Background: Hospitalized patients with COVID-19 often receive antimicrobial therapies due to concerns for bacterial and fungal coinfections. We analyzed patients admitted with COVID-19 to our VA facility to understand antimicrobial use, frequency of coinfections, and outcomes in our population. Methods: This retrospective study included veterans who were 18 years or older and hospitalized with COVID-19 from March 10, 2020, to March 9, 2021 at the Louis Stokes VA Medical Center in Cleveland, Ohio. We identified antimicrobials administered and coinfections with bacterial or fungal pathogens. Patients were deemed to have coinfection if there was supporting microbiological data and a consistent clinical course upon review of clinical records. Urinary tract infections were excluded because of difficulty determining infection. Odds ratios (ORs) and 95% confidence intervals (CIs) for 30-day mortality were derived using multivariate logistic regression models that included age, Charlson comorbidity index (CCI), corticosteroid use, and time of infection. Results: In our cohort of 312 patients, the median age was 70 years and 97% of the patients were male. The mean CCI was 3.7 (SD, 3.0), and 111 patients (35.6%) had a score ≥5. Oxygen was administered to 250 patients (80.1%), and 20 (6.4%) required mechanical ventilation. Antimicrobials were administered to 164 patients (52.6%) (Fig. 1). Of 20 patients (6.4%) with coinfection, 11 (3.5%) had a bloodstream infection (BSI) and 9 (2.9%) had bacterial pneumonia (Fig. 2). The overall 30-day mortality rate was 12.5% (39 of 312). Among patients with coinfection, the 30-day mortality rate was 45% (9 of 20). Diagnoses of BSI (OR, 6.35; 95% CI, 1.41–26.30) and bacterial pneumonia (OR, 9.34; 95% CI, 2.01–46.34) were associated with increased mortality. Of the data available, 12 (63%) of 19 patients with coinfection had elevated procalcitonin levels (ie, >0.50). At the time of COVID-19 diagnosis, the median absolute lymphocyte count in patients who died was 0.7 K/mm3 (95% CI, 0.6–1.12) in comparison to 1 K/mm3 (95% CI, 0.7–1.4) in patients who survived at 30 days. Conclusions: Our analysis of hospitalized COVID-19 patients with advanced age and underlying comorbid conditions demonstrated that coinfections were infrequent but that they were independently associated with increased mortality. This finding highlights the need for better tools to diagnose the presence or absence of bacterial and fungal coinfection in COVID-19 patients. Our findings also emphasize the need for judicious use of antimicrobials while discerning which patients are at risk of critical illness and mortality.

Funding: None

Disclosures: None

Background: Antimicrobial stewardship initiatives usually occur in the inpatient setting, and they are often lacking at transitions of care (TOC), including hospital discharge. We assessed the appropriateness of antibiotic treatment duration at the time of discharge from our institution. Methods: This retrospective chart review included 300 adult patients discharged on oral antibiotics for acute infections during a 3-month period in 2019. The primary outcome was the duration of antibiotic therapy (DOT). To assess appropriateness, we compared the prescribed DOT (1) to that recommended by clinical guidelines, (2) to the minimum supported by clinical trials, and (3) to the period beyond the point of clinical stability, defined as normal vital signs with improvement in symptoms present from diagnosis. Each indication and antibiotic was assessed using standards appropriate for the combination. Results: Results are shown in Tables 1 and 2 and Figure 1. Conclusions: Antibiotics were often given longer than necessary on hospital discharge. In this study, patients received a median 2 days of excess antibiotics compared to recommended guidelines and 6 days after reaching clinical stability. A pilot TOC stewardship program was initiated to address this problem.

Funding: No

Disclosures: None

Table 1.

Table 2.

Figure 1.

