The emergence of the novel coronavirus, SARS-CoV-2, and its associated clinical syndrome, COVID-19, resulted in the largest global pandemic since the 1918 influenza. While widespread in the general population, to date, there are few reports of COVID-19 in solid organ transplant (SOT) recipients. 1-5 Herein, we report a case of COVID-19 infection in the early postoperative period following lung transplantation (LT). A 68 year-old white female with idiopathic pulmonary fibrosis, gastroesophageal reflux disease, hyperlipidemia, and psoriasis was listed for bilateral LT with a lung allocation score of 31.8784. At admission for transplant, the patient reported feeling well without symptoms of acute respiratory infection. Vital signs included temperature, 37.1°C; heart rate, 78 beats per minute; blood pressure, 124/83 mm Hg; and oxygen saturation, 94% on 3 L/min oxygen. The donor, a 30 year-old female with a history of hypertension and inflammatory bowel disease treated with a tumor necrosis factor inhibitor presented to the hospital with severe headache, confusion, and vomiting. There was no history of fever or respiratory symptoms. She was intubated, and head CT revealed a large intracerebral hemorrhage. Due to poor neurologic prognosis, her family elected to pursue organ donation following cardiac death. Chest CT demonstrated "focal areas of consolidation in the bilateral dependent lower lobes with adjacent tree-in-bud opacities most consistent with pneumonia, possibly secondary to aspiration" (Figure 1A). Bronchoscopic examination identified erythematous mucosa of the trachea and main carina with purulent secretions in all lobes. Bronchoalveolar lavage (BAL) culture resulted in normal upper respiratory flora. No viral testing was performed, and no confirmed COVID-19 cases had been reported in the county of the donor hospital. p a O 2 on the last challenge arterial blood gas prior to procurement was 482 mm Hg.
Background GAS can cause severe postpartum infections and may be transmitted from colonized healthcare workers (HCWs). Methods Two cases of GAS bacteremia following vaginal delivery were identified on the L&D unit June-July 2019 (Cluster 1), prompting a carrier-disseminator investigation. Two additional cases were identified September-October 2019 (Cluster 2), followed by an additional 3 cases late October 2019, all of whom delivered on the same night (Cluster 3). All patients and HCWs were evaluated for GAS risk factors and screened for colonization via throat, vaginal and perirectal cultures. During Clusters 1 and 2, only HCWs with patient contact were screened, but this was expanded to the entire unit in October after Cluster 3 was identified. All GAS colonized HCWs were provided chemoprophylaxis and rescreened 7-10 days after treatment to ensure eradication. GAS isolates from patients and HCWs were analyzed by whole genome sequencing (WGS). Results During Cluster 1 a total of 43 HCWs were screened and HCWA was colonized at all three sites. In Cluster 2, nine HCWs were screened; HCWA was negative at that time but HCWB was colonized in the throat only. Patient 3 was confirmed to be community acquired by pulsed-field gel electrophoresis, patient 4 was closely related by WGS. A new policy was instituted that required all HCWs present at delivery to wear gowns, gloves, masks, eye protection, and to undergo infection prevention education and practice review. Following Cluster 3, all HCWs on the unit were screened (681 total). HCWA was again positive at all 3 sites and two additional HCWs were found to be colonized with the outbreak strain on throat swab only. Isolates from patients 1, 2, 4, 5, 6, 7 and the 4 HCWs were identified as subtype emm 28 and all closely related by WGS (figure 1). A household contact of HCWA was colonized with the outbreak strain as well. Figure 1 Conclusion A carrier-disseminator investigation identified clusters of nosocomial postpartum GAS infections involving 6 patients, 4 HCWs and a HCW household contact that were highly related based on WGS. The outbreak strain of GAS was likely spread amongst HCWs via ping pong transmission on the unit. Transmission to patients was halted with implementation of strict infection prevention measures and mass screening and chemoprophylaxis of all colonized HCWs. Disclosures All Authors: No reported disclosures
Background: The Ohio State University Wexner Medical Center identified a cluster of coronavirus disease 2019 (COVID-19) cases on an inpatient geriatric stroke care unit involving both patients and staff. The period of suspected severe acute respiratory coronavirus virus 2 (SARS-CoV-2) transmission and exposure on the unit was December 20, 2020, to January 1, 2021, with some patients and staff developing symptoms and testing positive within the 14 days thereafter. Methods: An epidemiologic investigation was conducted via chart review, staff interviews, and contact tracing to identify potential patient and staff linkages. All staff who worked on the unit were offered testing regardless of the presence of symptoms as well as all patients admitted during the outbreak period. Results: In total, 6 patients likely acquired COVID-19 in the hospital (HCA). An additional 6 patients admitted to the unit during the outbreak period subsequently tested positive but had other possible exposures outside the hospital (Fig. 1). One patient failed to undergo COVID-19 testing on admission but tested positive early in the cluster and is suspected to have contributed to patient to employee transmission. Moreover, 32 employees who worked on the unit in some capacity during this period tested positive, many of whom became symptomatic during their shifts. In addition, 18 employees elected for asymptomatic testing with 3 testing positive; these were included in the total. Some staff also identified