JerMa88/BMC_Womens_Health_Peer_Reviews huggingface dataset:
Title: Prevalence of chronic pelvic pain and associated factors among indigenous women of
reproductive age in Ecuador
Version: 3 Date: 23 Feb 2024
Reviewer:  Héctor González-de la Torre
Reviewer's report:
Dear Authors:
Thank you for allowing me to review your manuscript. I believe that you have done a wonderful
job and that your research can be published. I would like to make some small comments in order
to improve your manuscript:
Introduction: I think it is adequate and correct. Perhaps you could add a small paragraph
explaining the characteristics of the Kichwa population for those readers who are not familiar
with this population.
Method
Interviewer training and data management: I am familiar with the Red Cap system and it ensures
traceability and internal validity of the data. However, it is not clear to me what the recruitment
method was. You indicate systematic sampling, which I don't know what you mean. There is
probability sampling (e.g. random sampling, e.g. stratified or proportional in this case) or non-
probability sampling (e.g. convenience sampling or consecutive sampling). Indicate clearly what
type of sampling was done based on these terms. This is important to ensure representativeness
of the sample.
Sample size: I have not been able to evaluate if the sample size  calculation is adequate, as the
formula appears with errors and I cannot see the estimated prevalence. What was the estimated
prevalence used for the sample calculation and in reference to which study or data was it based
on.
Statistical methods: Indicate the normality tests used to determine the appropriateness of the use
of the parametric test (t student).
Results: are correct, although I would like to make a proposal to the editor regarding how to
represent the data. I attach  an example
Proposal Table
Features                OR[95% CI]    adjusted p-value OR PR[95% CI]       adjusted p-valuePR
Hypertension 4.5 [1.67-12.25]                0.003                          2.1[087-4.88] 0.154
Dyspareunia ------ ------- ----------- -------
Non-cyclic pelvic pain ------ --------- ------------- --------
Conclusions: I would eliminate reference number 72. In the conclusions section, references are
not usually included.
I congratulate the authors for the work done.
Title: Prevalence of chronic pelvic pain and associated factors among indigenous women of
reproductive age in Ecuador
Version: 3 Date: 26 Feb 2024
Reviewer's report:
Introduction
Interesting study but without focus. In the introduction, the research hypothesis must be made
explicit. Today, Things are known about chronic pelvic pain; which could be characteristic of
chronic pelvic pain for this population? This issue is very relevant to justified the study:  1. -
association between variables 2. - Regression model construction.
In the 21th century1, it is not possible to say that nothing is known about chronic pelvic pain
and do a descriptive study; using statistical inference tools such as regression models.
The title indicates "Prevalence of chronic pelvic pain and associated factors among indigenous
women of reproductive age in Ecuador" then “Chronic Pelvic Pain” must be used as the main
variable. The primary dysmenorrhea, non-cyclic pelvic pain, and persistent dyspareunia are
subtypes of pelvic pain.
Material and methods
Good description of information collection
Sample size: Do not put formulas, just reference. Indicate if there was age stratification. Indicate
margin of error and intervals confidence (alpha) used.
Statistical methods: indicate in more summary the software used. Regarding variable association
assessment, this must include the main variable; regarding possible predictors.
Regarding the regression model used, it is not clear if I use logistic regression or log-binomial
regression. If used log-binomial regression why did you report odds ratio?  The logistic
regression uses link function called logit. Log-binomial regression uses link function called log
of the probability.  Exponentiating a regression coefficient in logistic regression results in an
odds ratio (OR). Similarly, Exponentiating a regression coefficient in log-binomial regression
results in a risk ratio (RR) or prevalence ratio (PR). This is important because the "OR" loses
interpretation of relative risk on the prevalence of risk factors greater than 10%.
