Language impairment in adults with end-stage liver disease: application of natural language processing towards patient-generated health records.
case_control · Level III
Where this comes from
- Record sourced from PubMed, PMID 31701020.
- Also identified by DOI 10.1038/s41746-019-0179-9 and PMC identifier 6828779.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
End-stage liver disease (ESLD) is associated with cognitive impairment ranging from subtle alterations in attention to overt hepatic encephalopathy that resolves after transplant. Natural language processing (NLP) may provide a useful method to assess cognitive status in this population. We identified 81 liver transplant recipients with ESLD (4/2013-2/2018) who sent at least one patient-to-provider electronic message pre-transplant and post-transplant, and matched them 1:1 to "healthy" controls-who had similar disease, but had not been evaluated for liver transplant-by age, gender, race/ethnicity, and liver disease. Messages written by patients pre-transplant and post-transplant and controls was compared across 19 NLP measures using paired Wilcoxon signed-rank tests. While there was no difference overall in word length, patients with Model for End-Stage Liver Disease Score (MELD) ≥ 30 (<i>n</i> = 31) had decreased word length in pre-transplant messages (3.95 [interquartile range (IQR) 3.79, 4.14]) compared to post-transplant (4.13 [3.96, 4.28], <i>p</i> = 0.01) and controls (4.2 [4.0, 4.4], <i>p</i> = 0.01); there was no difference between post-transplant and controls (<i>p</i> = 0.4). Patients with MELD ≥ 30 had fewer 6+ letter words in pre-transplant messages (19.5% [16.4, 25.9] compared to post-transplant (23.4% [20.0, 26.7] <i>p</i> = 0.02) and controls (25.0% [19.2, 29.4]; <i>p</i> = 0.01). Overall, patients had increased sentence length pre-transplant (12.0 [9.8, 13.7]) compared to post-transplant (11.0 [9.2, 13.3]; <i>p</i> = 0.046); the same was seen for MELD ≥ 30 (12.3 [9.8, 13.7] pre-transplant vs. 10.8 [9.6, 13.0] post-transplant; <i>p</i> = 0.050). Application of NLP to patient-generated messages identified language differences-longer sentences with shorter words-that resolved after transplant. NLP may provide opportunities to detect cognitive impairment in ESLD.