potential community exposures. Additionally, staff reported an employee who was working while symptomatic with inconsistent mask use (index employee) early in the outbreak period. The index employee likely contributed to employee transmission but had no direct patient contact. Our epidemiologic investigation ultimately identified 12 employees felt to be linked to transmission based on significant, direct patient care provided to the patients within the outbreak period (Fig. 1). In addition, 3 employees had an exposure outside the hospital indicating likely community transmission. Conclusions: Transmission was felt to be multidirectional and included employee-to-employee, employee-to-patient, and patient-to-employee transmission in the setting of widespread community transmission. Interventions to stop transmission included widespread staff testing, staff auditing regarding temperature and symptom monitoring, and re-education on infection prevention practices. Particular focus was placed on appropriate PPE use including masking and eye protection, hand hygiene, and cleaning and disinfection practices throughout the unit. SARS-CoV-2 admission testing and limited visitation remain important strategies to minimize transmission in the hospital.Funding: NoDisclosures: None
Background: An increase in candidemia has been observed throughout the world since the start of the COVID-19 pandemic. Patients with COVID-19 may have different risk factors, clinical presentations, and outcomes compared to patients without COVID-19. Methods: We conducted a retrospective chart review of all inpatients with candidemia at a large, academic medical center from April 30, 2019, to February 19, 2021. The first case of COVID-19 was detected at our institution March 2020 and patients were sorted into pre– versus post–COVID-19 pandemic groups. Data regarding clinical characteristics, risk factors, and outcomes were collected. The rate of candidemia per 10,000 patient days was calculated from January 2013 through February 2021. Results: In total, 202 patients were identified with candidemia: 92 cases were identified before the pandemic and 110 cases were identified after the pandemic began. Moreover, 33 (16.3%) patients were diagnosed with COVID-19 during the admission and 169 (83.7%) did not have COVID-19. Patients with COVID-19 were significantly more likely to be older (median, 64.5 vs 54.8 years; P = .0006) and to have a higher body mass index (32.8 vs 29.1; P = .03) than patients without COVID-19. Patients with COVID-19 were less likely have some of the traditional risk factors (eg, abdominal surgery, total parenteral nutrition, history of injecting drugs) for candidemia compared to patients without COVID-19. Patients with COVID-19 were significantly more likely to require ICU care (97.0% vs 67.5%; P < .001) and to require mechanical ventilation (90.9% vs 53.9%; P < .001), and they had higher mortality at 30 days (66.7% vs 31.4%; P < .001). A multivariate logistic regression model showed that COVID-19 (OR, 2.53; 95% CI, 1.09–5.90) and higher age (OR 1.45, 95% CI, 1.11–1.91) were significant predictors of 30 day mortality. Using a Poisson regression model, the incidence rate ratio for candidemia per month after the start of the COVID-19 pandemic was 2.09 (95% CI, 1.85–2.36; P < .0001) compared to the years prior. Conclusions: Rates of candidemia significantly increased after the start of the COVID-19 pandemic. Patients with candidemia in the post–COVID-19 era tend to have nontraditional risk factors, to be more critically ill, and to have increased mortality compared to patients in the pre–COVID-19 era. COVID-19 and higher age were independent predictors of mortality. More studies are needed to further define risk factors for candidemia in patients with COVID-19.Funding: NoneDisclosures: None
BackgroundOpioid dependence and overdose are at epidemic levels in the United States. Ohio has the third highest rate of opioid-related overdose deaths. Infectious complications of intravenous drug use (IDU) include increased acquisition of hepatitis C, HIV and infective endocarditis. In this study, we aimed to characterize cases of infective endocarditis admitted to our healthcare system over a five-year period. We additionally sought to determine the validity of using ICD codes to identify infective endocarditis cases and IDU.MethodsPatients with ICD-9 or 10 discharge diagnosis codes for infective endocarditis were identified from our institution’s electronic health record. ICD codes pertaining to substance abuse were used to classify patients according to IDU status. Readmissions during the same episode of infective endocarditis were excluded. We compared chart review to ICD code for the identification of infective endocarditis and IDU in a random sample of 296 of 1590 cases.ResultsOf 296 charts reviewed, 133 (44.9%) were excluded because they did not meet criteria for definite infective endocarditis by modified Duke’s criteria or because the episode was a readmission. A total of 163 (55.1%) cases met inclusion criteria, all of whom were seen in consultation by the inpatient Infectious Disease service. Of these, 52 (31.9%) had ICD 9 or 10 codes linked to substance abuse. Following manual chart review, we established that in fact 86 of these 163 cases (52.8%) had evidence of substance abuse.ConclusionMisclassification due to use of ICD codes is a well-established challenge to epidemiological research. However, the extent of misclassification in this analysis was greater than expected. If prior research on IDU and infective endocarditis has relied on medical record data alone without verification through manual chart review, the observed epidemiological trends may not be accurate.Disclosures All authors: No reported disclosures.
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