Metabolic dysfunction-associated steatotic liver disease (MASLD) is an increasingly prevalent condition linked to obesity, diabetes, and metabolic syndrome, and can progress to fibrosis, cirrhosis, and hepatocellular carcinoma. Current diagnostic standards such as liver biopsy are invasive and unsuitable for routine screening. Liquid biopsy, particularly through analysis of extracellular RNAs (exRNAs), including microRNAs (e.g., miR-122, miR-21, miR-34a), long non-coding RNAs, and tRNA-derived fragments, offers a promising non-invasive alternative. These exRNAs, released from hepatocytes and carried in blood via extracellular vesicles or protein complexes, can be detected using techniques like RNA sequencing, qRT-PCR, and droplet digital PCR. These biomarkers correlate with histologic severity, fibrosis stage, and treatment response, and have shown promising diagnostic utility; however, their performance may differ across various populations and disease stages. Despite their potential, clinical translation is limited by a lack of standardization and large-scale validation. This review outlines recent advances in exRNA-based diagnostics for MASLD and MASH, emphasizing their role in early detection, disease monitoring, and the shift toward personalized hepatology.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is an increasingly prevalent condition linked to obesity, diabetes, and metabolic syndrome, and can progress to fibrosis, cirrhosis, and hepatocellular carcinoma. Current diagnostic standards such as liver biopsy are invasive and unsuitable for routine screening. Liquid biopsy, particularly through analysis of extracellular RNAs (exRNAs), including microRNAs (e.g., miR-122, miR-21, miR-34a), long non-coding RNAs, and tRNA-derived fragments, offers a promising non-invasive alternative. These biomarkers correlate with histologic severity, fibrosis stage, and treatment response, and may outperform traditional markers such as ALT and FIB-4 in diagnostic accuracy. Despite their potential, clinical translation is limited by a lack of standardization and large-scale validation. This review outlines recent advances in exRNA-based diagnostics for MASLD and MASH, emphasizing their role in early detection, disease monitoring, and the shift toward personalized hepatology.

Background/Objectives: Congestion drives most heart-failure (HF) hospitalizations, and several strategies now titrate therapy to a directly measured congestion signal rather than to symptoms; whether they differ by the signal measured has not been examined comparatively. Methods: We performed a systematic review and contrast-based network meta-analysis of randomized trials comparing imaging- or device-based congestion-triggered management with usual care. Thirteen chronic-phase trials formed a star network (no closed loops; rankings exploratory) of four strategies, pressure-guided (N1), lung ultrasound (N2), transthoracic lung impedance (N3), and cardiac-implantable-electronic-device (CIED) intrathoracic impedance (N5), with HF hospitalization as the primary outcome and six prespecified sensitivity analyses; four acute trials formed a gap map. Results: Only pressure-guided monitoring reduced HF hospitalization (0.72, 95% confidence interval 0.57–0.90), stable across sensitivities and matching external data. Lung ultrasound did not reduce hospitalization (0.72, 0.48–1.08) or mortality but reduced urgent visits (0.26, 0.13–0.50). The apparent CIED-impedance harm (1.12, 0.77–1.63) reflected an audible-alert trial and dissolved when early-terminated trials were excluded (0.87). Lung impedance gave the largest estimate (0.51, 0.31–0.83) but rested on one trial. No strategy tested in more than one trial reduced mortality. Conclusions: The congestion signal acted upon, and who receives the alert, track with the effect, although signal and workflow cannot be separated within trials; clinicians should match modality to the intended outcome, as these tools defer hospitalization, not death.