Facilitating systems-level analyses of all-cause and Covid-mediated sepsis through SeptiSearch, a manually-curated compendium of dysregulated gene sets.

Background: Sepsis is a dysfunctional host response to infection. The syndrome leads to millions of deaths annually (19.7% of all deaths in 2017) and is the cause of most deaths from severe Covid infections. High throughput sequencing or 'omics' experiments in molecular and clinical sepsis research have been widely utilized to identify new diagnostics and therapies. Transcriptomics, quantifying gene expression, has dominated these studies, due to the efficiency of measuring gene expression in tissues and the technical accuracy of technologies like RNA-Seq. Objective: Most of these studies seek to uncover novel mechanistic insights into sepsis pathogenesis and diagnostic gene signatures by identifying genes differentially expressed between two or more relevant conditions. However, little effort has been made, to date, to aggregate this knowledge from such studies. In this study we sought to build a compendium of previously described gene sets that combines knowledge gained from sepsis-associated studies. This would enable the identification of genes most associated with sepsis pathogenesis, and the description of the molecular pathways commonly associated with sepsis. Methods: PubMed was searched for studies using transcriptomics to characterize acute infection/sepsis and severe sepsis (i.e., sepsis combined with organ failure). Several studies were identified that used transcriptomics to identify differentially expressed (DE) genes, predictive/prognostic signatures, and underlying molecular responses and pathways. The molecules included in each gene set were collected, in addition to the relevant study metadata (e.g., patient groups used for comparison, sample collection time point, tissue type, etc.). Results: After performing extensive literature curation of 74 sepsis-related publications involving transcriptomics, 103 unique gene sets (comprising 20,899 unique genes) from thousands of patients were collated together with associated metadata. Frequently described genes included in gene sets as well as the molecular mechanisms they were involved in were identified. These mechanisms included neutrophil degranulation, generation of second messenger molecules, IL-4 and -13 signaling, and IL-10 signaling among many others. The database, which we named SeptiSearch, is made available in a web application created using the Shiny framework in R, (available at https://septisearch.ca). Conclusions: SeptiSearch provides members of the sepsis community the bioinformatic tools needed to leverage and explore the gene sets contained in the database. This will allow the gene sets to be further scrutinized and analyzed for their enrichment in user-submitted gene expression data and used for validation of in-house gene sets/signatures.

Pre-existing autoimmunity is associated with increased severity of COVID-19: A retrospective cohort study using data from the National COVID Cohort Collaborative (N3C).

BACKGROUND: Identifying individuals with a higher risk of developing severe COVID-19 outcomes will inform targeted or more intensive clinical monitoring and management. To date, there is mixed evidence regarding the impact of pre-existing autoimmune disease (AID) diagnosis and/or immunosuppressant (IS) exposure on developing severe COVID-19 outcomes. METHODS: A retrospective cohort of adults diagnosed with COVID-19 was created in the National COVID Cohort Collaborative enclave. Two outcomes, life-threatening disease, and hospitalization were evaluated by using logistic regression models with and without adjustment for demographics and comorbidities. RESULTS: Of the 2,453,799 adults diagnosed with COVID-19, 191,520 (7.81%) had a pre-existing AID diagnosis and 278,095 (11.33%) had a pre-existing IS exposure. Logistic regression models adjusted for demographics and comorbidities demonstrated that individuals with a pre-existing AID (OR = 1.13, 95% CI 1.09 - 1.17; P< 0.001), IS (OR= 1.27, 95% CI 1.24 - 1.30; P< 0.001), or both (OR = 1.35, 95% CI 1.29 - 1.40; P< 0.001) were more likely to have a life-threatening COVID-19 disease. These results were consistent when evaluating hospitalization. A sensitivity analysis evaluating specific IS revealed that TNF inhibitors were protective against life-threatening disease (OR = 0.80, 95% CI 0.66- 0.96; P=0.017) and hospitalization (OR = 0.80, 95% CI 0.73 - 0.89; P< 0.001). CONCLUSIONS: Patients with pre-existing AID, exposure to IS, or both are more likely to have a life-threatening disease or hospitalization. These patients may thus require tailored monitoring and preventative measures to minimize negative consequences of COVID-19.

