ONLINE FORMATIVE ASSESSMENT PRACTICES AMONG ACADEMICS OF TERTIARY EDUCATION IN SOKOTO STATE, NIGERIA

Purpose: This study examines the effect of two main factors, that is, lack of knowledge of ICT, and the availability of ICT facilities such as hardware, software, and internet access, which identified to be the common barriers towards practicing online formative assessment. Theoretical framework: Many educational institutions have been urged to adopt online learning due to the development of communications and digital device technology as well as the COVID-19 pandemic that ravaged the world in the previous two years. The shift from offline to online mode affects how formative assessment should be conducted during teaching and learning. The lack of knowledge of information and communication technology (ICT) and ICT facilities are prevalent in Nigeria. Design/methodology/approach: This study employed a survey design to examine online assessment feedback practice as well as factors contributing to the practices among 256 academics in one tertiary education in Sokoto. Descriptive and inferential statistical analyses were used. Findings: Online formative assessment feedback practice is at low level due to lack of knowledge of software applications and facilities. Research, Practical & Social implications: Government needs to invest more on educational technology by providing adequate ICT facilities in tertiary institutions in Sokoto, as well as offering suitable trainings on ICT literacy for academics. Originality/value: Online formative assessment contributes to enhancement in educational attainment and efficiency in learning and teaching. © 2022 by the Author(s).

Explanation of Multi-Label Neural Networks with Layer-Wise Relevance Propagation

Neural networks are considered a black-box model as their strength in modeling complex interactions makes its operation almost impossible to explain. Still, neural networks remain very interesting tools as they have shown promising performance in various classification tasks. Layer-wise relevance propagation is a technique that, based on a propagation approach, is able to explain the predictions obtained by a neural network. In this work, we propose four adaptations of this technique to operate on multi-label neural networks. The proposed methods provide new ways of distributing the relevance between the output layer and the preceding ones. The efficacy of these adaptations is demonstrated after an experimental study. The study is carried out based on existing evaluation criteria in the literature that measure the explanation's quality. These methods are applied to a case study in which a neural network is used to detect secondary coinfections in patients infected with SARS-CoV-2. Overall, the proposed methods provide a post-hoc interpretability stage of the results. © 2022 IEEE.

Higher Angiotensin Converting Enzymes Activities Are Observed In Covid-19 Positive Volunteers

The high transmissibility and the broad spectrum of clinical manifestations of COVID-19 are in part due to the high affinity of SARS-CoV-2 for its receptor, Angiotensin Converting Enzyme 2 (ACE2). The depletion of the biological functions of ACE2, due to the internalization of the receptor along with SARS-CoV-2, leads to impairment of Renin Angiotensin System (RAS), which can contribute to COVID-19 pathogenesis. In addition, genetic differences in RAS may be associated with more severe symptoms and complications observed in COVID-19 patients. This study aims to perform a comparative analysis between COVID-19 positive patients and uninfected individuals, to correlate such disease profiles with ACE I/D (Insertion/Deletion) and ACE2 G8790A polymorphisms, and their enzymatic activities. The anthropometric, demographic, clinical and cardiovascular parameters of 764 individuals from Ipaussu/SP (Brazil) were evaluated. ACE and ACE2 activities were measured by fluorometric assays, and assessment of both enzymes polymorphisms was performed by PCR. In this cohort, 35,2% (269 of 764) the volunteers were positive for COVID-19. The prevalence of COVID-19 was higher among women (67%) and individuals aged between 18 and 49 years. Also, comorbidities as obesity and arterial hypertension were more frequent in the positive group, when considered individuals under 60 years old. Higher ACE and ACE2 enzymatic activities were observed in positive group (46.4 vs 41.6 and 11.3 vs 8.5, respectively). Individuals with ID genotype in the positive group presented higher ACE activity compared to individuals with same genotype in control group (46.9 vs 41.7). In the positive group, ACE activity was increased in the DD (54.5) when compared to ID (46.9) and II (37.9) genotypes. No significant differences related to ACE2 activity and polymorphism were observed. ACE/ACE2 activity ratio was higher in the COVID-19 negative group (4.7 vs 3.7). The increased ACE activity for the DD genotype was in line with the literature data for hypertension and cardiovascular diseases. We can suggest a synergic effect between ACE DD genotype and COVID-19 infection enhancing ACE activity, what may contribute to pro-inflammatory phenotype and more severe symptoms of COVID-19.

IMPACT OF CONFINEMENT DURING THE COVID-19 PANDEMIC ON THE HEALTHCARE ACTIVITY OF ADULTS OVER 64 YEARS OF AGE IN AN ORAL HEALTH UNIT OF THE GRAN CANARIA HEALTH AREA

INTRODUCTION: The COVID-19 pandemic has meant a drastic change in many aspects of daily life and its impact has been even more evident for the elderly. OBJECTIVE: The aim of this study is to quantify the impact of confinement during the COVID-19 pandemic on the healthcare activity of the elderly over the age of 64 in an Oral Health Unit (USBD) of the Health Area of Gran Canaria. MATERIAL AND METHODS: This is a retrospective observational study with data from January 2017 to December 2020. Using an interrupted time series design, we compare the level of visits before and after the decree of the first state of alarm in March 2020. RESULTS: During the period of confinement, an average of 7 patients per day aged 64 years and older stopped visiting the USBD, -6.9573 [-10.40;-3.517]. This represents a drop of close to 85% per week, and 100% in institutionalised patients. 83% of the visits scheduled before confinement did not take place. CONCLUSIONS: The interruption of care activity during confinement has been almost total, which could lead to a higher risk of morbidity and mortality in the long term. The backlog of non received dental treatment represents a threat to patients' oral health and is likely to affect the USBD's capacity for care in the near future.

Remdesivir and Tocilizumab for the Treatment of Severe COVID-19 in a Community Hospital: A Retrospective Cohort Study

Background. Growing evidence supports the use of remdesivir and tocilizumab for the treatment of hospitalized patients with severe COVID-19. The purpose of this study was to evaluate the use of remdesivir and tocilizumab for the treatment of severe COVID-19 in a community hospital setting. Methods. We used a de-identified dataset of hospitalized adults with severe COVID-19 according to the National Institutes of Health definition (SpO2 < 94% on room air, a PaO2/FiO2 < 300 mm Hg, respiratory frequency > 30/min, or lung infiltrates > 50%) admitted to our community hospital located in Evanston Illinois, between March 1, 2020, and March 1, 2021. We performed a Cox proportional hazards regression model to examine the relationship between the use of remdesivir and tocilizumab and inpatient mortality. To minimize confounders, we adjusted for age, qSOFA score, noninvasive positive-pressure ventilation, invasive mechanical ventilation, and steroids, forcing these variables into the model. We implemented a sensitivity analysis calculating the E-value (with the lower confidence limit) for the obtained point estimates to assess the potential effect of unmeasured confounding. Figure 1. Kaplan-Meier survival curves for in-hospital death among patients treated with and without steroids The hazard ratio was derived from a bivariable Cox regression model. The survival curves were compared with a log-rank test, where a two-sided P value of less than 0.05 was considered statistically significant. Figure 2. Kaplan-Meier survival curves for in-hospital death among patients treated with and without remdesivir The hazard ratio was derived from a bivariable Cox regression model. The survival curves were compared with a log-rank test, where a two-sided P value of less than 0.05 was considered statistically significant. Results. A total of 549 patients were included. The median age was 69 years (interquartile range, 59 - 80 years), 333 (59.6%) were male, 231 were White (41.3%), and 235 (42%) were admitted from long-term care facilities. 394 (70.5%) received steroids, 192 (34.3%) received remdesivir, and 49 (8.8%) received tocilizumab. By the cutoff date for data analysis, 389 (69.6%) patients survived, and 170 (30.4%) had died. The bivariable Cox regression models showed decreased hazard of in-hospital death associated with the administration of steroids (Figure 1), remdesivir (Figure 2), and tocilizumab (Figure 3). This association persisted in the multivariable Cox regression controlling for other predictors (Figure 4). The E value for the multivariable Cox regression point estimates and the lower confidence intervals are shown in Table 1. The hazard ratio was derived from a bivariable Cox regression model. The survival curves were compared with a log-rank test, where a two-sided P value of less than 0.05 was considered statistically significant. The hazard ratios were derived from a multivariable Cox regression model adjusting for age as a continuous variable, qSOFA score, noninvasive positive-pressure ventilation, and invasive mechanical ventilation. Table 1. Sensitivity analysis of unmeasured confounding using E-values CI, confidence interval. Point estimate from multivariable Cox regression model. The E value is defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the exposure and the outcome, conditional on the measured covariates, to explain away a specific exposure-outcome association fully: i.e., a confounder not included in the multivariable Cox regression model associated with remdesivir or tocilizumab use and in-hospital death in patients with severe COVID-19 by a hazard ratio of 1.64-fold or 1.54-fold each, respectively, could explain away the lower confidence limit, but weaker confounding could not. Conclusion. For patients with severe COVID-19 admitted to our community hospital, the use of steroids, remdesivir, and tocilizumab were significantly associated with a slower progression to in-hospital death while controlling for other predictors included in the models.

Febrile crisis as initial manifestation of COVID-19

Introduction: COVID-19 is a disease that has shown low morbidity and mortality in pediatrics. Febrile crises are one of the most common causes of admission to emergency services and consultations with the neuropediatrician. Objective: Interpret the presence of simple febrile crisis in patients admitted to pediatric emergency services as an initial manifestation of COVID-19. Case presentation: One-year-old female patient, with a previous health history, who is attended in the emergency service with a fever of 38 ℃ and motor crisis, of widespread onset, with tonic-clonic seizures, which yielded with antypiretic measures. By protocol, lumbar puncture is performed which is negative. She was admitted, and 24 hours later there is an onset of catarrhal manifestations;an otoscopy is performed and acute otitis media is diagnosed, so antibiotic treatment is initiated. The polymerase chain reaction test for COVID-19 (PCR) is performed with a positive result, so, the patient is referred to the "San Miguel del Padrón" Pediatric Hospital. Conclusions: COVID-19 should be suspected in patients who attend to the emergency services due to a febrile crisis as the only health problem. COVID-19 is a disease that has been shown to occur in a variety of ways. © 2021, Editorial Ciencias Medicas. All rights reserved.

Layer-Wise Relevance Propagation in Multi-label Neural Networks to Identify COVID-19 Associated Coinfections

COVID-19 has been affected worldwide since the end of 2019. Clinical studies have shown that a factor that increases its lethality is the existence of secondary infections. Coinfections associated with the infection SARS-CoV-2 are classified into bacterial infections and fungal infections. A patient may develop one, both, or neither. From a machine learning point of view, this is considered a multi-label classification problem. In this work, we propose a multi-label neural network able to detect such infections in a patient with SARS-CoV-2 and thus provide the medical community with a diagnosis to guide therapy in these patients. However, neural networks are often considered a “black box” model, as their strength in modeling complex interactions, also make their operation almost impossible to explain. Therefore, we propose three adaptations of the Layer-wise Relevance Propagation algorithm to explain multi-label neural networks. The inclusion of this post-hoc interpretability stage made it possible to identify significant input variables in a classifier output. © 2021, Springer Nature Switzerland AG.

THE FIRST AND SECOND WAVES OF THE COVID-19 PANDEMIC IN A COMMUNITY HOSPITAL ICU

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: Several countries have seen a two-wave pattern of the COVID-19 pandemic. However, clinical characteristics and outcomes between waves vary across regions. A study in England suggested a substantial improvement in survival amongst people admitted to critical care with COVID-19, with markedly higher survival rates in people admitted in the first wave compared with those admitted in the second wave, while a study in Africa, the second wave appeared to be much more aggressive. Therefore, regional-specific analyses are needed. METHODS: We retrospectively reviewed a de-identified dataset of patients with COVID-19 admitted to our community hospital ICU, from March 1, 2020, to February 28, 2021. Only molecularly confirmed COVID-19 cases defined by a positive result on an RT-PCR assay or NAAT of a specimen collected on a nasopharyngeal swab were included. We then identified patients from the first wave as those admitted during the initial peak of admissions observed at our hospital between March 1, 2020, and September 3, 2020. The second wave was defined as those admitted during the second peak of admissions observed between October 1, 2020, and February 28, 2021. Descriptive statistics were performed to summarize data. RESULTS: Between March 1, 2020, and February 28, 2021, a total of 190 patients were admitted to our community-hospital ICU. Of those, 132 (69.5%) were identified as patients from the first wave, and 58 (30.5%) were identified as patients from the second wave. The median age was not significantly different among patients from the first and second wave (69 years [IQR 59 – 78 years] vs. 69 years [IQR 61 – 77.25 years;p=.841]. Sex distribution was also not significantly different between the two waves (85/132 males [64.4%] vs. 40/58 males [69%];p=.541). A significantly higher rate of patients was admitted from long-term care facilities during the first wave compared to the second wave (77/132 [58.3%] vs. 7/58 [12.1%];p<.001). The distribution of comorbidities was similar between groups, except for neurocognitive disorders, which were mostly observed in the first wave (46/132 [34.8% vs. 7/58 [12.1%];p=.001). While the rates of invasive mechanical ventilation were similar between groups (75/132 [56.8%] vs. 36-58 [62.1%];p=.499, significant higher rates of patients received humidified high-flow nasal cannula (19/132 [14.4%] vs. 29/58 [50%];p<.001) and noninvasive ventilation (9/132 [6.8%] vs. 23/58 [39.7%];p<.001) during the second wave. Following the release of some pivotal clinical trials, more patients during the second wave received corticosteroids (87/132 [65.9%] vs. 56/58 [96.6%];p<.001) and remdesivir (19/132 [14.4%] vs. 48/58 [82.8%];p<.001). However, the in-hospital case-fatality rate was not significantly different between groups (68/132 [51.5%] vs. 32/58 [55.2%];p=.642). CONCLUSIONS: While epidemiological characteristics of patients with COVID-19 admitted to our ICU between the two waves were grossly similar, a significantly higher rate of patients was admitted from long-term care facilities during the first wave, and non-invasive ventilation and targeted therapies were used more during the second wave. The in-hospital case-fatality rate was not significantly different. CLINICAL IMPLICATIONS: In our community hospital in the Chicago North Shore area, the ICU case-fatality rate was not significantly different between two different waves of the COVID-19 pandemic. DISCLOSURES: No relevant relationships by Chul Won Chung, source=Web Response No relevant relationships by Goar Egoryan, source=Web Response No relevant relationships by Harvey Friedman, source=Web Response No relevant relationships by Emre Ozcekirdek, source=Web Response No relevant relationships by Ece Ozen, source=Web Response No relevant relationships by Bidhya Poudel, source=Web Response No relevant relationships by Guillermo Rodriguez-Nava, source=Web Response No relevant relationships by Daniela Trelles Garcia, source=Web Response No relevant relationships by Valer a Trelles Garcia, source=Web Response No relevant relationships by Maria Yanez-Bello, source=Web Response No relevant relationships by Qishuo Zhang, source=Web Response

IN-HOSPITAL MORTALITY IN MECHANICALLY VENTILATED PATIENTS WITH COVID-19 WITH DIFFERENT ARDS PHENOTYPES

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: The purpose of the study is to investigate the in-hospital mortality of mechanically ventilated, COVID-19 (i.e., severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) patients with high lung compliance (i.e., atypical acute respiratory distress syndrome (ARDS)) compared to those with low lung compliance (i.e., classic ARDS). METHODS: It is a retrospective cohort study of patients older than 18 years diagnosed with COVID-19 infection that required mechanical ventilation (MV) for at least 24 hours between January 20, 2020, and April 30, 2020. Atypical ARDS was defined as driving pressure is less than 15 cm H2O throughout the period of MV, suggesting compliant lung based on the currently available evidence (Amato, Marcelo BP, et al., 2015). If it was impossible to maintain driving pressure less than 15 cm H2O for more than two days, the case was defined as classic ARDS with low compliance. Patients who required mechanical ventilation not more than 24 hours or expired within 24 hours since intubated and those transferred to another hospital were excluded. Patients who received remdesivir were also excluded because 95% of the patients did not receive it during their index hospitalization. The outcome was adjusted by age, sex, days of onset to ICU, the severity of illness estimated by APACHE score, and severity of ARDS based on PaO2/FiO2 ratio. RESULTS: A total of 60 patients that required mechanical ventilation for COVID-19 induced ARDS during the study period were reviewed per inclusion and exclusion criteria. In-hospital mortality of 30 patients of the atypical ARDS group was 50% during the index hospitalization whereas it was 53 % for 30 patients of the classic ARDS group (p=0.80) when both were treated with the same ARDS protocol, including low tidal volume and higher PEEP. The average duration of mechanical ventilation, length of ICU and hospital stay was 10.23, 12.33, and 12.93 days for the atypical ARDS group, respectively, compared to 16.57, 18.33, and 19.33 for the classic ARDS group (p=0.003, 0.011, and 0.004, respectively). The classic ARDS group required prone positioning (67% vs. 37%;p=0.02) and use of paralytics (73% vs. 43%;p=0.018) more frequently compared to the atypical ARDS group. CONCLUSIONS: In this retrospective cohort study of 60 patients that required mechanical ventilation for COVID-19 induced ARDS between January 20, 2020, and April 30, 2020, in-hospital mortality was not significantly different between the atypical ARDS group and the classic ARDS group. However, the duration of mechanical ventilation, length of ICU and hospital stay was significantly shorter in the atypical ARDS group compared to the classic ARDS group. CLINICAL IMPLICATIONS: The difference in the duration of mechanical ventilation between the two groups may suggest a different pathophysiologic process and a need for a different approach to COVID-induced ARDS depending on lung compliance. DISCLOSURES: No relevant relationships by Mariam Charkviani, source=Web Response No relevant relationships by Chul Won Chung, source=Web Response No relevant relationships by Harvey Friedman, source=Web Response No relevant relationships by Jooseob Lee, source=Web Response No relevant relationships by Guillermo Rodriguez-Nava, source=Web Response No relevant relationships by Daniela Trelles Garcia, source=Web Response No relevant relationships by Maria Yanez-Bello, source=Web Response

EXPERIENCE WITH REMDESIVIR FOR THE TREATMENT OF CRITICAL COVID-19 IN A COMMUNITY-BASED HOSPITAL IN EVANSTON, ILLINOIS

TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: In late December 2019, a novel coronavirus named SARS-CoV-2 was discovered in Wuhan, China using deep unbiased sequencing in samples from patients with pneumonia. From its discovery, SARS-CoV-2 has caused global public health emergencies, economic crises, and innumerable deaths. To date, only corticosteroids have been proven to be effective in reducing mortality from COVID-19. From antiviral agents, remdesivir has been recently recognized as a promising therapy against COVID-19, but its mortality benefit is still a matter of controversy. In this study, we analyzed the effect of remdesivir on in-hospital death in our community hospital in the Chicago North Shore. METHODS: We retrospectively reviewed a de-identified dataset of 190 patients with COVID-19 admitted to a community hospital Intensive Care Unit (ICU) in Evanston, Illinois, from March 2020 to December 2020. Only molecularly confirmed COVID-19 cases defined by a positive result on a reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay or nucleic acid amplification test (NAAT) of a specimen collected on a nasopharyngeal swab were included. We performed a Cox proportional hazards model to analyze the effect of remdesivir on the hazard of in-hospital death in our patient population. To minimize confounders, age, qSOFA score, invasive mechanical ventilation, and other targeted COVID-19 therapies used at any given time (including corticosteroids, tocilizumab, hydroxychloroquine, colchicine, azithromycin, and atorvastatin) were forced as covariables into the model. For sensitivity analysis, we calculated the E value (with the lower confidence limit) for the obtained point estimate. The E value is defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the exposure and the outcome, conditional on the measured covariates, to explain away a specific exposure-outcome association fully. RESULTS: Between 190 patients admitted to the ICU, the median age was 69 years (IQR, 59 – 78 years), 125 (65.8%) were male, 62 (23.6 %) were White, and 84 (44.2%) were admitted from a long-term care facility. Of those patients, 143 (75.3) received corticosteroids, 67 (35.3%) received remdesivir, and 66 (34.7%) received both. Among survivors, 34/90 (37.8%) received remdesivir compared to 33/100 (33%) nonsurvivors. The Cox regression model showed decreased hazard of in-hospital death associated with the administration of remdesivir (Hazard Ratio [HR] 0.55;95% CI 0.29 – 0.94, p=.028). The E value for the point estimate was 3.04 and the E value for the lower confidence interval was 1.32, meaning that a confounder not included in the multivariable Cox regression model associated with remdesivir use and in-hospital mortality in patients with critical COVID-19 by a hazard ratio of 1.32-fold each could explain away the lower confidence limit, but weaker confounding could not. CONCLUSIONS: According to the data presented above, we concluded that in our patient population, the patients who did not receive remdesivir had a 65% chance of dying sooner compared to the ones who did receive remdesivir (when probability = HR/HR + 1). This could indicate a potential mortality benefit of remdesivir in critically ill patients. CLINICAL IMPLICATIONS: In our patient population, the use of remdesivir was associated with a slower progression to death in critically ill patients with COVID-19. DISCLOSURES: No relevant relationships by Chul Won Chung, source=Web Response No relevant relationships by Goar Egoryan, source=Web Response No relevant relationships by Harvey Friedman, source=Web Response No relevant relationships by Emre Ozcekirdek, source=Web Response No relevant relationships by Ece Ozen, source=Web Response No relevant relationships by Bidhya Poudel, source=Web Response No relevant relationships by Guillermo Rodriguez-Nava, source=Web Response No relevant relationships by Daniela Trelles Garcia, source=Web Response No relevant relationships by Maria Y nez-Bello, source=Web Response No relevant relationships by Qishuo Zhang, source=Web Response

The COVID-19 Fear Scale (FCV-19S): Psychometric properties and invariance of the measure in the Spanish version

The emergence of COVID-19 worldwide has had serious consequences for physical and psychological health. Spain is one of the countries that has been most-seriously affected by the pandemic. This study aims to evaluate the psycho- metric properties of the Spanish version of the COVID-19 fear scale (FCV-19S), assessing its structural validity, differential item functioning, and measurement invariance by gender and age.

Demographic attributes of COVID-19 patients in an Infectious Disease Center of Nigeria

AJOL Abstract: Background: As part of our contribution to the growing pool of knowledge on the prevention and control of the COVID-19 pandemic, this study describes the demographic features of patients with COVID-19 hospitalized at Infectious Disease Center (IDC), Olodo, Ibadan, Oyo State, Nigeria.Methodology: This was a descriptive cross-sectional study of COVID-19 patients whose data were collected during admission between April 27, 2020 and June 20, 2020. SARS-CoV-2 infection was diagnosed on nasopharyngeal specimen using a real-time reverse transcription-polymerase chain reaction (rRT-PCR) assay. Data were analysed using the Statistical Package for Social Sciences (SPSS Inc., USA) version 20.0Results: Among 131 patients, 58% were between age 18 and 35 years, 48.1% were employees of private establishments, and 64.1% were males. High proportion (84.3%) of the patients spent less than 14 days on admission. As at June 20, 2020, the overall COVID-19 mortality in the IDC was 0.0%.Conclusion: This study concluded that COVID-19 was common among male Nigerians, those working in private establishments, and those aged 18-35 years. Future researches on COVID-19 in Nigeria must put gender and age into consideration

Using machine learning for prediction of poor clinical outcomes in adult patients hospitalized with COVID-19

Background: As the ongoing COVID-19 pandemic develops, there is a need for prediction rules to guide clinical decisions. Previous reports have identified risk factors using statistical inference model. The primary goal of these models is to characterize the relationship between variables and outcomes, not to make predictions. In contrast, the primary purpose of machine learning is obtaining a model that can make repeatable predictions. The objective of this study is to develop decision rules tailored to our patient population to predict ICU admissions and death in patients with COVID-19. Methods: We used a de-identified dataset of hospitalized adults with COVID- 19 admitted to our community hospital between March 2020 and June 2020. We used a Random Forest algorithm to build the prediction models for ICU admissions and death. Random Forest is one of the most powerful machine learning algorithms;it leverages the power of multiple decision trees, randomly created, for making decisions. Results: 313 patients were included;237 patients were used to train each model, 26 were used for testing, and 50 for validation. A total of 16 variables, selected according to their availability in the Emergency Department, were fit into the models. For the survival model, the combination of age >57 years, the presence of altered mental status, procalcitonin ≥3.0 ng/mL, a respiratory rate >22, and a blood urea nitrogen >32 mg/dL resulted in a decision rule with an accuracy of 98.7% in the training model, 73.1% in the testing model, and 70% in the validation model (Table 1, Figure 1). For the ICU admission model, the combination of age < 82 years, a systolic blood pressure of ≤94 mm Hg, oxygen saturation of ≤93%, a lactate dehydrogenase >591 IU/L, and a lactic acid >1.5 mmol/L resulted in a decision rule with an accuracy of 99.6% in the training model, 80.8% in the testing model, and 82% in the validation model (Table 2, Figure 2). Conclusion: We created decision rules using machine learning to predict ICU admission or death in patients with COVID-19. Although there are variables previously described with statistical inference, these decision rules are customized to our patient population;furthermore, we can continue to train the models fitting more data with new patients to create even more accurate prediction rules. (Table Presented).

Characteristics and Outcomes of Heart Transplant Recipients with Coronavirus-19 Disease

Purpose Heart transplant(HT) recipients with SARS-CoV-2 infection may be at high risk of developing critical illness. The aim was to describe the characteristics and clinical outcomes of HT recipients with coronavirus-19 disease(COVID-19). Methods We prospectively included all adult HT recipients who received the diagnosis of COVID-19 in our institution. Inclusion criteria were one or more clinical symptoms of SARS-CoV-2 infection in the previous seven days and positive SARS-CoV-2 RT-PCR in nasopharyngeal samples. The enrollment was carried out from April to June, 2020. Demographic features, clinical characteristics, modes of transmission, laboratory data and other known prognosis markers at admission and through follow up were recorded. Patients were categorized according to the ordinal scale developed by WHO Committee. Outcomes and follow up were recorded until Aug/2020. Results Twenty-one HT recipients were included, most of them were men (57%);with median age of 48 years old and median HT time of 12 mo. The majority needed hospitalization. Immunosuppressive therapy was reduced or withdrawn in the majority of patients, except from steroids. Ten patients were classified as having severe disease according to WHO Committee scale. Lymphopenia was an independent predictor of severe disease and absolute lymphocyte count <416/mm3 had 82% of sensitivity and 90% of specificity to define severe disease. Thirty-day mortality was 14%, similar to previously reported in other solid-organ transplant (SOT) cohorts. However, a longer follow up revealed increased 60-day mortality (33%) due to nosocomial infection. Conclusion In this case series of HT recipients with COVID-19, the 30-day mortality rate was similar to that previously reported in SOT recipient's cohorts, but a longer follow up revealed increased later mortality related to long in-hospital stay. Further, lymphopenia was associated with severe disease and worse prognosis. These findings suggest the need for strict long-term follow up of these patients.

THE ANTI-INFECTIVE AND IMMUNOMODULATOR PARADOX: INCREASED RISK OF COINFECTION WITH HYDROXYCHLOROQUINE IN CRITICAL PATIENTS WITH COVID-19

SESSION TITLE: Late-breaking Abstract Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: Coronavirus disease 2019 (COVID-19) is a new entity that has rapidly spread globally, claiming thousands of lives. Hydroxychloroquine, an agent used to prevent malaria and to treat autoimmune disorders, was being administered to COVID-19 cases to slow or prevent the disease. However, its use was rushed without sufficient evidence on efficacy and safety. METHODS: We retrospectively reviewed a de-identified dataset of 98 patients with COVID-19 admitted to a community hospital Intensive Care Unit (ICU) in Cook County, Illinois, from March 2020 to May 2020. Only confirmed COVID-19 cases, defined by a positive result on a reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of a specimen collected on a nasopharyngeal swab were included. Co-infections were identified as the presence of positive blood cultures, sputum cultures, Legionella or pneumococcus urine antigen test, or respiratory viral panel. We performed a multivariable logistic regression analysis forcing variables that could be associated with increased risk of infection into the model, including central line placement, intubation, tocilizumab, intravenous steroids, colchicine, and hydroxychloroquine. RESULTS: Of 98 patients, the median age was 67 years (interquartile range, 57.75 – 74.25 years), 66 (67.3%) were males, 32 (32.7%) were Caucasian, and 56 (57.1%) were admitted from a Long-Term Care Facility (LTCF). 83.7% of the individuals had two or more comorbidities;the most frequent were hypertension (68.4%) and diabetes (51%). The most common targeted interventions included intravenous steroids (64.6%), azithromycin (42.9%), and hydroxychloroquine (34.7%). Among the group treated with hydroxychloroquine, 16 (47.1%) patients were found to have co-infections compared to 13 (20.3%) patients not treated with hydroxychloroquine (p=.006). The multivariable logistic regression showed increased odds of co-infection associated with the administration of hydroxychloroquine (odds ratio [OR] 4.04;95% CI 1.37 – 11.98, p=.012;Hosmer and Lemeshow goodness-of-fit test p=.724) and central line placement (OR 7.27;95% CI 1.93 – 27.31;p=.003). CONCLUSIONS: In this retrospective analysis of 98 adults with COVID-19 hospitalized in a community ICU, the patients who received hydroxychloroquine were found to have increased risk of co-infections. CLINICAL IMPLICATIONS: Hydroxychloroquine may increase the risk of co-infections in critical COVID-19 patients DISCLOSURES: No relevant relationships by Daniel Bustamante-Soliz, source=Web Response No relevant relationships by Chul Won Chung, source=Web Response No relevant relationships by Harvey Friedman, source=Web Response No relevant relationships by Elizabeth Patino, source=Web Response No relevant relationships by Guillermo Rodriguez-Nava, source=Web Response No relevant relationships by Daniela Trelles Garcia, source=Web Response No relevant relationships by Valeria Trelles Garcia, source=Web Response No relevant relationships by Maria Yanez-Bello, source=Web Response