Title: Ovarian Response to Controlled Stimulation and Its Predictors in a Limited-resource
Setting
Version: 3 Date: 27 Jan 2024
Reviewer's report:
Title
The title is very interesting.
ABSTRACT
# Please do not used an abbreviation in the abstract section like ROC, CI, SD, etc
Background
-------------
Methods:
# Bivariate and multivariate binary logistic regression analysis cannot be used for achieving
your study aim, “the current study aimed to find out the success rate of controlled ovarian
stimulation and identify its predictive factors at St. Paul’s Hospital Reproductive Medicine and
Fertility Center.” This is because the success rate of controlled ovarian stimulation has a Poisson
distribution rather than binomial distribution. Therefore, a Poisson regression model (analysis)
is the appropriate analysis technique for this study.
Results:
----------
Conclusion:
# First it is better to define success rate of controlled ovarian stimulation in operational definition
section and then it will be conducive to interpret the result. Moreover, the statement “The success
rate of controlled ovarian stimulation was 67%, indicating a significant proportion of patients
respond poorly.” should be rewrite. I have checked the figure 67% in the result section and it
seems to me the proportion of women who have more than 3 retrieved oocytes. In addition, in
this statement unless the proportion of patients respond poorly or goodly is tested, the phrase
“indicating a significant” cannot be used.
Introduction
# Inconsistent description of study aim. For instance, look the statement “To the best of
our knowledge, there are no documents about ovarian stimulation and its predictors in the
country.” and “Therefore, the current study aimed to determine the success rate of controlled
ovarian stimulation as defined by the ovarian response and to identify predictors of ovarian
response at the Center for Fertility and Reproductive Medicine by including clinical factors,
treatment protocols, gonadotropins, hormonal factors, and transvaginal ultrasound findings.” In
the first statement the response variable seems the ovarian response, obliged to use Binomial
distribution and in the second statement the response variable seems success rate of controlled
ovarian stimulation, necessitates using Poisson distribution. It results to use different statistical
methodology.
Methods
Study Setting, Design, Populations
# I think there is patients follow up. As a result, the study design should be retrospective study
design rather than cross sectional study design. Is there retrospective analytical cross-sectional
study design type?
Operational Definitions:
# Please add the operational definitions for success rate of controlled ovarian stimulation
# Is there any standard to categorize ovarian response as poor and good. If there is, please add
the citation in these categories.
Dependent Variables
# To match with your title, it is better the dependent variable to be “success rate of controlled
ovarian stimulation”. Even if you used as it is (i.e Number of oocytes retrieved), the appropriate
model will be count regression model rather than multivariate binary logistic regression model.
Data Processing and Statistical Analysis
# The researchers have two options to do analysis for this study. The first is without modification
of title. In this case, you have to change your used methodology particularly you have to use
Poisson regression analysis and re-analysis the data. The second is with modification of title as
“Ovarian response to Controlled Ovarian Stimulation and Its Predictors among Women Enrolled
in the First Cycle of Ovulation Induction at a Fertility Center in Ethiopia”. In this case, you
cannot change the methodology. But, you have to revise other sections and re-analysis the data.
Result
# Table 3: do not mix descriptive statistics (the output under the column Good Response and
Poor Response) with model outputs.
# Imply reference categories at the footnote of Table 3
# In general this should be done by running Poisson regression model.
Discussion
------------
Conclusion
--------------