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Post-treatment Lyme disease symptoms score: Developing a new tool for research

  1. Author:
    Turk, Siu P
    Lumbard,Keith
    Liepshutz,Kelly
    Williams,Carla
    Hu, Linden
    Dardick, Kenneth [ORCID]
    Wormser, Gary P
    Norville, Joshua
    Scavarda, Carol
    McKenna, Donna
    Follmann, Dean
    Marques, Adriana [ORCID]
  2. Author Address

    Laboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America., Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States of America., Leidos Biomedical Research, Inc., Clinical Services Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States of America., Tufts University School of Medicine, Boston, Massachusetts, United States of America., Mansfield Family Practice, Storrs, Connecticut, United States of America., Infectious Diseases, New York Medical College, Valhalla, New York, United States of America., Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America.,
    1. Year: 2019
    2. Date: NOV 11
    3. Epub Date: 2019 11 11
  1. Journal: PloS one
    1. 14
    2. 11
    3. Pages: e0225012
  2. Type of Article: Article
  3. Article Number: e0225012
  4. ISSN: 1932-6203
  1. Abstract:

    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.

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External Sources

  1. DOI: 10.1371/journal.pone.0225012
  2. PMID: 31710647
  3. WOS: 000532699900035
  4. PII : PONE-D-19-21720

Library Notes

  1. Fiscal Year: FY2019-2020
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