Background: The COVID-19 pandemic has disproportionately affected nursing home residents, and emerging evidence suggests quality, location, resident demographics, and staffing levels may be related to COVID-19 incidence within facilities. We describe the distribution of COVID-19 cases in Wisconsin nursing homes from January 2020 to October 2020, the effect of rural versus urban locations on COVID-19 incidence, and the temporal changes in COVID-19 incidence. Methods: We constructed a database using the Center for Medicaid and Medicare Services’ (CMS) publicly available data. Variables obtained per facility included location, number of beds, ownership type, average census, 5-star ratings (overall, quality, health, staffing, and nurse staffing categories), number of COVID-19 cases, resident Medicaid/Medicare share, area deprivation index, and social vulnerability index. Nursing homes were divided into tertiles based on total COVID-19 cases for descriptive analysis (zero cases, 1–7 cases, >7 cases). Demographic and clinical variables were reported as frequencies, mean (standard deviation) or median (interquartile range). We compared groups using the Pearson χ2 test and the Kruskal-Wallis test. COVID-19 incidence rates were calculated by dividing the number of COVID-19 cases by monthly occupied bed days and multiplied by 10,000. Results: From January 1, 2020, to November 1, 2020, in total, 3,133 SARS-CoV-2–confirmed cases were reported among 248 (70.5%) nursing homes. Urban location (P = .027), overall 5-star rating (P = .035), number of beds (p < 0.001), and average count of residents per day (p < 0.001) were associated with a greater number of COVID-19 cases. Temporal analysis showed that the highest incidence rates of COVID-19 in NHs were observed from January to May and in October 2020 (11.36 and 30.33 cases per 10,000 occupied-bed days, respectively). Urban NHs experienced higher incidence rates until September, then incidence rates among rural facilities surged (Fig.1A). In the first half of the year, NHs with lower quality scores (1-3 stars) had a higher COVID-19 incidence rate; however, in August this trend reversed, and facilities with higher quality scores (4-5 stars) showed the highest incidence rates (Fig.1B). Fig. 2 shows a temporal depiction of the shift from urban to rural settings. Conclusions: Higher COVID-19 incidence rates during the first 5 months of the pandemic were observed in urban, larger facilities with lower 5-star rating. By the end of the year, nursing homes in rural areas and those with higher quality ratings had the highest incidence rates.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Background: Healthcare-associated transmission of influenza leads to significant morbidity, mortality, and cost. Most studies classify healthcare-associated viral respiratory infections (HA-VRI) as those with a positive test result after the first 3 days following admission, which does not account for healthcare exposures prior to admission. Utilizing an expanded definition of healthcare-associated influenza, we aimed to improve the estimates of disease prevalence on a population level. Methods: This study included laboratory-confirmed cases of influenza in adult and pediatric patients admitted to any acute-care hospital in a catchment area of 8 counties Tennessee identified between October 1, 2012, and April 30, 2019. Surveillance information was abstracted from hospital and state laboratory databases, hospital infection control practitioner databases, reportable condition databases, and electronic health records as a part of the Influenza Hospitalization Surveillance Network (FluSurv-NET) by the Centers for Disease Control and Prevention (CDC) Emerging Infections Program (EIP). Cases were defined as healthcare-associated influenza laboratory confirmation of infection occurred (1) on or after hospital day 4 (“traditional definition”), or (2) between hospital days 0 and 3 in patients transferred from a chronic care facility or with a recent discharge from another acute-care facility in the 7 days preceding the current index admission (ie, enhanced definition). The proportion of laboratory-confirmed influenza designated as HA-VRI using both the traditional definition as well as with the added enhanced definition were compared. Data were imported into Stata software for analysis. Results: We identified 5,904 cases of laboratory-confirmed influenza in hospitalized patients over the study period. Using the traditional definition for HA-VRI, only 147 (2.5%, seasonal range 1.3%–3.4%) were deemed healthcare associated (Figure 1). Adding the cases identified using the enhanced definition, an additional 317 (5.4%, range 2.3%–6.7%) cases were noted in patients transferred from a chronic care facility for the current acute-care admission and 336 cases (5.7%; range, 4.1%–7.4%) were noted in patients with a prior acute-care facility admission in the preceding 7 days. Using our expanded definition, the total proportion of healthcare-associated influenza in this cohort was 772 of 5,904 (13.1%; range, 10.6%–14.8%). Conclusion: HA-VRI due to influenza is an underrecognized infection in hospitalized patients. Limiting surveillance assessment of this important outcome to just those patients with a positive influenza test after hospital day 3 captured only 19% of possible healthcare-associated influenza infections across 7 influenza seasons. These results suggest that the traditionally used definitions of healthcare-associated influenza underestimate the true burden of cases.

Funding: No

Disclosures: None

Figure 1.