Regression models can give any result; and this does not mean that reality is this way. Thus,
must indicate in summary form for the regression model, if the following assumptions were met:
1. - Error specification (linktest) 2.-Linearity of continuous predictors for the link function of
the proposed model (Linear tendency test) 3.-Absence of multicollinearity between predictor
variables and 4. - Assessment of the influential outliers
Also, indicate "Validation Measures" for the final regression model. This includes calibration
and discrimination. The calibration of the regression model refers to the agreements between
the predicted outcome and observed outcome (show in summary form a comparison of the link
function predicted by the model and observed in the data). The discrimination of a regression
model reflects its ability to distinguish the outcomes between subjects (ROC analysis). These
aspects are important to assess how close or far the regression model is from reality.
Discussion and conclusion
Modify according to hypotheses and results
Title: Prevalence of chronic pelvic pain and associated factors among indigenous women of
reproductive age in Ecuador
Version: 3 Date: 28 Feb 2024
Reviewer's report:
Dear authors
Interesting study with a significant number of subjects from a specific population group. The
writing is clear, concise, relevant, original and of interest to readers. It's a well-presented study
design, with appropriate statistical analysis and pertinent and updated references. The discussion
is broad with a consistent critical analysis with the presented results. This is an important article
for the development of interprofessional preventive strategies in health care and intervention for
specific populations.
Best Regards
Title: Development and validation of a nomogram model of depression and sleep disorders and
the risk of disease progression in patients with breast cancer
Version: 0 Date: 06 Dec 2023
Reviewer's report:
This manuscript presents a significant study exploring the relationship between depression, sleep
disorders, and breast cancer progression, aiming to develop a predictive model. The use of
diverse prediction models is a strong aspect of the study, as well as the focus on biopsychosocial
factors in breast cancer is timely and important.
While the study's methodology and clinical focus are commendable, there are some minor
revisions that authors may want to consider:
1. Authors may state more clearly, in the material and methods section, the type of study that
has been conducted.
2. A detailed limitations section is missing, referring to the following elements:
a) The study relies solely on self-report measures. This may introduce limitations due to the
inherent subjectivity and potential biases of these methods. Participants' responses can be
influenced by various factors such as their current mood, personal perceptions, or a tendency to
respond in a socially desirable manner. This can lead to either underreporting or overreporting
of symptoms. This reliance is an element that authors may consider clearly stating in a dedicated
limitations section and in outlooks for future research.
b) The paper needs to account for potential confounders such as cancer stage, treatment types,
lifestyle factors, socioeconomic status, and psychological resilience. In particular, the perceived
social support is an element that can greatly impact disease progression.
c) The discussion on the generalizability of the results to other populations or settings is lacking
and should be included.
3. The statement in the discussion section, "Both methods can improve clinical decision-
making from multiple perspectives," along with the assertion that the approach may provide
theoretical guidance for clinically targeted interventions using precise multidisciplinary care
models, highlights the potential clinical implications of the study. However, the discussion
would benefit from a more detailed exploration of how exactly these findings and models can
be integrated into nursing practice, which currently remains unclear in the discussion section.
Title: Development and validation of a nomogram model of depression and sleep disorders and
the risk of disease progression in patients with breast cancer
Version: 0 Date: 18 Dec 2023
Reviewer's report:
Thank you for your effort. I have a major revision decision. I give some recommendations below.
Good luck!
Abstract
The result should be summarized. Important results should be written.
Statistical methods
What type of regression was used? Linear regression, logistic regression, cox regression, ….
Please revise it in all text.
For survival analysis, the survival and censoring time as well as the event must be defined.
Results
Table 1, for Follow-up time variable should be reported median and IQR (Inter Quartile Range).
Generally, according to the collinearity between the variables, the best model is Lasso. It is not
necessary to use other models and it does not work well.
Title: Development and validation of a nomogram model of depression and sleep disorders and
the risk of disease progression in patients with breast cancer
Version: 2 Date: 03 May 2024
Reviewer's report:
Dear Authors,
Thanks for your efforts in the revised manuscript.
There are some minor points.
1. In the method, ECT, CT, and MRI should be detailed in their use for the first time.
2. The period of those patients was so old. The recent data was collected in 2020. However, the
follow-up information was not updated. Please explain it.
A major point (most important):
You obtained informed consent from every patient, so it was a prospective study. However, the
data on ethical approval were more late than in 2015. Or did you obtain the informed consent
after 2022? You should check it and explain it.
Title: Primary Care and Abortion Provider Perspectives on Mail-order Medication Abortion:
a qualitative study
Version: 2 Date: 25 Feb 2024
Reviewer's report:
Thank you for the opportunity to review this article, which contributes to the field in our
understanding of how clinicians and administrators view mail-order medication abortion. The
expansion of reproductive health services, especially abortion, in primary care, is critical given
the current state of restrictions in the U.S. I recommend accepting the manuscript after minor
revisions:
Abstract:
• Remove “all” from first sentence of Methods.
Background:
• Note how even after removal of in-person dispensing requirement the study will make a
contribution to the field.
Methods:
• Describe states from which participants practice, in terms of abortion hostility at the time of
recruitment (presumably all supportive states, but what level as categorized by Guttmacher?)
• Second paragraph states “Patients…took the pills…” Was there documentation of them taking
the pills? If not, remove.
Results:
• Were there differences in concerns by administrators vs. clinicians? I assume their concerns
would be distinct.
• The distinction between logistical and clinical concerns isn’t clear. Shipping delays was noted
under logistical concerns and clinical concerns. Suggest combining those two themes.
•  Under legal concerns, the authors noted findings related to concerns about reliable mailing
address and confidentiality. These seem to align better in the logistical/clinical concerns.
Title: Significant increased isolation of Escherichia coli in Iranian women with endometriosis:
A case control – Study
Version: 1 Date: 22 Jan 2024
Reviewer:  Elena V. Kudryavtseva
Reviewer's report:
The topic of the article seems relevant. Endometriosis is one of the most common gynecological
diseases, but its pathogenesis is still not fully understood. The results obtained by the authors
may contribute to obtaining new knowledge about this pathology, which may help in adjusting
treatment regimens
Title: Significant increased isolation of Escherichia coli in Iranian women with endometriosis:
A case control – Study
Version: 1 Date: 24 Jan 2024
Reviewer's report:
In my opinion, the topic of the article was very interesting and well written.
But there were some problems in the manuscript, which are shown in the article as comment
and track changes.
Abstract:
Abstract should revise.
Keyword should check with Mesh term. Bacterial contamination is not included in the Mesh-
term. Instead of this, it should be better to write the design of study as keyword "Case-Control
Study".
Material & Methods:
Line 10: What is the meaning of "etc", here? It means your inclusion criteria have no limitations
and it may include many other diseases.
Line 11: Since the author wrote that the control group was selected from women who were
candidates for surgery due to some problems such as myoma or abnormal uterine bleeding, it
is unlikely those women who had these complications and were candidates for benign surgery
would have regular menstruation.
Line 12-13: This line is written repeatedly.
Line 15: It is not necessary to write again about age.
Results:
Line 8-9: The method of ASRM classification should move to the M&M section.
Line 22:  This sentence "By this means, endometriosis patients with E. coli positive cultures had
lower fertility rate." ,  Should move to the discussion.
Discussion:
The discussion section needs to be revised to have the necessary logical pattern.
Line 16: This sentence is not clear." Despite the next-generation sequencing (NGS) technologies
providing increased efficiency and data output through short and predictable identification
protocol, identification of unculturable and fastidious bacteria, producing accurate results, and
data portability , most fail to resolve isolated microbial communities to the species level."
Title: Significant increased isolation of Escherichia coli in Iranian women with endometriosis:
A case control – Study
Version: 2 Date: 26 Mar 2024
Reviewer:  Elena V. Kudryavtseva
Reviewer's report:
The issue of the article is quite relevant. The pathogenesis of endometriosis is multifaceted; in
recent years, there have been more and more reports that the characteristics of the endometrial
microbiome may play a role in the development of this disease. However, the article requires
improvement.
The authors indicate that a prospective study was conducted, but it is not prospective because it
was known in advance which group each patient belonged to.
Statistical processing is not entirely correct. Table 2 makes a comparison not between the study
groups, but between the group with endometriosis and the total number of patients. In Table
3, the authors divide the groups into additional small subgroups (depending on the presence/
absence of a particular microorganism), and these subgroups are too small in size to allow
high-quality statistical processing (in the group “Klebsiella positive” there are only 3 women,
“Enterobacter positive” " - only 2). In Table 4, it is unclear between what and what is being
compared to determine p.
Since the principles of statistical processing are not entirely clear, it is difficult to assess how
logical the authors’ conclusions are.
It is necessary in the “Materials and Methods” section to describe in more detail the statistical
processing, in particular whether the distribution was checked for normality (if the distribution
did not correspond to normal, it is preferable to indicate not the mean value, but the median
with interquartile range), what criteria were used to assess the statistical significance of the
differences .
The purpose of the study does not correspond to the described design. The authors write that
the purpose of the study is “to compare the cultures of endometriosis-affected women and
normal women,” however, the comparison group included not "normal women", but women
who have not been diagnosed with Endometriosis, but have other gynecological pathology. In
the conclusions, the authors write that e.coli is also associated with infertility and IVF failure,
although the "materials and methods" do not indicate that women with these conditions were
included in the study. Thus, the conclusions are not entirely consistent with the results.
Title: Significant increased isolation of Escherichia coli in Iranian women with endometriosis:
A case control – Study
Version: 4 Date: 30 Apr 2024
Reviewer's report:
It seems, after applying different revisions; the current version of the article lacks coherence
and is confusing.
For example:
In the background section of Abstract, it is stated that the cultures of two groups were compared.
It appears that these cultures were prepared prior to this study and not specifically for it. The
study methodology mentions that two groups were selected as candidates for the study and
culture samples were collected from them. However, there seems to be some confusion in this
section as it mentions both cross-sectional and case-control study designs. Please correct this
section.
The main issue with the article is that it contains significant flaws in terms of its writing and
structure. Therefore, it requires a thorough revision to address these problems. Some of these
issues have already been corrected as a track change in the article file, which has been attached
and sent.
Title: Predicting risk of the subsequent early pregnancy loss in women with recurrent pregnancy
loss based on preconception data
Version: 1 Date: 31 May 2024
Reviewer:  Yigit Cakiroglu
Reviewer's report:
General comments:
This manuscript has been processed in accordance with the author guidelines of the journal.
The writing style is clear and descriptive. The manuscript proposes information about prediction
models related with recurrent pregnancy loss. The MS should be checked for language (i.e..Line
14: but also to evaluation; Line 14: The study was to develop…)
Abstract:
The abstract accurately describes the short-summarized content of the article.  The conclusion
part of the abstract should be rewritten.
Key words are adequate in quality and number.
Introduction:
Information about pregnancy loss, recurrent pregnancy loss, and the role of machine learning
on the predicition of RPL have been given in the introduction section.
Materials and Methods
The materials and method section contains the method of the article, gives information about the
participicant selection, diagn#stic criteria, predictive variables and statistical methods employed.
Results
The result section contains important and significant findings and observations in regards of the
prediction models.
Discussion
The discussion section states the importance and significance of the findings.
Conclusion:
Conclusion part reflects the main idea of the MS.
References:
The references section contains appropriate and number of references.
Figures:
Figures are demonstrative and illustrative.
Tables:
Tables are well-designed.
Title: Predicting risk of the subsequent early pregnancy loss in women with recurrent pregnancy
loss based on preconception data
Version: 1 Date: 02 Jun 2024
Reviewer:  Fatih Akkus
Reviewer's report:
This study aims to develop a model that predicts early pregnancy loss (EPL) in women with
recurrent pregnancy loss (RPL). This model aims to improve clinical decisions using pre-
pregnancy data.
The research was conducted in a prospective cohort study of 1050 RPL women. Participants
were divided into training and validation groups. The best predictive model was determined
using advanced statistical methods such as LASSO regression, logistic regression, general linear
model (GLM), gradient boosting machine (GBM), random forest (RF) and deep learning (DP).
The results revealed that the GBM model showed the best performance with the highest AUC
(0.805). No significant difference was found between the 16-variable model selected by LASSO
regression and the 9-variable model selected by logistic regression, indicating that a simpler
model may also be effective.
The findings of the study emphasise the potential of the GBM model in predicting EPL in
RPL patients. It is stated that future studies should validate the clinical applications of this
model. Furthermore, a nomogram based on the best predictive features is developed, providing
a practical tool for clinicians.
It is a very good article, well designed, well written, using good statistical methods. I
congratulate the whole team.
Title: Use of ultrasound imaging Omics in predicting molecular typing and assessing the risk
of postoperative recurrence in breast cancer
Version: 0 Date: 07 May 2024
Reviewer:  Zongren Ding
Reviewer's report:
It is an honor to have this opportunity to review your manuscript. Your article is clinically
valuable and easy to read and understand. I would like the authors to address my queries noted
below to strengthen the work.
1. you mentioned that “Unet software was used for the AI outlining segment, and the
performance was rigorously tested”, please provide more details.
2. Breast ultrasound image acquisition was conducted by an experienced radiologist, explain
how to control image quality.
3. please check the Table 1 carefully, I found an obvious mistake in it.
4. please add a note to the Tables and Figures, to make more readable.
Title: Use of ultrasound imaging Omics in predicting molecular typing and assessing the risk
of postoperative recurrence in breast cancer
Version: 0 Date: 16 May 2024
Reviewer:  Yuanshen Zhao
Reviewer's report:
The manuscript presents a study on predicting the risk of postoperative recurrence and molecular
typing of breast cancer using multiparametric ultrasound imaging and radiomics. While it has
some clinical value, there are several limitations to consider. Here are some review comments:
1. The literature review in the introduction is broad but lacks a detailed discussion of key studies
and existing models. It fails to highlight the novelty and unique contributions of this research.
2. The criteria for sample selection are not described in sufficient detail. The specific reasons for
the exclusion criteria are not clearly stated, which could affect the reproducibility and credibility
of the study.
3. The description of clinical data collection methods is not specific enough, especially regarding
the acquisition process of ultrasound images. It is recommended to add details about image
quality control and acquisition consistency.
4. The process of feature extraction using the PyRadiomics package is too brief, lacking details
on feature selection and data processing, such as specific details on how the SMOTE method
was applied.
5. The description of using LASSO regression and SVM methods is too brief, lacking details on
model parameter selection and optimization. It is recommended to add specific steps for model
training and validation.
6. The statistical analysis in the results section is not detailed enough, lacking sufficient statistical
test results and significance levels. It is recommended to supplement with a detailed statistical
analysis report.
7. The results section lacks adequate figure support. The existing figures contain too little
information. It is recommended to add more figures to visually present the study results, such
as ROC curves and calibration curves for different molecular subtypes.
8. There's no need to include the exact same figure in Figure 1d and Figure 2d. There's a lot of
important results that could be better illustrated with more diverse and informative figures.
Title: Title: When Synchronous Mucinous Metaplasia and Neoplasia of the Female Genital
Tract and Peutz-Jeghers Syndrome Meet: A Case Report and Literature Reviews
Version: 1 Date: 27 Apr 2024
Reviewer's report:
Dear authors, I read your study,
I have some questions:
Why is this case significant?
abstract: conclusion is not along with the findings?
Abbreviation need to be fully introduced before its use. Serine/threonine kinase 11, TCT,
please consider this comment for all abbrivation.
Keywords should be based on the MESH.
Background: there should have refrence.
Literature Reviews: please make a table and based on the published date, bring all cases reported
in the table.