PONE-D-24-58827Different Methods of Ankle-Brachial Index Calculation on the Prevalence of Peripheral Arterial Disease and Arterial Calcification in Subjects with Type 2 Diabetes Mellitus from a Public Hospital in PeruPLOS ONE

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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: I am grateful for the opportunity to review the manuscript titled "Different Methods of Ankle-Brachial Index Calculation on the Prevalence of Peripheral Arterial Disease and Arterial Calcification in Subjects with Type 2 Diabetes Mellitus from a Public Hospital in Peru." This cross-sectional study investigates the frequency of peripheral arterial disease (PAD) and arterial calcification (AC) in patients with type 2 diabetes mellitus, utilizing three distinct methods for calculating the ankle-brachial index (ABI) based on data from a hospital-based program in Peru. The objective is to assess how these varying ABI calculation approaches influence the reported prevalence of PAD and AC.

Title:

Page 1, Lines 1-4: The title indicates a cross-sectional study by mentioning "prevalence," but it does not explicitly state the study design (e.g., "A Cross-Sectional Study"). This lack of clarity may obscure the design for readers unfamiliar with prevalence as a hallmark of cross-sectional research.

Page 1, Lines 1-4: The title refers to "Different Methods of Ankle-Brachial Index Calculation" but fails to specify these methods (e.g., highest, lowest, average systolic pressure).

Abstract:

Page 1, Lines 25-48: The abstract omits a background statement, leaving the context and significance of studying PAD and AC in diabetic patients unclear.

Page 1, Lines 29-36: The methods section vaguely describes ABI calculation ("using the lowest, highest, or average systolic pressure") without explaining the numerator and denominator or the measurement process.

Page 1, Lines 37-43: Prevalence rates for PAD and AC are reported, but confidence intervals are not included in the abstract despite being present in the main text (e.g., Page 20, Lines 244-245).

Page 1, Lines 44-48: The conclusions state a prevalence range but misreport "CA" instead of "AC" (likely a typographical error), introducing inconsistency. Additionally, the implications of the findings for clinical practice or research are not articulated beyond a call for further study.

Introduction

Page 10, Lines 52-100: The research question—determining PAD and AC prevalence using different ABI methods—is implied but not explicitly defined.

Page 11, Lines 85-89: The rationale for using three ABI methods is mentioned (e.g., detecting less severe cases or assessing severity), but it lacks justification tied to prior evidence or clinical relevance specific to diabetic patients in Peru.

Page 10, Line 68: The prevalence of PAD in Peruvian hospitals is cited as 18.9% (reference 9), but the cited study focuses on pulsioximetry, not ABI.

Page 12, Lines 101-103: The objectives mention determining PAD and AC frequency using ABI but do not specify the three methods (highest, lowest, average), misaligning with the title and methods section (e.g., Page 13, Lines 121-125).

Methods

Page 13, Lines 105-110: The study is described as cross-sectional, but it does not clarify that it is a secondary analysis of existing data from the Foot at Risk Program.

Page 13, Lines 111-118: Inclusion criteria mention records with complete ABI data, but exclusion criteria (e.g., lesions, severe pain) are listed without explaining their impact on ABI feasibility or prevalence estimates.

Page 17, Lines 208-211: Of 1,019 patients, 369 were excluded for incomplete ABI data, but no reasons (e.g., technical issues, patient factors) are provided.

Page 13, Lines 120-125: ABI methods are defined, but the measurement of systolic pressures (e.g., number of readings, operator consistency) is not detailed.

Page 14, Lines 139-144: Poor metabolic control (HbA1c ≥ 7%) is defined, but its role in the analysis (e.g., as a confounder or outcome modifier) is unclear.

Page 14, Lines 152-155: ABI measurement tools (sphygmomanometer, Doppler) are listed, but the protocol (e.g., cuff size, measurement sequence) and personnel training standardization are not described.

Page 15, Lines 164-165: No imputation for missing data is noted, but the extent and pattern of missingness (e.g., 369 incomplete ABI records) are not analyzed.

Page 13-16: Potential biases (e.g., selection bias from excluding incomplete records, information bias from self-reported variables like diabetes duration) are not identified or addressed.

Page 16, Lines 189-192: Adjustments in Poisson regression are made for variables with p < 0.2, but the rationale for this threshold and the specific confounders adjusted for are not specified.

Page 16, Lines 185-192: Poisson regression with robust variance is used, but the choice over other methods (e.g., logistic regression) and its application (e.g., model assumptions) are not explained.

Page 15, Lines 169-174: The ABI calculation algorithm prioritizes PAD over AC, but this hierarchical approach’s impact on AC prevalence (e.g., underreporting in mixed cases) is not acknowledged.

Results

Page 17, Lines 208-211: The participant flow excludes 369 subjects with incomplete ABI data, but no comparison of excluded vs. included subjects is provided.

Page 18, Lines 219-228: Baseline characteristics (e.g., 69.8% female, mean age 61.4) are reported, but missing data for variables like HbA1c (325/643 records) are not quantified or analyzed for bias.

Page 20, Lines 240-242: Prevalence estimates differ by ABI method (e.g., PAD: 7.8% vs. 28.2%), but the statistical significance of these differences is not tested.

Page 21, Lines 257-269: Adjusted prevalence ratios (aPRs) for PAD (e.g., aPR 8.2 for age > 75) are reported, but confidence intervals are wide (e.g., 1.11-60.1).

Page 25, Lines 280-294: AC associations (e.g., aPR 3.79 for diabetes > 20 years) are presented, but the lack of adjustment for key confounders like age in all models is not justified.

Discussion

Page 29, Lines 304-319: The summary of PAD prevalence aligns with objectives, but the interpretation (e.g., “optimize risk identification”) overstates findings without evidence of diagnostic accuracy.

Page 31, Lines 372-381: The claim that lowest ABI identifies more at-risk individuals assumes a link to mortality outcomes not tested in this study.

Page 32, Lines 389-400: Selection bias from hospital-based sampling and incomplete records is mentioned, but its direction and magnitude (e.g., overestimating PAD prevalence) are not explored.

Page 32, Lines 389-391: Generalizability is questioned due to the hospital setting, but no discussion addresses how the Peruvian context (e.g., healthcare access) affects external validity.

Page 29, Lines 310-319: Comparisons to US and French studies (references 27, 28) are made, but differences in population (e.g., multiethnic vs. Peruvian) and methodology are not critically analyzed.

Page 33, Lines 405-411: Future research is suggested, but the discussion lacks specific gaps (e.g., validation against outcomes) or hypotheses, reducing its utility.

Additional Comments

Throughout Manuscript: Terminology for ABI methods varies (e.g., “highest pressure criterion” on Page 20 vs. “high ABI” on Page 21), risking confusion.

Page 33, Line 407: “CA” is used instead of “AC” (consistent with Abstract, Line 45), indicating a persistent typographical error.

Page 22-28, Tables 3-4: Adjusted models include variables with p < 0.2 from crude analysis, but multicollinearity or model overfitting (e.g., many covariates for 643 subjects) is not addressed.

Reviewer #2: Dear Author

The manuscript presents a cross-sectional study evaluating the prevalence of peripheral arterial disease (PAD) and arterial calcification (AC) in patients with type 2 diabetes mellitus (T2DM) using three different methods for calculating the ankle-brachial index (ABI). The study highlights significant variations in PAD and AC prevalence depending on the ABI calculation method, with important clinical implications. While the study is well-designed and addresses a relevant clinical question, several areas require clarification and improvement.

Major Comments:

Study Design and Methodology:

The manuscript states that the study is observational, cross-sectional, and descriptive. However, it would benefit from a clearer justification for choosing this design over a longitudinal approach, which could provide insights into the progression of PAD and AC over time.

The exclusion criteria (e.g., major amputation, stroke, incomplete ABI data) are appropriate, but the high exclusion rate (369/1019, ~36%) due to incomplete ABIs raises concerns about potential selection bias. Please discuss how this might affect the generalizability of the findings.

ABI Calculation Methods:

The three ABI calculation methods (highest, lowest, and average systolic pressure) are clearly described, but the rationale for selecting these specific methods could be expanded. Are there clinical guidelines or prior studies that support these choices?

The manuscript mentions that the lowest ABI criterion increases sensitivity but decreases specificity. This trade-off should be discussed in greater depth, particularly in terms of clinical decision-making (e.g., how might false positives/negatives impact patient outcomes?).

Prevalence Estimates:

The reported prevalence of PAD varies widely (7.8% to 28.2%) depending on the ABI method. While this variability is a key finding, the discussion should address why such discrepancies exist and which method might be most appropriate for specific clinical scenarios (e.g., screening vs. diagnostic confirmation).

The prevalence of AC (11% to 18.2%) is less variable but still noteworthy. The authors should clarify whether AC was assessed independently of PAD or if overlapping cases were excluded.

Associations with Clinical Variables:

The association of PAD with older age and AC with longer diabetes duration is consistent with prior literature. However, the manuscript could better contextualize these findings by comparing them to similar studies in other populations.

The inverse association between obesity and PAD (using the high ABI method) is intriguing but counterintuitive. The authors should explore potential explanations (e.g., confounding by other metabolic factors) or limitations (e.g., small sample size in subgroups).

Limitations:

The hospital-based design limits generalizability, as acknowledged by the authors. However, the discussion should also address how the study population (e.g., predominantly female, mean age 61.4 years) might influence the results.

The underreporting of AC due to prioritization of PAD in the diagnostic algorithm is a significant limitation. The authors should discuss how this might have affected the observed prevalence and associations.

Minor Comments:

Clarity and Presentation:

The abstract could be more concise. For example, the methodology section repeats details (e.g., ABI calculation methods) that are elaborated in the main text.

Table 1 provides extensive demographic and clinical data, but some variables (e.g., education level, treated hypothyroidism) are not discussed in the results or discussion. Consider streamlining or highlighting the most relevant variables.

Statistical Analysis:

The use of Poisson regression with robust variance is appropriate, but the manuscript should clarify why this method was chosen over logistic regression, especially given the cross-sectional design.

The power calculation is well-described, but it would be helpful to include the actual observed prevalences alongside the expected values for comparison.

Figures and Tables:

Figure 1 (diagnostic flowchart) is clear but could be simplified for readability (e.g., reduce redundant text).

Tables 3 and 4 are dense and could benefit from reorganization (e.g., grouping related variables) to improve clarity.

References:

The references are comprehensive, but some citations (e.g., for ABI cut-off points) could be updated to reflect the most recent guidelines (e.g., 2024 ACC/AHA guidelines cited in the manuscript).

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Reviewer #1: No

Reviewer #2: No

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Prevalence of Peripheral Arterial Disease and Arterial Calcification Based on Three Ankle-Brachial Index Calculation Methods (Highest, Average, and Lowest Systolic Ankle Pressure): A cross-sectional study in Type 2 Diabetes Mellitus Patients in Peru

PONE-D-24-58827R1

Dear Dr. Yovera-Aldana,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Additional Editor Comments (optional):

Reviewer #2:

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Dear Author

This response document is excellent and demonstrates that the authors have made substantial improvements to the manuscript. The revisions align with the reviewers' comments and enhance the manuscript's scientific quality, clarity, and transparency.

The manuscript is now much stronger and should be considered for acceptance

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Reviewer #2: No

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