Comparative study for fatigue prevalence in subjects with diseases: a systematic review and meta-analysis
Bibliographic record
Abstract
Fatigue is one of the common symptoms in individuals with diseases or disorders, significantly affecting quality of life (QoL) and the prognosis of diseases. This study aimed to comprehensively compare the features of fatigue across a wide range of diseases. We systematically searched the PubMed and Cochrane Library databases from inception to March 31st, 2021, and conducted a meta-analysis to generate precise estimates. The analyses were stratified by classification of diseases, gender, and severity of fatigue (moderate and severe), and study quality was assessed using the Newcastle-Ottawa Scale (NOS). In total, 214 articles (233 prevalence data) met our eligibility criteria, covering 102,024 participants (mean 438 ± 1,421) across 88 diseases. Among these, seventy-eight data sets (52,082 participants) and thirty-nine data sets (10,389 participants) reported gender- and severity-related fatigue prevalence. The overall prevalence among subjects with 88 diseases was 49.4% [95% CI 46.9-52.1]. According to the International Classification of Diseases-10 (ICD-10) classification, the highest prevalence of fatigue (65.9% [95% CI 54.9-79.6]) was observed in patients with mental/behavioral diseases, whereas the lowest prevalence (34.7% [95% CI 24.5-49.2]) was found among those with circulatory system diseases. A slight female dominance (43.5% vs. 49.8%) was observed in the total data, with the most notable female predominance (1.8-fold) seen in patients with low back pain. The top disease groups with a moderate to severe level of fatigue included gastroparesis (92.3%), pulmonary hypertension (90.0%), chronic obstructive pulmonary disease (COPD, 83.2%), and multiple sclerosis (80.0%). These results are the first to comprehensively show the comparative features of fatigue prevalence among subjects across 88 diseases. Our findings provide valuable reference data for future research on fatigue and for the management of patients with fatigue.Prospero registration number: CRD42021270494.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.049 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".