936. Risk Factors and Clinical Outcomes for Extended-Spectrum Beta-Lactamase Producing Enterobacterales Blood Stream Infections in Patients with Hematologic Malignancies

Abstract Background Hematologic malignancy patients have high rates of antibiotic exposure, and increasing resistance is a major concern, particularly with extended-spectrum beta lactamases (ESBL) in Enterobacterales blood stream infections (BSIs). Identifying risk factors for ESBL-producing Enterobacterales (ESBL-E) BSIs may facilitate faster appropriate antibiotic use and decrease mortality. Methods This was a retrospective study of patients with hematologic malignancies and Escherichia coli or Klebsiella spp. bacteremia admitted to Carolinas Medical Center in Charlotte, NC from January 2010 through September 2020. The primary objective was to compare 30-day mortality rates for patients with ESBL-E BSIs to those with non-ESBL-E BSIs. Fisher’s exact or Mann-Whitney U tests were used for primary and secondary clinical outcomes as appropriate. Risk factors associated with 30-day mortality and ESBL production were assessed as secondary objectives using logistic regression models. Results A total of 28 patients with ESBL-E BSIs and 60 patients with non-ESBL-E BSIs were included. The 30-day mortality rate with ESBL-E BSIs was 25% compared to 15% with non-ESBL-E BSIs (P = .373). In-hospital mortality, 30-day infection recurrence, intensive care unit (ICU) admission, and length of stay after culture were not significantly different. However, time to optimal therapy was longer in the ESBL-E group (median 42.3 vs 1.9 hr; P < .001). Multivariate logistic regression analysis showed an association of 30-day mortality with ICU admission (OR 16.7; 95% CI, 3.56-78.4; P < .001) and longer time to optimal therapy (OR 1.03; 95% CI, 1.0-1.05; P = .026). Prior ESBL-positive culture was associated with ESBL-E BSI in the univariate logistic regression (OR 9.83; 95% CI, 1.05-92.56; P = .046). Additionally, prolonged neutropenia (OR 3.05; 95% CI, 1.01-9.23; P = .049) and prior intravenous antibiotic use (OR 2.96; 95% CI, 0.96-9.09; P = .059) were associated with ESBL-E BSI in the multivariate analysis. Conclusion Significantly longer time to optimal therapy was seen in ESBL-E BSIs and was associated with mortality in patients with hematologic malignancies. The identified ESBL risk factors create an opportunity to decrease delay in optimal therapy through risk stratification during initial antibiotic selection. Disclosures Ekaterina Kachur, PharmD, BCOP, Bristol Myers Squibb (Advisor or Review Panel member)Genentech (Employee)Glaxosmithkline (Advisor or Review Panel member)Kyowa Kirin (Advisor or Review Panel member)

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1328. Risk Factors for Severe Influenza Outcomes Among Infants Born Between 2011 and 2019

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab466.1520 ◽

2021 ◽

Vol 8 (Supplement_1) ◽

pp. S752-S752

Author(s):

Sarah Chamseddine ◽

Haniah A Zaheer ◽

John V Williams ◽

Judith M Martin ◽

Anne-Marie Rick ◽

...

Keyword(s):

