JerMa88/BMC_Womens_Health_Peer_Reviews huggingface dataset:
Title: Risk Factors for Postoperative Hypoproteinemia in Ovarian Cancer: A Predictive
Nomogram
Version: 1 Date: 09 Feb 2025
Reviewer's report:
The authors aim to identify risk factors for postoperative hypoproteinemia after radical
ovarian cancer surgery. They found high preoperative CRP level, low ALB level, excessive
intraoperative net fluid gain, weight loss >5% in the month prior to surgery, and concomitant
gastrointestinal surgery are independent risk factors for postoperative hypoalbuminemia in these
patients. A nomogram prediction model was developed with reasonable accuracy and prediction
value. This was a well done study addressing the need to recognize the high incidence of
postoperative hypoproteinemia which are associated with high morbidity.
I have a few questions:
1. Sincere there was a difference in the length of surgery (LOS)between the two groups, why
was LOS not part of the multivariate analysis? Obviously as the authors stated, longer surgery
requires more fluids, and fluids in itself was associated with hypoproteinemia.
2. Since all surgeries were performed by the same team, did longer surgery indicate higher grade
of cancer?
3. How many patients in each group received blood transfusion? Were the hemoglobin levels
different between the two groups?
Overall, I think it is a good paper to address the awareness of postoperative hypoproteinemia
and help explore treatment aimed at reduced morbidity and mortality.
I took the liberty to edit the manuscript, mostly to make it more succint.
Weike Tao, MD
Title: Risk Factors for Postoperative Hypoproteinemia in Ovarian Cancer: A Predictive
Nomogram
Version: 1 Date: 14 Feb 2025
Reviewer:  Kyung Jin Eoh
Reviewer's report:
The manuscript presents important findings and a predictive nomogram that could be of
significant clinical value. Below are some minor revisions that could further enhance the clarity
and accuracy of the paper.
1. In the abstract and throughout the manuscript, the terms "hypoproteinemia" and
"hypoalbuminemia" are used interchangeably. Since the study focuses on albumin levels, it
would be preferable to use "hypoalbuminemia" consistently to avoid potential confusion.
2. There are minor spacing inconsistencies in some sections (e.g., in the keywords:
"Keywords:Ovarian cancer,Radical surgery,Hypoproteinemia,Risk factors,Nomogram"). A
quick proofreading check to ensure proper spacing and uniform formatting would improve
readability.
3. In the results section, cut-off values for CRP (6.69 mg/L), ALB (43.35 g/L), and net fluid
balance/weight (40.71 mL/kg) were used. It would strengthen the validity of the study if a
brief explanation is provided on how these cut-off points were determined (e.g., ROC curve
optimization, clinical relevance, or prior literature).
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 1 Date: 04 Jun 2024
Reviewer:  Süleyman Cemil O#lak
Reviewer's report:
I consider that this study does not offer new information or significant findings that enhance our
knowledge regarding the correlation between serum lactate dehydrogenase level with disease
severity, and maternal and perinatal outcomes in preeclampsia. Lots of similar studies exist
in the literature. Also, a recent comprehensive review concluded similar findings (Deeksha
HS, Pajai S, Reddy Eleti M, Navalihiremath VU. A Comprehensive Review on Serum Lactate
Dehydrogenase (LDH) and Uric Acid in Preeclampsia: Implications for Maternal Health and
Disease Severity. Cureus. 2024;16(3):e56928).
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 1 Date: 04 Jun 2024
Reviewer's report:
Nasir et al. have aimed to evaluate the levels of lactate dehydrogenase (LDH) in pregnant
women complicated with preeclampsia and its correlation with the severity of the disease and
the maternal and perinatal outcomes.  Moreover, they emphasized that LDH can be a valuable
biomarker for predicting the severity of preeclampsia. The study is orginal, well prepared and
discused. In my opinion this paper has a potential to make a positive contribution to the co-
existing literature. I have only some minor recommendations for the authors:
1- I think that preeclampsia may cause neonatal and maternal morbidity due to its severity.
Uric acid and the platelet-lymphocyte ratio (PLR), which can be easily calculated clinically may
predict adverse neonatal outcomes. The study mentioned below may contribute to this article.
“Yaki#tiran B, Tanaçan A, Altinbo#a O, et al. Role of derived neutrophil-to-lymphocyte
ratio, uric acid-to-creatinine ratio and Delta neutrophil index for predicting neonatal
outcomes in pregnancies with preeclampsia. J Obstet Gynaecol. 2022;42(6):1835-1840.
doi:10.1080/01443615.2022.2040968”
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 1 Date: 09 Jun 2024
Reviewer:  Almagul Kurmanova
Reviewer's report:
The study is devoted to an urgent problem - early prediction of severe preeclampsia and adverse
obstetric and perinatal outcomes.
The introduction should justify the choice of LDH as a potential marker of severe preeclampsia.
In materials and methods - Normal levels of LDH in the blood can vary depending on the lab,
what LDH level was considered elevated?
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 2 Date: 26 Jun 2024
Reviewer's report:
1.There is a relatively large literatüre investigating serum lactate dehydrogenase level in
preeclampsia  This literatüre was underutilized here. It needs to be reviewed more fully to make
a stronger case for the importance of the study (in the Introduction and  Discussion).
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 2 Date: 29 Jun 2024
Reviewer's report:
Hi,
I found the study ineffective because conducting tests in the third trimester does not change
the disease outcome. Additionally, factors such as age and BMI, which are already known risk
factors for pre-eclampsia, introduce significant confounding variables. The study would have
been more valuable if conducted before the 20th week of gestation.
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 2 Date: 01 Jul 2024
Reviewer's report:
1. lines 36 to 39 are out of place. We should first mention that there are predictors of adverse
maternal and perinatal outcome  in preeclampsia cases and so on ...................
2. Lines 46 to 47 - erroneously written
3. Lines 81 to 82 - There is no criteria for mild preeclampsia if BP is equal to or more than
160/110. We need to repeat BP after 15 minutes and then label
4. Figure 1 : shows maternal complications in which study group ?
5. There is difference in mean levels of LDH given in study group in Table 3 and 4
6.  Please if you can specify when the sample for LDH was taken - at time  of induction in
study or at time of IOL, early labour or elective CS. A patient presenting at 28 weeks with mild
preeclampsia, may develop preeclampsia in coming weeks and be having high LDH which we
may not have evaluated
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 3 Date: 29 Jul 2024
Reviewer's report:
The authors have performed an original study  on the utility of uric acid to platelet ratio on the
prediction for severity of preeclampsia. I have some recommendations for the authors:
1) The pathophysiology of preeclapmsia  and its association with inflammation should be
discussed in more detail.
2) The duration of blood sampling should be clarified, at admission to hospital or earlier?
3) There are recent studies in the literature evaluating the utility of complete blood cell indices
for predicting preeclampsia. Please expand the discussion accordingly.
4) Please add more information regarding the recent biomarkers in the prediction of preeclampsia
like s-flt, endoglin, etc.
5) Please underline the limitations of biomarkers in the prediction of preeclampsia.
6) the following literature may be useful:
''Tanacan, A., Sakcak, B., Ipek, G., Agaoglu, Z., Peker, A., Haksever, M., ... & Sahin, D. (2023).
The role of first trimester eosinophil count and eosinophil-based complete blood cell indices in
the predictiction of preeclampsia: A case-control study. Placenta, 143, 16-21.''
''#pek, G., Tanaçan, A., A#ao#lu, Z., Ba#temur, A. G., Y#ld#z, E. G., & #ahin, D. (2024). The
role of aspartate aminotransferase to platelet ratio index (APRI) in the first trimester for the
prediction of superimposed preeclampsia: A case-control study from a tertiary center. Pregnancy
Hypertension, 37, 101132.''
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 3 Date: 31 Jul 2024
Reviewer's report:
Review
Serum lactate dehydrogenase level in Preeclampsia and its correlation with disease severity,
maternal and perinatal outcomes
Line 13
It says tocorrelate, it should say to correlate
Lines 36, and 37
It says: Uric acid and the platelet-lymphocyte ratio (PLR), which can be easily calculated
clinically, may predict adverse neonatal outcomes.
The authors should remove this text because it is not convenient.
Lines 79, 80, and 81
It says: The preeclampsia was diagnosed as mild when BP was #160/110 (which repeated after
15 minutes and then labelled) after 20 weeks of gestation in a pregnant woman with previously
normal blood pressure, as well as urine dipstick reading of + 2 protein 9,15.
This definition is incorrect
Line 111
Statistical analysis section
In this section I expected to find the Pearson correlation test or the Spearman correlation test
because the authors attempted to correlate serum LDH levels with other preeclampsia severity
variables, maternal outcome, and fetal outcome. The authors did not use correlation tests. The
authors found significant differences, but no correlations.
Introduction section
The authors should add the necessary text and references to explain the role of the LDH enzyme
in the pathophysiology of preeclampsia, the cause of its elevation, and its translation into the
clinical field.
Material and methods section
There are four isoenzymes of LDH, the authors should note which of them was titrated in the
laboratory or, if applicable, write that only LDH was reported without isoenzymes.
The authors should take into account that the major criteria for the severity of preeclampsia
are systolic and diastolic blood pressure and data on maternal organic lesions, but not fetal
data. The additional fetal data that were studied in the research are of clinical interest only,
because international organizations and expert groups do not consider them to be complications
of preeclampsia.
Results section
Figure 1. Authors should note the meaning of CVA.
Tables 3, 4, and 5. The authors should add the meaning of LDH.
Comment
The topic of research is not new, but it continues to interest the international community. The
content is valuable because it shows data from a contact center, but it is local results with
a descriptive design that has limitations. The authors must correct the details that have been
previously noted.
Title: Serum lactate dehydrogenase level in preeclampsia and its correlation with disease
severity, maternal and perinatal outcomes
Version: 4 Date: 21 Aug 2024
Reviewer's report:
Serum lactate dehydrogenase level in Preeclampsia and its correlation with disease severity,
maternal and perinatal outcomes
Authors carried out all recommendations from the first round of review.
The manuscript can be published without changes.
Title: Decomposing the effect of women's educational status on fertility across the six geo-
political zones in Nigeria: 2003-2018
Version: 1 Date: 27 Sep 2024
Reviewer's report:
I have reviewed the manuscript and its aim was to decompose the effect of women’s literacy
status on fertility in the geo-political zone of Nigeria. The study uses Demographic and Health
Survey data for the period 2003 to 2018. The paper has attempted to perform decomposition
analysis; however, the execution of the method is not easy to follow and replicate. The terms
‘educated’ and ‘uneducated’ versus ‘literate’ and ‘illiterate’ are used interchangeably when in
the strictest sense they can mean different things. The methods section of the manuscript needs
to be streamlined and remove excess details such as explanations of household listing. It also
needs to be clear of the DHS datasets were pooled or analyzed separately.  Also, how the weights
were applied. In this section, there is a mix of font type.
In the statistical analysis section, it is not clear why we have a number of estimates of fertility:
children ever borne, total fertility rates, parity progression ratios. What is the purpose of each
of these measures? How are they used in decomposition analysis? What is the purpose of using
risk difference? Why was the heat map used? Provide an explanation besides pointing to the
literature.
The results of the logistic regression analysis for the Blinder-Oaxaca decomposition are not
provided.
The magnitude of the contributing factors is not provided.
The manuscript requires proofreading and editing.
Title: Decomposing the effect of women's educational status on fertility across the six geo-
political zones in Nigeria: 2003-2018
Version: 1 Date: 29 Sep 2024
Reviewer:  Elhakim Ibrahim
Reviewer's report:
The study addresses a subject of wide public health interest and employs an appropriate
empirical approach to achieving its core objective. The paper reflects originality and substantial
contribution to knowledge on the topic. The empirical strategies are well documented.
However, I would like to suggest, except for evidence of multicollinearity, including some
variables such as “ever used of family planning”, “relationship to household head”, “perceived
problem getting permission to seek healthcare (not a big problem v a big problem)”, and
“perceived problem getting money to seek healthcare (not a big problem v a big problem)”.
