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OBJECTIVE Sepsis is associated with significant morbidity and mortality in pediatric hematology, oncology, and transplant (PHOT) patients. This study characterized PHOT patients who developed hospital-onset sepsis more than 12 hours after admission and identified risk factors for 30-day sepsis-attributable (SA) mortality. PATIENTS AND METHODS We analyzed an existing multicenter database of sepsis collected prospectively over 5 years (2017–2021) as part of the Improving Pediatric Sepsis Outcomes Collaborative. Sepsis was defined using operational elements documented in the health records based on International Classification of Diseases, Tenth Revision codes, treatment, diagnostic tests, and sepsis screen, huddle, or order set use. RESULTS A total of 9604 sepsis episodes in PHOT patients from 49 hospitals were analyzed: 70.5% were identified in the emergency department (ED), 10.9% in inpatient settings less than or equal to 12 hours from admission, and 18.6% were hospital onset. Only 52.5% of patients with hospital-onset sepsis were identified using a sepsis recognition method compared with 87.2% in the ED (P < .001). The overall 30-day SA mortality was 2.2%, with a higher rate (6.9%) among those with hospital-onset sepsis compared with those who developed sepsis at presentation or less than or equal to 12 hours (1.1%, P < .001). CONCLUSIONS Although the difference in SA mortality between hospitalized and nonhospitalized patients may be impacted by nonmeasurable confounders inherent to the type of patients presenting in the different care settings, we reported system-based improvements that may reduce mortality. The 30-day SA mortality was lower in hospitalized PHOT patients when sepsis was detected by early recognition methods, supporting the need for efforts to implement sepsis recognition tools in the inpatient setting.

Abstract Aims Atrial fibrillation (AF) is the most common cardiac arrhythmia. Although lipoprotein(a) [Lp(a)] is known to be a well-established risk factor for atherosclerotic cardiovascular disease, its role in the development of AF, independent of this association, remains unclear. Methods and results Adult patients from the three Mayo Clinic sites with a baseline Lp(a) and without AF history were included. Patients were categorized into two groups based on their Lp(a) levels: high Lp(a) (≥50 mg/dL) and low Lp(a) (<50 mg/dL). Survival probabilities free from incident AF were compared between Lp(a) groups, during a follow-up period up to 15 years, using the Kaplan–Meier curve and the log-rank test. Multivariable Cox regression analysis was also conducted. A total of 75 376 patients were included (median age: 55 years, 59% males), with a median follow-up duration of 8.8 (inter-quartile range: 3.4, 14.8) years. Incident AF was detected in 5738 (7.6%) patients. Survival probability free from incident AF was significantly lower in patients with elevated Lp(a) (86%) compared with those with low Lp(a) (88%, log-rank P < 0.001). Multivariable analysis adjusted for potential risk factors of AF showed a statistically significant association of elevated Lp(a) with an 11% increase in AF risk (adjusted hazard ratio: 1.11, 95% confidence interval: 1.05–1.18). Conclusion Our study suggests that elevated Lp(a) (≥50 mg/dL) is an independent risk factor for incident AF. Future prospective studies are warranted to validate our results and to test if reducing Lp(a) could mitigate the burden of AF.

BACKGROUND: Increased specialty competitiveness, alongside the inception of virtual interviews, has increased the number of applications submitted to the Electronic Residency Application Service (ERAS) in anesthesiology. ERAS introduced signals to provide applicants with a means to demonstrate interest in a select group of residency programs. In the 2023 to 2024 application cycle, anesthesiology applicants had the opportunity to send 5 gold and 10 silver signals in a tiered system. METHODS: This multicenter, cross-sectional (exempt) research survey was created by members of the executive council of the Association of Anesthesiology Core Program Directors (AACPD) and housed and distributed through REDCap and the University of Nebraska Medical Center. Publicly available contact information of anesthesiology core program directors was obtained from the Accreditation Council for Graduate Medical Education (ACGME) website and membership roster of the AACPD. In total, 174 anesthesiology programs were identified. A survey invitation was distributed on March 12, 2024, to all programs via e-mail with reminders. The survey closed on April 30, 2024. Survey responses were collected anonymously, with instructions to provide 1 response per program. All statistical summaries and analyses were performed using SAS 9.3 (SAS Institute). RESULTS: The survey was sent to all 174 identified programs, with a response rate of 48.9%. Small programs were defined as having <44 residents, medium 44 to 62 residents, and large >62 residents. Small programs received significantly fewer applications (median 1255) than medium (1420) and large (1558) programs ( P = .0005). There was a statistically significant difference in the number of gold signals received based on program size, with large programs receiving significantly more than medium (169 vs 116, P = .0238) or small programs (168 vs 71, P < .0001). Applicants sending gold signals were more likely to receive an interview compared to those who sent silver signals (56.7% vs 31%, P ≤ .0001). Of the those interviewed, applicants who sent gold signals comprised 42% (28.7%–52.6%), whereas applicants who sent silver signals comprised 45.5% (33%–54.7%). Applicants who did not send a program signal but signaled geographically made up a smaller portion of the interview group at 3% (0%–15.4%). The percentage of matched residents sending gold signals made up 66.7% (47.1%–82.4%) of a program’s match list, whereas those sending silver signals were 25% (11.1%–33.3%) of the matched cohort. CONCLUSIONS: Anesthesiology applicants who sent program signals were selected for a large majority of available interview positions, and interviewed applicants who submitted gold and silver signals comprised the vast majority of matched resident cohorts.

