PONE-D-21-23338Optimizing ECG to detect echocardiographic left ventricular hypertrophy using computer-based ECG data and Machine LearningPLOS ONE

Dear Dr. González Cantú,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Nov 15 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Kazuaki Negishi

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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 #1: Partly

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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3. 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 #1: Yes

Reviewer #2: Yes

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4. 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 #1: No

Reviewer #2: Yes

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5. 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 #1: The authors have conducted a useful case control study to validate the CHCM algorithm that they have developed. While it has limitations in its diagnostic accuracy relative to convolutional neural networks, there are advantages to having a simple system that does not have a black box algorithm. The authors should be commended for their work in optimising the CHCM model. I have a few revision suggestions which related to methodology and results. There are also some grammatical errors/clarifications which I have noted. I have included these as minor revisions.

Major Content Queries

There is now substantial evidence indicating the pitfalls of using BSA alone in indexing LVM. Did you consider using other indexation methods, such as height2.7 (De Simone et. al.) or fat free mass? Were alternative indexation methods considered to account for obesity, particularly given both of your population cohorts (LVH negative and LVH positive) were overweight? BSA has been shown to be a poor indexation method in the setting of obesity.

Did you look into the impact of increased body size on ECG voltage criteria, particularly given your population had a mean BMI of 28.7m2?

Line 131 (methods) -> no formula is listed here for body surface area. Which calculation did you use and what was the rationale for choosing this method? It is important to note that formulae such as Du Bois Du Bois are based on a very small cohort of 9 patients over 80 years ago, and as such have been discouraged in more recent literature for indexing body size variables.

Line 233 What was the variance (e.g. standard deviation) that you used in your sample size calculation? What outcome measure is the delta of o.1 referring to?

Were you able to explore whether certain patient characteristics affected your CHCM model’s accuracy, sensitivity or specificity? For example, was CHCM better/worse based on gender, BMI or the presence of IHD?

Minor grammatical/syntax queries

Line 21 (Abstract) -> Rather than “(ECHO-LVH) produces cardiovascular mortality”, the authors may consider rewording this e.g. “independent predictor of mortality”

Line 85 (background) -> change “produces” to “produce”

Line 88 -> change “are exploring” to “have explored”

Line 204 -> change “de” to “the”

Line 211 -> change “inhomogeneity” to “in homogeneity”

Line 213-> change “cut-values” to “cut-off values”

Lines 216/217 -> this sentence is difficult to understand, suggest breaking into smaller sentences “Also, decision trees can continue to grow indefinitely as more and more predictors are presented to the C5.0 algorithm -this is called overfitting- and created precise predictions in new datasets”

Reviewer #2: This paper presents a method that detects echocardiographic left ventricular hypertrophy (Echo-LVH) using electrocardiogram (ECG). The authors used the Philips DXL-16 algorithm to extract 458 ECG parameters. They then used the C5.0 machine learning (ML) algorithm to automatically find the most relevant parameters associated with Echo-LVH and used them to train a predictive model. The proposed model was evaluated in a retrospective manner on 439 patients and compared with other conventional detection approaches. The results show that the proposed predictive model had similar accuracy to other approaches using a new and fewer sets of parameters.

The proposed cardiac hypertrophy computer-based model (CHCM) is an extension of the authors’ prior work, Cardiac Hypertrophy Model which uses manually selected ECG parameters including ST ECH-LVH, voltage-left atrial enlargement LVH and voltage-duration LVH coupled with C5.50 ML algorithm. To me, it was difficult to clearly understand the contribution of CHCM in comparison to existing models. Apart from being able to leverage the digital data extracted from Phillips DXL-16 algorithm, there seems to be limited new insights and findings introduced from this paper. The in-depth discussions about derived ECG parameters and their corresponding roles in detecting Echo-LVH in comparison to existing algorithms would be important.

Other detailed comments:

1. Page 6, line 101: Inform --> Informed

2. Page 6, line 108: STARD --> not defined

3. Page 6, line 109: ML --> Machine Learning (ML)

4. Page 9, line 172: most of the sample --> what is sample in this context?

5. Page 13, line 244-249: The sentences in this paragraph are redundant.

6. Page 15, Table 2: Total sample --> Total Samples

7. Page 15, Table 2: why is the number of total samples 321? Why not 439, consistent with Table 1?

8. Page 17, line 309: more accuracy --> higher accuracy

9. Page 23, line 398: ‘However, the CHCM is half the size of the Cardiac Hypertrophy model, which gives a more biological coherent model based on the principle of parsimony-the simpler explanation is the most probable’ --> this seems to be an over justification that explains nothing much. Please be specific and articulate the differences.

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Reviewer #1: No

Reviewer #2: No

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PONE-D-21-23338R1Optimizing ECG to detect echocardiographic left ventricular hypertrophy using computer-based ECG data and Machine LearningPLOS ONE

Dear Dr. González Cantú,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 12 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Kazuaki Negishi

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Thank you for amending your manuscript. I believe that the manuscript became much stronger. However, as one of the reviewers pointed out, we would recommend seeking assistance from a native English speaker with scientific writing skills in order to help our readers.

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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 #1: (No Response)

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 #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

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 #1: Yes

Reviewer #2: Yes

**********

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 #1: No

Reviewer #2: Yes

**********

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 #1: The authors have made appropriate major changes, however none of the extensive grammatical issues identified have been addressed. As a result, the paper is not written in standard english. I would suggest that the authors seek assistance from an English grammer expert to proof read their manuscript prior to resubmission.

Reviewer #2: The authors have addressed all the comments satisfactorily. The contributions of the paper have been articulated.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Optimizing ECG to detect echocardiographic left ventricular hypertrophy with computer-based ECG data and Machine Learning

PONE-D-21-23338R2

Dear Dr. González Cantú,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Kazuaki Negishi

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Thank you for revising your manuscript. The current form reads much better.

Reviewers' comments: