Libertin, Claudia R.

Introduction Surgical site infections (SSI) continue to be a risk associated with surgery. The Centers for Disease Control (CDC) uses surgical wound class (SWC) to predict SSI postoperatively. Prior studies have shown that the current wound class definitions are unreliable for surgical subspecialties. Therefore, an alternative surgical wound classification (ASWC) was created to more accurately reflect risk of SSI following orthopedic procedures. The purpose of this study was to compare the two systems. Methods Seventy patients who developed 90-day SSI following total joint arthroplasty (TJA) were matched 1:1 to patients without postoperative SSI. The SWC was recorded from operative reports. Wounds were then retrospectively reclassified according to the ASWC based on preoperative history from the medical record. The degree of agreement and degree of association with occurrence of SSI was compared between the two systems. Results The proportion of agreement between the systems was poor (41.4%). The current SWC was associated with risk of SSI in both unadjusted (p=0.045) and multivariable analysis (p=0.050). Comparatively, the ASWC demonstrated a stronger association with SSI in both unadjusted (p=0.001) and multivariable analysis (p=0.001). Conclusion The results of this study suggest that the ASWC is more predictive for SSI following TJA than the current SWC definitions for total joint arthroplasty.

Abstract Background Few antiviral therapies have been studied in patients with coronavirus disease 2019 (COVID-19) and kidney impairment. Herein, the efficacy, safety, and pharmacokinetics of remdesivir, its metabolites, and sulfobutylether-β-cyclodextrin excipient were evaluated in hospitalized patients with COVID-19 and severe kidney impairment. Methods In REDPINE, a phase 3, randomized, double-blind, placebo-controlled study, participants aged ≥12 years hospitalized for COVID-19 pneumonia with acute kidney injury, chronic kidney disease, or kidney failure were randomized 2:1 to receive intravenous remdesivir (200 mg on day 1; 100 mg daily up to day 5) or placebo (enrollment from March 2021 to March 2022). The primary efficacy end point was the composite of the all-cause mortality rate or invasive mechanical ventilation rate through day 29. Safety was evaluated through day 60. Results Although enrollment concluded early, 243 participants were enrolled and treated (remdesivir, n = 163; placebo, n = 80). At baseline, 90 participants (37.0%) had acute kidney injury (remdesivir, n = 60; placebo, n = 30), 64 (26.3%) had chronic kidney disease (remdesivir, n = 44; placebo, n = 20), and 89 (36.6%) had kidney failure (remdesivir, n = 59; placebo, n = 30); and 31 (12.8%) were vaccinated against COVID-19. Composite all-cause mortality or invasive mechanical ventilation rates through day 29 were 29.4% and 32.5% in the remdesivir and placebo group, respectively (P = .61). Treatment-emergent adverse events were reported in 80.4% for remdesivir versus 77.5% for placebo, and serious adverse events in 50.3% versus 50.0%, respectively. Pharmacokinetic plasma exposure to remdesivir was not affected by kidney function. Conclusions Although the study was underpowered, no significant difference in efficacy was observed between treatment groups. REDPINE demonstrated that remdesivir is safe in patients with COVID-19 and severe kidney impairment. Clinical Trials Registration EudraCT 2020-005416-22; Clinical Trials.gov NCT04745351.

Background: While ‘immuno-competence’ is a well-known term, it lacks an operational definition. To address this omission, this study explored whether the temporal and structured data of the complete blood cell count (CBC) can rapidly estimate immuno-competence. To this end, one or more ratios that included data on all monocytes, lymphocytes and neutrophils were investigated. Materials and methods: Longitudinal CBC data collected from 101 COVID-19 patients (291 observations) were analyzed. Dynamics were estimated with several approaches, which included non-structured (the classic CBC format) and structured data. Structured data were assessed as complex ratios that capture multicellular interactions among leukocytes. In comparing survivors with non-survivors, the hypothesis that immuno-competence may exhibit feedback-like (oscillatory or cyclic) responses was tested. Results: While non-structured data did not distinguish survivors from non-survivors, structured data revealed immunological and statistical differences between outcomes: while survivors exhibited oscillatory data patterns, non-survivors did not. In survivors, many variables (including IL-6, hemoglobin and several complex indicators) showed values above or below the levels observed on day 1 of the hospitalization period, displaying L-shaped data distributions (positive kurtosis). In contrast, non-survivors did not exhibit kurtosis. Three immunologically defined data subsets included only survivors. Because information was based on visual patterns generated in real time, this method can, potentially, provide information rapidly. Discussion: The hypothesis that immuno-competence expresses feedback-like loops when immunological data are structured was not rejected. This function seemed to be impaired in immuno-suppressed individuals. While this method rapidly informs, it is only a guide that, to be confirmed, requires additional tests. Despite this limitation, the fact that three protective (survival-associated) immunological data subsets were observed since day 1 supports many clinical decisions, including the early and personalized prognosis and identification of targets that immunomodulatory therapies could pursue. Because it extracts more information from the same data, structured data may replace the century-old format of the CBC.