Knowledge, attitude, and practices of 2nd year MBBS students regarding the use of face mask to limit the spread of the new coronavirus disease

Face Mask;Second MBBS Students;Coronavirus Disease 19;Knowledge;Attitude;Practice;Limit the Spread INTRODUCTION With the advent of the Coronavirus disease 19 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2, strict hygiene practices became essential for the world. [10] Further, a recent metaanalytic study showed that mask use by healthcare workers provided a significant protective effect of 80% (Odds Radio = 0.20, 95% confidence interval = 0.11-0.37). [12] The World Health Organization (WHO) has stated that incorrect handling and disposal of face masks increases the amount of spread. [...]knowledge of proper use and handling of masks among HCWs is essential. A structured questionnaire was constructed based on previous literature on the correct usage of masks and the guidelines issued by the Centers for Disease Control.

Willingness to take COVID-19 vaccination in low-income countries: Evidence from Ethiopia.

BACKGROUND: In low-income countries, vaccination campaigns are lagging, and evidence on vaccine acceptance, a crucial public health planning input, remains scant. This is the first study that reports willingness to take COVID-19 vaccines and its socio-demographic correlates in Ethiopia, Africa's second most populous country. METHODS: The analysis is based on a nationally representative survey data of 2,317 households conducted in the informal economy in November 2020. It employs two logistic regression models where the two outcome variables are (i) a household head's willingness to take a COVID-19 vaccine or not, and (ii) if yes if they would also hypothetically pay (an unspecified amount) for it or not. Predictors include age, gender, education, marital status, income category, health insurance coverage, sickness due to COVID-19, chronic illness, trust in government, prior participation in voluntary activities, urban residence. RESULTS: Willingness to take the vaccine was high (88%) and significantly associated with COVID-19 cases in the family, trust in government and pro-social behavior. All other predictors such as gender, education, income, health insurance, chronic illness, urban residence did not significantly predict vaccine willingness at the 5% level. Among those willing to take the vaccine, 33% also answered that they would hypothetically pay (an unspecified amount) for it, an answer that is significantly associated with trust in government, health insurance coverage and income. CONCLUSION: The results highlight both opportunities and challenges. There is little evidence of vaccine hesitancy in Ethiopia among household heads operating in the informal economy. The role played by trust in government and pro-social behavior in motivating this outcome suggests that policy makers need to consider these factors in the planning of COVID-19 vaccine campaigns in order to foster vaccine uptake. At the same time, as the willingness to hypothetically pay for a COVID-19 vaccine seems to be small, fairly-priced vaccines along with financial support are also needed to ensure further uptake of COVID-19 vaccines.

Use of healthcare services during the COVID-19 pandemic in urban Ethiopia: evidence from retrospective health facility survey data.

OBJECTIVES: In recent years, Ethiopia has made enormous strides in enhancing access to healthcare, especially, maternal and child healthcare. With the onset and spread of COVID-19, the attention of the healthcare system has pivoted to handling the disease, potentially at the cost of other healthcare needs. This paper explores whether this shift has come at the cost of non-Covid related healthcare, especially the use of maternal and child health (MCH) services. SETTING: Data covering a 24-month period are drawn from 59 health centres and 29 public hospitals located in urban Ethiopia. PRIMARY AND SECONDARY OUTCOMES MEASURES: The primary outcome measures are the use of MCH services including family planning, antenatal and postnatal care, abortion care, delivery and immunisation. The secondary outcome measures are the use of health services by adults including antiretroviral therapy (ART), tuberculosis (TB) and leprosy and dental services RESULTS: There is a sharp reduction in the use of both inpatient (20%-27%, p<0.001) and outpatient (27%-34%, p<0.001) care, particularly in Addis Ababa, which has been most acutely affected by the virus. This decline does not come at the cost of MCH services. The use of several MCH components (skilled birth attendant deliveries, immunisation, postnatal care) remains unaffected throughout the period while others (family planning services, antenatal care) experience a decline (8%-17%) in the immediate aftermath but recover soon after. CONCLUSION: Concerns about the crowding out of MCH services due to the focus on COVID-19 are unfounded. Proactive measures taken by the government and healthcare facilities to ring-fence the use of essential healthcare services have mitigated service disruptions. The results underline the resilience and agility displayed by one of the world's most resource-constrained healthcare systems. Further research on the approaches used to mitigate disruptions is needed.

