Decreased Completion of Ordered Laboratories and Imaging in Telehealth Compared With In-person Hepatology Encounters.

OBJECTIVE: To evaluate order completion after telehealth compared with in-person encounters. BACKGROUND: Completion of ordered testing, including laboratories and imaging, is an important aspect of successful outpatient care of patients with liver disease. Whether the completion of orders from telehealth encounters differs from in-person visits is unknown. MATERIALS AND METHODS: Completion of ordered laboratories and imaging from hepatology encounters at our center from 2021 to 2022 were evaluated and compared between video telehealth and in-person visits. Laboratory completion was evaluated at 14 days, 30 days, and 90 days, and imaging completion was assessed at 1 year. RESULTS: Telehealth encounters were significantly less likely to have laboratories completed at all evaluated time points (14 d: 40.7% vs 90.9%; 30 d: 50.9% vs 92.2%; 90 d: 63.9% vs 94.3%, P< 0.001 for all). Among telehealth encounters, encounters in patients more remote from the center were less likely to have laboratories completed. Imaging ordered at telehealth encounters was also less likely to be completed within 1 year (62.5% vs 70.1%, P< 0.001), including liver ultrasounds (59.1% vs 67.6%, P= 0.001), which persisted when limited to encounters for cirrhosis (55.8% vs 66.4%, P= 0.01). CONCLUSIONS: Telehealth encounters were significantly less likely to have ordered laboratories and imaging completed compared with in-person visits, which has important clinical implications for effective outpatient care of patients with liver disease. Further research is needed to better understand the barriers to order completion for telehealth visits and ways to optimize this to improve the effectiveness of this visit modality.

Itching to find a diagnosis.

Content available: Audio Recording.

MRI-based radiomic feature analysis of end-stage liver disease for severity stratification.

PURPOSE: We aimed to develop a predictive model of disease severity for cirrhosis using MRI-derived radiomic features of the liver and spleen and compared it to the existing disease severity metrics of MELD score and clinical decompensation. The MELD score is compiled solely by blood parameters, and so far, it was not investigated if extracted image-based features have the potential to reflect severity to potentially complement the calculated score. METHODS: This was a retrospective study of eligible patients with cirrhosis ([Formula: see text]) who underwent a contrast-enhanced MR screening protocol for hepatocellular carcinoma (HCC) screening at a tertiary academic center from 2015 to 2018. Radiomic feature analyses were used to train four prediction models for assessing the patient's condition at time of scan: MELD score, MELD score [Formula: see text] 9 (median score of the cohort), MELD score [Formula: see text] 15 (the inflection between the risk and benefit of transplant), and clinical decompensation. Liver and spleen segmentations were used for feature extraction, followed by cross-validated random forest classification. RESULTS: Radiomic features of the liver and spleen were most predictive of clinical decompensation (AUC 0.84), which the MELD score could predict with an AUC of 0.78. Using liver or spleen features alone had slightly lower discrimination ability (AUC of 0.82 for liver and AUC of 0.78 for spleen features only), although this was not statistically significant on our cohort. When radiomic prediction models were trained to predict continuous MELD scores, there was poor correlation. When stratifying risk by splitting our cohort at the median MELD 9 or at MELD 15, our models achieved AUCs of 0.78 or 0.66, respectively. CONCLUSIONS: We demonstrated that MRI-based radiomic features of the liver and spleen have the potential to predict the severity of liver cirrhosis, using decompensation or MELD status as imperfect surrogate measures for disease severity.