These variables have been documented to play a crucial role in past studies. I believe that
addressing this minor observation could enhance the validity of the study findings.
Title: Decomposing the effect of women's educational status on fertility across the six geo-
political zones in Nigeria: 2003-2018
Version: 1 Date: 14 Oct 2024
Reviewer's report:
This study is interesting. However, for the manuscript to be in an acceptable form for publication,
I advise the authors consider my comments below to revise the manuscript.
Abstract
- The study uses a repeated cross-sectional analysis design so this should be stated
- The Background should include additional aims of the study since the study does more than
quantify the fertility rate between uneducated and educated women.
- Why is the total stated as “nTotal”? The way in which the DHS survey years are stated and
the total sample size should be separate sentences.
- Why stated proportions with no education for 2003 and 2014? The choice of those two years
in the abstract seems random.
Introduction
- The literature on the role of mass education on fertility in sub-Saharan Africa as well as the
role of abortion can be discussed since it contributed to fertility decline in sub-Saharan Africa.
- The authors need to comment on the extant fertility and education studies in Nigeria. These
seem to be missing.
- It is not clear why the authors choose to assess fertility across four surveys. The rationale for
all the survey years should be more evident.
-  Examples of studies with references are needed to explain the sentence about how fertility
varies due to diversities and differences based on sociocultural factors.
Methods
- Variable description – for the age at first marriage variable, how were never married women
classified? This needs to be indicated. If it is an oversight, it has to be rectified.
- Region was also not reported as a variable in the Variable description section
- The variable “neighbourhood socioeconomic status” is mentioned under the “statistical
analysis” section but is not mentioned in the “variable description”
- How the decomposition values in the heatmap are arranged by survey year and region needs
to be explained.
Results
- Tables 1 and 2 need to be looked at. Perhaps decimal places can be reduced to one place so
that all the columns fit well on each table.
- Why is the parity progression ratio needed? The concept is technical and needs explanation.
However, its inclusion should be justified.
- For Figure 1 – perhaps range plots would be best. It is not clear why some of the points are
an X and others an X with a line.
- Figure 3 needs to be changed. The y-axis needs better labelling. Does it indicate uneducated
and educated women across study waves? Why is the figure dark?
- Figure 5 has several points that may not be needed. The values across the waves and regions
by the different factors are too many. Does all this data add value to the study. The authors could
consider the decomposition analysis using two waves - 2003 and 2018. This would indicate
more recent implications.
Discussion
-  More discussion in relation to the regions should be mentioned. What have other findings
stated on the regional-education fertility differences.
Title: Decomposing the effect of women's educational status on fertility across the six geo-
political zones in Nigeria: 2003-2018
Version: 2 Date: 10 Nov 2024
Reviewer's report:
I have reviewed the manuscript for the second time. I still have the following comments:
Methods section:
How was the weighting done? The explanation of weighting is general rather than specific.
Application of the direct method of estimating total fertility rate (TFR) using Demographic and
Health Survey (DHS) data is not clearly described. Merely referencing Moultrie et al 2013 is not
adequate. There is a lot involved in applying the direct method of estimating TFR when using
DHS data. Add some more specific elaboration on how this was done.
A new variable has been introduced “neighbourhood socioeconomic status” How was this
variable constructed? It is also not in Table 1 and Table 2.
Results section:
Use of the terms ‘educated’ and ‘uneducated’ versus ‘literate’ and ‘illiterate’ in the results is
inconsistent. Table 2 and Figure 4 use ‘educated’ and ‘uneducated’ while Figures 1,2 and 3 use
‘literate’ and ‘illiterate’
Figure 2 with parity progression ratios (PPRs) is still part of the manuscript results despite the
responses to the comments indicating that this part has been removed. In fact, the PPRs results
in Figure 2 have not been interpreted as expected.
In Figure 4, the Risk Differences (RDs) have 2-decimal places while numbers being subtracted
have 1-decimal place. Ensure there is consistency. The weights in Figure 4 have not been
interpreted. Results from the Random Effects Model are presented in Figure 4 and yet there is
no mention of this in the methods.
The decomposition results in Figure 5 have not been fully interpreted as expected. The current
interpretation is general rather than analytical for the Blinder-Oaxaca regression.