Background: RSV is underrecognized in hospitalized adults. A better understanding of RSV in this population could help prioritize targeted viral-testing resources. Hospitalization and in-hospital outcomes are widely accepted as markers of clinical severity with respect to acute respiratory illness (ARI). We compared characteristics and clinical outcomes between adults hospitalized with ARI from October 2016 through May 2019. Methods: All hospitalized adults (≥ 18 years) who met a standardized case definition of ARI were prospectively enrolled across 3 respiratory seasons from 9 hospitals participating in the US Hospitalized Adult Influenza Vaccine Effectiveness Network (HAIVEN). Demographic data were collected during enrollment interviews, and electronic medical records (EMRs) were reviewed to extract comorbidity data. Throat and nasal swabs collected at enrollment were tested for ARI pathogens using real-time PCR assays at respective HAIVEN research laboratory sites. Characteristics and clinical outcomes of participants were compared using χ2 or nonparametric tests where appropriate. Multivariable logistic regression models were used to test associations between infection status, characteristics, and clinical outcomes, adjusting for age, sex, race, Charlson comorbidity index (CCI), body mass index (BMI), site, season, and days to admission. Results: In total, 10,311 adults were included, 22.3% (n = 2,300) were aged 18–49 years, 33.2% (n = 3,423) were aged 50–64 years, and 44.5% (n = 4,588) were aged ≥65 years. Moreover, 6% of adults tested positive for RSV (n = 622), 18.8% positive for influenza (n = 1,940), and 75.1% negative for both (n = 7,749). Obesity and age ≥65 years were significantly associated with RSV detection when compared with participants negative for both RSV and influenza. Patients aged 18–49 years and ≥65 years with RSV had significantly higher median CCI scores compared to patients with influenza (Fig. 1.). The proportion of adults with CHF or COPD was significantly (p-value Conclusions: Severe RSV illness may differ from severe influenza illness, and those infected with RSV may have different characteristics than those infected with influenza. Hospitalized adults with RSV infection were more likely to have underlying cardiopulmonary comorbidities and higher CCI scores as well as experience an extended length of hospital stay and need for mechanical ventilation. These data highlight the importance of retaining testing for RSV in older adults hospitalized with ARI.

Funding: None

Disclosures: None

Background: The IDSA recommends that when determining empiric treatment for a given patient, clinicians should consider previous organisms and associated antibiotic susceptibility data in the prior 6 months when multidrug-resistant/extended-spectrum β-lactamase gram-negative rods (MDR /ESBL GNR) is suspected. The presence of MDR GN in cultures on previous hospitalization or in surveillance cultures leads to use of broader-spectrum empiric antibiotic in subsequent admissions. We sought to determine whether the presence of an MDRO in 1 hospital admission dictates the need for broader-spectrum antibiotic use in subsequent hospitalizations when a different site is considered the source of infection. Methods: The study was conducted at a 700-bed tertiary-care level I trauma center. Infection control records were reviewed for patients aged 21–99 years admitted between July 1, 2013, through January 31, 2014, who had any ESBL or MDR GNR at any site including surveillance culture. The charts were surveyed until January 31, 2016, for ESBL or MDR gram-negative organisms at any site during subsequent hospitalizations. The CDC definition of MDR/ESBL was applied. Results: Of the 50 people followed, 34 patients (68%) had ESBL/MDR recovered at a single sentinel site, 6 patients (12%) had ESBL/MDR in multiple sites, and in 10 patients (20%) had ESBL/MDR only in surveillance cultures during their primary hospitalization. In 34 patients with a single sentinel site MDRO/ESBL in their primary hospitalization, 16 (47%) were identified in urine, 13 (38%) were identified by bronchoalveolar lavage (lung), 4 (12%) were identified on skin or MS, and 1 (3%) was identified at another site. When lung and urine were the sole sites of recovery of MDRO/ESBL in primary hospitalization, respectively, 3 patients (23%) and 2 patients (12.5%) subsequently developed MDROs in a secondary site on subsequent admissions. Overall, 10 bacteremia episodes occurred in 8 patients among 189 total admissions. MDRO/ESBL Klebsiella spp were identified in the cultures of 5 patients (50%), MDRO Acinetobacter spp were identified in the cultures of 3 patients (30%), and ESBL E. coli was identified in the cultures of 2 patients (20%). The organism causing bacteremia was present at a different sites during the same admission in only 3 (30%) of these cases: 2 were cultured from urine and 1 was cultured from a pulmonary source. Conclusions: The presence of MDRO at 1 site in a previous hospitalization may not be sufficient evidence to justify very broad antibiotics for patients during subsequent admissions, especially when another site is considered the source of infection. More studies are needed on natural history of MDRO in different patient populations with different risk factors.

Funding: None

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.

We observed that patients admitted to our hospital from a prestratified group of congregated living facilities had a numerically higher percentage of study-defined resistant organisms in sputum cultures compared to facilities without these characteristics [89.4% vs 78.3%, odds ratio [OR] = 2.34 (95% CI, 0.73–7.58)].

Background:Clostridioides difficile infection (CDI) is the most common healthcare-associated infection (HAI) in the United States. Healthcare facility-onset (HO) CDI reporting is a laboratory-identified (LabID) event and does not rely on symptoms. Inappropriate testing can lead to overdiagnosis in patients who are colonized, especially in those receiving promotility agents. Approximately 45% of HO-CDI cases at our institution occurred in the setting of laxative use in 2019. We assessed the effectiveness of an electronic medical record (EMR) “hard stop” in reducing inappropriate CDI testing and its impact on HO-CDI rates. Methods: We conducted a pre–post quasi-experimental retrospective study comparing test order rates per 1,000 patient days, CDI rate per 1,000 patient days, and standardized infection ratio (SIR) in the preintervention period (January 2018–December 2019) to the intervention period (April 2020–September 2021), at a 5-hospital healthcare system in southeastern Michigan. In February 2020, we implemented a hard stop in Epic that was triggered >3 days after admission for the following criteria: patients <1 year of age; repeated testing within 7 days, and receipt of promotility agents within 48 hours. After discontinuing the promotility agents for at least 48 hours, providers were allowed to place an order if diarrhea persisted. The medical director of infection prevention and control or designee had the ability to override the hard stop when deemed necessary after reviewing the case upon provider request. All orders expired after 24 hours if a specimen was not collected. We retrospectively reviewed the number of overrides after the intervention to determine the positivity rate. Results: Our CDI rates per 1,000 patient days were 3.21 in the preintervention period and 1.48 in the postintervention period, a 54% reduction (Fig. 1). The test order rates were 119.4 in the preintervention period and 87.7 in the postintervention period, a 26.5% reduction (Fig. 2). The SIR decreased from 0.542 in the preintervention period to 0.361 in the postintervention period, a 33% reduction (95% CI, 0.54–0.82; P = .0001). After the intervention, 299 patients had an override. Of these, samples from 218 patients (72.9%) were negative, 50 orders (16.7%) were cancelled, and 28 samples (9%) were positive. Conclusions: Diagnostic stewardship, utilizing an electronic hard stop, was effective in reducing inappropriate C. difficile testing in the setting of promotility agents without delaying diagnosis of HO-CDI. This strategy combined with standard best practices can significantly reduce HO-CDI rates.

Funding: None

Disclosures: None

Background: Detecting healthcare-associated transmission and outbreaks often relies on reactive whole-genome sequencing (WGS), which occurs after the suspected transmission has occurred. Additionally, reactive WGS frequently misidentifies transmission and misses transmission when it has occurred. We initiated weekly real-time WGS to detect bacterial transmission and direct infection prevention interventions. We describe our experience after 1 year of real-time WGS surveillance at the University of Pittsburgh Medical Center–Presbyterian Hospital, a large, tertiary-care facility. Methods: Weekly WGS surveillance was performed from November 1, 2021, to October 31, 2022. Cultured isolates of select bacterial pathogens from patients who were hospitalized for ≥3 days or had a recent healthcare exposure in the prior 30 days were collected and sequenced. Isolates that were ≤15 single-nucleotide polymorphisms (SNPs) were considered genetically related clusters except for Clostridioides difficile (≤2 SNPs). Genetically related clusters were investigated for epidemiological links and interventions to interrupt transmission were implemented at the discretion of the infection prevention team. We analyzed subsequent infections that occurred within an outbreak after an intervention was in place. Results: In total, 1,909 isolates were sequenced. Of 1,633 unique patient isolates clustered by sequence type, 74 clusters were identified comprising 210 (12.9%) patient isolates (Table 1). The median time from culture date to sequencing was 14 days (IQR, 5.25). The median cluster size was 2 (IQR, 1) (Table 2). Overall, 118 patient isolates (56.2%) had an epidemiological link to a prior isolate, indicating potential transmission. Of 74 clusters, 66 (89.2%) received infection prevention interventions after notification based upon epidemiological data. The infection prevention team performed 69 total interventions, which included unit education (n = 28), hand hygiene observations (n = 16), enhanced cleaning (n = 16), environmental cultures or removal of endoscope (n = 7), and enhanced microbiology surveillance (n = 2). The 59 subsequent infections after infection prevention notification included 17 (28.8%) with no clear epidemiological link, and 41 (69.5%) with an epidemiological link either to a new transmission route (n = 37) or the same route prior to infection prevention intervention (n = 4). Only 1 (1.7%) subsequent infection within a cluster occurred after an infection prevention intervention from the same potential route, which was a suspected unit-based transmission of vancomycin-resistant Enterococcus faecium. Conclusions: Real-time WGS was effective at detecting genetically related clusters, finding potential sources, and halting further transmission after interventions by the infection prevention team. Quick turnaround times from patient culture to sequencing and analysis were vital for successful WGS surveillance. Real-time WGS surveillance has the potential to substantially shift the infection prevention paradigm for outbreak detection.

