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IntroductionThe study assessed outcomes and toxicities of different treatment modalities for local and/or regional recurrent nasopharyngeal carcinoma (NPC) in a non-endemic area.MethodsPatients treated with curative intent for recurrent NPC with salvage surgery, photon-based radiotherapy, proton therapy (PT), with or without chemotherapy, at different Italian referral centers between 1998 and 2020 were included. Adverse events and complications were classified according to the Common Terminology Criteria for Adverse Events. Characteristics of the patients, tumors, treatments, and complications are presented along with uni- and multivariate analysis of prognostic factors. A survival predictive nomogram is also provided.ResultsA total of 140 patients treated from 1998 to 2020 were retrospectively assessed. Cases with lower age, comorbidity rate, stage, and shorter disease-free interval (DFI) preferentially underwent endoscopic surgery. More advanced cases underwent re-irradiation, fairly distributed between photon-based radiotherapy and PT. Age and DFI were independent factors influencing overall survival. No independent prognostic effect of treatment modality was observed. No significant difference in the morbidity profile of treatments was observed, with 40% of patients experiencing at least one adverse event classified as G3 or higher.ConclusionRecurrent NPC in a non-endemic area has dissimilar aspects compared to its endemic counterpart, suggesting the need for further studies that can guide the choice of the best treatment modality.

Despite therapeutic advancements, graft versus host disease (GVHD) is a major complication of hematopoietic stem cell transplantation (HSCT). Pathogen and damage associated molecular patterns released following pre-transplant conditioning play an important role in the initiation of GVHD. However, the role of extracellular mitochondria as an endogenous danger signal has not been fully explored. Herein, we report that cytotoxic conditioning with radiation leads to mitochondrial fission and dysfunction and impaired induction of PINK-1/PARKIN-dependent mitophagy, specifically in the intestinal mucosal layer. This radiation-induced imbalance in mitochondrial dynamics leads to the expulsion of mitochondria from intestinal epithelial cells in a cell-death independent manner bothin vitroin cell culture supernatants of the Caco-2 cell line andin vivoin plasma of BALB/c mice. Extracellular mitochondria released upon irradiation were damaged, with functional impairment in ATP production and, increased protein carbonylation. Transplantation of isolated damaged mitochondria along with HSCT and splenocytes in a C57BL6/J ➔ BALB/c mouse model of GVHD aggravated the disease-induced mortality. In mixed lymphocyte reactions, pre-incubation of BALB/c stimulator cells with syngeneic extracellular mitochondria increased the activation and proliferation of C57BL6/J responder T cells. In a cohort of pediatric patients who underwent HSCT, fractionated irradiation given with their conditioning regimen increased the abundance of circulating extracellular mitochondria and correlated with the incidence of GVHD. Our results suggest that modulation of extracellular mitochondria could be a novel therapeutic target to prevent GVHD after HSCT.

Cardiac troponin I (cTnI) is a sarcomeric protein critical to myocyte contraction. Unexpectedly, we found that some cTnI localized to the mitochondrial matrix in the heart, inhibited mitochondrial functions when stably expressed in non-cardiac cells and increased opening of the mitochondrial permeability transition pore under oxidative stress. Direct, specific, and saturable binding of cTnI to ATP synthase was demonstratedin vitro, using immune-captured ATP synthase, and in cells using proximity ligation assay. cTnI binding doubled F1F0ATPase activity, whereas skeletal troponin I and several human mutant cTnI variants associated with familial hypertrophic cardiomyopathy did not. A rationally-designed ten amino acid peptide, P888, inhibited cTnI binding to ATP synthase, inhibited cTnI-induced increase in ATPase activityin vitro, and reduced cardiac injury following transient ischemiain vivo. We therefore suggest that mitochondria-associated cTnI may inhibit cardiac ATP synthase under basal conditions; pharmacological agents that release this inactivating effect of cTnI and thus preventing ATP hydrolysis during cardiac ischemia may increase the reservoir of functional mitochondria to reduce cardiac injury.Significance StatementCardiac troponin I (cTnI) is a key sarcomeric protein involved in the regulation of myocardial contractility. We found that some cTnI is present in the mitochondrial matrix where it binds to ATP synthase, disrupting mitochondrial function; inhibition of the cTnI-ATP synthase interaction with a selective peptide inhibitor reduces cardiac dysfunction following ischemia and reperfusion injury. Several pathogenic cTnI mutations associated with hypertrophic cardiomyopathy do not affect ATP synthase activity, suggesting a potential mechanism that contributes to the diverse pathologies associated with these mutations.

PURPOSE Acute care use (ACU) is a major driver of oncologic costs and is penalized by a Centers for Medicare & Medicaid Services quality measure, OP-35. Targeted interventions reduce preventable ACU; however, identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data in the electronic health record (EHR). We aimed to predict risk of preventable ACU after starting chemotherapy using machine learning (ML) algorithms trained on comprehensive EHR data. METHODS Chemotherapy patients treated at an academic institution and affiliated community care sites between January 2013 and July 2019 who met inclusion criteria for OP-35 were identified. Preventable ACU was defined using OP-35 criteria. Structured EHR data generated before chemotherapy treatment were obtained. ML models were trained to predict risk for ACU after starting chemotherapy using 80% of the cohort. The remaining 20% were used to test model performance by the area under the receiver operator curve. RESULTS Eight thousand four hundred thirty-nine patients were included, of whom 35% had preventable ACU within 180 days of starting chemotherapy. Our primary model classified patients at risk for preventable ACU with an area under the receiver operator curve of 0.783 (95% CI, 0.761 to 0.806). Performance was better for identifying admissions than emergency department visits. Key variables included prior hospitalizations, cancer stage, race, laboratory values, and a diagnosis of depression. Analyses showed limited benefit from including patient-reported outcome data and indicated inequities in outcomes and risk modeling for Black and Medicaid patients. CONCLUSION Dense EHR data can identify patients at risk for ACU using ML with promising accuracy. These models have potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted, preventative interventions.

Objective To develop prediction models for intensive care unit (ICU) vs non-ICU level-of-care need within 24 hours of inpatient admission for emergency department (ED) patients using electronic health record data. Materials and Methods Using records of 41 654 ED visits to a tertiary academic center from 2015 to 2019, we tested 4 algorithms—feed-forward neural networks, regularized regression, random forests, and gradient-boosted trees—to predict ICU vs non-ICU level-of-care within 24 hours and at the 24th hour following admission. Simple-feature models included patient demographics, Emergency Severity Index (ESI), and vital sign summary. Complex-feature models added all vital signs, lab results, and counts of diagnosis, imaging, procedures, medications, and lab orders. Results The best-performing model, a gradient-boosted tree using a full feature set, achieved an AUROC of 0.88 (95%CI: 0.87–0.89) and AUPRC of 0.65 (95%CI: 0.63–0.68) for predicting ICU care need within 24 hours of admission. The logistic regression model using ESI achieved an AUROC of 0.67 (95%CI: 0.65–0.70) and AUPRC of 0.37 (95%CI: 0.35–0.40). Using a discrimination threshold, such as 0.6, the positive predictive value, negative predictive value, sensitivity, and specificity were 85%, 89%, 30%, and 99%, respectively. Vital signs were the most important predictors. Discussion and Conclusions Undertriaging admitted ED patients who subsequently require ICU care is common and associated with poorer outcomes. Machine learning models using readily available electronic health record data predict subsequent need for ICU admission with good discrimination, substantially better than the benchmarking ESI system. The results could be used in a multitiered clinical decision-support system to improve ED triage.

Aim: Identify, simulate, and evaluate the formal and informal patient-level and unit-level factors that nurse managers use to determine the number of nurses for each shift. Background: Nurse staffing schedules are commonly set based on metrics such as midnight census that do not account for seasonality or midday turnover, resulting in last-minute adjustments or inappropriate staffing levels. Methods: Staffing schedules at a pediatric intensive care unit (PICU) were simulated based on nurse-to-patient assignment rules from interviews with nursing management. Multivariate regression modeled the discrepancies between scheduled and historical staffing levels and constructed rules to reduce these discrepancies. The primary outcome was the median difference between simulated and historical staffing levels.Results: Nurse-to-patient ratios underestimated staffing by a median of 1.5 nurses per shift. Multivariate regression identified patient turnover as the primary factor accounting for this difference and subgroup analysis revealed that patient age and weight were also important. New rules reduced the difference to a median of 0.07 nurses per shift.Conclusion: Measurable, predictable indicators of patient acuity and historical trends may allow for schedules that better match demand.Implications for Nursing Management: Data-driven methods can quantify what drives unit demand and generate nurse schedules that require fewer last-minute adjustments.

