SynthesisFrontiers in neurology2022
The efficacy and safety of Chinese herbal medicine as an add-on therapy for amyotrophic lateral sclerosis: An updated systematic review and meta-analysis of randomized controlled trials.
Synthesis in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Herbal medicines for SOD1Frontiers in immunology · 2024Pooled it
- Traditional Chinese botanical medicines and plant-derived bioactive compounds in amyotrophic lateral sclerosis: mechanistic evidence, translational challenges, and therapeutic opportunities.Frontiers in pharmacology · 2026Review
- Effectiveness and safety of traditional Chinese therapies intreating patients with amyotrophic lateral sclerosis: a protocol for systematic review and meta-analysis.Frontiers in neurology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Amyotrophic lateral sclerosis (ALS) has attracted widespread attention because of its unknown pathogenesis, rapid progression, and life-threatening and incurable characteristics. A series of complementary therapies, including Chinese herbal medicine (CHM), is available for use in the clinic and has been the focus of much research. However, it is unclear as to whether supplementary CHM relieves disease symptoms or extends life span; thus, we conducted this updated meta-analysis to validate the efficacy and safety of this practice. Methods: We searched six electronic databases for randomized controlled trials involving CHM and patients with ALS that were published up to April 2022. Two researchers independently screened the literature, assessed the risk of bias for each trial, and then extracted data. The methodological quality of the included trials was assessed using the Cochrane risk of bias tool, and a pooled data analysis was performed using RevMan 5.3. Results: A total of 14 trials led to the publication of 15 articles featuring 1,141 participants during the study period; the articles were included in the systematic review. In terms of increasing ALS functional rating scale (ALSFRS) scores, CHM was superior to the placebo after 3 months of treatment [mean difference (MD):0.7; 95% CI:0.43 to 0.98; Conclusion: The analysis suggested that the short-term adjunct use of CHM could improve the ALSFRS score and clinical effect with a good safety profile when compared with the placebo or riluzole alone. However, future research should be centered on the long-term efficacy of patient-oriented outcomes. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=323047, identifier: CRD42022323047.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.