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AF is the most common sustained arrhythmia encountered in clinical practice. Among the largest contributing factors to the rapid increase in the incidence of AF are aging and obesity within the global population. Obstructive sleep apnoea (OSA) is a risk factor for AF that is clearly linked to obesity. Guidelines have advocated interrogation for clinical signs of OSA in all AF patients. The aim of this article is to provide practical advice for clinicians seeking to manage patients with AF and OSA. The authors discuss questionnaires to screen for OSA, various types of tests available for the diagnosis of OSA and data to assess the impact of treatment of OSA after various treatment options in AF patients. Finally, they outline the many areas that warrant further investigation in this patient population.

Introduction Women and underrepresented groups in medicine hold few academic leadership positions in the field of hematology/oncology. In this study, we assessed gender and race/ethnicity representation in editorial board positions in hematology/oncology journals. Materials and Methods Editorial leadership board members from 60 major journals in hematology and oncology were reviewed; 54 journals were included in the final analysis. Gender and race/ethnicity were determined based on publicly available data for Editor-in-Chief (EiC) and Second-in-Command (SiC) (including deputy, senior, or associate editors). Descriptive statistics and chi-squared were estimated. In the second phase of the study, editors were emailed a 4-item survey to self-identify their demographics. Results Out of 793 editorial board members, 72.6% were men and 27.4% were women. Editorial leadership were non-Hispanic white (71.1%) with Asian editorial board members representing the second largest majority at 22.5%. Women comprised only 15.9% of the EiC positions (90% White and 10% Asian). Women were about half as likely to be in the EiC position compared with men [pOR 0.47 (95% CI, 0.23-0.95, P = .03)]. Women represented 28.3% of SiC editorial positions. Surgical oncology had the lowest female representation at 2.3%. Conclusion Women and minorities are significantly underrepresented in leadership roles on Editorial Boards in hematology/oncology journals. Importantly, the representation of minority women physicians in EiC positions is at an inexorable zero. Assessing gender and race representation in leadership editorial board positions in major journals is critical in furthering equity. This article examines the gender and race/ethnicity representation in editorial board positions at leading hematology and oncology journals.

PurposeApproximately 10–40% of strokes are cryptogenic (CS). Long-term electrocardiographic (ECG) monitoring has been recommended in these patients to search for atrial fibrillation (AF). An unresolved issue is whether ambulatory ECG (AECG) monitoring should be performed first, followed by an implantable loop recorder (ILR) if AECG monitoring is non-diagnostic, or whether long-term ECG monitoring should be initiated using ILRs from the onset. The purpose of this study was to assess, using an ILR, AF incidence in the first month after CS.MethodsWe enrolled consecutive CS patients referred for an ILR. All patients were monitored via in-hospital continuous telemetry from admission until the ILR (Medtronic [Minneapolis, MN] LINQ™) was implanted. The duration and overall burden of all AF episodes ≥ 2 min was determined.ResultsThe cohort included 343 patients (68 ± 11 years, CHA2DS2-VASc 3.5 ± 1.7). The time between stroke and ILR was 3.7 ± 1.5 days. During the first 30 days, only 18 (5%) patients had AF. All episodes were paroxysmal, lasting from 2 min to 67 h and 24 min. The median AF burden was 0.85% (IQR 0.52, 10.75). During 1 year of follow-up, 67 (21%) patients had AF.ConclusionThe likelihood of AF detection by an ILR in the first month post-CS is low. Thus, the diagnostic yield of 30 days of AECG monitoring is likely to be limited. These data suggest a rationale for proceeding directly to ILR implantation prior to hospital discharge in CS patients, as many have AF detected during longer follow-up.

Background/Objectives: Adolescents in Latin America are experiencing rising rates of overweight/obesity and non-communicable diseases, while public health nutrition efforts targeting this group remain limited. This study explores adherence to the EAT-Lancet diet and its relationship with micronutrient adequacy and ultra-processed food (UPF) consumption. Methods: Cross-sectional data from national nutrition surveys of 19,601 adolescents across six Latin American countries were analyzed. Data on sociodemographics, anthropometrics, and dietary habits were collected using standardized questionnaires and 24 h dietary recalls or food records. Nutrient intake was estimated via statistical modeling, and nutrient adequacy ratios were based on age- and sex-specific requirements. UPF intake was classified using the NOVA system, and adherence to the EAT-Lancet diet was assessed with the Planetary Health Diet Index. Results: Overall adherence to the EAT-Lancet diet was low (mean score: 28.3%). Rural adolescents had higher adherence than urban adolescents, and those aged 10–13 and 17–19 showed better adherence compared to adolescents aged 14–16. Adolescents from lower socioeconomic backgrounds adhered more than those from higher socioeconomic backgrounds. Adherence varied from 20.2% in Argentina to 30.2% in Brazil and Chile. Higher adherence was associated with lower UPF intake. Among urban adolescents, greater adherence was linked to a higher risk of inadequate riboflavin, niacin, and cobalamin intake, a trend not observed in rural adolescents. Conclusions: Adherence to the EAT-Lancet diet is low among Latin American adolescents, particularly in urban areas. Public health efforts should prioritize reducing UPF consumption, improving access to nutrient-dense, culturally appropriate foods, and supporting fortified staple foods.

Objectives While fully supervised learning can yield high-performing segmentation models, the effort required to manually segment large training sets limits practical utility. We investigate whether data mined line annotations can facilitate brain MRI tumor segmentation model development without requiring manually segmented training data. Methods In this retrospective study, a tumor detection model trained using clinical line annotations mined from PACS was leveraged with unsupervised segmentation to generate pseudo-masks of enhancing tumors on T1-weighted post-contrast images (9911 image slices; 3449 adult patients). Baseline segmentation models were trained and employed within a semi-supervised learning (SSL) framework to refine the pseudo-masks. Following each self-refinement cycle, a new model was trained and tested on a held-out set of 319 manually segmented image slices (93 adult patients), with the SSL cycles continuing until Dice score coefficient (DSC) peaked. DSCs were compared using bootstrap resampling. Utilizing the best-performing models, two inference methods were compared: (1) conventional full-image segmentation, and (2) a hybrid method augmenting full-image segmentation with detection plus image patch segmentation. Results Baseline segmentation models achieved DSC of 0.768 (U-Net), 0.831 (Mask R-CNN), and 0.838 (HRNet), improving with self-refinement to 0.798, 0.871, and 0.873 (each p  < 0.001), respectively. Hybrid inference outperformed full image segmentation alone: DSC 0.884 (Mask R-CNN) vs. 0.873 (HRNet), p  < 0.001. Conclusions Line annotations mined from PACS can be harnessed within an automated pipeline to produce accurate brain MRI tumor segmentation models without manually segmented training data, providing a mechanism to rapidly establish tumor segmentation capabilities across radiology modalities. Key Points • A brain MRI tumor detection model trained using clinical line measurement annotations mined from PACS was leveraged to automatically generate tumor segmentation pseudo-masks . • An iterative self-refinement process automatically improved pseudo-mask quality, with the best-performing segmentation pipeline achieving a Dice score of 0.884 on a held-out test set . • Tumor line measurement annotations generated in routine clinical radiology practice can be harnessed to develop high-performing segmentation models without manually segmented training data, providing a mechanism to rapidly establish tumor segmentation capabilities across radiology modalities .