OBJECTIVES Machine learning (ML) has experienced a revolutionary decade with advances across many disciplines. We seek to understand how recent advances in ML are going to specifically influence the practice of surgery in the future with a particular focus on thoracic surgery. METHODS Review of relevant literature in both technical and clinical domains. RESULTS ML is a revolutionary technology that promises to change the way that surgery is practiced in the near future. Spurred by an advance in computing power and the volume of data produced in healthcare, ML has shown remarkable ability to master tasks that had once been reserved for physicians. Supervised learning, unsupervised learning and reinforcement learning are all important techniques that can be leveraged to improve care. Five key applications of ML to cardiac surgery include diagnostics, surgical skill assessment, postoperative prognostication, augmenting intraoperative performance and accelerating translational research. Some key limitations of ML include lack of interpretability, low quality and volumes of relevant clinical data, ethical limitations and difficulties with clinical implementation. CONCLUSIONS In the future, the practice of cardiac surgery will be greatly augmented by ML technologies, ultimately leading to improved surgical performance and better patient outcomes.

Recent publications have shown that mitochondrial dynamics can govern the quality and quantity of extracellular mitochondria subsequently impacting immune phenotypes. This study aims to determine if pathologic mitochondrial fission mediated by Drp1/Fis1 interaction impacts extracellular mitochondrial content and macrophage function in sepsis-induced immunoparalysis.Laboratory investigation.University laboratory.C57BL/6 and BALB/C mice.Using in vitro and murine models of endotoxin tolerance (ET), we evaluated changes in Drp1/Fis1-dependent pathologic fission and simultaneously measured the quantity and quality of extracellular mitochondria. Next, by priming mouse macrophages with isolated healthy mitochondria (MC) and damaged mitochondria, we determined if damaged extracellular mitochondria are capable of inducing tolerance to subsequent endotoxin challenge. Finally, we determined if inhibition of Drp1/Fis1-mediated pathologic fission abrogates release of damaged extracellular mitochondria and improves macrophage response to subsequent endotoxin challenge.When compared with naïve macrophages (NMs), endotoxin-tolerant macrophages (ETM) demonstrated Drp1/Fis1-dependent mitochondrial dysfunction and higher levels of damaged extracellular mitochondria (Mitotracker-Green + events/50 μL: ETM = 2.42 × 106 ± 4,391 vs NM = 5.69 × 105 ± 2,478; p0.001). Exposure of NMs to damaged extracellular mitochondria (MH) induced cross-tolerance to subsequent endotoxin challenge, whereas MC had minimal effect (tumor necrosis factor [TNF]-α [pg/mL]: NM = 668 ± 3, NM + MH = 221 ± 15, and NM + Mc = 881 ± 15; p0.0001). Inhibiting Drp1/Fis1-dependent mitochondrial fission using heptapeptide (P110), a selective inhibitor of Drp1/Fis1 interaction, improved extracellular mitochondrial function (extracellular mitochondrial membrane potential, JC-1 [R/G] ETM = 7 ± 0.5 vs ETM + P110 = 19 ± 2.0; p0.001) and subsequently improved immune response in ETMs (TNF-α [pg/mL]; ETM = 149 ± 1 vs ETM + P110 = 1,150 ± 4; p0.0001). Similarly, P110-treated endotoxin tolerant mice had lower amounts of damaged extracellular mitochondria in plasma (represented by higher extracellular mitochondrial membrane potential, TMRM/MT-G: endotoxin tolerant [ET] = 0.04 ± 0.02 vs ET + P110 = 0.21 ± 0.02; p = 0.03) and improved immune response to subsequent endotoxin treatment as well as cecal ligation and puncture.Inhibition of Drp1/Fis1-dependent mitochondrial fragmentation improved macrophage function and immune response in both in vitro and in vivo models of ET. This benefit is mediated, at least in part, by decreasing the release of damaged extracellular mitochondria, which contributes to endotoxin cross-tolerance. Altogether, these data suggest that alterations in mitochondrial dynamics may play an important role in sepsis-induced immunoparalysis.

To use machine learning to predict rupture, dissection, and all-cause mortality for patients with descending and thoracoabdominal aortic aneurysms in an effort to improve on diameter-based surgical intervention criteria.Retrospective data from 1083 patients with descending aortic diameters 3.0 cm or greater were collected, with a mean follow-up time of 3.52 years and an average descending diameter of 4.13 cm. Six machine learning classifiers were trained using 44 variables to predict the occurrence of dissection, rupture, or all-cause mortality within 1, 2, or 5 years of initial patient encounter for a total of 54 (6 × 3 × 3) separate classifiers. Classifier performance was measured using area under the receiver operator curve.Machine learning models achieved area under the receiver operator curves of 0.842 to 0.872 when predicting type B dissection, 0.847 to 0.856 when predicting type B dissection or rupture, and 0.820 to 0.845 when predicting type B dissection, rupture, or all-cause mortality. All models consistently outperformed descending aortic diameter across all end points (area under the receiver operator curve = 0.713-0.733). Feature importance inspection showed that other features beyond aortic diameter, such as a history of myocardial infarction, hypertension, and patient sex, play an important role in improving risk prediction.This study provides surgeons with a more accurate, machine learning-based, risk-stratification metric to predict complications for patients with descending aortic aneurysms.

Purpose To estimate the prevalence of smell or taste impairment in household contacts of mildly symptomatic home-isolated SARS-CoV-2 positive patients.Methods Cross sectional study based on ad hoc questions.Results Of 214 mildly symptomatic COVID-19 patients managed at home under self-isolation, 179 reported to have at least one household contact, with the total number of no study participants contacts being 296. Among 175 household contacts not tested for SARS-CoV-2 infection, 67 (38.3%) had SARS-CoV-2 compatible symptoms, 39 (22.3%) had loss of smell or taste with 7 (4.0%) having loss of smell or taste in the absence of other symptoms. The prevalence of smell or taste impairment was 1.5% in patients tested negative compared to 63.0% of those tested positive for SARS-CoV-2 (pConclusion Smell or taste impairment are quite common in not-tested household contacts of mildly symptomatic home-isolated SARS-CoV-2 positive patients. This should be taken into account when estimating the burden of loss of sense of smell and taste during COVID-19 pandemic, and further highlights the value of loss of sense of smell and taste as a marker of infection.

Mitochondrial dysfunction is a key contributor to septic cardiomyopathy. Although recent literature implicates dynamin related protein 1 (Drp1) and its mitochondrial adaptor fission 1 (Fis1) in the development of pathologic fission and mitochondrial failure in neurodegenerative disease, little is known about the role of Drp1/Fis1 interaction in the context of sepsis-induced cardiomyopathy. Our study tests the hypothesis that Drp1/Fis1 interaction is a major driver of sepsis-mediated pathologic fission, leading to mitochondrial dysfunction in the heart. Methods H9C2 cardiomyocytes were treated with lipopolysaccharide (LPS) to evaluate changes in mitochondrial membrane potential, oxidative stress, cellular respiration, and mitochondrial morphology. Balb/c mice were treated with LPS, cardiac function was measured by echocardiogaphy, and mitochondrial morphology determined by electron microscopy (EM). Drp1/Fis1 interaction was inhibited by P110 to determine whether limiting mitochondrial fission can reduce LPS-induced oxidative stress and cardiac dysfunction. Results LPS-treated H9C2 cardiomyocytes demonstrated a decrease in mitochondrial respiration followed by an increase in mitochondrial oxidative stress and a reduction in membrane potential. Inhibition of Drp1/Fis1 interaction with P110 attenuated LPS-mediated cellular oxidative stress and preserved membrane potential. In vivo, cardiac dysfunction in LPS-treated mice was associated with increased mitochondrial fragmentation. Treatment with P110 reduced cardiac mitochondrial fragmentation, prevented decline in cardiac function, and reduced mortality. Conclusions Sepsis decreases cardiac mitochondrial respiration and membrane potential while increasing oxidative stress and inducing pathologic fission. Treatment with P110 was protective in both in vitro and in vivo models of septic cardiomyopathy, suggesting a key role of Drp1/Fis1 interaction, and a potential target to reduce its morbidity and mortality.

