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SESSION TITLE: Outcomes Across COVID-19 SESSION TYPE: Rapid Fire Original Inv PRESENTED ON: 10/19/2022 11:15 am - 12:15 pm PURPOSE: The ROX index (Respiratory rate - OXygenation), obtained by the calculation of SpO2/FiO2/respiratory rate (RR), is a tool previously found to predict intubation in patients with acute hypoxic respiratory failure (AHRF). There is variation in the time intervals described from HFNC to ROX index assessment as well as the cutoff value. This study investigates the role of the ROX index from 12 to 72 hours after HFNC initiation to predict intubation or death while on HFNC in patients with COVID-19 AHRF. METHODS: Adult patients (18 years or older) with confirmed nasopharyngeal PCR SARS-CoV-2 infection who received HFNC therapy between March 1 and July 15, 2020, at Monmouth Medical Center were included. 52 patients were available for analysis. Patients were divided into two groups: those able to be weaned to traditional nasal cannula (group one) and those who were intubated or died while on HFNC (group two). RESULTS: Of the 52 patients evaluated, 28 (54%) required intubation or died while on HFNC (Group two). Group two mortality was 53.85% and overall mortality was 42.31%. A Kaplan-Meier analysis comparing patients whose ROX remained above 4.67 (Group A) with those with ROX <= 4.67 (Group B) within the first 12 hours showed that patients in Group B had a significantly shorter time to the event than those in Group A. CONCLUSIONS: Generally, higher ROX index values are associated with a lower risk of intubation on HFNC in AHRF. In this patient sample, any ROX index less than 4.67 at 12 hours or less than 4.04 at 24 hours was associated with an increased risk of eventual intubation or death while on HFNC. Thus, a low or decreasing ROX index may prompt more frequent reassessment and, if accompanied by other evidence of deterioration, may trigger an escalation of care. CLINICAL IMPLICATIONS: This study shows that the ROX index can stratify patients into low or higher risk for deterioration on HFNC among patients with COVID-19 AHRF. This could help optimize the use of critical care services, minimize PPE use, and promote safety for patients and healthcare workers. Future studies may include prospective analysis of the ROX index and exploration of modalities for monitoring patients receiving non-invasive ventilation. DISCLOSURES: No relevant relationships by Reem alhashemi no disclosure on file for Alvin Buemio;No relevant relationships by Kenneth Granet No relevant relationships by Ikwinder Preet Kaur No relevant relationships by Violet Kramer No relevant relationships by Mohsin Mughal No relevant relationships by Chandler Patton
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Background: While a common phenomenon in other viral illnesses, data regarding coinfection/superinfections in Coronavirus Disease 2019 (COVID-19) is limited and emerging. Superinfections may contribute to the overall high mortality in those suffering from severe COVID19. We aimed to study the rate of coinfections and secondary bacterial/fungal infections among SARS-CoV-2 positive cases in a community hospital. Methods: This is a single-centre IRB approved, retrospective observational study. Adult patients with laboratory-confirmed SARS-CoV-2 by Real-Time Reverse Transcriptase-Polymerase Chain Reaction assay of nasopharyngeal swabs admitted from March 1st to April 20th 2020 were included. Relevant clinical and laboratory data were manually collected from electronic medical records. Results: A total of 129 patients were included in the study. 91 patients had a respiratory pathogen panel PCR on admission. This panel includes testing for influenza, parainfluenza virus, respiratory syncytial virus, coronavirus, adenovirus, rhinovirus, Bordetella pertussis, Bordetella parapertussis, Chlamydophila pneumoniae, and Mycoplasma pneumoniae. Only one patient was positive for coinfection with the parainfluenza virus. None of them was found to be positive for bacterial coinfection at admission. Thirteen patients (10.1%) had secondary bacterial or fungal infections that developed during their respective hospital stays, 12 of them were critically ill. The mean duration from admission to the onset of secondary infection was 13 days. Positive Blood Cultures Positive Lower Respiratory Tract Cultures Conclusion: Our data revealed that the rate of viral coinfection was 1.1 % and bacterial coinfection was 0% at admission. Study timing can play a role as upper respiratory virus infection rate is low in the population during March and April. Secondary infections were found to be common in patients admitted to the ICU. Potential explanations for this include compromised immunity in severely ill patients, extended ICU stay, central venous catheters and endotracheal intubation. It is evident that with severe COVID-19 illness, an extended hospital course often ensues, leading to increased risk of secondary infections and contributing to the overall high mortality of these patients.
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SESSION TITLE: Lessons from the ICU: What have We Learned about the Management of COVID-19 SESSION TYPE: Original Investigations PRESENTED ON: October 18-21, 2020 PURPOSE: A high mortality rate (up to 97%) has been observed in intubated Coronavirus Disease 2019 (COVID-19) patients;advanced age, high SOFA score, and elevated inflammatory markers are common risk factors. Data are scarce regarding the predictors of successful extubation in these patients. The purpose of our study is to compare inflammatory markers including lactate dehydrogenase (LDH), ferritin, D-dimer, interleukin-6 levels (IL-6) in successfully extubated patients with the non-survivors. Patients 65 years or older were excluded. Puja Mehta et al. suggested that patients with severe COVID-19 have cytokine storm syndrome associated with poor prognosis. The clinical judgement regarding successful extubation in COVID-19 patients is still evolving. We hypothesized that the successfully extubated patients would have lower levels of inflammatory markers. METHODS: This is a single-centre, retrospective observational study approved by the institutional review board (IRB). SARS-CoV-2 confirmed intubated patients (n=12) with age <65 years were included. Data were manually extracted from electronic medical records. We compared patients who were successfully extubated (Group A) and those who died (Group B). Group A had six male patients, while group B had six patients with a male to female ratio of 2:1. To investigate the association of inflammatory markers with successful extubation, statistical analysis was performed using the Wilcoxon two-sample test. RESULTS: Mean values of LDH max, ferritin max, D-dimer max during hospitalization, and IL-6 level on admission in group A were 793 IU/L, 1266.8 ng/ml, 3.6 FEU, and 69.37 pg/ml respectively. Mean values of LDH max, ferritin max, D-dimer max during the hospitalization, and IL-6 level on admission in group B were 1693.8, 6136.6, 4.2, and 10606.86 respectively. Group B had higher mean values as compared to group A. The mean values of ferritin max and IL-6 on admission showed a statistically significant difference in both groups ( p-values 0.008, 0.03 respectively). However, the difference in mean values of LDH max and D-dimer max (p-value 0.17, 0.45 respectively) were not significant. CONCLUSIONS: Higher values of inflammatory markers were seen in COVID-19 patients who died as compared to patients who successfully got extubated. Our data indicate that patients who were successfully weaned off the invasive mechanical ventilation had lower levels of ferritin and IL-6 as compared to patients who died. However, statistical significance could not be established for LDH and D-dimer. Limitations of our study include small sample size and single-centre data. CLINICAL IMPLICATIONS: Higher mean values of inflammatory markers (ferritin and IL-6) can correlate with the severity of the illness and failed extubation. Replicative studies with larger sample size will define the clinical impact of our findings. DISCLOSURES: No relevant relationships by Denise Lauren Dalmacion, source=Web Response No relevant relationships by Kenneth Granet, source=Web Response No relevant relationships by Ali Jaffery, source=Web Response No relevant relationships by Ikwinder Preet Kaur, source=Web Response No relevant relationships by Violet Kramer, source=Web Response No relevant relationships by Mohsin Mughal, source=Web Response No relevant relationships by Chandler Patton, source=Web Response