Functional Effects of Cardiomyocyte Injury in COVID-19.

COVID-19 affects multiple organs. Clinical data from the Mount Sinai Health System show that substantial numbers of COVID-19 patients without prior heart disease develop cardiac dysfunction. How COVID-19 patients develop cardiac disease is not known. We integrated cell biological and physiological analyses of human cardiomyocytes differentiated from human induced pluripotent stem cells (hiPSCs) infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the presence of interleukins (ILs) with clinical findings related to laboratory values in COVID-19 patients to identify plausible mechanisms of cardiac disease in COVID-19 patients. We infected hiPSC-derived cardiomyocytes from healthy human subjects with SARS-CoV-2 in the absence and presence of IL-6 and IL-1ß. Infection resulted in increased numbers of multinucleated cells. Interleukin treatment and infection resulted in disorganization of myofibrils, extracellular release of troponin I, and reduced and erratic beating. Infection resulted in decreased expression of mRNA encoding key proteins of the cardiomyocyte contractile apparatus. Although interleukins did not increase the extent of infection, they increased the contractile dysfunction associated with viral infection of cardiomyocytes, resulting in cessation of beating. Clinical data from hospitalized patients from the Mount Sinai Health System show that a significant portion of COVID-19 patients without history of heart disease have elevated troponin and interleukin levels. A substantial subset of these patients showed reduced left ventricular function by echocardiography. Our laboratory observations, combined with the clinical data, indicate that direct effects on cardiomyocytes by interleukins and SARS-CoV-2 infection might underlie heart disease in COVID-19 patients. IMPORTANCE SARS-CoV-2 infects multiple organs, including the heart. Analyses of hospitalized patients show that a substantial number without prior indication of heart disease or comorbidities show significant injury to heart tissue, assessed by increased levels of troponin in blood. We studied the cell biological and physiological effects of virus infection of healthy human iPSC-derived cardiomyocytes in culture. Virus infection with interleukins disorganizes myofibrils, increases cell size and the numbers of multinucleated cells, and suppresses the expression of proteins of the contractile apparatus. Viral infection of cardiomyocytes in culture triggers release of troponin similar to elevation in levels of COVID-19 patients with heart disease. Viral infection in the presence of interleukins slows down and desynchronizes the beating of cardiomyocytes in culture. The cell-level physiological changes are similar to decreases in left ventricular ejection seen in imaging of patients' hearts. These observations suggest that direct injury to heart tissue by virus can be one underlying cause of heart disease in COVID-19.

The effect of asthma or chronic obstructive pulmonary disease on hospitalization outcomes of COVID-19 patients: A retrospective cohort study

