COPD Patient Indices by TCM Constitution from a Systematic Review
by Sheng Xie·Updated 16d ago
3.5 MB1files
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Description
A systematic review and network meta-analysis of 11 studies with 2,168 participants, investigating the relationship between Traditional Chinese Medicine constitutions and clinical indices in Chronic Obstructive Pulmonary Disease patients. The analysis was conducted by Sheng Xie and registered with PROSPERO, with results last updated in May 2026. The dataset likely contains aggregated results comparing TCM constitutions like yang-deficiency and qi-deficiency against smoking index, FEV1/FVC, FEV1%Pred, acute exacerbations per year, and CAT scores.
Use Cases
Compare the severity of clinical indices like FEV1%Pred across different TCM constitutions such as yang-deficiency and qi-deficiency.
Identify TCM constitutions associated with higher smoking index or annual acute exacerbation rates in COPD patients.
Support clinical decision-making for prevention and rehabilitation by analyzing the systematic review's aggregated findings on constitution-index relationships.
Strengths
Aggregates data from 11 studies encompassing 2,168 participants, providing a consolidated evidence base.
Uses established quality assessment tools (AHRQ checklist, Newcastle-Ottawa Scale) and network meta-analysis software (Stata, Addis).
Study protocol is registered with a public registry (PROSPERO CRD42023433078), enhancing methodological transparency.
Limitations
The underlying row-level patient data is not provided; the dataset contains aggregated meta-analysis results.
Column-level documentation for the analysis outputs is absent; data structure must be inferred from the DOCX file.
The 3.5 MB file size suggests a small-scale document, limiting the volume of directly usable numerical data.
Provenance
Source
Sheng Xie, via figshare.
Collection Method
Systematic review and network meta-analysis of literature retrieved from PubMed, Embase, Cochrane Library, CNKI, VIP, Wanfang Database, and Sinomed.
Freshness
Last updated 2026-05-22 05:35:25.
Primary data format is a DOCX document; extracting structured tabular data for analysis may require manual processing.