Natural Language Processing Improves Care for Liver Failure Patients

Researchers at Johns Hopkins Medicine have developed natural language processing (NLP) tools that can diagnose the early and subtle signs of language-associated cognitive impairments in patients with liver failure.

The team used NLP to evaluate electronic message samples from patients with end-stage liver disease (ESLD), also called chronic liver failure. The condition is associated with cognitive abnormalities such as diminished attention span, loss of memory, and reduced psychomotor speed, which is a person’s ability to respond to the world around them. This can occur when a failing liver cannot properly remove toxins in the blood and they cross the brain-blood barrier.

About 80 percent of patients with ESLD have neurocognitive changes associated with poorer quality of life, including deteriorating sleep and work performance. Approximately 20 percent of adults with ESLD can develop the most severe form of cognitive impairment, overt hepatic encephalopathy, which has a mortality rate of 43 percent after one year.

“We currently do not have a reliable method for identifying cognitive abnormalities in patients who need a liver transplant,” said senior study author Douglas Mogul, MD, MPH, assistant professor of pediatrics and medical director of pediatric liver transplantation at Johns Hopkins Children’s Center.

“Our findings suggest that NLP may provide that early diagnosis of cognitive issues, guide us in managing the problem, and help improve a patient’s quality of life until a donor organ is available.”

The team found that overall, the NLP tool detected distinct yet subtle pre-transplant and post-transplant differences in sentence length, word length and other language characteristics, indicating that the technology could be used as a valuable diagnostic tool. The researchers noted that the liver is the second most transplanted organ after the kidney. In 2017, 8,100 ESLD patients received a liver transplant, and nearly 14,000 were on the waiting list for a donor organ.

In the study, researchers evaluated 81 ESLD patients who had received a liver transplant at the Johns Hopkins Hospital between April 2013 and January 2018. Those in the ESLD group sent at least one patient-to-provider electronic message both pre- and post-transplant. They were matched by age, gender, and race and ethnicity with a control group that had liver disease but were not evaluated for transplant, and also had email messages available in their records.

Messages from both groups were evaluated using 19 NLP measures of language characteristics, including word length, sentence length, word type, and subject-verb-object ratio. The severity of each patient’s liver disease was graded using the Model for End-Stage Liver Disease, or MELD, a numerical ranking between six and 40 based on laboratory tests. A MELD score of 30 or greater identifies a patient who most urgently needs a transplant.

“For patients with the highest MELD scores, we found that their messages had fewer letters per word, fewer words of six letters or more, and more words per sentence before their transplants,” said study co-author and computational linguist Masoud Rouhizadeh, MSc, PhD, one of the NLP leads at the Johns Hopkins Institute for Clinical and Translational Research and co-founder of its Center for Clinical NLP.

“It was like they were searching for words to make themselves understood.”

After transplant surgery, the majority of patients returned to normal or near-normal language patterns, with more concise sentences and longer words, including an increased number with six letters or more.

The study’s results have significant implications for the use of NLP algorithms in the healthcare space.

“We are among the first to try using it to track down neurocognitive impairments present in the messages composed by ESLD patients,” Mogul said.

“The more we can refine and develop our new diagnostic tool, the more we can validate its effectiveness, and then, possibly open the door to applying this technology to other diseases in which cognitive functioning is impaired, such as Alzheimer’s.”