Introduction: First identified in Wuhan, China in December 2019, COVID-19 infection, caused by severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2), is responsible for the ongoing global pandemic that has claimed more than 1.5 million lives. The United States has become one of the epicenters for the outbreak. The effects of asthma or chronic obstructive pulmonary disease (COPD) are unknown with regards to the outcomes of patients with COVID-19 infection. This study aims to evaluate the effect of asthma or COPD on patients admitted with COVID-19 viral infection at a safety-net hospital in Long Island, New York. Method: In this retrospective single-center study, we identified 636 patients (age ≥18), admitted to our institution for COVID-19 infection from March 2020 to May 2020. Diagnosis of asthma or COPD was documented through patient history upon admission. The primary outcome was in-hospital all-cause mortality. In addition, secondary outcomes included cardiac arrest, acute respiratory distress syndrome (ARDS), intubation/mechanical ventilation, shock, and hospital and intensive care unit length of stay. Chi-square tests and independent T-sample tests were used to analyze categorical and continuous variables, respectively. Multivariate logistic regression analyses were performed to measure the odds of inpatient mortality and other secondary outcomes. All statistical analyses were performed using SPSS. Results: Of the 636 patients, 67 (10.5%) reported a history of asthma or COPD, 567 (89.2%) denied and 2 (0.3%) were unable to provide history. Patients with asthma or COPD had a statistically elevated risk of mortality than those without (44.8% vs. 30.7%, p=0.008) and a higher rate of cardiac arrest (35.8% vs. 21.5%, p=0.021). Patients with asthma or COPD had an increased rate of comorbidities compared to those without (Table 1). There was no statistical difference in between groups for other secondary outcomes including intubation, shock, ARDS, and arrhythmias. Mean age in those with asthma or COPD was 66.3 versus 59.1 (standard deviation 14.1 and 15.9 respectively, p=0.243). There was also no statistical difference between the two groups in the hospital or intensive care unit (ICU) length of stay (Table 1). Conclusion: Our study supports that COVID-19 patients with asthma or chronic obstructive pulmonary disease (COPD) demonstrated an elevated risk of all-cause in-hospital mortality and cardiac arrest but did not correlate with an increase in intubation, ARDS, arrhythmias, shock, and hospital/ICU length of stay.

Suburban race and insurance disparities in COVID-19: Insights from a safety-net hospital in new york

RATIONALE: While ethnic and socioeconomic disparities in COVID-19 from metropolitan samples are reported, there is a scarcity of studies examining suburban cohorts. In other disorders, previous studies report suburban populations have worse outcomes and are generally underrepresented in literature. We describe racial and insurance disparities in COVID-19 from the largest safety-net hospitals in suburban Nassau County, a county with the largest COVID-19 burden in the state after New York City. METHODS: A retrospective unmatched singlecenter study with the first 636 COVID-19 patients (age≥18 years) admitted to our facility from March to May 2020. Sample was stratified into race, insurance status and analyzed via SPSS using Pearson Chi-square, independent T-sample tests. Primary outcome was all-cause in-hospital mortality, with other overall clinical parameters as secondary. Statistical analyses performed using SPSS. RESULTS: Of 636 COVID-19 hospitalized patients, ethnicities were 36.5% Hispanic (HI), 26.1% African-American (AA), and 22.0% Caucaisan (CA). HI patients were younger, had highest rates of uninsurance, obesity, DM2 and had better overall clinical outcomes. Compared to HI or CA, AA patients were associated with worse clinical outcomes of ICU admission (33.15% vs. CA 27.9%, HI 25.4% p= 0.787), Intubation (27.7% vs. CA 24.3%, HI 24.1%, p=0.709), developing shock requiring inotropes (20.5% vs. CA 15.0%, HI 15.9% p=0.353), new AKI (36.4% vs. CA 24.3%, HI 17.2% p=0.001), renal failure requiring HD/RRT (5.5% vs. CA 3.6%, HI 5.2% p=0.982). AA had worse outcomes than CA counterparts despite being younger, and similar comorbidities (CCS score AA 3.39, CA 3.39, p <0.05). CA patients had higher ARDS (CA 41.4%, AA 39.4%, HI 37.1%, p=0.207), cardiac arrest (CA 28.6, AA 25.3, HI 19.0 p=0.302) and highest mortality (42.9%, vs AA 34.3%, HI 23.7%, p=0.002). CONCLUSION: Despite being a smaller proportion in suburban areas, suburbanAA and Hispanic patients with COVID-19 were overrepresented than their Caucasian counterparts, even more than metropolitan cohorts. AA patients had worse clinical outcomes, yet had lower mortality than CA patients. Understanding racial disparities in COVID-19 in suburban populations paramount in improving clinical understanding of a rising pandemic throughout the United States.

