Title: Molecular Prevalence of Chlamydia trachomatis Infection among Women Attending
Gynaecological Clinic for Infertility Evaluation
Version: 0 Date: 01 May 2025
Reviewer's report:
Methodological Rigor and Clarity
Study Design & Population: This section is ok, but one improvement could be inclusion of
a control group (e.g. fertile women) to strengthen any inference about C. trachomatis being
associated with infertility.
Sample Collection & PCR Technique: The methods for specimen collection , DNA stabilization ,
extraction and laboratory analysis are sound. The diagnostic target was the ompA gene of C.
trachomatis, amplified by PCR – a sensible choice as ompA (MOMP gene) is a conserved and
specific marker . These details indicate rigor in the molecular method. However, one missing
detail is whether positive controls (known C. trachomatis DNA) and negative controls were run
to validate the PCR results – mentioning this would further strengthen confidence in the assay.
Additionally, providing primer sequences or a reference for them would improve transparency.
The text has a small typographical error in the annealing temperature (“[I65°C]” instead of 65°C)
Data Collection & Variables: The study collected a thorough set of demographic and clinical
variables via structured questionnaires . Overall, the methodology is described with good clarity
and organization (divided into clear subsections like “Study Design and Setting,” “Sample
Collection,” etc.), which allows reproducibility.
Statistical Analysis: The use of IBM SPSS for analysis is noted, and statistical tests are
appropriate. The analysis section could be clearer on which variables were entered into
the logistic model (presumably all measured risk factors) and whether any model selection
procedure was used.
Clarity and Organization of Writing
Abstract: One point of confusion is in the Results portion of the abstract: it states that “younger
age (OR=0.46, p=0.007) … and PID (OR=2.67, p=0.005) were significant predictors” The
inclusion of odds ratios is appropriate, but the interpretation is counter-intuitive in the case of age
– an OR of 0.46 for younger age actually suggests lower odds of infection in younger women,
yet the text implies the opposite (treating younger age as a risk factor). This likely stems from
coding older age as the reference group, making the OR for the 18–26 group <1. This nuance
could confuse readers; the authors might clarify by stating explicitly which age group is the
reference and phrasing the finding as “infection odds were significantly higher in the youngest
age group compared to women >26” or similar. Aside from that, the abstract is clear and provides
a good snapshot of the study.
Introduction: The introduction clearly identifies a gap – limited data on the molecular prevalence
of C. trachomatis in Nigerian women specifically seeking infertility care. It culminates in a
concise aim: “to investigate the molecular prevalence of CTI among women attending the
gynaecological clinic for infertility evaluation at Edo University Teaching Hospital, Auchi,
Nigeria.” This statement is clear and appropriately placed at the end of the introduction. One
notable issue is an inconsistency in the study setting: the Introduction/Methods indicate the study
was done at Edo University Teaching Hospital in Auchi (Edo State), but the Discussion refers
to the prevalence being in “Osogbo, Nigeria” which is a different location. This discrepancy
should be corrected for clarity – presumably Edo (Auchi) is the correct site, unless the study was
actually in Osogbo and the earlier section is in error. Apart from this, the introduction is well-
written, logically structured, and provides a strong justification for the study.
Methods: The methods section is well-organized with clear subheadings. Overall, the
methodology is communicated clearly, enabling readers to understand and potentially replicate
the study.
Results: The results are presented in a logical sequence, and the narrative is augmented by tables
that are appropriately titled. The first part of the results describes the prevalence and baseline
characteristics, referencing Table 1 . The text notes the overall prevalence (37/135, 27.4%) and
highlights key observations: the highest infection rate was in the youngest age group (31.6%
in age 18–26) but without statistical significance (p=0.38); women with secondary education
had higher infection rate (36.7%) than those with tertiary education (20.0%, p=0.05); widowed
women had a slightly higher rate than married (34.3% vs 25%, p=0.40); and histories of STIs
and PID were associated with significantly higher infection rates (40% vs 20% for STI history,
45% vs 20% for PID. These descriptions align well with the data in Table 1 and are easy to
follow. The percentages and p-values in text match the table, indicating internal consistency.
The second part of the results focuses on symptomatology, with a clear paragraph summarizing
Table 2  It explicitly states that presence of vaginal discharge overall was not significantly
associated with infection (p=0.48), nor was the color of discharge (noting, for instance, that
“reddish” discharge was 40% in infected vs 20% in uninfected, p=0.51, which is not significant).
It points out that foul-smelling discharge showed a higher infection rate (34% vs 23.5%) that
approached significance (p=0.08). Also, no significant differences were found for symptoms of
itching, irritation, or burning (p=0.98) . This level of detail is excellent, as it assures readers
that all measured clinical symptoms were analyzed and reports even the near-significant finding
candidly. The text could be polished slightly to avoid repetition (the word “significant” appears
often; using “no statistically significant association” versus “approached significance” is fine
as is, though).
The final part of results presents the multivariate logistic regression findings, corresponding to
Table 3. The narrative here is mostly clear: it states that the logistic model identified younger age
(18–26) as significantly associated with infection (OR=0.46, 95% CI 0.26–0.81, p=0.007) ,while
the 27–35 and #35 age groups had no significant association (their ORs ~0.9 and 0.5 with
p#0.05). It also reports that a history of STIs was strongly associated with higher odds of
infection (reported OR=0.24, 95% CI 0.12–0.49, p<0.001), PID history likewise increased the
odds (OR=2.67, 95% CI 1.28–5.56, p=0.005) ,and tertiary education was protective (OR=0.42,
95% CI 0.19–0.91, p=0.028) . The inclusion of confidence intervals is a strong point, as it
quantifies the estimate precision. However, here the writing has a notable confusion: the text
says “women in the 18–26 age group were significantly more likely to be infected (OR=0.46…)”
An OR of 0.46 actually indicates lower odds of infection for that group relative to the reference
(which presumably are older women). Similarly, for STI history, an OR of 0.24 suggests a
quarter of the odds (if “yes history” is compared to “no”). Yet the raw data and discussion
indicate women with STI history had higher infection rates. Indeed, in the Discussion it is stated
this corresponds to “more than a fourfold increase in risk”. This discrepancy implies that in
the regression the coding/reference categories were inverted (perhaps “no history” was the risk
category by mistake). The authors should correct this by either inverting the ORs (reporting
their reciprocals) or rephrasing to match the numerical values. As it stands, the Results section
has all the right data but the interpretation of OR < 1 as “higher likelihood” is an error that
could confuse readers. Other than that, the results are detailed and well-structured. The tables
themselves contain the necessary data; a minor formatting issue is the stray parenthesis in
Table 1 (“98(72.6))”) which should be edited, and ensuring consistent decimal places/format
in tables would enhance readability. But generally, data presentation is adequate and the text-
tables consistency is good.
Discussion: This section demonstrates good scientific communication, as it helps readers and
reviewers trust that the authors are aware of their study’s scope.
Conclusion: The conclusion section itself is essentially a succinct paragraph that mirrors the
abstract conclusion and discussion highlights. It emphasizes the practical implications: because
many infections are asymptomatic (and they observed no symptom-based differences), routine
molecular screening should be integrated into infertility care. This is a strong takeaway message
and is fully justified by the study’s findings and discussion.
Strengths and Limitations of the Study
Strengths: The use of PCR for detection is a major strength, as noted. PCR testing for C.
trachomatis has higher sensitivity and specificity than syndromic diagnosis or even some antigen
tests, reducing the chance of false negatives/positives. This means the prevalence found is likely
accurate. Another strength is the comprehensive data collected, allowing multivariate analysis
to pinpoint independent risk factors. The study addresses a clear gap and has a well-defined
population, which adds focus to the findings. Additionally, by including a relatively updated set
of references, the authors demonstrate engagement with current research, enhancing the study’s
relevance.
Limitations:
Additionally, the study did not perform any typing of C. trachomatis strains or assess chronicity
(e.g., via IgG antibodies) – so we do not know if these infections are new or long-standing.
Perhaps minor, but worth considering, is that PCR detects DNA and cannot distinguish between
an active infection vs residual DNA from a past infection that was perhaps treated. If any
participants had been treated in the past, a persistent positive could be misleading. The eligibility
criteria did exclude recent antibiotics, which helps, and presumably many were asymptomatic
and untreated, so this is likely a minor concern. It could be mentioned if the authors want to
be extremely thorough.
Recommendations for Improvement
Ensure Consistency and Accuracy: Correct the inconsistency in the study location (Edo vs
Osogbo) so that the setting is uniformly described .Double-check all numeric values (prevalence
percentages, ORs) and their interpretations – particularly the logistic regression results – to
eliminate contradictions (e.g., clarify the OR for STI history to reflect increased risk rather than a
protective effect) These fixes will prevent reader confusion and bolster confidence in the results.
Clarify Methodological Details: Add a brief note on quality control in PCR (for instance,
mention running known positive and negative controls, or internal controls for sample adequacy
if that was done). If primer sequences or sources are available, include them or cite a reference
protocol for the ompA-based PCR. This improves transparency and reproducibility. Also,
explicitly label the Statistical Analysis subsection and list the variables included in logistic
regression, for complete clarity.
Polish the Writing: Do a careful proofreading pass to catch minor typos (such as the missing
space in “(PCR)was” and the “[I65°C]” error in annealing temperature) . These small edits will
make the paper look more professional.
In the Abstract and Results, consider rephrasing statements where an odds ratio <1 is described
as a risk factor – instead, describe the finding in plain terms or recode the reference group so
that ORs >1 correspond to risk increases, which is more intuitive. For example, the statement
could be: “Logistic regression confirmed that women aged 18–26 had significantly higher odds
of infection (approximately 2.2-fold) compared to women over 35 (reference group)” – this
conveys the result without the confusion of an inverted OR.
Enhance Data Presentation: Tidy up the tables with consistent formatting. Make sure each table
can stand alone: include units where appropriate (e.g., years for age), and perhaps add footnotes
to explain that p-values in Table 2 correspond to comparisons across categories (for discharge
color, odor, etc.). Aligning the p-value column and removing any extraneous parentheses will
improve readability. Also, check that all values mentioned in text (like the 34.3% for widows)
are either present in a table or add them to ensure transparency.
Emphasize Public Health Implications: In the discussion or conclusion, the authors could
underscore how their findings support implementing routine C. trachomatis screening in
infertility clinics in Nigeria. They do imply this, but a stronger statement (backed by their data
that symptoms are unreliable) could leave a lasting impression on policymakers or clinicians
reading the paper. For instance, recommending that infertility evaluations in similar settings
include mandatory NAAT testing for C. trachomatis would be a direct application of the study’s
results.