Post-treatment Lyme disease symptoms score: Developing a new tool for research.
Some patients have residual non-specific symptoms after therapy for Lyme disease, referred to as post-treatment Lyme disease symptoms or syndrome, depending on whether there is functional impairment. A standardized test battery was used to characterize a diverse group of Lyme disease patients with a...
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2019-01-01
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Online Access: | https://doi.org/10.1371/journal.pone.0225012 |
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doaj-9ce3eee6fff0492b9936bccd41942d732021-03-04T11:21:00ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-011411e022501210.1371/journal.pone.0225012Post-treatment Lyme disease symptoms score: Developing a new tool for research.Siu P TurkKeith LumbardKelly LiepshutzCarla WilliamsLinden HuKenneth DardickGary P WormserJoshua NorvilleCarol ScavardaDonna McKennaDean FollmannAdriana MarquesSome patients have residual non-specific symptoms after therapy for Lyme disease, referred to as post-treatment Lyme disease symptoms or syndrome, depending on whether there is functional impairment. A standardized test battery was used to characterize a diverse group of Lyme disease patients with and without residual symptoms. There was a strong correlation between sleep disturbance and certain other symptoms such as fatigue, pain, anxiety, and cognitive complaints. Results were subjected to a Logistic Regression model using the Neuro-QoL Fatigue t-score together with Short Form-36 Physical Functioning scale and Mental Health component scores; and to a Decision Tree model using only the QoL Fatigue t-score. The Logistic Regression model had an accuracy of 97% and Decision Tree model had an accuracy of 93%, when compared with clinical categorization. The Logistic Regression and Decision Tree models were then applied to a separate cohort. Both models performed with high sensitivity (90%), but moderate specificity (62%). The overall accuracy was 74%. Agreement between 2 time points, separated by a mean of 4 months, was 89% using the Decision Tree model and 87% with the Logistic Regression model. These models are simple and can help to quantitate the level of symptom severity in post-treatment Lyme disease symptoms. More research is needed to increase the specificity of the models, exploring additional approaches that could potentially strengthen an operational definition for post-treatment Lyme disease symptoms. Evaluation of how sleep disturbance, fatigue, pain and cognitive complains interrelate can potentially lead to new interventions that will improve the overall health of these patients.https://doi.org/10.1371/journal.pone.0225012 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Siu P Turk Keith Lumbard Kelly Liepshutz Carla Williams Linden Hu Kenneth Dardick Gary P Wormser Joshua Norville Carol Scavarda Donna McKenna Dean Follmann Adriana Marques |
spellingShingle |
Siu P Turk Keith Lumbard Kelly Liepshutz Carla Williams Linden Hu Kenneth Dardick Gary P Wormser Joshua Norville Carol Scavarda Donna McKenna Dean Follmann Adriana Marques Post-treatment Lyme disease symptoms score: Developing a new tool for research. PLoS ONE |
author_facet |
Siu P Turk Keith Lumbard Kelly Liepshutz Carla Williams Linden Hu Kenneth Dardick Gary P Wormser Joshua Norville Carol Scavarda Donna McKenna Dean Follmann Adriana Marques |
author_sort |
Siu P Turk |
title |
Post-treatment Lyme disease symptoms score: Developing a new tool for research. |
title_short |
Post-treatment Lyme disease symptoms score: Developing a new tool for research. |
title_full |
Post-treatment Lyme disease symptoms score: Developing a new tool for research. |
title_fullStr |
Post-treatment Lyme disease symptoms score: Developing a new tool for research. |
title_full_unstemmed |
Post-treatment Lyme disease symptoms score: Developing a new tool for research. |
title_sort |
post-treatment lyme disease symptoms score: developing a new tool for research. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2019-01-01 |
description |
Some patients have residual non-specific symptoms after therapy for Lyme disease, referred to as post-treatment Lyme disease symptoms or syndrome, depending on whether there is functional impairment. A standardized test battery was used to characterize a diverse group of Lyme disease patients with and without residual symptoms. There was a strong correlation between sleep disturbance and certain other symptoms such as fatigue, pain, anxiety, and cognitive complaints. Results were subjected to a Logistic Regression model using the Neuro-QoL Fatigue t-score together with Short Form-36 Physical Functioning scale and Mental Health component scores; and to a Decision Tree model using only the QoL Fatigue t-score. The Logistic Regression model had an accuracy of 97% and Decision Tree model had an accuracy of 93%, when compared with clinical categorization. The Logistic Regression and Decision Tree models were then applied to a separate cohort. Both models performed with high sensitivity (90%), but moderate specificity (62%). The overall accuracy was 74%. Agreement between 2 time points, separated by a mean of 4 months, was 89% using the Decision Tree model and 87% with the Logistic Regression model. These models are simple and can help to quantitate the level of symptom severity in post-treatment Lyme disease symptoms. More research is needed to increase the specificity of the models, exploring additional approaches that could potentially strengthen an operational definition for post-treatment Lyme disease symptoms. Evaluation of how sleep disturbance, fatigue, pain and cognitive complains interrelate can potentially lead to new interventions that will improve the overall health of these patients. |
url |
https://doi.org/10.1371/journal.pone.0225012 |
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