ArticleTranslational pediatrics2026
Traditional Chinese medicine combined with conventional Western medicine for chronic cough following respiratory infection in children: a systematic review and meta-analysis.
Article in Translational pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Chronic cough following respiratory infection in children is often refractory to conventional therapies. However, the current clinical evidence regarding the efficacy of traditional Chinese medicine (TCM) remains inconclusive and lacks systematic synthesis, leaving clinicians without clear guidance. This study systematically evaluated the efficacy and safety of TCM for chronic cough following respiratory infection in children to support clinical decision-making. Methods: A systematic search was conducted in the Cochrane Library, PubMed, Embase, Web of Science, Wiley Online Library, China National Knowledge Infrastructure (CNKI), and Wanfang databases. Randomized controlled trials (RCTs) of TCM for chronic cough following respiratory infection in children were included. Meta-analyses were performed using RevMan 5.4 and Stata 16.0. Results: A total of 23 RCTs involving 2,126 children were included. Meta-analysis demonstrated that, compared with conventional Western medical treatment alone, TCM combined with conventional treatment significantly improved the overall clinical effectiveness rate [risk ratio (RR) =1.19, 95% confidence interval (CI) (1.15, 1.24), P<0.001], shortened the time to cough resolution [mean difference (MD) =-3.19, 95% CI (-4.42, -1.97), P<0.001] and the time to disappearance of pulmonary rales [MD =-2.00, 95% CI (-2.47, -1.54), P<0.001], and significantly reduced cough symptom scores [MD =-1.32, 95% CI (-1.69, -0.95), P<0.001]. For secondary outcomes, combined TCM therapy significantly reduced TCM syndrome scores, improved immune function indicators [immunoglobulin A (IgA), immunoglobulin M (IgM), and immunoglobulin G (IgG)], and decreased levels of inflammatory biomarkers [C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and monocyte chemoattractant protein-4 (MCP-4)]. No statistically significant difference was observed between groups in the incidence of adverse events. Conclusions: TCM used as an adjunct to conventional Western medical treatment may provide additional benefits in improving clinical outcomes and alleviating symptoms in children with post-infectious chronic cough. However, due to limitations in study quality and heterogeneity, further high-quality, well-designed studies are warranted to strengthen the evidence base.
Indexed as
Identifiers
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.