Title: Decomposing the effect of women's educational status on fertility across the six geo-
political zones in Nigeria: 2003-2018
Version: 2 Date: 14 Nov 2024
Reviewer's report:
-The authors still need to report what has been studied on this subject in Nigeria. That seems
to still be missing in the Introduction.
- Variable Description: How was the analysis adjusted to fit the age of respondents?
- The ‘Variable Description’ and ‘Statistical Analysis’ sections have a different font style which
need to be changed.
- A few comments from the previous review were responded to with cursory comments and thus
still need to be addressed. For example, how were women with no births and those not married
categorized in the study? This was still not explained when age at first birth and marriage were
explained.
- Also, the authors state that the way in which some variables are measured are reported in
another paper. However, some readers may not have access to those additional papers, so at least
the response categories for the neighborhood socioeconomic status variable should be stated.
- The authors fail to explain the need for the parity progression ratio figure in the manuscript
but indicate in the reviewers’ comments that they have removed this data from the study. The
authors should resolve this discrepancy.
- How the decomposition values in the heatmap are arranged by survey year and region still
needs additional explanation. The sentence that has been included does not provide information
on why the regions and survey years are arranged in that order.
Title: Decomposing the effect of women's educational status on fertility across the six geo-
political zones in Nigeria: 2003-2018
Version: 4 Date: 16 Jan 2025
Reviewer's report:
I have reviewed the manuscript, and I note that a number of my earlier observations have been
addressed and there is some improvement in the quality of the manuscript. However, I still have
some lingering comments:
Methods section
Study design and Data: The manuscripts states that ‘women’s files’ were used in the analysis,
but it is silent on the ‘child recode’ files that were used in the computation of total fertility rate
(TFR).
Variable description: The manuscript states that the dependent variable is children ever born
(CEB) and the mean was computed (MCEB). The TFR was also calculated. For the sake of
clarity, what was used to compute the Risk Differences (RDs)?  Is it the MCEB or TFR? This is
not clear. If the RD values were computed using MCEB, then what was the purpose of calculating
TFR?
The application of the direct method of estimating TFR using Demographic and Health Survey
(DHS) data as referenced in Moultrie et al 2013 has been elaborated. The steps of computing
the TFR have been outlined, however, there is a part that is still not explained that sums up
the age-specific fertility rates (ASFRs) into TFR. Also, how this was done by education status?
Elaborate.
Minor comment
Proofread and edit the manuscript and ensure consistence in the use of ‘educated’ and
‘uneducated’ versus ‘literate’ and ‘illiterate’
Title: Pelvic peritoneal endometriosis is linked to the endometrial inflammatory profile: a
prospective cohort study
Version: 3 Date: 17 Jan 2025
Reviewer:  Irene Iavarone
Reviewer's report:
I read with great interest the present Manuscript which falls within the aim of the Journal. In my
honest opinion, the topic is interesting enough to attract the readers’ attention. Methodology is
accurate and conclusions are supported by the data analysis. Nevertheless, authors should clarify
some points and improve the discussion citing relevant and novel key articles about the topic.
For all those reasons, I suggested performing the minor revisions.
- Inclusion criteria number II and III should be included in the exclusionary criteria;
- In enrich the Discussion adding details upon potential treatment strategies deriving from
the results of the study. Consider: "Cicinelli E, de Ziegler D, Vitagliano A. In women with
endometriosis, effective treatment of chronic endometritis with antibiotics lowers serum CA-125
levels. Fertil Steril. 2024;121(6):1066-1068. doi:10.1016/j.fertnstert.2024.02.041";
- Authors may parallel their findings with other diagnostic biomarkers in endometriosis, as
extracellular vesicles. Please see: "Ronsini C, Fumiento P, Iavarone I, Greco PF, Cobellis
L, De Franciscis P. Liquid Biopsy in Endometriosis: A Systematic Review. Int J Mol Sci.
2023;24(7):6116. Published 2023 Mar 24. doi:10.3390/ijms24076116";
- Authors have not adequately highlighted the strength of the study. I suggest better specifying
that point.