Background: Antibiotics are frequently prescribed in nursing homes, often inappropriately. Data sources are needed to facilitate measurement and reporting of antibiotic use to inform antibiotic stewardship efforts. Previous analyses have shown that the type of nursing-home stay, that is, short stay (<100 days), is a strong predictor of high antibiotic use compared to longer nursing-home stays. The study objective was to compare 2 different data sources, electronic health record (EHR) and long-term care (LTC) pharmacy data, for surveillance of antibiotic use and type of nursing-home stay. Methods: EHR and pharmacy data during 2017 were included from 1,933 and 1,348 US-based nursing homes, respectively. We compared data elements available in each data source for antibiotic use reporting. In each data set, we attempted to describe antibiotic use as the proportion of residents on an antibiotic, days-of-therapy (DOT) per 1,000 resident days (RD), and distribution of antibiotic course duration, overall and at the facility level. Facility proportion of short-stay and long-stay (>100 days) nursing-home residents were calculated using admission dates and census data in the EHR data set and a payor variable in the pharmacy data set (Figure 1). The 2 data sources also provided antibiotic characteristics, including antibiotic class, agent, and route of administration. The deidentified nature of facility data prevented direct comparison of antibiotic use measures between facilities. Results: The EHR and pharmacy data sets contained 381,382 and 326,713 residents, respectively (Table 1). Within the EHR, 51% of residents were prescribed an antibiotic in 2017, at a median rate of 77 DOT per 1,000 RD. In the LTC pharmacy, 46% of residents were prescribed an antibiotic at a median rate of 79 DOT per 1,000 RD (Table 1). Short-stay residents contributed a smaller proportion of total RDs in the EHR relative to the pharmacy cohort (21% vs 50%, respectively). Conclusions: Nursing-home antibiotic use data obtained from EHR and pharmacy vendors can be used for calculating antibiotic use measures, which is important for antibiotic use reporting and facility-level tracking to identify opportunities for improving prescribing practices and provide facility-level benchmarks. Further validation of both data sources in the same facilities is needed to compare antibiotic use rates and to determine the most appropriate proxy for type of nursing-home stay for facility-level risk adjustment of antibiotic use rates.

Funding: No

Disclosures: None

Figure 1.

Table 1.

Background: Evidence-based hospital antimicrobial stewardship interventions, such as postprescription review with feedback, prior authorization, and handshake stewardship, involve communication between stewards and frontline prescribers. Hierarchy, asymmetric responsibility, prescribing etiquette, and autonomy can obstruct high-quality communication in stewardship. Little is known about the strategies that stewards use to overcome these barriers. The objective of this study was to identify how stewards navigate communication challenges when interacting with prescribers. Methods: We conducted semistructured interviews with antimicrobial stewards recruited from hospitals across the United States. Interviews were audio recorded, transcribed, and analyzed using a flexible coding approach and the framework method. Social identity theory and role theory were used to interpret framework matrices. Results: Interviews were conducted with 58 antimicrobial stewards (25 physicians and 33 pharmacists) from 10 hospitals (4 academic medical centers, 4 community hospitals, and 2 children’s hospitals). Respondents who felt empowered in their interactions with prescribers explicitly adopted a social identity that conceptualized stewards and prescribers as being on the “same team” with shared goals (in-group orientation). Drawing on the meaning conferred via this social role identity, respondents engaged in communication strategies to build and maintain common bonds with prescribers. These strategies included moderating language to minimize defensive recommendations when delivering stewardship recommendations, aligning the goals of stewardship with the goals of the clinical team, communicating with prescribers about things other than stewardship, compromising for the sake of future interactions, and engaging in strategic face-to-face interaction. Respondents who felt less empowered in their interactions thought of themselves as outsiders to the clinical team and experienced a heightened sense of “us versus them” mentality with the perception that stewards primarily serve a gate-keeping function (ie, outgroup orientation). These respondents expressed deference to hierarchy, a reluctance to engage in face-to-face interaction, a feeling of cynicism about the impact of stewardship, and a sense of low professional accomplishment within the role. Respondents who exhibited an in-group orientation were more likely than those who did not to describe the positive impact of stewardship mentors or colleagues on their social role identity. Conclusions: The way antimicrobial stewards perceive their role and identity within the social context of their healthcare organization influences how they approach communication with prescribers. Social role identity in stewardship is shaped by the influence of mentors and colleagues, indicating the importance of supportive relationships for the development of steward skill and confidence.

Funding: No

Disclosures: None

Background: Urine cultures are the most common microbiological tests in the outpatient setting and heavily influence treatment of suspected urinary tract infections (UTIs). Antibiotics for UTI are usually prescribed on an empiric basis in primary care before the urine culture results are available. However, culture results may be needed to confirm a UTI diagnosis and to verify that the correct antibiotic was prescribed. Although urine cultures are considered as the gold standard for diagnosis of UTI, cultures can easily become contaminated during collection. We determined the prevalence, predictors, and antibiotic use associated with contaminated urine cultures in 2 adult safety net primary care clinics. Methods: We conducted a retrospective chart review of visits with provider-suspected UTI in which a urine culture was ordered (November 2018–March 2020). Patient demographics, culture results, and prescription orders were captured for each visit. Culture results were defined as no culture growth, contaminated (ie, mixed flora, non-uropathogens, or ≥3 bacteria isolated on culture), low-count positive (growth between 100 and 100,000 CFU/mL), and high-count positive (>100,000 CFU/mL). A multivariable multinomial logistic regression model was used to identify factors associated with contaminated culture results. Results: There were 1,265 visits with urine cultures: 264 (20.9%) had no growth, 694 (54.9%) were contaminated, 159 (12.6%) were low counts, and 148 (11.7%) were high counts. Encounter-level factors are presented in Table 1. Female gender (adjusted odds ratio [aOR], 15.8; 95% confidence interval [CI], 10.21–23.46; P < .001), pregnancy (aOR, 13.98; 95% CI, 7.93–4.67; P < .001), and obesity (aOR, 1.9; 95% CI 1.31–2.77; P < .001) were independently associated with contaminated cultures. Of 264 patients whose urine cultures showed no growth, 36 (14%) were prescribed an antibiotic. Of 694 patients with contaminated cultures, 153 (22%) were prescribed an antibiotic (Figure 1). Conclusions: More than half of urine cultures were contaminated, and 1 in 5 patients were treated with antibiotics. Reduction of contamination should improve patient care by providing a more accurate record of the organism in the urine (if any) and its susceptibilities, which are relevant to managing future episodes of UTI in that patient. Optimizing urine collection represents a diagnostic stewardship opportunity in primary care.

Funding: This study was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (grant no. UM1AI104681). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Disclosures: None

Table 1.

Figure 1.

Background: Adherence to core elements of antimicrobial stewardship programs (ASPs) is increasing nationally but the robustness of programs and inclusion of pediatrics is poorly understood. We describe the details of ASP in Colorado hospitals and identify steps by which academic centers and public health departments can assist community ASPs. Methods: We invited ASP leaders at the 102 acute-care hospitals (ACHs) and critical-access hospitals (CAHs) in Colorado to participate in a web-based survey regarding their ASPs. Questions related to adherence to Centers for Disease Control and Prevention (CDC) core elements, barriers to improvement, desired resources, and extension to pediatrics. Enrollment began in August 2020. Hospital types were compared using the Fisher exact test. Results: As of January 1, 2021, 31 hospitals (30% of targeted hospitals) completed the web-based survey including 19 ACH and 12 CAH. Hospitals were distributed across the state. Median number of beds was 52 (range, 11–680). Of the responding hospitals, 87% were adherent to all CDC core elements. However, if action was defined as prospective audit and feedback or prior authorization, tracking was defined as measuring antibiotic use in days of therapy (DOT) or defined daily dose (DDD) quarterly, and reporting was defined as providing unit- or provider-specific antibiotic use reports annually. Overall adherence fell to 35% including 81% for action, 58% for tracking, and 58% for reporting. CAHs were less likely to adhere to these strict criteria than ACHs (Figure 1). In the 27 hospitals (87% of hospitals) caring for pediatric patients, adherence to a strict action for at least 1 pediatric population was 59%. Reported barriers to improved ASP were available time and personnel, information technology support, perceived concerns about provider attitudes, and education gaps (Figure 2). CAHs were less likely to use the NHSN antibiotic use or resistance modules or have a data analyst than ACHs (Figure 3). Pediatric pharmacy expertise and guidelines were often not available in hospitals caring for pediatric patients. Desired ASP resources included assistance with data analysis, access to stewardship expertise and education, and treatment guidelines, including for pediatrics. Conclusions: Adherence to CDC core elements of an ASP was excellent but fell dramatically when stricter criteria were used and was worse in pediatric patients. Academic centers and public health departments can assist community hospitals by providing educational resources, assistance in analyzing data including using the NHSN ED: /AR modules, and ASP expertise and clinical care guidelines including those for pediatrics.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Figure 3.

Background: The Centers for Disease Control and Prevention (CDC) estimates that outpatient settings account for 85%–90% of antibiotic prescriptions in the United States, and ~30% of those prescriptions are unnecessary. One of the most common examples of inappropriate prescribing is for viral upper respiratory infections (URIs). Up to 50% of prescriptions written for URIs are deemed inappropriate, making it an important focus for Antibiotic Stewardship programs. In this study, we evaluated the effect of a behaviorally enhanced quality improvement intervention in reducing inappropriate antibiotic prescribing for viral URIs. Methods: A quasi-experimental study assessed the effects of an Antibiotic Stewardship intervention on antibiotic prescribing for viral URIs. The outcome of interest was a change in the number of antibiotics prescribed at each participating clinic over a 1-year preimplementation period and a 2-year postimplementation period. Time trends were analyzed using segmented regression analysis, and a stepped wedge design was used to account for intervention roll-out across clinics. Results: From 2017 to 2020, there were 63,028 patient visits in 21 clinic locations. Antibiotics were prescribed an average of 11.5% and 5.8% of visits during the pre- and postimplementation periods, respectively. The most frequently prescribed antibiotic over the study period was azithromycin (n = 3,551), followed by amoxicillin (n = 924). Overall, the intervention was associated with a 46% reduction in antibiotic prescriptions or 0.54 times (P = .001) as many inappropriate antibiotics prescribed as before the intervention. There was no significant change in the month-to-month trend in inappropriate prescriptions after the intervention was implemented (P = .87). Conclusions: Our study demonstrates that a behaviorally enhanced quality improvement intervention to reduce inappropriate prescribing for URI in ambulatory care encounters was successful in reducing potentially inappropriate prescriptions for presumed viral respiratory infections.

Funding: No

Disclosures: None

Background: Bats are recognized as important vectors in disease transmission. Frequently, bats intrude into homes and buildings, increasing the risk to human health. We describe bat intrusions and exposure incidents in our hospital over a 3-year period. Methods: The University of Iowa Hospitals and Clinics (UIHC) is an 811-bed academic medical center in Iowa City, Iowa. Established in 1928, UIHC currently covers 209,031.84 m2 (~2,250,000 ft2) and contains 6 pavilions built between 1928 and 2017. We retrospectively obtained bat intrusion calls from the infection prevention and control program call database at UIHC during 2018–2020. We have also described the event management for intrusions potentially associated with patient exposures. Results: In total, 67 bat intrusions occurred during 2018–2020. The most frequent locations were hallways or lounges 28 (42%), nonclinical office spaces 19 (14%), and stairwells 8 (12%). Most bat intrusions (65%) occurred during the summer and fall (June–November). The number of events were 15 in 2018, 28 in 2019, and 24 in 2020. We observed that the number of intrusions increased with the age of each pavilion (Figure 1). Of 67 intrusions, 2 incidents (3%) were associated with potential exposure to patients. In the first incident, reported in 2019, the bat was captured in a patient care area and released before an investigation of exposures was completed and no rabies testing was available. Also, 10 patients were identified as having had potential exposure to the bat. Among them, 9 patients (90%) received rabies postexposure prophylaxis. In response to this serious event, we provided facility-wide education on our bat control policy, which includes the capture and safe handling of the bat, assessment of potential exposures, and potential need for rabies testing. We also implemented a bat exclusion project focused on the exterior of the oldest hospital buildings. The second event, 1 patient was identified to have potential exposure to the bat. The bat was captured, tested negative for rabies, no further action was needed. Conclusions: Bat intrusions can be an infection prevention and control challenge in facilities with older buildings. Hospitals may need animal intrusion surveillance systems, management protocols, and remediation efforts.

Funding: No

Disclosures: None

Figure 1.

Background: Medical University of South Carolina Health began vaccinating care team members December 15, 2020, with the Pfizer-BioNTech SARS-CoV-2 mRNA vaccine. We report surveillance data for cases diagnosed following vaccination. Methods: Care team members (CTMs) diagnosed with COVID-19 following SARS-CoV-2 vaccination were self-identified during online electronic contact-tracing surveys. Demographic data, symptoms, and dates of symptoms were recorded. CTMs testing positive at MUSC were linked to viral burden data from nasopharyngeal swabs tested on Abbott PCR platforms. Results: As of January 31, 2021, 111 CTMs tested positive for SARS-CoV-2 following vaccination: 99 and 12 after 1 and 2 doses, respectively, at medians of 10 days (range, 1–22) and 5 days (range, 1–16), respectively, from vaccination to testing. Of 2 cases that tested positive >14 days from dose 2, CTMs had symptom onset at 4 and 12 days from dose 2. Among CTMs reporting symptoms, 104 did so after a median of 7 days (mean 6.3, range −23 to +22) from vaccination to symptom onset, with 8 reporting symptoms before vaccination, 9 on the day of vaccination, and 3 CTMs at 1 day after vaccination, 6 CTMs at 2 days after vaccination, and 11 CTMs at 3 days after vaccination. Overall, 86 (78%) of 111 were female and 95 (86%) of 111 were white. The median age was 44 years (range, 22–71). Clinical job roles were most frequently nurses (n = 31, 28%), physicians or physician extenders (n = 19, 17%), and CTMs with no patient contact (n = 21, 19%). Assessment by the contact-tracing team assigned sources as household clusters (n = 22, 23%), local transmission (n = 21, 22%), occupational acquisition from coworkers (n = 11, 12%), travel related (n = 9, 10%), and unknown (n = 32, 34%). Only 32 (32%) CTMs were compliant with physical distancing. Among 104 CTMs reporting symptoms, cough (75%), headache (71%), rhinorrhea (63%), myalgia (60%), sore throat (48%), anosmia (44%), and subjective fever (40%) were the most commonly reported symptoms. Among 54 symptomatic CTMs with available viral-load data, the median and mean cycle numbers (Cn) were 19.98 and 21.91, respectively, for samples tested a median 3 days from symptom onset. Asymptomatic and symptomatic CTMs had a median Cn of 30.1 vs 20.9, respectively (p <0.001) and overall 50% of vaccinated CTMs had Cn >20, with no significant effect seen by vaccine dose (Figure 1). Conclusions: Most COVID-19 cases following vaccination occurred in CTMs with infection incubating prior to vaccination. No significant attenuation of viral load is apparent among vaccinated CTMs with COVID-19, but asymptomatic CTMs diagnosed with COVID-19 following vaccination appear to have resolved infections. Our data reinforce the need to adhere to public health measures by people who have been vaccinated.

Funding: No

Disclosures: None

Figure 1.

Background: The disease caused by SARS-CoV-2, COVID-19, has caused a pandemic leading to strained healthcare systems worldwide and an unprecedented public health crisis. The hallmark of severe COVID-19 is lower respiratory tract infection (LRTI) and hypoxia requiring hospitalization. A paucity of data on bacterial coinfection and a lack of therapeutic options for COVID-19 during the first surge of cases has increased pressure on antimicrobial use and has challenged antimicrobial stewardship programs (ASPs). We implemented a multimodal approach to antimicrobial stewardship in an urban safety-net community hospital targeting selection and duration of therapy. Methods: Retrospective review of cases during the first wave of COVID-19 in a 151-bed urban safety-net community hospital from March to June 2020. EMR order sets (Figure 1) and prospective audit and feedback by ASPs targeting empiric antimicrobial selection and duration were implemented as part of the COVID-19 response. Hospitalized patients with COVID-19 were reviewed retrospectively. Demographic information was collected. Data on antimicrobial use were tabulated, including selection and duration of antimicrobials (Figure 1). Results: In total, 302 patients were reviewed, of whom 221 (73%) received empiric antimicrobials. The most commonly used antimicrobials were ceftriaxone and azithromycin (Figure 2). Days of therapy per 1,000 patient days (DOT/1,000 PD) for ceftriaxone increased from 71 in the quarter prior to 113 during the study period. Average duration of therapy was 6 days. In the ICU, average duration was 8 days compared to 5 days in non-ICU settings. Average durations of parenteral therapy were 5.54 days in the ICU and 3.36 days in non-ICU settings. Procalcitonin was obtained in 37 cases (17%) and ranged from 0.09 to 12.57 ng/mL, with an average of 1.21 ng/mL. No cases had documented bacterial coinfection (Figure 1). Conclusions: Antimicrobials were commonly prescribed during the first wave of COVID-19 in a safety-net community hospital. Procalcitonin did not guide therapy nor did lack of documented coinfection change physician behavior. With limited resources, ASP successfully guided clinicians toward IDSA guideline recommendations for selection and duration, as evidenced by antimicrobial use. During this unprecedented surge of LRTIs, a multimodal approach to antimicrobial stewardship was used and guided toward early transition to oral agents and shorter durations.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Background: The disease caused by SARS-CoV-2, COVID-19, has caused a pandemic leading to strained healthcare systems worldwide and an unprecedented public health crisis. Lower respiratory tract infections (LRTIs) and hypoxia caused by COVID-19 has led to an increase in hospitalizations. We sought to define the impact of COVID-19 on antimicrobial use and antimicrobial resistance (AMR) in an urban safety-net community hospital. Methods: Retrospective review of antimicrobial use and AMR in a 151-bed urban community hospital. Antimicrobial use was calculated in days of therapy per 1,000 patient days (DOT/1,000 PD) for ceftriaxone, piperacillin-tazobactam and meropenem during 2019 and 2020. Ceftriaxone, piperacillin-tazobactam and meropenem were reviewed for calendar year 2019 and 2020. AMR was assessed by comparing the carbapenem resistant Enterobacteriaceae (CRE) infection incidence rate per 1,000 patient days between 2019 and 2020. Results: The average quarterly DOT/1,000 PD increased from 359.5 in 2019 to 394.25 in 2020, with the highest increase in the second and fourth quarters of 2020, which temporarily correspond to the first and second waves of COVID-19. Ceftriaxone and meropenem use increased during the first and second waves of COVID-19. Piperacillin-tazobactam use increased during the first wave and declined thereafter (Figure 1). Rates of CRE increased from a quarterly average of 0.57 to 0.68 (Figure 2). Conclusions: Antimicrobial pressure increased during the first and second waves of COVID-19. Ceftriaxone was the most commonly used antimicrobial, reflecting internal guidelines and ASP interventions. CRE rates increased during COVID-19. This finding may be due to an overall increase in antimicrobial pressure in the community and in critically ill patients. Antibiotics are a precious resource, and antimicrobial stewardship remains important during the COVID-19 pandemic. Appropriate use of antimicrobials is critical to preventing AMR.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Background: The gold standard for diagnosis of COVID-19 has been SARS-CoV-2 detection by reverse-transcriptase-quantitative polymerase chain reaction (RT-qPCR), which provides a semiquantitative indicator of viral load (cycle threshold, Ct). Our research group previously described how African American race and poverty were associated with an increased likelihood of hospitalization due to COVID-19. We sought to characterize the relationship between Ct values and clinical outcomes while controlling for sociodemographic factors. Methods: We conducted a cross-sectional study of SARS-CoV-2–positive patients admitted to Froedtert Health between March 16 and June 1, 2020. Ct values were obtained by direct interrogation of either cobas SARS-CoV-2 or Cepheid Xpert Xpress platforms. Patient demographics, comorbidities, symptoms at admission, health insurance, and hospital course were collected using electronic medical records. A proxy for socioeconomic disadvantage, area-deprivation index (ADI), was assigned using ZIP codes. Multivariate models were performed to assess associations between Ct values and clinical outcomes while controlling for ADI, race, and type of insurance. Results: Overall, 302 patients were included. The mean age was 60.89 years (SD, 18.2); 161 (53%) were men, 177 (58%) were African Americans; and 156 (51%) had Medicaid or were uninsured. Of the 302 inpatients, 158 (52%) required admission to the ICU, 199 (65.9%) were discharged to home, 49 (16.2%) were discharged to a nursing home, and 54 (17.9%) died. Lower Ct values (higher viral load) were associated with Medicaid or lack of insurance (coefficient, −2.88, 95% confidence interval [CI], −4.96 to −0.79, P = .007) and age >60 years old (coefficient, −2.98, 95% CI −4.87 to −1.08, P = .002). Contrary to what was expected, higher CT values (lower viral load) were associated with higher ADI scores (coefficient, 2.62, 95% CI, 0.52–4.85; P = .017). However, when patients were stratified into low, medium, and high ADI, those with Medicaid or no insurance had the lowest mean Ct values (23.3, 25.9, and 27.6, respectively) compared to Medicare or other insurance (Figure 1). Body mass index (odds ratio [OR], 1.04; 95% CI, 1.02–1.07; P = .001) and male sex (OR, 2.15; 95% CI, 1.28–3.60; P = .004) were independently associated with ICU admission. Every increase of a CT point (OR, 0.90; 95% CI, 0.85–0.95; p <0.001) and age >60 years old (OR 2.62, 95% CI; 1.14-6.04; p=0.023) was associated with death. Conclusions: In this cross-sectional study of adults tested for COVID-19 in a large midwestern academic health system, lower Ct values were independently associated with poverty and age >60 years old.

Funding: No

Disclosures: None

Figure 1.

Background: Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 RNA can be detected by real-time reverse-transcription polymerase chain reaction (RT-PCR) for several weeks after infection. Discerning persistent RT-PCR positivity versus reinfection is challenging and the frequency of COVID-19 reinfections is unknown. We aimed to determine the frequency of clinically suspected reinfection in our center and confirm reinfection using viral whole-genome sequencing (WGS). Methods: The University of Iowa Hospitals and Clinics (UIHC) is an 811-bed academic medical center. Patients with respiratory complaints undergo COVID-19 RT-PCR using nasopharyngeal swabs. The RT-PCR (TaqPath COVID-19 Combo kit) uses 3 targets (ORF1ab, S gene, and N gene). We identified patients with previous laboratory-confirmed COVID-19 who sought care for new respiratory complaints and underwent a repeated SARS-CoV-2 test at least 45 days from their first positive test. We then identified patients with median RT-PCR cycle threshold (Ct) values. Results: During the study period, 13,603 patients had a SARS-CoV-2– positive RT-PCR. Of these, 296 (2.2%) had a clinical visit for new onset of symptoms and a repeated RT-PCR assay >45 days from the first test. Moreover, 29 patients (9.8%) had a positive RT-PCR assay in the repeated testing. Ct values were available for samples from 25 patients; 7 (28%) had Ct values. Conclusions: In patients with a recent history of COVID-19 infection, repeated testing for respiratory symptoms was infrequent. Some had a SARS-CoV-2–positive RT-PCR assay on repeated testing, but only 1 in 4 had Ct values suggestive of a reinfection. We confirmed 1 case of reinfection using WGS.