Sweet hydrothorax-a rare complication of peritoneal dialysis

Hydrothorax resulting from pleuroperitoneal communication is a rare complication of peritoneal dialysis (PD), occurring in less than 2% of all continuous ambulatory peritoneal dialysis (CAPD) patients. Imaging findings revealing the presence of a pleuroperitoneal fistula and pleural fluid analysis with high glucose gradient confirming the diagnosis of “sweet hydrothorax”. The proposed mechanism for the development of hydrothorax includes acquired weakening of the diaphragmatic fibers secondary to high intra-abdominal pressures that occur during peritoneal dialysis and impairment in the lymphatic drainage. A 56-year-old Hispanic male with end-stage renal disease on CAPD daily at home 4 months before admission, hypertension, hyperlipidemia, and recent COVID-19 infection (2 weeks before admission) presented to the ED complaining of dyspnea for two days, exacerbated when lying in the left lateral decubitus position and relieved when lying on right lateral decubitus or supine. He denied worsening dyspnea on exertion, palpitations, or chest pain. He reported compliance with daily PD. He denied fever, night sweats, chills, weight loss, or abdominal pain. Other review of systems was negative. Vitals on admission were BP 141/53, HR 87, Temp 98F, with saturation of 86 % on room air, which improved to 96-97% after being placed on BIPAP with settings of IPAP 10 EPAP 5, FiO2 40%. Physical exam was only positive for absent breath sounds over the right lung base. Chest X-Ray and CT Thorax were performed with findings of a large-right sided pleural effusion. Thoracentesis performed revealed transudative fluid with a high glucose level compared to serum. CT Peritoneography done showed findings of the presence of a right-sided pleuroperitoneal fistula with a diaphragmatic defect. The patient was then transitioned temporarily to hemodialysis.The pathophysiology of the PD leaks is mainly due to congenital or acquired diaphragmatic defects, disorders of lymphatic drainage, or high pleuroperitoneal pressure gradients. It has been postulated that during the PD treatment, increased intraabdominal pressure can tear the previously intact collagen fibers or worsen a congenital diaphragmatic defect, which promotes the translocation of dialysate into the pleural space. A positive pleural/serum fluid glucose measurement ratio is very highly sensitive & specific for PD leak thus referred to as “sweet hydrothorax”. First step to management is the discontinuation of PD. The removal of the pressure gradient between the peritoneum and pleura leads to conservative healing of the diaphragmatic defect. Another approach is the repair of the diaphragmatic defect which includes conventional, or video-assisted thoracoscopy (VATS).

Physiology of cardiomyocyte injury in COVID-19 (preprint)

COVID-19 affects multiple organs. Clinical data from the Mount Sinai Health System shows that substantial numbers of COVID-19 patients without prior heart disease develop cardiac dysfunction. How COVID-19 patients develop cardiac disease is not known. We integrate cell biological and physiological analyses of human cardiomyocytes differentiated from human induced pluripotent stem cells (hiPSCs) infected with SARS-CoV-2 in the presence of interleukins, with clinical findings, to investigate plausible mechanisms of cardiac disease in COVID-19 patients. We infected hiPSC-derived cardiomyocytes, from healthy human subjects, with SARS-CoV-2 in the absence and presence of interleukins. We find that interleukin treatment and infection results in disorganization of myofibrils, extracellular release of troponin-I, and reduced and erratic beating. Although interleukins do not increase the extent, they increase the severity of viral infection of cardiomyocytes resulting in cessation of beating. Clinical data from hospitalized patients from the Mount Sinai Health system show that a significant portion of COVID-19 patients without prior history of heart disease, have elevated troponin and interleukin levels. A substantial subset of these patients showed reduced left ventricular function by echocardiography. Our laboratory observations, combined with the clinical data, indicate that direct effects on cardiomyocytes by interleukins and SARS-CoV-2 infection can underlie the heart disease in COVID-19 patients.

