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SESSION TITLE: Using Imaging for Diagnosis Case Posters SESSION TYPE: Case Report Posters PRESENTED ON: 10/19/2022 12:45 pm - 01:45 pm INTRODUCTION: Point of care ultrasonography (POCUS) uses an ultrasound technique that helps physicians augment physical examination findings and guide clinical decision-making at the bedside. We present a case that became a watershed moment for internal medicine residents at Abington Jefferson Hospital to use POCUS for every patient with atrial flutter/fibrillation with RVR prior to initiating diltiazem drip. CASE PRESENTATION: A 73-year-old male presented to the emergency department with complaints of palpitations. He was tachycardic with a heart rate in the 150s, and his rhythm was irregular. His basic labs were normal;an electrocardiogram investigation showed that he was experiencing an atrial flutter with 2:1 and 3:1 blocks. Chest X-ray was clear. He was given IV metoprolol 10 mg twice without achieving rate control and then started on a diltiazem drip, which initially improved his heart rate to 70s with rhythm changing to atrial flutter with 4:1 block. However, he started to become hypoxic, requiring intubation and then hemodynamically unstable, requiring initiation of pressors. Postintubation CXR indicated bilateral diffuse pulmonary edema and vascular congestion. Subsequently, he had Pulseless electrical activity (PEA) arrest. Return of spontaneous circulation (ROSC) was achieved after 3 minutes of chest compression and one round of epinephrine injection. Transthoracic echocardiogram showed an ejection fraction of 10%. He had a right heart catheterization which showed a CI of 1.7 and elevated PCWP and RVP. He was started on milrinone for ionotropic support and needed norepinephrine, vasopressin and phenylephrine to sustain his blood pressure. DISCUSSION: Atrial flutter and fibrillation are routinely seen arrhythmias in hospital settings. Patients with irregular rhythm who are in rapid ventricular rate and normotensive are often given IV metoprolol few times and then started on a diltiazem drip if RVR continues. Diltiazem not only decreases heart rate (negative chronotropic) but also decreases ventricular squeeze (negative ionotropic). It is contraindicated in patients with reduced ejection fraction. Patients’ ejection fraction values are not always known, especially if they have never had a transthoracic echocardiogram in the past or prior records are not available. POCUS helps physicians and residents to access and estimate LV function quickly and augments clinical decision making at the bedside. CONCLUSIONS: Internal Medicine Residents at Abington Hospital have made it a part of their protocol to always perform bedside ultrasonography in patients with atrial flutter/fibrillation with rapid ventricular rate before initiating diltiazem drip to prevent further avoidable cardiogenic shocks. Reference #1: Fey H, Jost M, Geise AT, Bertsch T, Christ M. Kardiogener Schock nach bradykardisierender Therapie bei tachykardem Vorhofflimmern : Fallvorstellung einer 89-jährigen Patientin [Cardiogenic shock after drug therapy for atrial fibrillation with tachycardia : Case report of an 89-year-old woman]. Med Klin Intensivmed Notfmed. 2016 Jun;111(5):458-62. German. doi: 10.1007/s00063-015-0089-9. Epub 2015 Oct 6. PMID: 26440099. Reference #2: Bitar ZI, Shamsah M, Bamasood OM, Maadarani OS, Alfoudri H. Point-of-Care Ultrasound for COVID-19 Pneumonia Patients in the ICU. J Cardiovasc Imaging. 2021 Jan;29(1):60-68. doi: 10.4250/jcvi.2020.0138. PMID: 33511802;PMCID: PMC7847790. Reference #3: Murray A, Hutchison H, Popil M, Krebs W. The Use of Point-of-Care Ultrasound to Accurately Measure Cardiac Output in Flight. Air Med J. 2020 May-Jun;39(3):218-220. doi: 10.1016/j.amj.2019.12.008. Epub 2020 Jan 14. PMID: 32540116. DISCLOSURES: No relevant relationships by Fnu Aisha No relevant relationships by Lucy Checchio No relevant relationships by Ans Dastgir No relevant relationships by Shravya Ginnaram No relevant relationships by Syeda Hassan No relevant relationships by Chaitra Janga No relev nt relationships by Rameesha Mehreen No relevant relationships by Rahat Ahmed Memon No relevant relationships by Binod Poudel No relevant relationships by Shreeja Shah
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Background: There are various COVID-19 vaccines launched in different parts of the world. As the vaccination drive is increasing, the reports of adverse events following immunization (AEFI) are increasingly reported. Therefore, this research aims to document the adverse events and their determinants following COVID-19 vaccination.
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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.
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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
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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
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Background: A few COVID-19 related retrospective studies have established that older age, elevated neutrophil-lymphocyte ratio (NLR), and decreased lymphocyte-CRP ratio (LCR) were associated with worse outcome. Herein, we aim to identify new prognostic markers associated with mortality. Methods: We conducted a retrospective hospital cohort study on patients ≥ 18 years old with confirmed COVID-19, who were admitted to our hospital between 03/15/2020 and 05/25/2020. Study individuals were recruited if they had a complete CBC profile and inflammatory markers such as CRP, ferritin, D-dimer and LDH, as well as a well-defined clinical outcomes (discharged alive or expired). Demographic, clinical and laboratory data were reviewed and retrieved. Univariate and multivariate logistic regression methods were employed to identify prognostic markers associated with mortality. Results: Out of the 344 confirmed COVID-19 hospitalized patients during the study period, 31 who did not have a complete blood profile were excluded;303 patients were included in the study, 89 (29%) expired, and 214 (71%) were discharged alive. Demographic analysis was tabulated in Table 1. The univariate analysis showed a significant association of death with absolute neutrophil count (ANC, p=0.022), NLR (p=002), neutrophil-monocyte ratio (NMR, p=< 0.0001), LCR (p=0.007), lymphocyte-LDH ratio (LLR, p=< 0.0001), lymphocyte- D-dimer ratio (LDR, p=< 0.0001), lymphocyte-ferritin ratio (LFR, p=< 0.0001), and platelets (p=0.037) with mortality. With multivariable logistic regression analysis, the only values that had an odds of survival were high LDR (odds ratio [OR] 1.763;95% confidence interval [CI], 1.20-2.69), and a high LFR (OR 1.136, CI 1.01-1.34). We further build up a model which can predict >85% mortality in our cohorts with the utilization of D-dimer (>500 ng/ml), Ferritin (>200 ng/ml), LDR (< 1.6), LFR (< 4) and ANC (>2.5). This new model has a ROC of 0.68 (p< 0.0001). Conclusion: This retrospective cohort study of hospitalized patients with COVID-19 suggests LDR and LFR as potential independent prognostic indicators. A new model with combination of D-dimer, Ferritin, LDR, LFR and ANC, was able to predict >85% mortality in our cohort with ROC of 0.68, it will need to be validated in a prospective cohort study. (Table Presented).