Risk stratification and outreach to hematology/oncology patients during the COVID-19 pandemic.

PURPOSE: Cancer patients have many medical and psychosocial needs, which may increase during the COVID-19 pandemic. We sought to (1) risk-stratify hematology/oncology patients using general medicine and cancer-specific methods to identify those at high risk for acute care utilization, (2) measure the correlation between two risk stratification methods, and (3) perform a telephone-based needs assessment with intervention for high-risk patients. METHODS: Patients were risk-stratified using a general medical health composite score (HCS) and a cancer-specific risk (CSR) stratification based on disease and treatment characteristics. The correlation between HCS and CSR was measured using Spearman's correlation. A multi-disciplinary team developed a focused needs assessment script with recommended interventions for patients categorized as high-risk by either method. The number of patient needs identified and referrals for services made in the first month of outreach are reported. RESULTS: A total of 1697 patients were risk-stratified, with 17% high-risk using HCS and 22% high-risk using CSR. Correlation between HCS and CSR was modest (ρ = 0.41). During the first month of the pilot, 286 patients were called for outreach with 245 contacted (86%). Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients. CONCLUSION: There is a high burden of unmet medical and psychosocial needs in hematology/oncology patients during the COVID-19 pandemic. A telephone-based outreach program results in the identification of and intervention for these needs; however, additional cancer-specific risk models are needed to improve targeting to high-risk patients.

The Natural Products Discovery Center: Release of the First 8490 Sequenced Strains for Exploring Actinobacteria Biosynthetic Diversity.

Actinobacteria, the bacterial phylum most renowned for natural product discovery, has been established as a valuable source for drug discovery and biotechnology but is underrepresented within accessible genome and strain collections. Herein, we introduce the Natural Products Discovery Center (NPDC), featuring 122,449 strains assembled over eight decades, the genomes of the first 8490 NPDC strains (7142 Actinobacteria), and the online NPDC Portal making both strains and genomes publicly available. A comparative survey of RefSeq and NPDC Actinobacteria highlights the taxonomic and biosynthetic diversity within the NPDC collection, including three new genera, hundreds of new species, and ~7000 new gene cluster families. Selected examples demonstrate how the NPDC Portal's strain metadata, genomes, and biosynthetic gene clusters can be leveraged using genome mining approaches. Our findings underscore the ongoing significance of Actinobacteria in natural product discovery, and the NPDC serves as an unparalleled resource for both Actinobacteria strains and genomes.

Interplay of emerging and established technologies drives innovation in natural product antibiotic discovery.

A continued rise of antibiotic resistance and shortages of effective antibiotics necessitate the discovery and development of new antibiotics with novel modes of action (MoAs) against resistant pathogens. While natural products remain the best resource for antibiotic discovery, their exploration faces many challenges, including (i) unknown MoAs, (ii) high rediscovery rates, (iii) tedious isolation and structure elucidation, and (iv) insufficient production for further development. We have identified recent innovations in screening methods, microbiology, bioinformatics, and metabolomics technologies, as well as natural product-inspired synthesis and synthetic biology, that have contributed to new natural product antibiotics in the past two years. We highlight their interplay as the key element for successful applications, driving future opportunities to increase the pool of natural product-based antibacterial antibiotics.

Education based on publicly-available keyword data is associated with decreased stress and improved trajectory of in-training exam performance.

STUDY OBJECTIVE: This study aimed to assess the impact of data-driven didactic sessions on metrics including fund of knowledge, resident confidence in clinical topics, and stress in addition to American Board of Anesthesiology In-Training Examination (ITE) percentiles. DESIGN: Observational mixed-methods study. SETTING: Classroom, video-recorded e-learning. SUBJECTS: Anesthesiology residents from two academic medical centers. INTERVENTIONS: Residents were offered a data-driven didactic session, focused on lifelong learning regarding frequently asked/missed topics based on publicly-available data. MEASUREMENTS: Residents were surveyed regarding their confidence on exam topics, organization of study plan, willingness to educate others, and stress levels. Residents at one institution were interviewed post-ITE. The level and trend in ITE percentiles were compared before and after the start of this initiative using segmented regression analysis. RESULTS: Ninety-four residents participated in the survey. A comparison of pre-post responses showed an increased mean level of confidence (4.5 ± 1.6 vs. 6.2 ± 1.4; difference in means 95% CI:1.7[1.5,1.9]), sense of study organization (3.8 ± 1.6 vs. 6.7 ± 1.3;95% CI:2.8[2.5,3.1]), willingness to educate colleagues (4.0 ± 1.7 vs. 5.7 ± 1.9;95% CI:1.7[1.4,2.0]), and reduced stress levels (5.9 ± 1.9 vs. 5.2 ± 1.7;95% CI:-0.7[-1.0,-0.4]) (all p < 0.001). Thirty-one residents from one institution participated in the interviews. Interviews exhibited qualitative themes associated with increased fund of knowledge, accessibility of high-yield resources, and domains from the Kirkpatrick Classification of an educational intervention. In an assessment of 292 residents from 2012 to 2020 at one institution, there was a positive change in mean ITE percentile (adjusted intercept shift [95% CI] 11.0[3.6,18.5];p = 0.004) and trajectory over time after the introduction of data-driven didactics. CONCLUSION: Data-driven didactics was associated with improved resident confidence, stress, and factors related to wellness. It was also associated with a change from a negative to positive trend in ITE percentiles over time. Future assessment of data-driven didactics and impact on resident outcomes are needed.