EVALUATING OBESITY PARADOX IN COVID 19: INSIGHTS FROM A SAFETY-NET HOSPITAL IN NEW YORK

SESSION TITLE: New Developments in the Diagnosis and Management of Mycobacterial and Bacterial Chest Infections SESSION TYPE: Original Investigations PRESENTED ON: October 18-21, 2020 PURPOSE: The United States has become the new epicenter for COVID-19 infection. The role of obesity in COVID-19 infection and ARDS is unclear. Previous studies indicate obese hospitalized patients may have better outcomes including mortality, a phenomenon referred to as “obesity paradox.” This study aims to evaluate the effect of obesity on patients admitted with COVID-19 infection in a suburban safety-net hospital in New York. METHODS: A retrospective unmatched single-center study of the first 142 patients (age≥18 y) admitted to our facility from March 9, 2020 to March 30, 2020 with the diagnosis of COVID-19 infection. Body mass index (kg/m2) was used to stratify patients into nonobese (BMI <30) and obese (BMI>30). Further subdivisions based on WHO classification include underweight (<18.5), normal weight (≥18.5 to 24.9), overweight (≥25.0 to 29.9). Obesity subdivided into Class I (30.0 to 34.9), Class II (35.0 to 39.9), Class III morbid obesity (≥40). Statistical analyses were performed using SPSS. The primary outcome was all-cause mortality, secondary outcomes include ICU admission, intubation, ARDS and more. RESULTS: Out of the total 142 patients, 54 (37.46%) were obese. Obese patients had statistically significant higher rates of requiring ICU admission (50% vs 27% p=0.014), developing ARDS (48.1% vs. 29.2%), had longer hospital length of stay (11.2 vs. 8.2, p=0.031) and were more likely to be admitted directly to the ICU from ED (29.6% vs. 11.2%, p=0.019). Obese patients had higher mortality (42.6% vs. 36.0%, p= 0.429) than nonobese. Obese Covid-19 patients had more severe hypoxia on initial presentation (55.6% vs. 42.7% p=0.136), intubation (40.7% vs. 28.1%, p=0.118), worse PaO2/FIO2 ratios (173.9 vs. 276.6, p=0.635) and septic shock (31.5% vs. 20.2%, p=0.129). No statistical significance was seen between groups in terms of ethnicities, comorbidities including hypertension, diabetes and Charlson Comorbidity Index. No statistical significance was observed in obesity subdivisions, however the morbidly obese group had the highest frequency of mortality at 54%. CONCLUSIONS: Our study does not support the evidence of “Obesity Paradox” in COVID-19 infection, as obesity does not confer a statistical reduction in mortality. In contrast, our study suggests increased morbidity based on increased ICU admissions, development of ARDS and longer hospital stay in obese patients. Further studies are required to evaluate the role of obesity as an independent risk factor in COVID-19. CLINICAL IMPLICATIONS: Contrary to the "Obesity Paradox", Obese patients with COVID-19 infection may have worse clinical outcomes than non-obese. DISCLOSURES: No relevant relationships by Shiva Arjun, source=Web Response No relevant relationships by Andres Castillo, source=Web Response No relevant relationships by Jiten Desai, source=Web Response No relevant relationships by Kristen Farraj, source=Web Response No relevant relationships by Sandra Gomez Paz, source=Web Response No relevant relationships by Jaehyuck Im, source=Web Response No relevant relationships by Javed Iqbal, source=Web Response No relevant relationships by Paul Mustacchia, source=Web Response No relevant relationships by Upenkumar Patel, source=Web Response No relevant relationships by Rajmohan Rammohan, source=Web Response No relevant relationships by Kevin Yeroushalmi, source=Web Response

