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Record W4414435310 · doi:10.51793/os.2025.28.9.009

Chronic fatigue syndrome in the practice of a general practitioner: prevalence, diagnosis, and management of patients (literature review)

2025· article· ru· W4414435310 on OpenAlexaboutno aff
Л А Камышникова, А.А. Жердева

Bibliographic record

VenueЛечащий врач · 2025
Typearticle
Languageru
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsChronic fatigue syndromeChronic fatigueQuality of life (healthcare)Chronic diseasePrimary careChronic conditionGeneral practiceMedical care

Abstract

fetched live from OpenAlex

Background. In modern medicine, chronic fatigue syndrome is an urgent problem for internists. The high prevalence of chronic fatigue syndrome, which has a significant impact on public health, requires primary care professionals to have an in-depth understanding of the diagnosis and management of this condition. This literature review analyzes the prevalence, diagnostic criteria, and approaches to managing patients with chronic fatigue syndrome in the practice of a general practitioner in order to raise awareness and improve the quality of medical care. Results. Chronic fatigue syndrome is defined as unexplained, prolonged fatigue lasting more than six months, which is not eliminated by rest and increases with physical or mental exertion. The prevalence of chronic fatigue syndrome varies in different regions of the world, reaching, according to some estimates, from 120 to 140 million cases. In North America, prevalence rates range from 0.2% to 0.7%, in Europe from 0.1% to 1%, and in Australia from 0.2% to 0.4%. Among patients seeking therapy, the prevalence of chronic fatigue syndrome ranges from 5% to 10%. Risk factors for developing chronic fatigue syndrome include being female, low income, and living outside major cities. Genetic studies have revealed a link between chronic fatigue syndrome and 14 different genes. Various factors such as toxins, chronic stress, viral or bacterial infections, as well as an imbalance of the intestinal microflora (dysbiosis) can act as triggers triggering the development of chronic fatigue syndrome. The diagnosis of chronic fatigue syndrome presents certain difficulties due to the lack of specific biomarkers. Various criteria are used to make a diagnosis, including the CDC/Fukuda criteria, the Canadian Consensus Criteria, and the IOM/NAM criteria. Comprehensive treatment of chronic fatigue syndrome includes normalization of the daily routine, physiotherapy, psychotherapy and pharmacotherapy (including vitamins, immunocorrectors and drugs aimed at improving mitochondrial metabolism). At the same time, an individual approach to each patient is important. The effectiveness of treatment can be high, but relapses of the disease are possible. Prompt detection of chronic fatigue syndrome and provision of qualified, personalized management of patients suffering from this condition is a crucial factor in ensuring a significant improvement in overall well-being, increased physical and psycho-emotional activity, as well as restoration of full-fledged social and professional adaptation, which together contributes to a significant improvement in the quality of life of these people.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.476
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.308
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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