(Re)discovering Educational Purpose: The Common Academic Program (CAP) as an Opportunity for Change

Building on our 2021 Learning Teaching Forum and the Academic Senate’s five-year review of CAP, this panel brings together the four CAP Component Coordinators — Elizabeth Mackay (Humanities Commons), Cassandra Secrease (Principles of Oral Communication, CMM 100), Christopher Brough (Social Science Interdisciplinary SSC 200), and Youssef Farhat (Diversity and Social Justice) — to discuss what we are learning about our components and their values, purposes, and roles in practice. More specifically, we will think together about how our components help us rediscover our roles as coordinators facilitating these conversations; better understand our institutional learning goals and values; and reflect on what has changed or is changing about our components

Responsive and Adaptive: The Common Academic Program (CAP) in a Time of Distress

With its innovative curriculum, the Common Academic Program is a unique learning experience that is responsive and adaptive to the changing times while remaining grounded in the Habits of Inquiry principles and Catholic and Marianist intellectual traditions at the University of Dayton. In 2020, COVID-19 brought new realities and challenges, especially to the student-centered classrooms and personalized educational experiences that CAP attempts to craft and deliver. As tomorrow\u27s leaders, our students must understand the complexities of the world and the crises of the now and the future. CAP is meant to teach them how to respond thoughtfully to such challenges, crises, and opportunities, and to do so with creativity, compassion, and their whole selves. CAP introduces key questions and topics across a wide range of academic disciplines, challenging students to value and synthesize diverse points of view and to examine issues critically with an open mind. In this session, the CAP Component Coordinators — Christopher Brough (Social Sciences, SSC 200), Youssef Farhat (Diversity and Social Justice), Elizabeth Mackay (Humanities Commons), and Cassandra Secrease (Principles of Oral Communication, CMM 100) will reflect on how CAP at large and these components specifically offer and/or create opportunities for faculty and student learning and development. The panelists will introduce themselves to campus community and address a series of reflective questions: What each individual CAP component (SSC 200, CMM100, HC, and DSJ) is designed to do for students and faculty, as well as the University community at large, given the foundational aspects of CAP experiences. How each component pivoted (or didn’t or couldn’t) in Spring 2020 in the remote learning environment. What that moment taught us about our components and CAP communities and where we are taking that learning as we are moving forward in this academic year (2020-21). What role CAP coordinators played in supporting faculty in adapting to and addressing arising changes in the classroom. How, under the circumstances of the pandemic, the CAP coordinators are becoming a more formal, organized, and collaborative group. What our collaboration can mean for the larger CAP community

Sharing Commonality in Our Aspirations: The Common Academic Program (CAP) as a Community of Learners

What does it take to prepare future leaders through CAP foundational courses? Three years into their roles, the four CAP Component Coordinators-- Elizabeth Mackay (Humanities Commons), Cassandra Secrease (Principles of Oral Communication, CMM 100), Christopher Brough (Social Science Interdisciplinary, SSC 200), Youssef Farhat (Diversity and Social Justice) -- come together to discuss how their components help instill a sense of community and agency in our students, share updates and reflect on lessons learned from the University Senate’s planned 5-Year Review of CAP. More specifically, we will think together about how our components, individually and collectively, help us rediscover our roles in supporting faculty in shaping future leadership inspired by our institutional learning goals and values

Predictive Factors for Latency Period and a Prognostic Model for Survival in Patients with Therapy-Related AML

Abstract Abstract 2589 Therapy-related acute myeloid leukemia (t-AML) is an increasingly recognized sequela in patients (pts) receiving chemotherapy or radiotherapy for a primary malignancy or autoimmune disease. Factors that adversely affect treatment response and survival in t-AML pts include poor cytogenetics, type of antecedent disorder (AD) and type of preceding therapy. The goal of this study was to design a comprehensive prognostic model integrating pt disease- and treatment-related characteristics to predict clinical outcome and to assess factors related to the latency period (LP) between the AD and t-AML diagnosis (dx). We evaluated a retrospective cohort of newly diagnosed t-AML pts treated at Cleveland Clinic from 2001 to 2011. Data on age at initial dx of AD, type of AD, preceding treatment, type of chemotherapy, age at t-AML dx, gender, peripheral blood counts at t-AML dx, peripheral and marrow blasts, pathologic classification, metaphase cytogenetics (per CALGB/Alliance 8461 criteria), LP, complete remission (CR) and overall survival (OS) measured from t-AML dx were collated from our IRB approved AML database. Multivariable log-linear, logistic, and proportional hazards models with step-wise variable selection were used to identify independent predictors of each outcome. Of 730 patients treated with cytarabine-based induction chemotherapy over the 10-year period, 77 had t-AML. Most (68%) were female; median age at dx of antecedent disorder was 56 years (range, 16–75); median age at t-AML dx was 61 yrs (range, 19–79); and median latency period to t-AML dx was 4.6 yrs (range, 0.5–38.4). Most (71%) had an antecedent solid tumor [breast cancer (44%), prostate (10%); colon (6%), other organ sites (8%); 23% had a prior hematologic malignancy [non-Hodgkin lymphoma (16%), Hodgkin lymphoma (4%), and leukemia (4%)]; and 5% had autoimmune diseases. Previous treatments for AD included radiation (26%), chemotherapy (30%), and chemotherapy and radiation (44%). Of 57 pts previously treated with chemotherapy, 68% received alkylating agents, 65% anthracyclines, 51% mitotic inhibitors (MI) and 30% all three drug classes. Cytogenetic risk distribution at t-AML dx was: favorable (19%), intermediate-risk (52%), and unfavorable (29%). Overall, 48 pts (62%) achieved a CR with induction chemotherapy and median OS was 9.6 months, with 30% surviving >2 years. Independent prognostic factors of shorter LP were age at AD >55 (p=.001) and prior treatment with MI (p=.001). Median LP for pts aged 55 but no prior MI, and 2.0 years for pts >55 and prior treatment with MI. Age at t-AML (p=.001) was the only independent predictor of CR. Independent predictors for inferior OS were unfavorable cytogenetics (p=.002), antecedent hematologic or autoimmune disease (p=0.007) and platelet counts <25000/μL at the time of t-AML dx (p=0.02). A prognostic model based on these factors categorized t-AML pts into two risk groups based on previous diagnosis type, cytogenetics, and platelet count at t-AML dx (Table 1). This score-based risk stratification used a cutoff of 2 points to categorize pts as favorable or unfavorable. Pts with a favorable profile had an estimated median OS of 28.4 months compared to 5.0 months for pts with an unfavorable profile (p=.0003). In conclusion, multicomponent prognostic models that integrate well-established disease or treatment-related covariates can be clinically helpful in risk stratifying t-AML pts undergoing induction therapy, identifying those who might benefit from more intensive interventions. Table 1. Predictive model for OS using cytogenetics, antecedent disease and platelet count at t-AML diagnosis Risk Group Score Patients N Median Survival (Months) Hazard Ratio (95% CI) p Solid tumor (0 points) and favorable cytogenetics (0) OR Solid tumor (0), intermediate cytogenetics (2), and platelets > 25000 (0) OR Favorable 0 or 2 38 28.4 Hematologic/autoimmune (2), favorable cytogenetics (0), and platelets >25000 (0) Unfavorable cytogenetics (3) OR Solid tumor (0), intermediate cytogenetics (2) and platelets 2 37 5.0 2.70 (1.57-4.64) .0003 Hem/autoimmune (2), favorable cytogenetics (0) and platelets <25000 (2) OR Hematologic/autoimmune (2) and intermediate cytogenetics (2) Disclosures: No relevant conflicts of interest to declare

Impact of Myocardial Infarction On Survival in Acute Myeloid Leukemia

Abstract Abstract 4321 Acute myeloid leukemia (AML) may present with vascular phenomena, commonly manifested in the pulmonary and neurologic systems, and often attributed to leukostasis, thrombotic abnormalities as with acute promyelocytic leukemia (APL), and anemia. Myocardial infarction (MI) may be the initial presentation of these vascular changes, preceding a diagnosis of AML. We reviewed the incidence of MI in the setting of a new AML diagnosis, associated risk factors, and impact on overall survival (OS). All patients diagnosed with AML at Cleveland Clinic between 2001 and 2012 who were also diagnosed with MI (either a ST-elevation MI or a non-ST-elevation MI with compatible cardiac biomarkers) at the time of AML diagnosis (median same day, range from 2 days before to 93 days after MI diagnosis) were identified (cases). We performed a case-control analysis in which MI patients were randomly matched 3:1 to non-MI patients based on gender, age at diagnosis (±5 years), year of diagnosis (±3 years), and if available, cytogenetics and etiology. Overall survival (OS) was the primary endpoint; also compared were MI risk factors (previous MI, hypertension, hyperlipidemia, and diabetes); complete blood count (CBC) characteristics (white count, hemoglobin, and platelets); and AML type (APL and non-APL). Statistical analyses included Fisher's exact, chi-square, and Wilcoxon rank sum test (patient characteristics and MI risk factors); and the logrank test and frailty models (OS). Out of 774 AML patients, 12 (1.6%) presented with a MI: 54% were male and the median age at diagnosis was 61 years (range 19–94); 19% had one of more risk factors for MI (heart disease, hypertension, hyperlipidemia, and diabetes); 52% were non-smokers, 25% were former smokers, and 23% currently smoked. Most (71%) were newly-diagnosed, 24% had prior myelodysplastic or myeloproliferative neoplasms, 6% was therapy-related, and 6% had APL. Most (83%) received standard cytarabine-based induction therapy, and 67% achieved a complete remission. Median follow-up for patients still alive was 19.3 months. Of the patients presenting with MI, 11 of 12 have died with a median OS of 7.9 months, compared with a median OS of 13.1 months in the entire non-MI cohort (95% CI 11.0–15.1, p=.02). MI remained associated with worse OS in multivariable analyses (HR 1.71, 0.91–3.22, p=.09). In case-control analyses, controls had a median OS of 14.0 months compared to 7.9 months for MI cases (95% CI 8.7–26.6, p=.04 adjusting for the matching and number of comorbidities present, Figure). Factors associated with MI included previous MI (p=.01) and > 2 comorbidities (p=.02). Other MI risk factors, CBC characteristics, and APL compared to non-APL did not differ significantly between the two groups. In conclusion, AML patients presenting with MI have a worse OS than non-MI AML patients. Preceding comorbidities place patients at greater risk for MI than leukemia-related factors. Disclosures: Advani: Novartis: Research Funding. Maciejewski:Novartis: Research Funding. Sekeres:Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau

Comparison of diagnoses of early-onset sepsis associated with use of Sepsis Risk Calculator versus NICE CG149: a prospective, population-wide cohort study in London, UK, 2020–2021

Objective We sought to compare the incidence of early-onset sepsis (EOS) in infants ≥34 weeks’ gestation identified &gt;24 hours after birth, in hospitals using the Kaiser Permanente Sepsis Risk Calculator (SRC) with hospitals using the National Institute for Health and Care Excellence (NICE) guidance.Design and setting Prospective observational population-wide cohort study involving all 26 hospitals with neonatal units colocated with maternity services across London (10 using SRC, 16 using NICE).Participants All live births ≥34 weeks’ gestation between September 2020 and August 2021.Outcome measures EOS was defined as isolation of a bacterial pathogen in the blood or cerebrospinal fluid (CSF) culture from birth to 7 days of age. We evaluated the incidence of EOS identified by culture obtained &gt;24 hours to 7 days after birth. We also evaluated the rate empiric antibiotics were commenced &gt;24 hours to 7 days after birth, for a duration of ≥5 days, with negative blood or CSF cultures.Results Of 99 683 live births, 42 952 (43%) were born in SRC hospitals and 56 731 (57%) in NICE hospitals. The overall incidence of EOS (&lt;72 hours) was 0.64/1000 live births. The incidence of EOS identified &gt;24 hours was 2.3/100 000 (n=1) for SRC vs 7.1/100 000 (n=4) for NICE (OR 0.5, 95% CI (0.1 to 2.7)). This corresponded to (1/20) 5% (SRC) vs (4/45) 8.9% (NICE) of EOS cases (χ=0.3, p=0.59). Empiric antibiotics were commenced &gt;24 hours to 7 days after birth in 4.4/1000 (n=187) for SRC vs 2.9/1000 (n=158) for NICE (OR 1.5, 95% CI (1.2 to 1.9)). 3111 (7%) infants received antibiotics in the first 24 hours in SRC hospitals vs 8428 (15%) in NICE hospitals.Conclusion There was no significant difference in the incidence of EOS identified &gt;24 hours after birth between SRC and NICE hospitals. SRC use was associated with 50% fewer infants receiving antibiotics in the first 24 hours of life

Pain, Analgesic Use, and Patient Satisfaction With Spinal Versus General Anesthesia for Hip Fracture Surgery : A Randomized Clinical Trial.

BACKGROUND: The REGAIN (Regional versus General Anesthesia for Promoting Independence after Hip Fracture) trial found similar ambulation and survival at 60 days with spinal versus general anesthesia for hip fracture surgery. Trial outcomes evaluating pain, prescription analgesic use, and patient satisfaction have not yet been reported. OBJECTIVE: To compare pain, analgesic use, and satisfaction after hip fracture surgery with spinal versus general anesthesia. DESIGN: Preplanned secondary analysis of a pragmatic randomized trial. (ClinicalTrials.gov: NCT02507505). SETTING: 46 U.S. and Canadian hospitals. PARTICIPANTS: Patients aged 50 years or older undergoing hip fracture surgery. INTERVENTION: Spinal or general anesthesia. MEASUREMENTS: Pain on postoperative days 1 through 3; 60-, 180-, and 365-day pain and prescription analgesic use; and satisfaction with care. RESULTS: A total of 1600 patients were enrolled. The average age was 78 years, and 77% were women. A total of 73.5% (1050 of 1428) of patients reported severe pain during the first 24 hours after surgery. Worst pain over the first 24 hours after surgery was greater with spinal anesthesia (rated from 0 [no pain] to 10 [worst pain imaginable]; mean difference, 0.40 [95% CI, 0.12 to 0.68]). Pain did not differ across groups at other time points. Prescription analgesic use at 60 days occurred in 25% (141 of 563) and 18.8% (108 of 574) of patients assigned to spinal and general anesthesia, respectively (relative risk, 1.33 [CI, 1.06 to 1.65]). Satisfaction was similar across groups. LIMITATION: Missing outcome data and multiple outcomes assessed. CONCLUSION: Severe pain is common after hip fracture. Spinal anesthesia was associated with more pain in the first 24 hours after surgery and more prescription analgesic use at 60 days compared with general anesthesia. PRIMARY FUNDING SOURCE: Patient-Centered Outcomes Research Institut