Abstract Background Early diagnosis, prognostication, and treatment initiation are the cornerstones of sepsis management. There remains an immense interest in exploring the diagnostic and prognostic roles of neutrophil-lymphocyte ratio (NLR) in the sepsis population. Methods We performed a retrospective multi-center observational study including patients admitted to different Mayo Clinic sites with a diagnosis of sepsis between October 2018 and August 2022. Patients were excluded if they were aged < 18 years, lacked research authorization, or had missing Neutrophil or Lymphocyte count at admission. Data were collected from an existing sepsis database and Mayo Data Explorer (MDE). Categorical variables were summarized as percentages and continuous variables were summarized as medians. Chi-square test for significance, independent sample t-test, and multivariate Cox Proportional Hazard models were performed on IBM SPSS Statistics v28.0. Results Our study cohort consisted of 13968 patients, of which the majority were males (55.9%), Caucasian (91.6%), and non-Hispanic or Latino (94.3%). The median age of the cohort was 71 (60, 80) years, and the median BMI was 27.7 (23.4, 33.3) kg/m2. Among all sepsis patients, 6.0% had a positive blood culture and the most common organisms were E. coli (26.5%), Klebsiella sp. (15.6%), Streptococcus sp. (12.8%) and Staphylococcus aureus (9.9%). 13131 patients (94.1%) survived the hospital stay and 837 (5.9%) did not. There was no difference in mortality based on blood culture positivity status (6.0% vs 6.6%, p=0.41). However, the median NLR was higher among patients with a positive blood culture (16.4 vs. 12.1, p< 0.001) and among non-survivors (14.3 vs 12.2, p< 0.001). NLR did not significantly vary based on the type of organism growing in the blood culture. A multivariate model revealed NLR as an independent predictor of mortality (HR 1.003, 95% CI: 1.000-1.006, p=0.029) after adjusting for comorbidities, baseline clinical and laboratory variables. (Tables 1 & 2) Conclusion Our retrospective multicentric study showed that the Neutrophil-Lymphocyte ratio at admission was higher among bacteremic sepsis patients and non-survivors. Further prospective studies are needed to explore its diagnostic and prognostic utility. Disclosures All Authors: No reported disclosures

AbstractBackgroundWhile COVID‐19 immunization programs attempted to reach targeted rates, cases rose significantly since the emergence of the delta variant. This retrospective cohort study describes the correlation between antispike antibodies and outcomes of hospitalized, breakthrough cases during the delta variant surge.MethodsAll patients with positive SARS‐CoV‐2 polymerase chain reaction hospitalized at Mayo Clinic Florida from 19 June 2021 to 11 November 2021 were considered for analysis. Cases were analyzed by vaccination status. Breakthrough cases were then analyzed by low and high antibody titers against SARS‐CoV‐2 spike protein, with a cut‐off value of ≥132 U/ml. Outcomes included hospital length of stay (LOS), need for intensive care unit (ICU), mechanical ventilation, and mortality. We used 1:1 nearest neighbor propensity score matching without replacement to assess for confounders.ResultsAmong 627 hospitalized patients with COVID‐19, vaccine breakthrough cases were older with more comorbidities compared to unvaccinated. After propensity score matching, the unvaccinated patients had higher mortality (27 [28.4%] vs. 12 [12.6%], p = 0.002) and LOS (7 [1.0–57.0] vs. 5 [1.0–31.0] days, p = 0.011). In breakthrough cases, low‐titer patients were more likely to be solid organ transplant recipients (16 [34.0%] vs. 9 [12.3%], p = 0.006), with higher need for ICU care (24 [51.1%] vs. 22 [11.0%], p = 0.034), longer hospital LOS (median 6 vs. 5 days, p = 0.013), and higher mortality (10 [21.3%] vs. 5 [6.8%], p = 0.025) than high‐titer patients.ConclusionsHospitalized breakthrough cases were more likely to have underlying risk factors than unvaccinated patients. Low‐spike antibody titers may serve as an indicator for poor prognosis in breakthrough cases admitted to the hospital.

