all masks (Groups 1-4) compared to unmasked (Group 5). The mean colony forming units (CFU) at the sterile field was 0 CFUs for elastomeric respirator (+/- mask), N95, and surgical mask versus unmasked growing 1.875 CFUs. Compared to the unmasked control, the elastomeric respirator (+/- mask), N95, and surgical masks all resulted in a -0.75 difference in contamination (95% CI -0.91 to -0.48, p < 0.001). No significant difference in contamination between the elastomeric respirator (+/- mask) and a surgical mask was detected. No significant difference in particle counts (0.2 µm+ and 2.0 µm+) between the elastomeric respirator (+/- mask) and a standard surgical mask.Conclusion and Relevance: Elastomeric respirators with or without mitigation are as effective as a surgical mask and N95 for reducing contamination at the sterile field in an operating room. Consideration should be given to expanding the use of elastomeric respirators to operating rooms during high-risk aerosol generating procedures.