Atrial fibrillation (AF) is the most common sustained arrhythmia and a growing global health burden, yet conventional monitoring with Holter devices, event recorders and implantable loop recorders often fails to adequately capture recurrence. Rapid advances in digital health, wearable biosensors and artificial intelligence (AI) have transformed consumer smartwatches and wearables into potential clinical tools capable of continuous, real-world rhythm surveillance. This narrative review synthesizes contemporary evidence on smartwatch-based AF monitoring, spanning core technologies—photoplethysmography, single-lead electrocardiography and AI fusion algorithms—and validation studies across post-ablation follow-up. Compared with traditional modalities, smartwatch-based AF monitoring demonstrates improved detection of AF recurrence, enhanced characterization of AF burden, symptom–rhythm correlation, and greater patient engagement. At the same time, key limitations are critically examined, including motion artifacts, false-positive alerts, short recording windows, adherence dependence, digital literacy and access gaps, as well as unresolved issues around regulation, interoperability and data privacy. By integrating engineering advances with guideline-directed care pathways, smartwatch-based AF monitoring holds promise to complement, rather than immediately replace, established diagnostic tools and to enable more proactive, individualized AF management. Future work must focus on robust clinical validation, equitable implementation and clear regulatory frameworks to safely scale these technologies.

Background: Diabetes management in patients with hematologic malignancies is challenging because of advanced age, multimorbidity, and cancer-related therapies. However, real-world evidence regarding glycemic control in this population remains limited. We aimed to evaluate glycemic control, glucose-lowering treatment patterns, and factors associated with tight glycemic control in patients with type 2 diabetes and hematologic malignancies. Methods: This retrospective cross-sectional study included 86 adults treated at a tertiary university hematology department. Demographic, clinical, laboratory, and treatment data were extracted from medical records. Low measured glycated hemoglobin (HbA1c) was defined as HbA1c <6.5%. Associated factors were examined using exploratory multivariable logistic regression. Results: The mean age was 75.0 ± 11.6 years; 48 patients (55.8%) were men. Among the 80 patients with available HbA1c measurements, the median HbA1c was 6.6% (interquartile range 6.0–7.2), and 37 (46.3%) had HbA1c <6.5%. Exploratory regression analyses suggested higher odds of HbA1c <6.5% with higher estimated glomerular filtration rate (adjusted odds ratio [OR], 1.03; 95% confidence interval [CI], 1.002–1.055; p = 0.035) and lower odds with diabetic vascular complications (adjusted OR, 0.30; 95% CI, 0.09–0.99; p = 0.048). At the alternative HbA1c threshold of <7.0%, corticosteroid exposure was associated with lower odds (adjusted OR, 0.35; 95% CI, 0.13–0.98; p = 0.046). Fifteen patients (18.8%) had HbA1c <6.5% while receiving insulin and/or a sulfonylurea. Conclusions: Low HbA1c values were common in this cohort, including among patients receiving insulin and/or sulfonylureas. These findings describe low measured HbA1c and associated treatment patterns but do not establish unnecessarily intensive treatment, clinical inappropriateness, hypoglycemia, or treatment-related harm. Prospective studies incorporating individualized treatment targets and documented hypoglycemia are needed to clarify their clinical significance.