CASE REPORT OF SEVERE PULMONARY FIBROSIS AS A SEQUELAE OF COVID-19 INFECTION

SESSION TITLE: Medical Student/Resident Chest Infections Posters SESSION TYPE: Med Student/Res Case Rep Postr PRESENTED ON: October 18-21, 2020 INTRODUCTION: Though acute pulmonary manifestations of COVID-19 infection are well documented, the long-term sequelae from this viral infection are unclear. We report a case of a patient presenting with persistent respiratory failure after recovery from COVID-19 infection with imaging showing evidence of new onset pulmonary fibrosis. CASE PRESENTATION: 56 year-old Hispanic male with Diabetes Mellitus presents to ED for shortness of breath on exertion after recent hospitalization 16 days ago for Covid-19 infection. He reports progressive dyspnea since discharge, interfering with daily activities including walking to the bathroom and preparing food. He denies dyspnea at rest, cough, constitutional symptoms, or exposure to sick contacts. On his last visit, he was hospitalized for 24 days for Covid-19 pneumonia, and finished a course of antibiotics, hydroxychloroquine and steroids. PaO2/Fio2 ratio was 250, and oxygen requirements were met with nasal cannula, with gradual improvement to 95% saturation on room air. He denied previous hospitalizations, family history, occupational exposures and substance abuse. Vital Signs showed blood pressure 137/91 mmHg, Pulse 116 BPM, RR 22 Temperature 98.4 F. Physical exam was pertinent for fine velcro-like inspiratory and expiratory crackles auscultated at lung bases, saturating 94% on room air at rest but desaturating to 85% after walking 5 steps. Labs revealed chest x-ray showed patchy opacities diffusely worsened from previous visit. CTPE showed no pulmonary embolism, but diffuse bilateral patchy infiltrates with ground glass opacities and bronchiectasis. WBC was 8.64 [K/mm3], absolute lymphocyte count 1.73 K/mm3. BNP, procalcitonin, lactate, autoimmune workup and Echocardiogram were normal. Inflammatory markers were elevated but decreased from last admission. Quantiferon Gold was positive with three negative AFB smears suggesting latent tuberculosis. PFTs showed a moderate restrictive pattern. He was treated with methylprednisolone and oxygen to prevent further fibrosis in areas of active inflammation and isoniazid for latent TB. After symptomatic improvement, he was discharged on home oxygen and steroid taper with outpatient follow up. DISCUSSION: The true long term implications of COVID-19 are uncertain. We highlight a patient who recovered from COVID-19 infection with mild ARDS yet has profound hypoxia on exertion with imaging showing severe fibrotic changes and areas of active inflammation. While severe ARDS alone has been shown to cause rapidly forming pulmonary fibrosis, exact sequelae of mild COVID-19 respiratory failure is unknown. Possible mechanisms include proliferation of proinflammatory cytokines like IL-6 during the acute infection, which has been linked to development of fibrosis. CONCLUSIONS: Our case reinforces the need for close outpatient follow-up of COVID-19 recovered patients and outlines a potential cause of hospital readmissions. Reference #1: Spagnolo P, Balestro E, Aliberti S, et al. Pulmonary fibrosis secondary to COVID-19: a call to arms? [published online ahead of print, 2020 May 15]. Lancet Respir Med. 2020;S2213-2600(20)30222-8. doi:10.1016/S2213-2600(20)30222-8 Reference #2: Leask A. COVID-19: is fibrosis the killer? [published online ahead of print, 2020 May 13]. J Cell Commun Signal. 2020;1. doi:10.1007/s12079-020-00569-0 Reference #3: Cabrera-Benitez NE, Laffey JG, Parotto M, et al. Mechanical ventilation-associated lung fibrosis in acute respiratory distress syndrome: a significant contributor to poor outcome. Anesthesiology. 2014;121(1):189-198. doi:10.1097/ALN.0000000000000264 DISCLOSURES: No relevant relationships by Fatima Anjum, source=Web Response No relevant relationships by Shiva Arjun, source=Web Response No relevant relationships by Javed Iqbal, source=Web Response No relevant relationships by Dolly Patel, source=Web Response No relevant relationships by Raghavendra Sanivarapu, source=Web Res onse

Clinical features of COVID-19 mortality: development and validation of a clinical prediction model.

