Title: Perianal Ultrasound (PAUS) – visualization of sphincter muscles and comparison with
digital-rectal examination (DRE) in females
Version: 1 Date: 24 Feb 2021
Reviewer:  Faris Mujezinovi#
Reviewer's report:
Dear authors,
Interesting study with a novel approach worth publishing. I would recommend several changes
before publishing your data.
Introduction:
In my opinion, the background is too long and not focused enough. I would suggest that FI and
current diagnostic tools be summarized in 2-3 sentences. Describe the DRE and PUS in short
form. Then focus on their disadvantages and possible advantages of other dg tools as PAUS.
What would be useful to know about PAUS but still unknown, and then integrate your study in
that unknown. What is known about the physiology of contraction of anal muscle and what is
not. Aims could stay as they currently are.
Methods:
I assume that some protection for the probe was used. It was not described.
I would recommend a real picture of the position of the probe in relation to the pelvis. It is not
clear to me how you put the US probe on the anus with that angle tilting. Do you use the pillow
under the patient's pelvis to elevate it or something else?
Describe why 4 mm above the first slice is chosen for a measurement – is there any physiological
explanation for that – the point of the greatest thickness of the sphincter or something else.
Could you describe Jorge-Wexner-Score more in detail in Methods and not just use reference.
Statistics – I would suggest that you use Altman-Bland plot as a method of comparing the
agreement between investigators.
Results:
When eliminating patients from analysis after initial 50 patients, firstly I would recommend
using the group of 35 patients that had fulfilled the condition for analysis and then from this
group (35) eliminate those with bad questionnaires.
Tables: Table 1 no units, table 2 is not so informative and rather confusing. I would suggest
evaluated parameters to be placed in rows and data in columns. Statistical data – only p value
should be included and not statistics from statistical tests.
Table 4. Also confusing, I would use the same format as above. Number of decimal places (one
is sufficient) should be the same across the tables. Table 5. I am not sure what the z parameter
is. In my opinion, it should be removed. Table 7 is in my opinion unnecessary.
Term »Thickness of the muscle at different positions« is too general. If I understand correctly
there were only four positions 9, 12, 15, 18 o' clock evaluated.
Discussion:
Discussion needs polishing and better structure.
I would report first your main results  (thickness, diameters - differences at rest and at
contraction, correlation with DRE and questionnaire results) first and then explain the relevance
of these results (physiology, comparison with other US dg. tools and DRE).
Surprising finding is the oval and uneven contraction across horizontal and vertical axis. Explain
in detail why it is so, and what are the findings from other dg. tools.
Correlation with DRE scoring should be better explained, as we are talking about completely
different approaches (DRE more categorical and subjective). Explain where are the differences
and where similarities (difference of diameter and scoring system). Explain the real and potential
clinical value of both parameters.
Explain in which clinical situations your findings could have a potential clinical value. We are
talking only about a potential as your sample group was free of any pathology, your analysis
was focused on phyiscal process of anal contraction.
For generalisability of your results, the characteristics of your patients are of great importance.
They are of older age and their physiology of contraction could be different from the general
population or different age group. Put it in context of other studies.
Discuss the reasons for such a great shrinkage of sample size. What could be improved in future
studies to accomplish better volumes and larger return of fulfilled questionnaires.
Discuss the small sample size in terms of power to detect differences, how much the mean
difference is your sample size is able to capture. Is this power clinically relevant or have other
values (as a pilot study or something similar) .
Kind regards,
Faris Mujezinovi#