Dataset Information

Warning Signals of Post-Exertional Malaise in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Retrospective Analysis of 197 Patients.

ABSTRACT: Post-exertional malaise (PEM), the key feature of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), is characterized by baseline symptom exacerbation after exposure to a stressor, and some patients can experience new or non-typical symptoms. We hypothesized that new or non-typical symptoms occurring long enough before onset of baseline symptom exacerbation could be warning signals predicting PEM. Adult ME/CFS patients who attended the internal medicine department of Angers University Hospital (France) between October 2011 and December 2019 were included in a retrospective medical records review. Patients who experienced one or more new or non-typical symptoms before baseline symptom exacerbation were compared with the rest of the study population for PEM features, epidemiological characteristics, fatigue features, and comorbidities. New or non-typical symptoms preceded baseline symptom exacerbation in 27/197 (13.7%) patients, and the most frequent ones were mood disorders (37%). When compared to the rest of the study population, only PEM intensity was significantly lower in these patients (p = 0.004), even after adjustment for sex and age at disease onset (p = 0.007). New or non-typical symptoms preceding baseline symptom exacerbation in some ME/CFS patients could be warning signals for PEM. Their identification could help preventing PEM occurrences or reducing their intensity leading to improving disease prognosis.

SUBMITTER: Ghali A

PROVIDER: S-EPMC8201170 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:Post-exertional malaise (PEM) is considered to be the hallmark characteristic of myalgic encephalomyelitis/ chronic fatigue syndrome (ME/CFS). Yet, patients have rarely been asked in formal studies to describe their experience of PEM. OBJECTIVES:To describe symptoms associated with and the time course of PEM. METHODS:One hundred and fifty subjects, diagnosed via the 1994 Fukuda CFS criteria, completed a survey concerning 11 symptoms they could experience after exposure to two different types of triggers. We also inquired about onset and duration of PEM and included space for subjects to write in any additional symptoms. Results were summarized with descriptive statistics; McNemar's, paired t-, Fisher's exact and chi-square goodness-of-fit tests were used to assess for statistical significance. RESULTS:One hundred and twenty-nine subjects (90%) experienced PEM with both physical and cognitive exertion and emotional distress. Almost all were affected by exertion but 14 (10%) reported no effect with emotion. Fatigue was the most commonly exacerbated symptom but cognitive difficulties, sleep disturbances, headaches, muscle pain, and flu-like feelings were cited by over 30% of subjects. Sixty percent of subjects experienced at least one inflammatory/ immune-related symptom. Subjects also cited gastrointestinal, orthostatic, mood-related, neurologic and other symptoms. Exertion precipitated significantly more symptoms than emotional distress (7±2.8 vs. 5±3.3 symptoms (median, standard deviation), p<0.001). Onset and duration of PEM varied for most subjects. However, 11% reported a consistent post-trigger delay of at least 24 hours before onset and 84% endure PEM for 24 hours or more. CONCLUSIONS:This study provides exact symptom and time patterns for PEM that is generated in the course of patients' lives. PEM involves exacerbation of multiple, atypical symptoms, is occasionally delayed, and persists for extended periods. Highlighting these characteristics may improve diagnosis of ME/CFS. Incorporating them into the design of future research will accelerate our understanding of ME/CFS.

Dataset Information

Warning Signals of Post-Exertional Malaise in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Retrospective Analysis of 197 Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets