The HEARRT-C Score: Is Aspirin Protective in COVID-19 Patients? A Single-Centre Retrospective Study

Response to Reviewer 1 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Questions for General Evaluation

Reviewer’s Evaluation

Response and Revisions

Does the introduction provide sufficient background and include all relevant references?

Yes

Are all the cited references relevant to the research?

Yes

Is the research design appropriate?

Yes

Are the methods adequately described?

Yes

Are the results clearly presented?

Yes

Are the conclusions supported by the results?

Yes

3. Point-by-point response to Comments and Suggestions for Authors

Comments 1: Τhis study adds a rather simple and accurate tool for clinicians to estimate the probability of early to mid-term death in hospitalized COVID-19 patients using simple demographic, clinical, laboratory and imaging parameters on admission. The findings are in fairly high agreement with other existing scores, while adding a new and powerful prognostic marker, coronary artery calcification. In addition, it should be noted that patients were enrolled in this relatively small single-center sudy at an early stage of the pandemic, when specific antiviral agents were not in widespread use. Hence a significantly increased mortality (one in three hospitalized patients) was recorded. With the widespread use of antiviral drugs and the  acquirement of collective experience in the overall treatment of COVID-19 patients by clinicians, the overall mortality has decreased significantly. So it's not clear whether the study's findings can be safely extrapolated to current conditions.

Response 1:

We acknowledge the limitations of our study, primarily its relatively small sample size and single-center design. However, in comparison to previous studies, our sample size is substantial. For instance, Dillinger et al. [3] examined coronary calcifications in COVID-19 patients with a sample of 209, while Ferver et al. [4] analyzed aortic calcifications in 70 patients.

We added this to methods section as;

To ensure statistical rigor, we determined our sample size using G*Power 3.1.9.7. The required sample size was calculated based on a dependent two-sample t-test, with a power of 95%, an α error probability of 0.05, and a medium effect size (Cohen's d = 0.5). As a result, a minimum of 95 patients was needed; however, we included 325 patients, analyzing their most recent thoracic CT scans. [page 2, line 71-75].

Regarding mortality, all-cause mortality was observed in 104 patients (32%) during follow-up, while in-hospital mortality occurred in 67 patients (20%), aligning with rates reported in randomized controlled trials [15].

We added this to discussion section as;

Although the WHO estimated an overall COVID-19 mortality rate of 2.1% as of February 2024, data specific to hospitalized patients remain scarce. Given the ongoing uncertainty surrounding long-term COVID-19 outcomes, we believe our findings contribute meaningful insights.

While antiviral treatments enhance clinical outcomes, their effectiveness may be compromised by emerging SARS-CoV-2 variants and limited global accessibility (Fotouh S et al., Virology Journal, vol. 20, article 241, 2023). Our proposed scoring system could facilitate risk stratification before treatment initiation. Moreover, the anti-inflammatory properties of ASA, a widely available agent, may provide clinical benefits.

Thank you for this valuable feedback. We have revised the manuscript accordingly. The changes can be found on [page 12, line 317-325].

Comments 2: In the discussion reference to other similar scoring system predicting mortality risk in hospitalized COVID-19 patients and their comparative presentation would be useful for clinicians

Response 2:

We appreciate this insightful comment. Scoring systems such as SIRS, NEWS, MEWS, 4C Mortality, and qSOFA, widely used for assessing sepsis and septic shock, have also been employed as predictors of COVID-19 mortality. Additionally, several novel scoring models have been developed specifically for COVID-19 patients. However, a detailed review of these systems reveals that none incorporate cardiac biomarkers such as hs-troponin or thoracic CT calcification data, despite cardiac complications being a significant contributor to COVID-19-related mortality.

Our proposed scoring system addresses this gap by integrating both cardiac biomarkers and imaging parameters, offering a more comprehensive risk stratification approach. To emphasize this point, we have revised the manuscript and addes this to discussion section accordingly. The modifications can be found on [page 12, line 327-335].

4. Response to Comments on the Quality of English Language

Point 1: The English is fine and does not require any improvement.

Response 1:---

5. Additional clarifications:

-

A

B

Response to Reviewer 2 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Questions for General Evaluation

Does the title describe the article's topic with sufficient precision?

Reviewer’s Evaluation

The title could be more specific to reflect the core contribution of the study such as the development and performance of the HEARRT-C score in predicting COVID-19 mortality. Adding the term 'single center' study would provide clarity about the study.

Response and Revisions

Title changed as ‘’HEARRT-C Score: Is Aspirin Protective In COVID-19 Patients? A Single Centre Retrospective Study’’

Does the introduction provide sufficient background and include all relevant references?

The intro is overly brief and does not sufficiently discuss existing mortality prediction models.

Currently, no COVID-19-specific scoring system integrates cardiac biomarkers and imaging findings, despite cardiac risk being a major contributor to mortality in this population."

We agree with the reviewer that this statement is relevant for the Introduction section, as it provides broader context. [page 2, line 46-52].

Are all the cited references relevant to the research?

The manuscript does not adequately cite recent literature on COVID-19.

In our study, previous research utilizing imaging techniques has been referenced

Is the research design appropriate?

Are the methods adequately described?

The criteria for excluding cohort need clarification. There is no mention of inter rater reliability for imaging assessment.

The inclusion and exclusion criteria have been added to the Methods section. [page 2, line 60-70].

Are the results clearly presented?

Results are not entirely clear. The Conclusion claim significant applicability but fail to compare HEARRT-C with existing tools.

The distinguishing features of our scoring system compared to other models have been emphasized in the Conclusion section. [page 13, line 360-363].

Are the conclusions supported by the results?

Yes/Can be improved/Must be improved/Not applicable

3. Point-by-point response to Comments and Suggestions for Authors

Comments 1: Strengths of the study: The study addresses a critical issue, mortality prediction in hospitalized COVID-19 patients, which remains significant for healthcare systems worldwide. The use of univariate and multivariate Cox proportional hazards models demonstrates robust statistical analysis. The study identifies key predictors like age, troponin levels, and calcification, which align with current knowledge of COVID-19 pathophysiology.

Critique: The study is limited to single center, which reduces the generalizability of its findings. A clearer explanation of patients and its potential impact on result is needed. The HEARRT-C scoring requires external validation to confirm its utility. Several typos, such as Diyabetes mellitus and Cerebrovaskulary disease, need correction. 

Response 1:

Our study's primary limitations include its relatively small sample size and single-center design. However, when contextualized within the existing literature, similar studies have employed comparable sample sizes. For instance, Dillinger et al. [3] investigated coronary calcifications in COVID-19 patients with a cohort of 209, while Ferver et al. [4] assessed aortic calcifications in a cohort of 70 patients.

We added G Power analysis and added this in the methods section as;

The sample size for our study was determined using G*Power 3.1.9.7 software. A dependent two-sample t-test was used to estimate the required sample size, assuming a power of 95%, an α error probability of 0.05, and a medium effect size (Cohen's d = 0.5). Based on these parameters, a minimum of 95 patients was required. However, we included 325 patients, utilizing their most recent thoracic CT scans for analysis. [page 2, line 71-75].

We apologize for the typographical errors in the manuscript. The necessary corrections have been made.

While our findings provide valuable insights, further large-scale studies are necessary to validate the proposed scoring system and enhance its generalizability.

Comments 2: This study makes a significant contribution to the literature by introducing the HEARRT-C scoring system. However, its clinical utility and generalizability require further validation and refinement. Addressing the highlighted issues would enhance the manuscript’s impact and applicability The manuscript contains several significant shortcomings that must be addressed to ensure scientific rigor. Firstly, the exclusion of 70% of the cohort is inadequately justified, leaving readers unclear about the criteria used and the potential impact of such exclusions on the study's validity. It is essential to provide a detailed explanation of the inclusion and exclusion criteria and to discuss the representativeness of the remaining population. Additionally, the absence of a power calculation or justification for the chosen sample size raises concerns about the study’s ability to detect meaningful differences or associations. Incorporating this information is critical to strengthen confidence in the findings. The methodology section is another area requiring improvement. Key details regarding variable measurements, the handling of missing data, and adjustments for confounders are insufficiently described. These omissions make it difficult to evaluate the reliability and reproducibility of the study. Providing comprehensive methodological details, including statistical techniques and potential sources of bias, is necessary. