Title: Mechanistic investigation and the optimal dose based on baicalin in the treatment of
ulcerative colitis--A preclinical systematic review and meta-analysis
Version: 3 Date: 28 Oct 2024
Reviewer:  Amira A A Othman
Reviewer's report:
In this meta-analysis titled "Mechanistic investigation and the optimal dose based on baicalin in
the treatment of ulcerative colitis – A preclinical systematic review and meta-analysis”, Chong
et al. assess baicalin’s therapeutic potential for treating ulcerative colitis (UC) in animal models,
focusing on its effectiveness in reducing inflammation and supporting gut health. This research
is relevant as it addresses the need for alternative treatments with fewer side effects for UC
patients. Below is an evaluation based on key aspects of the paper.
Chong et al. concluded that baicalin's anti-inflammatory and antioxidant qualities make it a
promising treatment for ulcerative colitis. They did point out that more investigation is required
to establish the ideal dosage for human use. The results might support baicalin clinical trials for
UC in the future, but given the limits of animal research, care must be taken.
In the Search Strategy Section:
It seems apparent that the authors employed particular search phrases relating to “baicalin” and
“UC” and performed a thorough search across multiple databases “PubMed, EBSCO, Web of
Science, and Science Direct”. They made sure the research chosen was pertinent and could offer
insightful comparisons by using animal studies that concentrated especially on the effects of
UC and baicalin.
In Data Extraction and Quality Assessment Sections
- Data was extracted independently by two authors, which is a good approach to minimize errors.
- They rated and identified potential bias areas, such as blinding and randomization, using the
SYRCLE risk of bias tool to assess the quality of the included studies. However, the overall
reliability may be impacted by the unclear or significant bias in many research in areas like
blinding and allocation concealment.
In Data Analysis and Heterogeneity
- The analysis included both fixed and random-effects models, depending on heterogeneity. They
provided subgroup and sensitivity analyses to explore and address high variability in outcomes.
- Significant heterogeneity was assessed using the Chi-square and I2 tests, but subgroup analyses
based on factors like animal species and dosage helped reduce it, though some variability
remained unexplained.
In Results Section:
The results were clearly interpreted, with the effects of baicalin on UC symptoms and biomarkers
visualized using 3D scatter plots and forest plots. Egger's test for publication bias was performed,
and the majority of measures showed little bias. However, because of the way the studies were
chosen, some results might still be biased.
The authors tried to contribute to this field of research with new findings, nevertheless, there are
some limitations identified in the paper, for which sufficient justification must be obtained.
1. High levels of heterogeneity among the included studies are revealed by the meta-analysis,
suggesting inconsistent findings. Even though sensitivity and subgroup analyses were performed
to address this, certain sources of variability are still unknown, which could make the overall
findings less reliable.
2. The reliability of the results may be impacted by bias introduced by the unclear or high risks
of bias in several of the included studies in areas like allocation concealment and blinding. This
affects the confidence in determining the effectiveness of baicalin.
3. It is challenging to extrapolate the results of this study to humans because it solely uses animal
models to assess baicalin's impact on ulcerative colitis. Clinical studies are required to verify its
effectiveness and safety in people.
4. The included studies might overestimate the effects of baicalin due to publication bias favoring
positive outcomes. Even if this was evaluated using Egger's test, several metrics still suggested
possible biases that could have affected trustworthiness.
5. Specific details about experimental protocols, such as how control groups were created and
how the best dosages were calculated, are missing from certain research. Reproducibility and
the capacity to validate results are impacted.
6. The lack of human clinical trials means that further research is necessary to discover the
best dosages and guarantee safety when applied to humans, even though the study points to a
promising role for baicalin.
Title: Mechanistic investigation and the optimal dose based on baicalin in the treatment of
ulcerative colitis--A preclinical systematic review and meta-analysis
Version: 3 Date: 28 Oct 2024
Reviewer:  Amira A A Othman
Reviewer's report:
In this meta-analysis titled "Mechanistic investigation and the optimal dose based on baicalin in
the treatment of ulcerative colitis – A preclinical systematic review and meta-analysis”, Chong
et al. assess baicalin’s therapeutic potential for treating ulcerative colitis (UC) in animal models,
focusing on its effectiveness in reducing inflammation and supporting gut health. This research
is relevant as it addresses the need for alternative treatments with fewer side effects for UC
patients. Below is an evaluation based on key aspects of the paper.
Chong et al. concluded that baicalin's anti-inflammatory and antioxidant qualities make it a
promising treatment for ulcerative colitis. They did point out that more investigation is required
to establish the ideal dosage for human use. The results might support baicalin clinical trials for
UC in the future, but given the limits of animal research, care must be taken.
In the Search Strategy Section:
It seems apparent that the authors employed particular search phrases relating to “baicalin” and
“UC” and performed a thorough search across multiple databases “PubMed, EBSCO, Web of
Science, and Science Direct”. They made sure the research chosen was pertinent and could offer
insightful comparisons by using animal studies that concentrated especially on the effects of
UC and baicalin.
In Data Extraction and Quality Assessment Sections
- Data was extracted independently by two authors, which is a good approach to minimize errors.
- They rated and identified potential bias areas, such as blinding and randomization, using the
SYRCLE risk of bias tool to assess the quality of the included studies. However, the overall
reliability may be impacted by the unclear or significant bias in many research in areas like
blinding and allocation concealment.
In Data Analysis and Heterogeneity
- The analysis included both fixed and random-effects models, depending on heterogeneity. They
provided subgroup and sensitivity analyses to explore and address high variability in outcomes.
- Significant heterogeneity was assessed using the Chi-square and I2 tests, but subgroup analyses
based on factors like animal species and dosage helped reduce it, though some variability
remained unexplained.
In Results Section:
The results were clearly interpreted, with the effects of baicalin on UC symptoms and biomarkers
visualized using 3D scatter plots and forest plots. Egger's test for publication bias was performed,
and the majority of measures showed little bias. However, because of the way the studies were
chosen, some results might still be biased.
The authors tried to contribute to this field of research with new findings, nevertheless, there are
some limitations identified in the paper, for which sufficient justification must be obtained.
1. High levels of heterogeneity among the included studies are revealed by the meta-analysis,
suggesting inconsistent findings. Even though sensitivity and subgroup analyses were performed
to address this, certain sources of variability are still unknown, which could make the overall
findings less reliable.
2. The reliability of the results may be impacted by bias introduced by the unclear or high risks
of bias in several of the included studies in areas like allocation concealment and blinding. This
affects the confidence in determining the effectiveness of baicalin.
3. It is challenging to extrapolate the results of this study to humans because it solely uses animal
models to assess baicalin's impact on ulcerative colitis. Clinical studies are required to verify its
effectiveness and safety in people.
4. The included studies might overestimate the effects of baicalin due to publication bias favoring
positive outcomes. Even if this was evaluated using Egger's test, several metrics still suggested
possible biases that could have affected trustworthiness.
5. Specific details about experimental protocols, such as how control groups were created and
how the best dosages were calculated, are missing from certain research. Reproducibility and
the capacity to validate results are impacted.
6. The lack of human clinical trials means that further research is necessary to discover the
best dosages and guarantee safety when applied to humans, even though the study points to a
promising role for baicalin.
Please review this paper.
user
Title: Mechanistic investigation and the optimal dose based on baicalin in the treatment of
ulcerative colitis--A preclinical systematic review and meta-analysis
Version: 3 Date: 28 Oct 2024
Reviewer:  Amira A A Othman
Reviewer's report:
In this meta-analysis titled "Mechanistic investigation and the optimal dose based on baicalin in
the treatment of ulcerative colitis – A preclinical systematic review and meta-analysis”, Chong
et al. assess baicalin’s therapeutic potential for treating ulcerative colitis (UC) in animal models,
focusing on its effectiveness in reducing inflammation and supporting gut health. This research
is relevant as it addresses the need for alternative treatments with fewer side effects for UC
patients. Below is an evaluation based on key aspects of the paper.
Chong et al. concluded that baicalin's anti-inflammatory and antioxidant qualities make it a
promising treatment for ulcerative colitis. They did point out that more investigation is required
to establish the ideal dosage for human use. The results might support baicalin clinical trials for
UC in the future, but given the limits of animal research, care must be taken.
In the Search Strategy Section:
It seems apparent that the authors employed particular search phrases relating to “baicalin” and
“UC” and performed a thorough search across multiple databases “PubMed, EBSCO, Web of
Science, and Science Direct”. They made sure the research chosen was pertinent and could offer
insightful comparisons by using animal studies that concentrated especially on the effects of
UC and baicalin.
In Data Extraction and Quality Assessment Sections
- Data was extracted independently by two authors, which is a good approach to minimize errors.
- They rated and identified potential bias areas, such as blinding and randomization, using the
SYRCLE risk of bias tool to assess the quality of the included studies. However, the overall
reliability may be impacted by the unclear or significant bias in many research in areas like
blinding and allocation concealment.
In Data Analysis and Heterogeneity
- The analysis included both fixed and random-effects models, depending on heterogeneity. They
provided subgroup and sensitivity analyses to explore and address high variability in outcomes.
- Significant heterogeneity was assessed using the Chi-square and I2 tests, but subgroup analyses
based on factors like animal species and dosage helped reduce it, though some variability
remained unexplained.
In Results Section:
The results were clearly interpreted, with the effects of baicalin on UC symptoms and biomarkers
visualized using 3D scatter plots and forest plots. Egger's test for publication bias was performed,
and the majority of measures showed little bias. However, because of the way the studies were
chosen, some results might still be biased.
The authors tried to contribute to this field of research with new findings, nevertheless, there are
some limitations identified in the paper, for which sufficient justification must be obtained.
1. High levels of heterogeneity among the included studies are revealed by the meta-analysis,
suggesting inconsistent findings. Even though sensitivity and subgroup analyses were performed
to address this, certain sources of variability are still unknown, which could make the overall
findings less reliable.
2. The reliability of the results may be impacted by bias introduced by the unclear or high risks
of bias in several of the included studies in areas like allocation concealment and blinding. This
affects the confidence in determining the effectiveness of baicalin.
3. It is challenging to extrapolate the results of this study to humans because it solely uses animal
models to assess baicalin's impact on ulcerative colitis. Clinical studies are required to verify its
effectiveness and safety in people.
4. The included studies might overestimate the effects of baicalin due to publication bias favoring
positive outcomes. Even if this was evaluated using Egger's test, several metrics still suggested
possible biases that could have affected trustworthiness.
5. Specific details about experimental protocols, such as how control groups were created and
how the best dosages were calculated, are missing from certain research. Reproducibility and
the capacity to validate results are impacted.
6. The lack of human clinical trials means that further research is necessary to discover the
best dosages and guarantee safety when applied to humans, even though the study points to a
promising role for baicalin.
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