Risk Factors ◽

Influenza Vaccination ◽

Bacterial Infections ◽

Panel Member ◽

Antibiotic Use ◽

Chronic Medical Conditions ◽

Review Panel ◽

Icu Admission ◽

Severe Influenza ◽

Independent Risk Factors

Abstract Background Influenza in infancy can cause significant morbidity and mortality. This study aimed to characterize influenza outcomes in infants < ορ = 12 months and identify risk factors for severe infection. Methods A retrospective cohort of infants ≤ 12 months born between 2011-2019 who received longitudinal ambulatory and inpatient care within a multi-facility hospital system and had laboratory-confirmed influenza were included. Perinatal, medical and illness characteristics were described. Risk factors for severe influenza (hospitalization, intensive-care unit (ICU) admission, secondary bacterial infections) were analyzed using Chi-square analysis and multivariate logistic regression. Results Among 421 infants with influenza, 134 (32%) were < 6 months (m), 28 (6.5%) were born prematurely (< 35 weeks gestational age), and 41(10%) had chronic medical conditions (CMC). 62 (15%) required hospital admission, 13 (21%) of which required ICU care. No deaths were reported. Secondary bacterial infections were diagnosed in 101 (24%) including acute otitis media (84%), pneumonia (15%) and sinusitis (3%). Prematurity (OR 3.6, 95%CI:1.5-8.3), age < 6m (OR 3.4, 95%CI:1.9-5.9), and CMC (OR 7.6, 95%CI 3.8-15.3) were significantly associated with hospitalization. Prematurity, age < 6m, and CMC were also associated with ICU admission. Infants > 6m (OR 2, 95%CI:1.2-3.5) were more likely to be diagnosed with a secondary bacterial infection than younger infants. Among infants > 6m, complete influenza vaccination (2 doses) was associated with lower rates of antibiotic use (OR 0.5, 95% CI:0.3-0.9) compared to partial or no vaccination, but did not significantly affect hospitalization, ICU admission, or frequency of secondary bacterial infections. Adjusting for prematurity, age < 6m remained associated with hospitalization (aOR 4, 95%CI: 2.1-7.3) as did presence of CMC (aOR 7.3, 95%CI 3.3- 15.7). For ICU admission, age < 6m (aOR 6.3, 95%CI:1.6-24.1) and CMC (aOR 19.7,95%CI:4.9-79.5) were also independent risk factors. Conclusion Younger age and chronic medical conditions were independent risk factors for severe influenza infection. Complete influenza vaccination in eligible age groups was associated with decreased antibiotic use. Disclosures John V. Williams, MD, GlaxoSmithKline (Advisor or Review Panel member, Independent Data Monitoring Committee)Quidel (Advisor or Review Panel member, Scientific Advisory Board) Judith M. Martin, MD, Merck Sharp and Dohme (Consultant)

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1104. Risk Factors and Outcomes of Refractory and/or Resistant Cytomegalovirus (CMV) Infection after Allogeneic Hematopoietic Stem Cell Transplantation

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.1290 ◽

2020 ◽

Vol 7 (Supplement_1) ◽

pp. S582-S583

Author(s):

Eleni Karantoni ◽

Yiqi Su ◽

Anat Stern ◽

Phaedon D Zavras ◽

Sergio Giralt ◽

...

Keyword(s):

Risk Factors ◽

Overall Survival ◽

T Cell ◽

Panel Member ◽

Multivariable Model ◽

Research Support ◽

Review Panel ◽

Material Support ◽

Advisory Boards ◽

Research Grant

Abstract Background The epidemiology of CMV end-organ disease (EOD) after Hematopoietic Cell Transplant (HCT) in the era of preemptive therapy (PET) is defined. In contrast, less data exists on refractory and/or resistant (R/R) CMV. We report on 1) the incidence; 2) risk factors and outcomes of R/R CMV by 1-year post HCT. Methods Retrospective review of 167 CMV seropositive (R+) recipients of first marrow or peripheral blood HCT from 1/2014 - 12/2017 managed by PET. Refractory CMV was defined as failure to achieve >1 log10 decrease in CMV viral load (VL) and having VL >1,000 IU/mL after ≥14 day of PET. Resistant CMV required genotypic confirmation of resistance mutation(s) in UL54 and/or UL97 genes. End organ disease (EOD) was defined by standard criteria. Patients (pts) were followed through 1-year post HCT and were categorized in two mutually exclusive groups as R/R and no R/R. Demographics, clinical characteristics and outcomes were extracted from medical records and hospital databases. Univariable and multivariable logistic models were used to identify risk factors for R/R CMV. Results Of 167 PET recipients, 91 (54.5%) received ex vivo T cell depleted (TCD) HCT; 40 (24.0%) had mismatched donor; and 26 (15.6%) had multiple myeloma. 66/167 (39.5%) pts developed refractory CMV (6 pts also had resistant CMV). Time from HCT to CMV viremia was shorter in R/R group: median (IQR) 21.5 (17.2-27.8) days compared to no R/R group: 26 (19-32) days (p=0.031). Maximum VL was higher for R/R compared to no R/R: median (IQR) 9,118 (2,849-18,456) and 868 (474-1,908), respectively (p< 0.001). In multivariable model, risk factors for R/R included TCD HCT (p< 0.0001) and higher VL at PET initiation (p=0.0002). In contrast, CMV seropositive donor (p=0.035) was protective (Figure 1). CMV EOD developed in 28.2% of R/R and 16.2% of no R/R groups (p=0.085) (Figure 2). Overall survival at 1 year was 59.1% for R/R compared to 83.1% for no R/R group (p=0.00027) (Figure 3). Figure 1. Adjusted odds ratio (OR) and 95% confidence interval (CI) from multivariable model evaluating risk factors of refractory/resistant (R/R) CMV. Figure 2. Cumulative incidence curves of CMV end-organ disease (EOD) at 1-year post HCT Figure 3. Kaplan-Meier survival curves of overall survival (OS) at 1-year post HCT Conclusion 1) Refractory and/or resistant CMV occurred in 39,5% of PET recipients. 2) T-cell depletion and higher CMV VL at PET initiation were risk factors for R/R CMV in multivariable models. 3) R/R CMV was associated with more EOD and worse overall survival. Disclosures Sergio Giralt, MD, Amgen (Advisor or Review Panel member, Research Grant or Support, Served an advisory board for Amgen, Actinuum, Celgene, Johnson & Johnson, JAZZ pharmaceutical, Takeda, Novartis, KITE, and Spectrum pharma and has received research support from Amgen, Actinuum, Celgene, Johnson & Johnson, and Miltenyi, Takeda.) Miguel-Angel Perales, MD, Abbvie (Other Financial or Material Support, Honoraria from Abbvie, Bellicum, Celgene, Bristol-Myers Squibb, Incyte, Merck, Novartis, Nektar Therapeutics, Omeros, and Takeda.)ASTCT (Other Financial or Material Support, Volunteer member of the Board of Directors of American Society for Transplantation and Cellular Therapy (ASTCT), Be The Match (National Marrow Donor Program, NMDP), and the CIBMTR Cellular Immunotherapy Data Resource (CIDR) Committee)Cidara Therapeutics (Advisor or Review Panel member, Other Financial or Material Support, Serve on DSMBs for Cidara Therapeutics, Servier and Medigene, and the scientific advisory boards of MolMed and NexImmune.)Kite/Gilead (Research Grant or Support, Other Financial or Material Support, Received research support for clinical trials from Incyte, Kite/Gilead and Miltenyi Biotec.) Genovefa Papanicolaou, MD, Chimerix (Research Grant or Support)Merck&Co (Research Grant or Support, Investigator and received funding and consulting fees from Merck, Chimerix, Shire and Astellas)

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Risk factors and clinical outcomes associated with blood culture contamination

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2021.111 ◽

2021 ◽

pp. 1-7

Author(s):

Justin M. Klucher ◽

Kevin Davis ◽

Mrinmayee Lakkad ◽

Jacob T. Painter ◽

Ryan K. Dare

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Blood Culture ◽

Hospital Mortality ◽

Clinical Outcomes ◽

Tertiary Care ◽

Blood Cultures ◽

Hospital Charges ◽

Patient Specific ◽

Contaminated Blood

Abstract Objective: To determine patient-specific risk factors and clinical outcomes associated with contaminated blood cultures. Design: A single-center, retrospective case-control risk factor and clinical outcome analysis performed on inpatients with blood cultures collected in the emergency department, 2014–2018. Patients with contaminated blood cultures (cases) were compared to patients with negative blood cultures (controls). Setting: A 509-bed tertiary-care university hospital. Methods: Risk factors independently associated with blood-culture contamination were determined using multivariable logistic regression. The impacts of contamination on clinical outcomes were assessed using linear regression, logistic regression, and generalized linear model with γ log link. Results: Of 13,782 blood cultures, 1,504 (10.9%) true positives were excluded, leaving 1,012 (7.3%) cases and 11,266 (81.7%) controls. The following factors were independently associated with blood-culture contamination: increasing age (adjusted odds ratio [aOR], 1.01; 95% confidence interval [CI], 1.01–1.01), black race (aOR, 1.32; 95% CI, 1.15–1.51), increased body mass index (BMI; aOR, 1.01; 95% CI, 1.00–1.02), chronic obstructive pulmonary disease (aOR, 1.16; 95% CI, 1.02–1.33), paralysis (aOR 1.64; 95% CI, 1.26–2.14) and sepsis plus shock (aOR, 1.26; 95% CI, 1.07–1.49). After controlling for age, race, BMI, and sepsis, blood-culture contamination increased length of stay (LOS; β = 1.24 ± 0.24; P < .0001), length of antibiotic treatment (LOT; β = 1.01 ± 0.20; P < .001), hospital charges (β = 0.22 ± 0.03; P < .0001), acute kidney injury (AKI; aOR, 1.60; 95% CI, 1.40–1.83), echocardiogram orders (aOR, 1.51; 95% CI, 1.30–1.75) and in-hospital mortality (aOR, 1.69; 95% CI, 1.31–2.16). Conclusions: These unique risk factors identify high-risk individuals for blood-culture contamination. After controlling for confounders, contamination significantly increased LOS, LOT, hospital charges, AKI, echocardiograms, and in-hospital mortality.

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