Funding: No

Disclosures: None

Background: SARS-CoV-2 detected by reverse transcription polymerase chain reaction (RT-PCR) can persist for weeks to months in some individuals. Cycle threshold (Ct) values represent the number of cycles needed to amplify viral ribonucleic acid (RNA) to reach a detectable level. As such, Ct values are inversely related to the amount of virus in a sample. As knowledge of SARS-CoV-2 viral dynamics continues to evolve, understanding the relationship between Ct values, type of symptoms, and timing of symptom onset can help determine when infected individuals are most likely to be infectious. Methods: We conducted a retrospective cohort study of 1,027 healthcare workers (HCWs) who tested positive for SARS-CoV-2 by RT-PCR from nasopharyngeal specimens between June 27, 2020, and September 21, 2020. All HCWs were interviewed within 72 hours of their diagnosis for symptom history. Due to multiple PCR platforms being in use in our facility, only 360 HCWs (35%) had Ct values available for analysis. Multivariate linear regression models examined the effect of COVID-19–related symptoms and timing of symptom onset to test on Ct values. Results: The most frequently reported symptoms were congestion (55.6%), cough (50.3%), and headache (46.7%). Other symptoms less commonly reported were fatigue (36.7%), loss of taste or smell (36.4%), fever (35.4%), muscle aches (33.3%), sore throat (27.4%), and diarrhea (26.7%). Symptomatic HCWs (88.3% of sample) had lower Ct values (ORF-1 M = 22.66, SD = 5.17; E-Gene M = 24.34, SD = 6.60) than asymptomatic individuals (ORF-1 M = 25.46, SD = 6.06; E-Gene M = 29.34, SD = 7.96). Of all symptoms measured, only presence of fever, congestion, and muscle aches predicted significantly lower Ct values. Mean Ct values decreased 2 days prior to symptom onset, were lowest the day of symptom onset, then increased in a curvilinear fashion. There were no significant 2-way interactions between symptoms and time of symptom onset to testing. Conclusions: The curvilinear pattern of Ct values over time from symptom onset are consistent with disease progression patterns and support current understanding of infectivity being highest 2 days prior to symptom onset through day 8. Presence of fever, congestion, and muscle aches are significantly correlated with lower Ct values, suggesting that these symptoms are associated with higher viral load. Although Ct values are not without limitations, our findings support the current understanding that presymptomatic and symptomatic individuals, particularly those with fever, congestion, and muscle aches, may pose higher risk of transmission to others.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Table 1.

Group Name: DHHS Epi

Background: The inoculation with SARS-CoV-2 vaccine at long-term care facilities (LTCFs) in Nebraska began on December 28, 2020, as part of the Centers for Disease Control and Prevention (CDC) Pharmacy Partnership for Long-Term Care Program.1 As of February 5, 2021, 159 skilled nursing facilities (SNFs) had completed their first vaccine clinic, and 7,271 residents and 6,768 staff had received the first dose of the 2-dose series. Surveillance data before vaccination (December 21–27, 2020) and after the first vaccination dose (January 25–31, 2021) indicate that the weekly SARS-CoV-2 positivity rate at SNFs decreased from 1.18% to 0.42% for residents and 0.54% to 0.11% for staff.2,3,4 In this study, we examined the perceived decrease in new transmission initiated by the first dose of vaccine at SNFs. Methods: We analyzed the data with separate logistic regressions for residents and staff. We included 145 SNFs that completed their first vaccine clinic, and we used the Federal and Pharmacy Partnership database for the number of residents and staff that received the first dose of vaccine at the first vaccine clinic. We followed the SNFs for 21 days after the first vaccine clinic from December 28, 2020, through February 5, 2021, for any first-time SARS-CoV-2–positive cases. The National Healthcare Safety Network (NHSN) database was used to collect the information on the number of residents present at the facility on the day of the first vaccine clinic, if available, or days before in the same week as the first vaccine clinic. The staff count for each facility was extracted from Nebraska Licensure for LTCFs. We collected new case information from the state surveillance, the NHSN, and the Test-Nebraska platform. Results: The mean resident vaccine coverage was 80% and the median staff vaccine coverage was 43%. We found a reverse association between staff vaccine coverage and new positive staff cases. For each percentage increase in staff vaccine coverage, the odds of having a new staff positive case 7 days and 14 days after the first vaccine clinic decrease by 26% and 48%, respectively. No association between coverage and new resident transmission was detected. Possible confounding exists when infected residents might have tested positive 7–14 days after the first vaccine clinic who were not affected by the vaccine. Conclusions: Although we observed the association between lower case count with increased facility-level vaccine coverage, we would need to wait for the administration of the second dose of vaccine before assessing the level of association between coverage and new transmission. Further initiatives are warranted to increase the suboptimal vaccine coverage for staff.

Funding: No

Disclosures: None

Background: Hospital semiprivate rooms may lead to coronavirus disease 2019 (COVID-19) patient exposures. We investigated the risk of COVID-19 patient-to-patient exposure in semiprivate rooms and the subsequent risk of acquiring COVID-19. Methods: The University of Iowa Hospitals & Clinics is an 811-bed tertiary care center. Overall, 16% of patient days are spent in semiprivate rooms. Most patients do not wear masks while in semiprivate rooms. Active COVID-19 surveillance included admission and every 5 days nasopharyngeal SARS-CoV-2 polymerase chain reaction (PCR) testing. We identified inpatients with COVID-19 who were in semiprivate rooms during their infectious periods during July–December 2020. Testing was repeated 24 hours after the first positive test. Cycle threshold (Ct) values of the two tests (average Ct <30), SARS-CoV-2 serology results, clinical assessment, and COVID-19 history were used to determine patient infectiousness. Roommates were considered exposed if in the same semiprivate room with an infectious patient. Exposed patients were notified, quarantined (private room), and follow-up testing was arranged (median seven days). Conversion was defined as having a negative test followed by a subsequent positive within 14 days after exposure. We calculated the risk of exposure: number of infectious patients in semiprivate rooms/number of semiprivate patient-days (hospitalization days in semiprivate rooms). Results: There were 16,427 semiprivate patient days during July–December 2020. We identified 43 COVID-19 inpatients who roommates during their infectious periods. Most infectious patients (77%) were male; the median age was 67 years; and 22 (51%) were symptomatic. Most were detected during active surveillance: admission testing (51%) and serial testing (28%). There were 57 exposed roommates. The risk of exposure was 3 of 1,000 semiprivate patient days. In total, 16 roommates (28%) did not complete follow-up testing. Of 41 exposed patients with follow-up data, 8 (20%) converted following their exposure. Median time to conversion was 5 days. The risk of exposure and subsequent conversion was 0.7 of 1,000 semiprivate patient days. Median Ct value of the source patient was 20 for those who converted and 23 for those who did not convert. Median exposure time was 45 hours (range, 3–73) for those who converted and 12 hours (range, 1–75) for those who did not convert. Conclusions: The overall risk of exposure in semiprivate rooms was low. The conversion rate was comparable to that reported for household exposures. Lower Ct values and lengthier exposures may be associated with conversion. Active COVID-19 surveillance helps early detection and decreases exposure time.

Funding: No

Disclosures: None

Background: The COVID-19 pandemic has created personal protective equipment (PPE) shortages, particularly of N95 respirators. Institutions have used decontamination strategies including vaporous hydrogen peroxide (VHP) to augment respirator supplies. VHP can be used to decontaminate nonporous surfaces without compromising material integrity. However, little is known about its impact on N95 respirator efficacy. We assessed whether repeated VHP reprocessing altered 4 key respirator efficacy qualities: quantitative fit, qualitative fit, seal check, and filtration rate. Methods: We conducted a prospective cohort study from June 15 to August 31, 2020. In total, 7 participants were fitted to a 3M 1860 small or regular N95 respirator based on qualitative and quantitative fit testing. Respirators underwent 25 disinfection cycles with the Bioquell BQ-50 VHP generator. After each cycle, participants donned and doffed respirators and performed a seal check. Participants were given 2 attempts to pass their seal check. Every 10 cycles, qualitative fit testing was done using an aerosolized Bitrex solution. Quantitative fit testing was conducted using a PortaCount Pro 8038 Fit Tester to generate a fit factor score. Appropriate fit is defined as a fit factor score of 100 or greater. Quantitative testing was done at cycles 1, 3, 5, 7, 10, 15, 20, and 25. Filtration efficiencies of particles ≥0.3 µm in diameter were measured using the TSI Optical Particle Sizer 3330 at cycles 1, 5, 10, 15, 20, and 25. The Fisher exact test was used to assess qualitative fit and seal check. The Kruskal-Wallis test was used to analyze quantitative fit and filtration rate. Results: We observed no seal-check or quantitative-fit test failures during the study window. All participants passed qualitative fit testing. Although there was a significant degree of variability in fit factor scores across disinfection cycles (mean score 163.5, p <0.05), there was no significant difference between participants (p = 0.6) (Figure 1). There was no statistically significant change in mean filtration rate from cycle 10 to 25 (P = .05), and the filtration rate remained >95% by cycle 25 (Figure 2). Conclusions: VHP reprocessing did not diminish the efficacy of N95 respirators based on the 4 metrics we assessed: filtration rate, seal check, qualitative fit, and quantitative fit. Of significance, the filtration rate remained well above the 95% standard filtration for N95 respirators—even through 25 cycles of reprocessing. VHP reprocessing is a safe, viable strategy to disinfect N95 respirators and extend their use, particularly during supply shortages.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Background: Sink drains can act as breeding grounds for multidrug-resistant (MDR) bacteria, leading to outbreaks. Drains provide a protected humid environment where nutrient-rich substances are available. Recent and growing installation of water and energy conservation devices have led to increased frequency of drain blockage due to biofilm accumulation. Ineffective drainage may lead to backflow and accumulation of water in the sink during use, increasing the risk of contaminated aerosols formation or direct contamination of surrounding material and equipment. Cleaning and disinfection procedures of sink drains need to be improved to prevent amplification and dispersion of MDR bacteria. The objective of this study was to investigate alternatives to reduce the biofilm and risk of contamination through aerosols. Methods: Sink drains from patient rooms were randomly selected in the neonatal intensive care unit of a 450-bed pediatric hospital. We tested 4 approaches: (1) new drain; (2) self-disinfecting heating-vibration drain; (3) chemical disinfection with 20 ppm chlorine for 30 minutes; and (4) thermal disinfection with > 90°C water for 30 minutes. A special device was used during disinfection to increase the disinfectant contact time with the biofilm. Treatments were conducted weekly, with prior sampling of drain water. Other drains were also sampled weekly, including a control drain with no intervention. Bacterial loads were evaluated using flow cytometry and heterotrophic plate counts. The drains were made of stainless steel, a heat-conductive material. Results: Preliminary results show that chlorine disinfection had a small impact (<1 log) on culturable bacteria at 48 hours after disinfection but not after a week or repeated weekly disinfection. Thermal disinfection using boiling water is promising, showing an important decrease of 4 log in culturable cells after 48 hours and a concentration still 100× lower 1 week after the disinfection. Repeated weekly thermal disinfection maintained lower culturable levels in the drain. No culturable cells were detected in water from the self-disinfecting drain 2 months after installation, whereas the new drain became fully colonized to concentrations similar to those of drains prior to interventions during the same period. Conclusions: Thermal disinfection of drains is a promising alternative to chlorine. This solution is interesting because it is nontoxic and easy to perform, requiring a small volume of hot water. The rapid recolonization of the new drain suggests that replacing contaminated drains is not a sustainable solution and would need to be paired with a thermal disinfection program to maintain low culturable cells.

Funding: No

Disclosures: None

Background: A pathogenic group of invasive extraintestinal pathogenic (ExPEC) Escherichia coli possess the ability to infect normally sterile body sites and cause severe invasive ExPEC disease (IED). ExPEC is a leading cause of bacteremia and sepsis worldwide and is associated with older age and multidrug-resistant infections. Janssen Vaccines & Prevention is developing a novel multivalent glycoconjugate vaccine to prevent IED. We aimed to use an unbiased approach, with no prespecified potential risk factors, using machine-learning models, to screen for and identify IED risk factors for further validation. Methods: We used a patient-level prediction study design to model the probability of a patient developing IED within 14 days to 1 year from a given date based on their prior 2 years of health records. We used the Optum EHR database (~98 million subjects) in the common data model (CDM) format, with health features encoded in the following categories: conditions, procedures, drugs, healthcare visits, recent laboratory measurements, and age and gender. A gradient boosting model (XGBoost) was used with Shapley additive explanation (SHAP) values to identify which features were most important to the model’s decisions and to characterize precisely the relationship between features and outcomes (binary or continuous). Results: Study participants were aged ≥60 years at index with no previously recorded IED. Of ~6,500,000 cases included, ~8,000 had IED during the prediction window. We found that having ≥1 urinary tract infection (UTI) in the retrospective period increased the model’s probability of predicting IED for that patient, with more frequent or more recent UTIs increasing IED prediction chance (Figure 1). Higher age linearly increased the model’s likelihood of predicting that a patient would develop IED. The model also identified ≥1 inpatient or ER visit and laboratory values indicative of renal or immune dysfunction to be correlated with increased IED risk. This methodology is a generalizable approach to screening for potential risk factors for an outcome using EHR databases; it requires little to no prespecification of the health factors or precise relationship between the factors and outcome. Conclusions: Using a new, impartial methodology (with no prespecification), older age and a history of UTIs were key predictive features for IED, factors previously identified through traditional analysis, confirming the validity of the methodology. Novel features, including recent hospitalization, were shown to increase IED risk relative to existing criteria. Our findings may be used to inform the clinical development of preventive strategies.

Funding: Janssen Research and Development

Disclosures: None

Figure 1.

Background: Gram-negative bacteria cause a variety of hospital-associated infections (HAIs). Of concern is Pseudomonas aeruginosa, which is a leading cause of HAIs. Early and adequate therapy of P. aeruginosa blood stream infection (BSI) is associated with decreased mortality. Additionally, infectious disease consultation has also shown to improve health outcomes, streamline care, and decrease costs. Therefore, the goal of this study was to describe treatment of P. aeruginosa BSI and impact of infectious disease consultations on health outcomes. Methods: In this retrospective cohort study, we analyzed national VA medical, encounter, pharmacy, microbiology, and laboratory data from January 1, 2012 to December 31, 2018. The cohort included all hospitalized adult veterans (aged ≥18 years) who had a positive blood culture for P. aeruginosa. Only the first P. aeruginosa blood culture per patient was included, and duplicate cultures within 30 days were removed. Treatment was identified within −2 to +5 days of the culture date. Multidrug-resistant (MDR) cultures were identified based on resistance to at least 1 agent in at least 3 or more antimicrobial categories tested. Multivariable logistic regression models were fit to assess infectious disease consultations and adequate treatment on in-hospital mortality and 30-day mortality. Results: In total, 3,256 patients had a BSI with P. aeruginosa, of which 386 (11.5%) were MDR. Most of these patients were male (97.5%), >65 years of age (70.9%), and non-Hispanic white (63.8%). Also, 784 patients (23.3%) died during hospitalization and 870 (25.8%) died within 30 days of their culture. In multivariable regression models, infectious disease consultations were associated with decreased odds of in-hospital mortality (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.53–0.77) and 30-day mortality (OR, 0.56, 95% CI, 0.48–0.67) even after adjusting for age, race, care setting, Charlson score, and prior healthcare exposures. Furthermore, inadequate definitive treatment was associated with increased odds of in-hospital mortality (OR, 2.77; 95% CI, 1.35–5.69) and 30-day mortality (OR, 2.37; 95% CI, 1.18–4.79), even after adjusting for age, Charlson score, care setting, and prior healthcare exposures. In addition, carbapenem treatment was associated with increased odds of in-hospital mortality (OR, 1.38; 95% CI, 1.12–1.70) and 30-day mortality (OR, 1.49; 95% CI, 1.22–1.81), whereas fluoroquinolone treatment was associated with lower odds of in-hospital mortality (OR, 0.49; 95% CI, 0.41–0.59) and 30-day mortality (OR, 0.60; 95% CI, 0.50–0.71). Finally, extended-spectrum cephalosporin was also associated with lower odds of in-hospital mortality (OR, 0.82; 95% CI, 0.68–0.98). Conclusions: Use of infectious disease consultations and any adequate definitive treatment for those with P. aeruginosa BSI lowered odds of in-hospital and 30-day mortality. Early consultation with infectious disease physicians regarding adequate treatment has direct positive impact on clinical outcomes for patients with P. aeruginosa BSI.

Funding: No

Disclosures: None