Abstract Background Treating COVID-19 infection in SOT is challenging due to long-term use of immunosuppressive agents. REM is the only FDA-approved anti-viral for SARS-COV-2 infection. DEX showed decrease in mortality in the Recovery Trial. COVID-19 treatment guidelines for SOT patients are the same as NTP despite limited literature on those outcomes. Our primary objective was to determine if 30-day mortality was different between SOT and NTP matched cohorts using these 2 drugs. The secondary objectives included comparisons of length of stay (LOS), days on mechanical ventilation (DMV), and the use of other treatment modalities. Methods We retrospectively collected data for hospitalized SOT and NTP, 18 years and older, with pcr-confirmed SARS-CoV-2 infection receiving REM and DEX from May 1, 2020, to October 10, 2020, at Mayo Clinic Florida. IRB approval was obtained. Descriptive statistics were used to analyze the data. Continuous variables were summarized as mean (standard deviation) or median (range) where appropriate, while categorical variables were reported as frequency (percentage). Results Of 80 patients who met the inclusion criteria, 28 were SOT, and 52 were NTP. The SOT cohort was subcategorized below: SOT patients were significantly younger than NTP (p < .001). Further, SOT patients had significantly longer LOS (p = 0.043) and more COVID-19 modalities (75% vs. 36.5%, p = 0.002) compared to NTP. Among the 28 SOT patients, 2 of them died within 30 days of admission, and among the 52 NTP patients, 7 of them died within 30 days. The 30-d survival estimate for SOT group is 92.9% (95% CI: 83.8% - 100.0%) and for NTP group is 86.5% (95% CI: 77.7% - 96.3%). The log-rank test was not significant between the groups (p=0.37), but the NTP has a worse survival curve from the figure below. SOT-NTP Survival Curve Conclusion SOT group was younger, had longer LOS, and more COVID-related modalities. The 30-d survival estimate for SOT group is 92.9% and for NTP group is 86.5%, but the survival curve for NTP was worse likely secondary to age. Use of REM & DEX in SOT recipients is a valid recommendation. Disclosures Claudia R. Libertin, MD, Gilead (Grant/Research Support)

Abstract Background To determine whether CBC differentials of COVID+ inpatients can predict, at admission, both maximum oxygen requirements (MOR) and 30-day mortality. Methods Based on an approved IRB protocol, CBC differentials from the first 3 days of hospitalization of 12 SARS CoV-2 infected patients were retrospectively extracted from hospital records and analyzed with a privately owned Pattern Recognition Software (PRS, US Patent 10,429,389 B2) previously validated in sepsis, HIV, and hantavirus infections. PRS partitions the data into subsets immunologically dissimilar from one another, although internally similar. Results Regardless of the angle considered, the classic analysis −which measured the percentages of lymphocytes, monocytes, and neutrophils− did not distinguish outcomes (A). In contrast, non-overlapping patterns generated by the PRS differentiated 3 (left, vertical, and right) groups of patients (B). One subset was only composed of survivors (B). The remaining subsets included the highest oxygenation requirements (B). At least two immunologically interpretable, multi-cellular indicators distinguished the 3 data subsets with statistically significant differences (C, p≤ 0.05). Survivors (the left subset) showed lower N/L and/or higher M/L ratios than non-survivors (the vertical subset, C).Therefore, PRS partitioned the data into subsets that displayed both biological and significant differences. Because it offers visually explicit information, clinicians do not require a specialized training to interpret PRS-generated results. CBCs vs. outcomes - Software-analyzed CBCs vs. outcomes Conclusion (1) Analysis of blood leukocyte data predicts MOR and 30-d mortality. (2) Real time PRS analysis facilitates personalized medical decisions. (3) PRS measures two dimensions rarely assessed: multi-cellularity and dynamics. (4) Even with very small datasets, PRS may achieve statistical significance. (5) Larger COVID+ infected cohort is being analyzed for potential commercialization. Disclosures Claudia R. Libertin, MD, Gilead (Grant/Research Support)