Disclosure: None

We retrospectively reviewed the records of 136 veterans with a penicillin allergy label during a quality improvement initiative. We identified 82 inpatients eligible for removal of penicillin allergy by oral amoxicillin challenge, including 40 out of 82 (48%) still eligible after accounting for other limiting factors.

The rich and complex electronic health record presents promise for expanding infection detection beyond currently covered settings of care. Here, we review the “how to” of leveraging electronic data sources to expand surveillance to settings of care and infections that have not been the traditional purview of the National Healthcare Safety Network (NHSN), including a discussion of creation of objective and reproducible infection surveillance definitions. In pursuit of a ‘fully automated’ system, we also examine the promises and pitfalls of leveraging unstructured, free-text data to support infection prevention activities and emerging technological advances that will likely affect the practice of automated infection surveillance. Finally, barriers to achieving a completely ‘automated’ infection detection system and challenges with intra- and interfacility reliability and missing data are discussed.

The coronavirus disease 2019 (COVID-19) pandemic negatively affected antimicrobial stewardship programs at hospitals throughout Japan by diverting resources toward managing the pandemic. However, antimicrobial stewardship needs to continue regardless of hospital size or supervening crises. Herein, we discuss the impact of COVID-19 on antimicrobial stewardship at a small, local hospital in Japan.

Objectives: Carbapenem-resistant Enterobacteriaceae (CRE) is a multidrug-resistant gram-negative bacteria (MDR-GNB) that is rapidly emerging as a life-threatening nosocomial disease in many countries. We sought to identify the risk factors associated with mortality for carriage of CRE in patients at a tertiary-care teaching hospital. Methods: A retrospective observational study was conducted between January 2020 to December 2021 in a tertiary-care teaching healthcare facility, University Malaya Medical Centre in Malaysia. The study included all inpatients aged ≥18 years who had a CRE infection or were colonized during the study period. The genotype was identified by polymerase chain reaction (PCR). Statistical analysis of data including a multivariate logistic regression analysis was conducted using SPSS version 23.0 software. Results: In total, 176 cases of CRE (130 infection and 46 colonized) were identified, and the mortality rate was 31.8%. The main sources of CRE were rectal swab (61.9%), blood (11.9%), and respiratory sources (11.9%). Klebsiella pneumoniae (55.7%) was the predominant species, followed by Escherichia coli (21.6%). Among the isolates, 17.7% were non–CPE-CRE and 82.3% were CPE-CRE: NDM (69.3%) and OXA (10.8%). In multivariate analysis, the factors associated with mortality were older age (OR, 1.040; 95% CI, 1.012–1.069), longer length of stay (OR, 0.974; 95% CI, 0.955–0.994), use of central venous catheter (OR, 0.287; 95% CI, 0.094–0.878), and arterial lines (OR, 0.292; 95% CI, 0.095–0.891). Conclusion: Patients with CRE had a high mortality rate. Older age, longer duration of stay, indwelling CVC and arterial line were independent risk factors for death. Infection prevention and control measures to reduce CRE, such as active surveillance, contact precautions, compliance to intravenous catheter care bundles, healthcare worker education, and hand hygiene adherence, should be implemented.