Objectives: Cervical esophageal cancer (CEC) is an uncommon malignancy accounting for <5% of all esophageal carcinomas. Treatment of CEC varies and is adapted from established regimens used for squamous cell carcinoma (SCC) or the lower esophageal and head and neck. The present systematic review and guidelines are intended to assist treatment decision making for patients with CEC based on the available evidence. Methods: Using the Population, Intervention, Comparator, Outcome, Timing, and Study Design (PICOTS) framework, the evidence regarding treatment outcomes was assessed using Cochrane and PRISMA 2020 methodology. Eligible studies included prospective Phase II to III trials and retrospective analyses published between January 1, 2013 and February 23, 2024 in the Ovid Medline database. These references were assessed through the American Radium Society (ARS) Appropriate Use Criteria (AUC) methodology. A systematic review PRISMA 2020 checklist confirmed the completion of essential elements. RAND-UCLA consensus methodology was used by the expert panel to rate the appropriateness of the treatment options. Results: ARS AUC recommendations include (1) larynx preservation using endoscopic resection (EMR or ESD) alone for the typical case with pT1a cN0 cM0 CEC, (2) definitive CRT for the typical case with cT1bN0M0 in patients who cannot undergo endoscopic resection, (3) larynx-preserving using definitive CRT (with or without induction chemotherapy) for the typical case with nonmetastatic locally advanced CEC (advanced T-stage tumors or involved lymph nodes), with surgery reserved for those patients with incomplete response or locoregional recurrence. Conclusions: This ARS AUC summary provides guidelines for the management of SCC of the cervical esophagus provides based on available evidence. Topics that warrant further investigation include optimization of (1) patient selection; (2) multimodality therapies including chemotherapy, immunotherapy, and targeted agents; (3) radiation dose, schedule, and treatment volume; and (4) supportive care for patients with CEC. Ongoing trials continue to improve outcomes for patients with CEC.

Key Points Loss-of-function ALG8 and ALG9 variants were enriched in polycystic kidney/liver groups and International Classification of Diseases–coded cystic individuals in population cohorts. The ALG8 and ALG9 kidney phenotypes were usually mild to moderate, and lower eGFR or kidney failure was rare. ALG8 pathogenic variants sometimes resulted in severe polycystic liver disease. Background Autosomal dominant polycystic kidney disease (ADPKD) is a common, inherited nephropathy often resulting in kidney failure. It is genetically heterogeneous; along with the major genes, PKD1 and PKD2 , at least eight others have been suggested. ALG8 pathogenic variants have been associated with autosomal dominant polycystic liver disease and implicated in ADPKD, while ALG9 has been suggested as an ADPKD gene, but details of the phenotypes and penetrance are unclear. Methods We screened >3900 families with cystic kidneys and/or livers using global approaches to detect ALG8 or ALG9 pathogenic variants. In addition, population cohorts with sequence data (Genomics England 100K Genomics Project, UK Biobank, and Mayo Clinic Biobank [MCBB]) were screened for ALG8 / ALG9 pathogenic variants. Results Multicenter screening of individuals with polycystic kidney and/or liver disease identified 51 (1.3%) ALG8 (7 multiplex) and 23 (0.6%) ALG9 (5 multiplex) families—frequencies that were approximately 10× and approximately 24× greater than nonpolycystic kidney disease controls. Analysis of individuals with polycystic kidney disease phenotypes in 100K Genomics Project, UK Biobank, and MCBB identified nine ALG8 (0.39%) and nine ALG9 (0.39%) families, an enriched frequency over controls. Two individuals had PKD1 and ALG8 pathogenic changes. Eighty-nine percent of individuals with ALG8 mutations with imaging in the entire MCBB had kidney cysts (50%, >10 cysts), with greater median kidney and liver cyst numbers than controls. For ALG9, 78% had kidney cysts (27%, >10 cysts). Individuals with ALG8 mutations typically had mild cystic kidneys with limited enlargement. Liver cysts were common (71%), with enlarged livers (>2L) found in 11 of 62 patients, although surgical intervention was rare. The ALG9 kidney phenotype was also of mild cystic kidneys, but enlarged livers were rare; for both genes, CKD or kidney failure were rare. Conclusions ALG8 and ALG9 are defined as cystic kidney/liver genes but with limited penetrance for lower eGFR.

Introduction and Hypothesis: New bleeding in cerebral cavernous malformations (CCM) heralds increased risk of future hemorrhage for several years, yet conventional imaging only detects new bleeding that occurred in the prior weeks. A biomarker of hemorrhage could help identifying high risk lesions. An increase of mean lesional quantitative susceptibility mapping (QSM) ≥6% on MRI has been adjudicated as reflecting new bleeding in CCM during longitudinal follow-up. However, mean lesional QSM from a single acquisition could not diagnose or prognosticate a bleed. We hypothesize that machine learning (ML) may identify diagnostic and prognostic features of bleeding within QSM maps at a single point in time. Material and Methods: Two hundred and sixty-five QSM maps of CCM lesions were acquired in 120 patients enrolled in National Institute of Health (NIH) multisite trial readiness project (NCT03652181). Each map was classified (Yes/No) in association with symptomatic hemorrhage (SH) and/or biomarker event with QSM increase ≥6% in the prior (diagnostic association) and subsequent (prognostic association) year. Twenty-eight features were extracted including 14 texture, 5 first-order statistical, as well as 3 size, shape, and morphological. Five-fold cross-validation was conducted on a support-vector machine (SVM) with linear stepwise kernel for both diagnostic and prognostic associations. Performance of individual features and composite classifiers was evaluated using student t-test ( p <0.05) with Bonferroni-correction and receiver operating characteristic (ROC) analysis, area under the curve (AUC). Results: Lesions with SH in the prior year had lower average values for sum variance (AUC=0.79, p<0.001), variance (AUC=0.79, p<0.001), and correlation (AUC=0.71, p=0.004) as compared to lesions without SH. The SVM classification method tasked with distinguishing lesions with mean QSM increase ≥6% in the prior year included recurrent selection of sum average, mean, sphericity and margin sharpness, yielding an AUC of 0.61 (p=0.02). In the prognostic cohort, no individual feature nor any SVM classification model was able to distinguish cases with a subsequent clinical bleed or biomarker event. Conclusion: This proof-of-concept suggests that ML may assist in deriving features on QSM maps acquired at a single timepoint, which reflect prior hemorrhagic activity in CCM. Further investigation is planned in larger cohorts and in conjunction with clinical trials of bleeding in CCM.

366 Background: While improved survival has been previously demonstrated, the impact of immunotherapy on HRQoL in ESCC has not been well examined. Traditional PRO-based analyses in oncology trials, such as time to deterioration (TTD) and mixed models for repeated measures (MMRMs), are limited by discounting recurrent PRO events. Thus, we applied a 3-component joint model (JM) framework to define more clinically interpretable associations between patient-reported symptoms, treatment effects, and OS among subgroups of patients with ESCC from RATIONALE-306, which met its primary endpoint, with PD-L1 expression of ≥1%, ≥5%, and ≥10%. Methods: The final analytic sample included 226 patients in the tislelizumab + chemotherapy arm (T+C), 242 in the placebo + chemotherapy arm (P+C) for PD-L1 ≥1%, 113 in the T+C arm and 103 in the P+C arm for PD-L1 ≥5%, and 168 in the T+C arm and 178 in the P+C arm for PD-L1 ≥10%.From EORTC QLQ-C30 and OES18, 7 keysymptom domains were modeled (GHS, physical functioning, fatigue, dysphagia, pain, reflux, dietary restrictions). PRO data were collected at baseline and at every treatment cycle (up to 6 cycles), then every other cycle, and at safety follow-up, and change from baseline (CFBL) was analyzed. The joint model comprised three components: 1) linear mixed model predicting CFBL symptom scores; 2) Cox proportional hazard model (CPH) for time to OS; and 3) frailty (random effects for recurrent deterioration events [RDEs]) CPH model for time to PRO-based RDEs. Osoba (1998) 10-point threshold was used to define RDEs. Results: Adjusted completion rates were >90% in the ITT population for both arms. Significant T+C treatment effects wereobserved for physical functioning in PD-L1 ≥5% ( P =0.0476), and pain in PD-L1 ≥1% ( P =0.0028) and PD-L1 ≥5% ( P =0.0149) subgroups, but not in PD-L1 ≥10%. For other 5 symptoms (ie, GHS, fatigue, reflux, dysphagia, dietary restrictions), there were no statistically significant differences between treatment arms. However, T+C was associated with significant reductions in the risk of death across all 7 key symptoms and PD-L1 subgroups. As one example, with respect to interaction between pain and OS, T+C was associated with a 22% (HR, 0.78 [95% CI, 0.652-0.931]), 33% (HR, 0.67 [95% CI, 0.515-0.860]), and 47% (HR, 0.50 [95% CI, 0.344-0.720]) reduction in the risk of death in PD-L1 ≥1%, ≥5%, and ≥10%, respectively compared with P+C. Conclusions: In this analysis, the addition of tislelizumab to chemotherapy was associated with significantly less deterioration in multiple PRO symptoms including physical functioning and pain, alongside a lower risk of death, after adjusting for recurring deterioration events using a frailty model across multiple PD-L1 expression subgroups.