Abstract Background Severe coronavirus disease 2019 (COVID-19) often results from the immune-mediated cytokine storm, triggered by granulocyte macrophage-colony stimulating factor (GM-CSF), potentially leading to respiratory failure and death. Lenzilumab, a novel anti-human GM-CSF monoclonal antibody, neutralizes GM-CSF and demonstrated potential to improve clinical outcomes in a matched case-cohort study of patients with severe COVID-19 pneumonia. This Phase 3 randomized, double-blind, placebo-controlled trial investigated the efficacy and safety of lenzilumab to improve the likelihood of survival without invasive mechanical ventilation (SWOV), beyond available treatments. Methods Hypoxic patients, hospitalized with COVID-19 (n=520), requiring supplemental oxygen, but not invasive mechanical ventilation, were randomized on Day 0 to receive lenzilumab (1800mg, n=261) or placebo (n=259), and available treatments, including remdesivir and/or corticosteroids; and were followed through Day 28. Results Baseline demographics were comparable between groups: male, 64.7%; mean age, 60.5 years; median CRP, 79.0 mg/L. Patients across both groups received steroids (93.7%), remdesivir (72.4%), or both (69.1%). Lenzilumab improved the primary endpoint, likelihood of SWOV in the mITT population, by 1.54-fold (HR: 1.54; 95%CI: 1.02-2.32, p=0.0403). Lenzilumab improved SWOV by 1.91-fold (nominal p=0.0073) and 1.92-fold (nominal p=0.0067) in patients receiving remdesivir or remdesivir and corticosteroids, respectively. A key secondary endpoint of incidence of IMV, ECMO or death was also improved in patients receiving remdesivir (p=0.020) or remdesivir and corticosteroids (p=0.0180). Treatment-emergent serious adverse events were similar across both groups. Conclusion Lenzilumab significantly improved SWOV in hypoxic COVID-19 patients upon hospitalization, with the greatest benefit observed in patients receiving treatment with remdesivir and corticosteroids. NCT04351152 Disclosures Zelalem Temesgem, MD, Humanigen, Inc (Grant/Research Support) Jason Baker, MD, Humanigen, Inc (Grant/Research Support) Christopher Polk, MD, Atea (Research Grant or Support)Gilead (Advisor or Review Panel member, Research Grant or Support)Humanigen (Research Grant or Support)Regeneron (Research Grant or Support) Claudia R. Libertin, MD, Gilead (Grant/Research Support) Colleen F. Kelley, MD, MPH, Gilead Sciences (Individual(s) Involved: Self): Grant/Research Support; Moderna (Individual(s) Involved: Self): Grant/Research Support; Novavax (Individual(s) Involved: Self): Grant/Research Support; Viiv (Individual(s) Involved: Self): Grant/Research Support Vincent Marconi, MD, Bayer (Consultant, Scientific Research Study Investigator)Eli Lilly (Consultant, Scientific Research Study Investigator)Gilead Sciences (Consultant, Scientific Research Study Investigator)ViiV (Consultant, Scientific Research Study Investigator) Victoria Catterson, PhD, Humanigen, Inc (Consultant) William Aronstein, MD, PhD, Humanigen, Inc (Consultant) Cameron Durrant, MD, Humanigen, Inc (Employee) Dale Chappell, MD, Humanigen, Inc (Employee) Omar Ahmed, PharmD, Humanigen, Inc (Employee) Gabrielle Chappell, MSc, Humanigen, Inc (Consultant) Andrew Badley, M.D., AbbVie (Consultant) for the LIVE-AIR Study Group, n/a, Humanigen, Inc (Grant/Research Support)

Introduction In the unprecedented era of COVID-19, ongoing research and evolution of evidence has led to ever-changing guidelines for clinical monitoring and therapeutic options. Formulating treatment protocols requires the understanding and application of the evolving research. Objective The primary objective of this study is to present a systematic evidence-based approach to synthesize the necessary data in order to optimize the management of COVID-19. Methods At Mayo Clinic Florida, we developed a multidisciplinary centralized COVID Treatment Review Panel (TRP) of expert pulmonologists, intensivists, infectious disease specialists, anesthesiologists, hematologists, rheumatologists, and hospitalists that in real-time reviews the latest evidence in peer-reviewed journals, the available clinical trials, and help guide the rapid application of therapeutics or interventions to the patient and the bedside provider. Results/Conclusions The multi-disciplinary team approach of synthesizing clinical data and coordinating care is effective in responding to rapidly evolving and changing evidence. Systematic data collection and evidence-based treatment algorithms enable physicians to rapidly translate the current literature to clinical practice, and improve care and outcomes of patients.