Background: Blood cultures are commonly ordered for patients with low risk of bacteremia. Liberal blood-culture ordering increases the risk of false-positive results, which can lead to increased length of stay, excess antibiotics, and unnecessary diagnostic procedures. We implemented a blood-culture indication algorithm with data feedback and assessed the impact on ordering volume and percent positivity. Methods: We performed a prospective cohort study from February 2022 to November 2022 using historical controls from February 2020 to January 2022. We introduced the blood-culture algorithm (Fig. 1) in 2 adult surgical intensive care units (ICUs). Clinicians reviewed charts of eligible patients with blood cultures weekly to determine whether the blood-culture algorithm was followed. They provided feedback to the unit medical directors weekly. We defined a blood-culture event as ≥1 blood culture within 24 hours. We excluded patients aged <18 years, absolute neutrophil count <500, and heart and lung transplant recipients at the time of blood-culture review. Results: In total, 7,315 blood-culture events in the preintervention group and 2,506 blood-culture events in the postintervention group met eligibility criteria. The average monthly blood-culture rate decreased from 190 blood cultures per 1,000 patient days to 142 blood cultures per 1,000 patient days (P < .01) after the algorithm was implemented. (Fig. 2) The average monthly blood-culture positivity increased from 11.7% to 14.2% (P = .13). Average monthly days of antibiotic therapy (DOT) was lower in the postintervention period than in the preintervention period (2,200 vs 1,940; P < .01). (Fig. 3) The ICU length of stay did not change before the intervention compared to after the intervention: 10 days (IQR, 5–18) versus 10 days (IQR, 5–17; P = .63). The in-hospital mortality rate was lower during the postintervention period, but the difference was not statistically significant: 9.24% versus 8.34% (P = .17). The all-cause 30-day mortality was significantly lower during the intervention period: 11.9% versus 9.7% (P < .01). The unplanned 30-day readmission percentage was significantly lower during the intervention period (10.6% vs 7.6%; P < .01). Over the 9-month intervention, we reviewed 916 blood-culture events in 452 unique patients. Overall, 74.6% of blood cultures followed the algorithm. The most common reasons overall for ordering blood cultures were severe sepsis or septic shock (37%), isolated fever and/or leukocytosis (19%), and documenting clearance of bacteremia (15%) (Table 1). The most common indications for inappropriate blood cultures were isolated fever and/or leukocytosis (53%). Conclusions: We introduced a blood-culture algorithm with data feedback in 2 surgical ICUs and observed decreases in blood-culture volume without a negative impact on ICU LOS or mortality rate.

Disclosure: None

Background: Clinical antibiotic susceptibility testing (AST) interpretations based on minimum inhibitory concentrations (MIC) breakpoints are important for both clinical decision making and some reportable condition criteria. Standardization of MIC breakpoints across clinical laboratories is lacking; AST instruments are often validated for outdated Clinical and Laboratory Standards Institute (CLSI) MIC breakpoint guidelines. In this study, we analyzed the agreement between the reported clinical laboratory AST interpretations and the guideline CLSI interpretation. Methods: Clinical laboratory AST data collected from the Multisite Gram-Negative Surveillance Initiative (MuGSI) carbapenem-resistant Enterobacterales (CRE) surveillance program in Tennessee between 2019 and 2021 were utilized. MIC values from the clinical instrument were used to calculate CLSI standard interpretations following the 2019–2021 CLSI M100 guidelines. Agreement between the clinical laboratory and CLSI interpretations of the reported MIC values were measured using a weighted Cohen κ calculated in SAS version 9.4 software. Total matches were isolates with identical CLSI and clinical laboratory interpretations. Results: In total, 14 antibiotics were assessed. Of those, 9 antibiotics had at least moderate agreement (κ > 0.41) between interpretations. Agreement between the clinical laboratory and the CLSI interpretations were near perfect (κ > 0.81) for 3 antibiotics. Agreement between the clinical laboratory and the CLSI interpretations were poor for cefazolin (0.06) and ertapenem (0.14). Cefotaxime (−0.07) was the only antibiotic that suggested no agreement. Conclusions: Of the antibiotics included in the analysis, 36% had less than moderate agreement between clinical laboratory and CLSI AST interpretations. Given the increases in antimicrobial resistance globally and the emphasis placed on antibiotic stewardship, standardization across clinical AST panels should be prioritized. Inconsistencies have the potential to contribute to inappropriate antibiotic use in addition to under- or overidentification of reportable conditions, including CRE.

Disclosures: None