Farah, W H

Abstract Background Single breath diffusing capacity of the lung for carbon monoxide (DLCO) remains the most widely used test to assess pulmonary gas exchange. GLI DLCO reference equations are based on a larger, more diverse dataset and offer age-specific and internally consistent reference values. However, their impact on interpretation in a real-world population remains uncertain. Research Question Describe the direction and magnitude of DLCO interpretation changes resulting from our multicenter PFT laboratory transition from Miller to GLI reference equations. Study Design and Methods In this multicenter cross-sectional study, we reanalyzed 88,060 DLCO measurements in a large pulmonary function laboratory database performed between 2016 and 2022 using GLI and Miller reference equations, stratified by self-reported race and ethnicity. Baseline patient characteristics and lung function measurements were summarized with continuous characteristics as median (IQR) and categorical variables as n (%). Kruskal-Wallis test was used to evaluate the difference between GLI and Miller DLCO % predicted difference between races, and two-by-two and four-by-four tables were generated to summarize the proportion of concordance and discordance of GLI to Miller severity levels. A repeated measures multivariable logistic regression was used to evaluate discordance between GLI and Miller severity and patient characteristics (age, sex, race, and BMI). Results We included 63,357 individuals with 88,060 PFT visits; 91.6% (58,076) identified as Caucasian, 5.2% (3,262) as Black, 1.4 % (895) as Asian, and 1.8% (1,113) as mixed/other race. Fifty-one percent were female with an median age of 64 years (range: 5- 85). 7.4% (6509) of DLCO results were discordant, with 0.5% (n = 439) abnormal by GLI only, and 6.9% (n = 6070) abnormal by Miller only. Compared to the Miller, GLI interpretations were associated with a greater shift toward normal interpretations. Younger age, lower BMI, female sex, and being of NE Asian, SE Asian, or Other/mixed race compared to Caucasian were associated with higher odds of discordance in DLCO severity/normal classification. Interpretation The use of GLI reference equations substantially alters the interpretation of DLCO results, shifting a meaningful subset of patients from abnormal to normal classification. While GLI reference equations offer more comprehensive, population-based approach, it is crucial to place these interpretations within the context of the patient presentation until further investigations more clearly define the clinical implications of these transitions. This abstract is funded by: none

Abstract Rationale Community-acquired pneumonia (CAP) remains a leading cause of morbidity and mortality worldwide; current guidelines recommend either the use of β-lactam therapy with a macrolide (azithromycin; AZM) or monotherapy with a fluoroquinolone for treatment. Limited evidence exists on their comparative effectiveness. To address this gap, we examined the differences in outcomes among CAP patients treated with β-lactam therapy plus AZM or fluoroquinolone monotherapymethods: We emulated a randomized clinical trial that hypothetically assigned patients to β-lactam therapy plus AZM or fluoroquinolone. Eligible patients were all adults hospitalized for nonsevere community-acquired pneumonia (CAP) based on ATS/IDSA criteria; at Mayo Clinic hospitals (3 academic and 16 community) between May 2018 and September 2022 and received one of the two treatments within 12 hours of admission. Ensemble machine learning with augmented inverse probability weighting (AIPW) was used to evaluate “intention to treat” effects on hospital-free days (HFDs), 180-day mortality, use of advanced respiratory support, in-hospital mortality, and the composite of advanced respiratory support and/or in-hospital mortality. We used the E-value and post-discharge systolic blood pressure (SBP) (negative outcome) to evaluate effects of potential unmeasured confounding and alternative “doubly robust” inverse probably weighting with regression adjustment (IPWRA) to evaluate robustness of the findings. Results 2,451 patients (2,142 β-lactam therapy plus AZM and 309 fluoroquinolone) were eligible and included in the analyses: 53.9% were female, 86.8% were White, and mean age was 58.4 years (SD: 17.02). Compared with β-lactam therapy plus AZM, the fluoroquinolone group experienced significantly higher HFD (1.50 days; 95% CI: 1.08, 1.91), lower use of advanced respiratory support (RR: 0.32; 95% CI: 0.09, 0.54), lower in-hospital mortality (RR: 0.14; 95% CI: 0.00, 0.40), and composite of advanced respiratory support and/or in-hospital mortality (RR: 0.29; 95% CI: 0.08, 0.49). Moderate to large e-values (ranging from 3.50 to 4.74) and use of negative outcomes (post-discharge SBP) suggested that unmeasured confounding is unlikely to change the findings. Sensitivity analysis using IPWRA showed very similar results. Conclusion Among hospitalized patients with non-severe CAP, treatment with fluoroquinolone monotherapy was associated with more hospital-free days, lower in-hospital mortality, and reduced need for advanced respiratory support compared with AZM and β-lactam combination. The findings highlight the role of fluoroquinolone as a beneficial alternative CAP patients. However, further studies are needed to explore the underlying mechanisms driving these differences and assess whether specific patient subgroups may benefit most from quinolone-based therapy. This abstract is funded by: none

Abstract Background Despite the reported benefits, lung cancer screening (LCS) uptake remains alarmingly low in comparison to other cancer screening programs. Objective To develop and evaluate an automated, electronic health record (EHR)-embedded LCS outreach program designed to increase screening uptake while minimizing workload for referring providers and schedulers. Methods We developed an automated outreach and referral program at two Mayo Clinic campuses (Rochester [RST] and northwest Wisconsin [NWW]) coupled with a streamlined virtual care delivery process. Eligible patients were identified based on the information in the EHR regarding US Preventive Services Task Force guidelines for screening and were contacted through either a patient portal message, letter, or both. Outreach included LCS educational materials and self-scheduling instructions for a telephone or video shared decision-making (SDM) visit. During the visit, a licensed care team member discussed the risks and benefits of a low dose computed tomography (LDCT) scan with patients who could choose to enroll in the Lung Cancer Screening Program or decline. Results During the study period, 8,845 eligible patients (RST: 2201, NWW: 6644) were contacted using automated portal messages, letters, or both. Among the RST cohort, 2,156 portal messages and 1,060 letters were distributed in comparison to 7,642 portal messages, 6,441 letters, and 618 text messages in the NWWI cohort. The study showed increase in shared decision-making visits completion and screenings for eligible patients across both groups. Portal engagement was higher among the RST group 75.4% than 55.8% in the NWWI group, as was digital brochure access (14.1% vs 6.5%). Scheduling for share-decision-making visits was noted to be higher among the RST group (22% vs 13.6%), though visit completion rates were similar across sites (12.6 vs 13.6%). A lower opt-out rate was noted among the RST group (12.6% vs. 14.3%). Collectively, both campuses demonstrated meaningful patient engagement. Conclusion The automated outreach program effectively increased lung cancer screening engagement and uptake for eligible patients without adding significant administrative burden on primary care providers and clinical staff. Observed differences in engagement between sites, as well as relatively low completion rates highlight the need for further investigation into contextual and operational factors influencing program performance. This abstract is funded by: none