Background: The COVID-19 pandemic has affected millions of individuals and caused hundreds of thousands of deaths worldwide. Predicting mortality among patients with COVID-19 who present with a spectrum of complications is very difficult, hindering the prognostication and management of the disease. We aimed to develop an accurate prediction model of COVID-19 mortality using unbiased computational methods, and identify the clinical features most predictive of this outcome. Methods: In this prediction model development and validation study, we applied machine learning techniques to clinical data from a large cohort of patients with COVID-19 treated at the Mount Sinai Health System in New York City, NY, USA, to predict mortality. We analysed patient-level data captured in the Mount Sinai Data Warehouse database for individuals with a confirmed diagnosis of COVID-19 who had a health system encounter between March 9 and April 6, 2020. For initial analyses, we used patient data from March 9 to April 5, and randomly assigned (80:20) the patients to the development dataset or test dataset 1 (retrospective). Patient data for those with encounters on April 6, 2020, were used in test dataset 2 (prospective). We designed prediction models based on clinical features and patient characteristics during health system encounters to predict mortality using the development dataset. We assessed the resultant models in terms of the area under the receiver operating characteristic curve (AUC) score in the test datasets. Findings: Using the development dataset (n=3841) and a systematic machine learning framework, we developed a COVID-19 mortality prediction model that showed high accuracy (AUC=0·91) when applied to test datasets of retrospective (n=961) and prospective (n=249) patients. This model was based on three clinical features: patient's age, minimum oxygen saturation over the course of their medical encounter, and type of patient encounter (inpatient vs outpatient and telehealth visits). Interpretation: An accurate and parsimonious COVID-19 mortality prediction model based on three features might have utility in clinical settings to guide the management and prognostication of patients affected by this disease. External validation of this prediction model in other populations is needed. Funding: National Institutes of Health.

Local spikes in COVID-19 cases: Recommendations for maintaining otolaryngology clinic operations.

The Coronavirus Disease-2019 (COVID-19) pandemic has created an unprecedented economic and public health crisis in the United States. Following efforts to mitigate disease spread, with a significant decline in some regions, many states began reopening their economies. As social distancing guidelines were relaxed and businesses opened, local outbreaks of COVID-19 continue to place person on healthcare systems. Among medical specialties, otolaryngologists and their staff are among the highest at risk for becoming exposed to COVID-19. As otolaryngologists prepare to weather the storm of impending local surges in COVID-19 infections there are several practical measures that can be taken to mitigate the risk to ourselves and our staff.

Clinical predictors of COVID-19 mortality (preprint)

Background: The coronavirus disease 2019 (COVID-19) pandemic has affected over millions of individuals and caused hundreds of thousands of deaths worldwide. It can be difficult to accurately predict mortality among COVID-19 patients presenting with a spectrum of complications, hindering the prognostication and management of the disease. Methods: We applied machine learning techniques to clinical data from a large cohort of 5,051 COVID-19 patients treated at the Mount Sinai Health System in New York City, the global COVID-19 epicenter, to predict mortality. Predictors were designed to classify patients into Deceased or Alive mortality classes and were evaluated in terms of the area under the receiver operating characteristic (ROC) curve (AUC score). Findings: Using a development cohort (n=3,841) and a systematic machine learning framework, we identified a COVID-19 mortality predictor that demonstrated high accuracy (AUC=0.91) when applied to test sets of retrospective (n= 961) and prospective (n=249) patients. This mortality predictor was based on five clinical features: age, minimum O2 saturation during encounter, type of patient encounter (inpatient vs. various types of outpatient and telehealth encounters), hydroxychloroquine use, and maximum body temperature. Interpretation: An accurate and parsimonious COVID-19 mortality predictor based on five features may have utility in clinical settings to guide the management and prognostication of patients affected by this disease.