HPV-driven oropharyngeal carcinomas (OPCs) show geographical variations with increasing temporal trends in several areas. We investigated their frequency and clinical outcomes within a prospective multicenter cohort study in North-East Italy. A tumor was defined as HPV-driven by using at least two different biomarkers, usually HPV-DNA positivity and p16INK4A overexpression. Different survival outcomes were compared among patients with HPV-driven and non-HPV-driven tumors. Overall, 42/130 (32.3%) patients with newly diagnosed OPC during the period 2000–2018 resulted HPV-driven; HPV16 was involved in 37 cases (88%), HPV33 in 3 cases (7%), HPV58 and HPV18 in 1 case each. Over time, HPV-driven cases raised from 16.7% (6/36) during 2000–2006 to 46.1% (24/52) during 2013–2018 (p

We demonstrate laser-driven Helium ion acceleration with cut-off energies above 25 MeV and peaked ion number above $10^8$ /MeV for 22(2) MeV projectiles from near-critical density gas jet targets. We employed shock gas jet nozzles at the high-repetition-rate (HRR) VEGA-2 laser system with 3 J in pulses of 30 fs focused down to intensities in the range between $9\times10^{19}$ W/cm$^2$ and $1.2\times10^{20}$ W/cm$^2$. We demonstrate acceleration spectra with minor shot-to-shot changes for small variations in the target gas density profile. Difference in gas profiles arise due to nozzles being exposed to a experimental environment, partially ablating and melting., 22 pages, 28 figures

BACKGROUND Pressure on the US health care system has been increasing due to a combination of aging populations, rising health care expenditures, and most recently, the COVID-19 pandemic. Responses to this pressure are hindered in part by reliance on a limited supply of highly trained health care professionals, creating a need for scalable technological solutions. Digital symptom checkers are artificial intelligence–supported software tools that use a conversational “chatbot” format to support rapid diagnosis and consistent triage. The COVID-19 pandemic has brought new attention to these tools due to the need to avoid face-to-face contact and preserve urgent care capacity. However, evidence-based deployment of these chatbots requires an understanding of user demographics and associated triage recommendations generated by a large general population. OBJECTIVE In this study, we evaluate the user demographics and levels of triage acuity provided by a symptom checker chatbot deployed in partnership with a large integrated health system in the United States. METHODS This population-based descriptive study included all web-based symptom assessments completed on the website and patient portal of the Sutter Health system (24 hospitals in Northern California) from April 24, 2019, to February 1, 2020. User demographics were compared to relevant US Census population data. RESULTS A total of 26,646 symptom assessments were completed during the study period. Most assessments (17,816/26,646, 66.9%) were completed by female users. The mean user age was 34.3 years (SD 14.4 years), compared to a median age of 37.3 years of the general population. The most common initial symptom was abdominal pain (2060/26,646, 7.7%). A substantial number of assessments (12,357/26,646, 46.4%) were completed outside of typical physician office hours. Most users were advised to seek medical care on the same day (7299/26,646, 27.4%) or within 2-3 days (6301/26,646, 23.6%). Over a quarter of the assessments indicated a high degree of urgency (7723/26,646, 29.0%). CONCLUSIONS Users of the symptom checker chatbot were broadly representative of our patient population, although they skewed toward younger and female users. The triage recommendations were comparable to those of nurse-staffed telephone triage lines. Although the emergence of COVID-19 has increased the interest in remote medical assessment tools, it is important to take an evidence-based approach to their deployment.

