The use of acupuncture for addressing neurological and neuropsychiatric symptoms in patients with long COVID: a systematic review and meta-analysis
Bibliographic record
Abstract
Importance Acupuncture has been used to treat neurological and neuropsychiatric symptoms in China and other parts of the world. These symptoms, such as fatigue, headache, cognitive impairment, anxiety, depression, and insomnia, are common in people experiencing long COVID. Objective This study aims to explore the feasibility of acupuncture in the treatment of neurological and neuropsychiatric symptoms in long COVID patients. Data Sources A systematic search was conducted in four English and four Chinese databases from inception to 23 June 2023. Literature selection and data extraction were conducted by two pairs of independent reviewers. Study Selection Randomized controlled trials (RCTs) that explored the effect of acupuncture on fatigue, depression, anxiety, cognitive abnormalities, headache, and insomnia were included. Data Extraction and Synthesis RCTs that explored the effect of acupuncture on fatigue, depression, anxiety, cognitive abnormalities, headache, and insomnia were included. A meta-analysis was performed using R software. Heterogeneity was measured using I2. Subgroup analyses were performed focusing on the duration of treatment and acupuncture modalities. The systematic review protocol was registered on PROSPERO (registration number: CRD42022354940). Main outcomes and measures Widely adopted clinical outcome scales included the Fatigue Scale for assessing fatigue, the Hamilton Depression Rating Scale for evaluating depression, the Mini-Mental State Examination for assessing cognitive impairment, the Visual Analog Scale for headache severity, and the Pittsburgh Sleep Quality Index for measuring insomnia. Results A total of 110 RCTs were included in the systematic review and meta–analysis. Overall, acupuncture was found to improve the scores of the Fatigue Scale (vs. medication: mean differences (MD): −2.27, P < 0.01; vs. sham acupuncture: MD: −3.36, P < 0.01), the Hamilton Depression Rating Scale (vs. medication: MD: −1.62, 95%, P < 0.01; vs. sham acupuncture: MD: −9.47, P < 0.01), the Mini–Mental State Examination (vs. medication: MD: 1.15, P < 0.01; vs. sham acupuncture: MD: 1.20, P < 0.01), the Visual Analog Scale (vs. medication: MD: −1.05, P < 0.01; vs. waitlist: MD: −0.48, P=0.04), and the Pittsburgh Sleep Quality Index (vs. medication: MD: −2.33, P < 0.01; vs. sham acupuncture: MD: −4.19, P < 0.01). Conclusion and relevance This systematic review suggested acupuncture as a potentially beneficial approach for the treatment of neurological and neuropsychiatric symptoms, as assessed using clinical scales, and it may have applicability in long COVID patients. Further well-designed clinical studies specifically targeting long COVID patients are needed to validate the role of acupuncture in alleviating long COVID symptoms. Systematic Review Registration PROSPERO, identifier [CRD42022354940].
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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 | 0.012 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.025 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".