Title: Candidiasis profile at the Outpatient Department of the University of Cape Coast hospital
in the Central region of Ghana: A retrospective study
Version: 7 Date: 21 Dec 2022
Reviewer's report:
The authors have tried to provide answers to some of the previous comments but there remain
some uncertainties and errors to be addressed.
Abstract
Line 29: The results are in percentages and frequencies. This appears redundant as the results
also contains risk ratios and their 95% Cis.
Authors respectfully need to ensure chronology in the statistics used and adhere to the use of
appropriate terminologies.
Line 26-29: ………. samples were tested for their sensitivity and specificity for the diagnosis
of candidiasis. As I pointed out in my previous comments, sensitivity and specificity are largely
not statistical tests but test statistics or test outcomes from the Receiver Operator Characteristics
(ROC) test. Thus, the sensitivity and specificity are values based on which decisions are made
relative to the discriminatory ability of a diagnostic instrument or method. A good way to
put what authors intend to put across is “we used the Receiver Operator Characteristic test to
ascertain, determine, etc. the sensitivity and specificity of -, - and – in predicting, diagnosing etc.
candidiasis among the study participants”. If other statistical models or test were used instead of
the Receiver Operator Characteristics, authors should clearly state it and desist from referring to
sensitivity and specificity as statistical tests as these are only values and not tests in themselves.
Line 30-32: This is not clear. Chi-square test is a statistical test used to assess statistical
difference or association between two variables, one explanatory and the other, outcome. The
association or difference comes out either significant or not significant by the p-value attached.
What the Chi-square value wouldn’t tell you is the magnitude of the association as would relative
risk, odds ratio etc. Its important to state exactly what the Chi-square was used for. In my opinion,
the Chi-square was used to assess the association between relevant explanatory variables and
candidiasis. This is what I would have stated in the abstract but state the exact explanatory
variables in the main methodology. Meanwhile, because relative risk or risk ratios does not only
tell the association but also tell the magnitude of the association compared to Chi-square which
would largely tell the presence or absence of an association, presenting both relative risk and
Chi-square in table 1 for example seems off for me. Authors should take a second look at such
analysis and make the necessary changes; I suggest the Chi-square portion is removed. Finally,
the Bayes’ theorem for diagnostic tests is not used to assess statistical significance as portrayed
but rather to determine the conditional probability of a positive outcome, in this case, having
candidiasis due to an alteration in the explanatory variables. If this is the same definition based
on which the Bayes’ theorem was used, then am afraid I’m unsure what exactly in this study the
Bayes’ theorem was used for. Authors should be clear on the analysis please.
Authors should state which statistical software was used in the analysis and also state what
defines a statistically significant association under the abstract.
Methods
Line 159: …. And Chi-square test risk were used to assess. Kindly delete risk in this sentence
The information in both lines 160-161 and lines 161-163 seems to be talking about the same
thing yet are different. In one breath, the severity of candidiasis is determined using ratios of
RBCs, ECs and PCs while in the other, candidiasis severity is determined using a determined
threshold of counts of RBCs, ECs and PCs per HPF. Authors should kindly clarify.
Lines 163-165: Same comments on the use of ROC and Bayes’ theorem as above. Meanwhile,
I am unsure whether the Bayes’ theorem is available as a statistical tool in GraphPad. If not,
authors should state explicitly the formula for the Bayes’ theorem as used and provide the
appropriate reference.
Table 4: I strongly advise that authors present only the overall diagnostic accuracy of the makers
of candidiasis assessed. Presenting the yearly diagnostic accuracy or capacity of the markers of
candidiasis by means of the sensitivity and specificity does not really make scientific sense if
I could out it that way. It doesn’t bring to bare any relevant scientific knowledge and certainly
wouldn’t form part of any scientific discourse to eventually effect any change in the diagnosis
of candidiasis.
Figure 3 and 4: the vertical axis of figures a, b and c are labelled Prevalence Candidiasis %. I
think this is misleading as these figures present the distribution of RBCs, PCs, and ECs according
to age. I think only figure d is showing the prevalence of candidiasis. Authors should revise. For
all the graphs, of is missing from the vertical axis label. Put the % sign in parenthesis. Aside the
horizontal labels, which varies between figure 3 and 4, consistency in the vertical labels of the
graphs should be ensured and that includes the legend labels. For example, the legend labels for
figure 3d are different from that of figure 4d.
General comments.
It is important that authors take the statistical analysis seriously. It must first be appropriate,
easily comprehensible, and also reproducible by the target population. When the statistical
analysis is flawed, the entire study loses its value and aside dwindling the credibility of the
authors, the reputation of the journal also becomes questionable.
In reporting the statistical analysis, some level of chronology must be exercised. Thus, from less
complicated to more complicated. In this study, this is what I would have written.
The results of this study were presented in the form of tables and figures. Frequencies and
percentages where appropriate were used to present the results of relevant variables. The
Clopper-Pearson test was used to determine the confidence intervals of proportions of relevant
outcomes variables under study. The relative risk and its associated confidence intervals were
used to assess the risk of candidiasis stratified by sociodemographic and clinical variables. Using
the Receiver Operator Characteristic Test, the diagnostic accuracy of urine and HVS wet mount
enumerated RBCs, ECs and PCs were assess in the diagnosis of candidiasis among the study
participants. Finally, whatever the Bayes’ statistics was used for, that should also be clearly
stated. All p-values less than 0.05 were considered statistically significant. All data analysis
were performed using GraphPad vs 3.3.1.
I advise that authors take their time, seek for the help of a statistician if required and revise the
manuscript properly.