Myocardial infarction is the leading cause of cardiovascular mortality, with myocardial injury occurring during ischemia and subsequent reperfusion (IR). We previously showed that the inhibition of protein kinase C delta (δPKC) with a pan-inhibitor (δV1-1) mitigates myocardial injury and improves mitochondrial function in animal models of IR, and in humans with acute myocardial infarction, when treated at the time of opening of the occluded blood vessel, at reperfusion. Cardiac troponin I (cTnI), a key sarcomeric protein in cardiomyocyte contraction, is phosphorylated by δPKC during reperfusion. Here, we describe a rationally-designed, selective, high-affinity, eight amino acid peptide that inhibits cTnI’s interaction with, and phosphorylation by, δPKC (ψTnI), and prevents tissue injury in a Langendorff model of myocardial infarction, ex vivo. Unexpectedly, we also found that this treatment attenuates IR-induced mitochondrial dysfunction. These data suggest that δPKC phosphorylation of cTnI is critical in IR injury, and that a cTnI/δPKC interaction inhibitor should be considered as a therapeutic target to reduce cardiac injury after myocardial infarction.

Purpose of review: Defining the best practice of surgical care for patients affected by malignant head and neck tumors is of great importance. In this review we aim to describe the evolution of "best practice" guidelines in the context of quality-of-care measures and discuss current evidence on "best practice" for the surgical treatment of cancers of the sino-nasal tract, skull base, aero-digestive tract, and the neck. Recent findings: Current evidence based on certain structure and outcome indicators, but mostly based on process indicators already helps defining the framework of "Best practice" for head and neck cancer surgery. However, many aspects of surgical treatment still require in-depth research. Summary: While a framework of "Best practice" strategies already exists for the conduction of the surgical treatment of head and neck cancers, many questions still require additional research in particular in case of rare histologies in the head and neck region.

1511 Background: Acute care use is one of the largest drivers of cancer care costs. OP-35: Admissions and Emergency Department Visits for Patients Receiving Outpatient Chemotherapy is a CMS quality measure that will affect reimbursement based on unplanned inpatient admissions (IP) and emergency department (ED) visits. Targeted measures can reduce preventable acute care use but identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data available in the Electronic Health Record (EHR). We hypothesized dense, structured EHR data could be used to train machine learning algorithms to predict risk of preventable ED and IP visits. Methods: Patients treated at Stanford Health Care and affiliated community care sites between 2013 and 2015 who met inclusion criteria for OP-35 were selected from our EHR. Preventable ED or IP visits were identified using OP-35 criteria. Demographic, diagnosis, procedure, medication, laboratory, vital sign, and healthcare utilization data generated prior to chemotherapy treatment were obtained. A random split of 80% of the cohort was used to train a logistic regression with least absolute shrinkage and selection operator regularization (LASSO) model to predict risk for acute care events within the first 180 days of chemotherapy. The remaining 20% were used to measure model performance by the Area Under the Receiver Operator Curve (AUROC). Results: 8,439 patients were included, of whom 35% had one or more preventable event within 180 days of starting chemotherapy. Our LASSO model classified patients at risk for preventable ED or IP visits with an AUROC of 0.783 (95% CI: 0.761-0.806). Model performance was better for identifying risk for IP visits than ED visits. LASSO selected 125 of 760 possible features to use when classifying patients. These included prior acute care visits, cancer stage, race, laboratory values, and a diagnosis of depression. Key features for the model are shown in the table. Conclusions: Machine learning models trained on a large number of routinely collected clinical variables can identify patients at risk for acute care events with promising accuracy. These models have the potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted preventative interventions. Future work will include prospective and external validation in other healthcare systems.[Table: see text]

Background Pressure on the US health care system has been increasing due to a combination of aging populations, rising health care expenditures, and most recently, the COVID-19 pandemic. Responses to this pressure are hindered in part by reliance on a limited supply of highly trained health care professionals, creating a need for scalable technological solutions. Digital symptom checkers are artificial intelligence–supported software tools that use a conversational “chatbot” format to support rapid diagnosis and consistent triage. The COVID-19 pandemic has brought new attention to these tools due to the need to avoid face-to-face contact and preserve urgent care capacity. However, evidence-based deployment of these chatbots requires an understanding of user demographics and associated triage recommendations generated by a large general population. Objective In this study, we evaluate the user demographics and levels of triage acuity provided by a symptom checker chatbot deployed in partnership with a large integrated health system in the United States. Methods This population-based descriptive study included all web-based symptom assessments completed on the website and patient portal of the Sutter Health system (24 hospitals in Northern California) from April 24, 2019, to February 1, 2020. User demographics were compared to relevant US Census population data. Results A total of 26,646 symptom assessments were completed during the study period. Most assessments (17,816/26,646, 66.9%) were completed by female users. The mean user age was 34.3 years (SD 14.4 years), compared to a median age of 37.3 years of the general population. The most common initial symptom was abdominal pain (2060/26,646, 7.7%). A substantial number of assessments (12,357/26,646, 46.4%) were completed outside of typical physician office hours. Most users were advised to seek medical care on the same day (7299/26,646, 27.4%) or within 2-3 days (6301/26,646, 23.6%). Over a quarter of the assessments indicated a high degree of urgency (7723/26,646, 29.0%). Conclusions Users of the symptom checker chatbot were broadly representative of our patient population, although they skewed toward younger and female users. The triage recommendations were comparable to those of nurse-staffed telephone triage lines. Although the emergence of COVID-19 has increased the interest in remote medical assessment tools, it is important to take an evidence-based approach to their deployment.

