Table 1_Autologous regenerative cell therapy for female stress urinary incontinence: a sys
by Jiemei Chen·Updated 2d ago
9.9 KB1files
Available on 1 platform
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Description
A 2026 systematic review and meta-analysis by Jiemei Chen, aggregating data from 19 studies involving 591 patients. The dataset compiles clinical outcomes, including cure and improvement rates, pad test results, leakage frequency, and quality-of-life scores, to evaluate the efficacy and safety of autologous regenerative cell therapy for female stress urinary incontinence.
Use Cases
Evaluating the pooled efficacy of regenerative cell therapy based on reported cure and improvement rates.
Analyzing treatment safety profiles based on compiled adverse event and loss-to-follow-up rates.
Assessing changes in patient-reported outcomes based on incontinence-specific questionnaire and quality-of-life scores.
Investigating heterogeneity in clinical trial results based on the subgroup and sensitivity analyses described.
Strengths
Includes data from 19 studies encompassing 591 patients, providing a quantitative synthesis of the field.
Reports specific pooled outcome rates, including a 41% cure rate and 55% improvement rate.
Analyzes multiple secondary outcomes including urodynamic parameters, pad tests, and quality-of-life measures.
Dataset is openly licensed under CC-BY-4.0, facilitating reuse and sharing.
Limitations
Row count and column-level documentation are unknown, requiring manual inspection after download to understand data structure.
The underlying studies are described as having short follow-up, significant heterogeneity, and low-to-moderate quality, which may limit the strength of conclusions.
The dataset is very small at 9.9 KB, indicating a limited scope focused on aggregated summary statistics rather than individual patient data.
Provenance
Source
figshare, authored by Jiemei Chen.
Collection Method
Systematic review and meta-analysis of studies from PubMed, Web of Science, EMBASE, Cochrane Library, and CINAHL databases.
Freshness
Last updated 2026-06-03 04:47:23.
Data is provided in an XLSX (Excel) format; users will need compatible software to open it.