2021
DOI: 10.1186/s12967-020-02683-4
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The evidence base for physiotherapy in myalgic encephalomyelitis/chronic fatigue syndrome when considering post-exertional malaise: a systematic review and narrative synthesis

Abstract: Background Due to the inconsistent use of diagnostic criteria in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), it is unsure whether physiotherapeutic management regarded effective in ME/CFS is appropriate for patients diagnosed with criteria that consider post-exertional malaise (PEM) as a hallmark feature. Purpose To appraise current evidence of the effects of physiotherapy on symptoms and functioning in ME/CFS patients in view of t… Show more

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Cited by 78 publications
(36 citation statements)
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“…In a different case–control study in the same country, 138 mildly affected patients were matched with 82 negative controls, and serum 25(OH)D levels were significantly lower in affected people but were not a predictor of disease outcome. That finding called for additional large population-based RCTs to further confirm the results [ 73 ].…”
Section: Discussionmentioning
confidence: 99%
“…In a different case–control study in the same country, 138 mildly affected patients were matched with 82 negative controls, and serum 25(OH)D levels were significantly lower in affected people but were not a predictor of disease outcome. That finding called for additional large population-based RCTs to further confirm the results [ 73 ].…”
Section: Discussionmentioning
confidence: 99%
“…From that moment on, I didn’t have anyone in my room without earphones and earmuffs. Only when I discovered Ativan and Abilify [ 7 ] in the last few months of 2020 and improved was I able to be around people without earmuffs and actually listen to them speak, but only with Ativan or when my body naturally releases adrenaline to enable me to get up to have a bowel movement in the bathroom (a 6-foot walk). I will explain this natural adrenaline release later in this article.…”
Section: From Severe To Extremely Severementioning
confidence: 99%
“…Previous machine learning studies highlight that some demographic variables, patients’ comorbidities, and laboratory findings can be predictive factors for COVID-19 mortality [ [9] , [10] , [11] , [12] ]. However, most of these studies included a small sample size, which may impact the model’s robustness and reliability of findings (e.g., low sensitivity) [ [14] , [15] , [16] ] and prevent its use in practice. Moreover, to date, specific biomarkers associated with the disease severity and patients’ hospitalisation in intensive care units are still unknown, which may hamper the development of further targeted treatments [ 13 ].…”
Section: Introductionmentioning
confidence: 99%