Objectives/Hypothesis: Epidermal growth factor receptor (EGFR) is a type I transmembrane glycoprotein that is overexpressed in a wide variety of malignancies, including oral squamous cell carcinoma (OSCC). Our objective was to assess the EGFR diagnostic and prognostic value in OSCC by investigating its expression in serum and saliva of patients in comparison with healthy subjects. Study Design: Prospective case-control study. Methods: Serum and saliva samples were collected from a cohort of 63 treatment-naïve OSCC patients before surgery and a matched group of 60 healthy subjects. EGFR concentrations in serum and saliva were quantified by an enzyme-linked immunosorbent assay. Results: OSCC patients showed lower values of serum EGFR compared with controls (P =.0002). Conversely, saliva EGFR concentrations were higher in OSCC patients than in controls (P =.0014). Saliva EGFR levels were also increased in patients with higher T category (pT4 vs. pT

Representations of thyroid swelling, intended as an enlarged anterior neck region, in the artworks of various periods are sporadically reported in the scientific literature, and different intents may be hypothesized. A comprehensive review of the international literature was performed on PubMed, Embase, and ResearchGate with the aim to analyze the modalities of representation of thyroid swelling through the ages by different artistic movements. Thyroid swelling is frequently represented in the artworks of many stylistic periods and seems to be a known condition even by the earliest cultures. Thyroid swelling may be considered a common finding among forms of art distant in time and style. It is not always possible to define whether thyroid swelling is a realistic representation or a detail added by the author. Although the function of the gland was discovered only at the end of the 19th century, thanks to the artworks of authors in many cultures, it is nowadays possible to formulate hypotheses about the distribution of thyroid diseases over the centuries.

Thoracic aortic aneurysm and dissection (TAAD) affects many patients globally and has high mortality rates if undetected. Once thought to be solely a degenerative disease that afflicted the aorta due to high pressure and biomechanical stress, extensive investigation of the heritability and natural history of TAAD has shown a clear genetic basis for the disease. Here, we review both the cellular mechanisms and clinical manifestations of syndromic and non-syndromic TAAD. We particularly focus on genes that have been linked to dissection at diameters

Objective Data from several centers worldwide have demonstrated that transnasal endoscopic surgery performed with or without a transcranial approach is capable of achieving radical resection of selected sinonasal malignancies. We report our experience with endoscopic management of sinonasal cancers, with emphasis on naso-ethmoidal malignancies encroaching on the anterior skull base. Methods Major series reporting results concerning the endoscopic endonasal approach with or without craniectomy for treatment of sinonasal and anterior skull base cancers were reviewed. Preoperative work-up, indications and exclusion criteria, surgical techniques, postoperative management, and adjuvant therapy are reported. Results In the 2 largest series analyzed, the most common malignancies were adenocarcinoma (28%), olfactory neuroblastoma (14.5%), and squamous cell carcinoma (13.5%). The 5-year disease-specific survival rate ranged from 81.9%–87%, with no major differences in the mean follow-up time (34.1 months vs. 37 months). Conclusions Endoscopic endonasal resection performed with or without a transcranial approach, when properly planned and in expert hands, has an accepted role with precise indications in the surgeon’s armamentarium for the treatment of sinonasal and skull base malignancies.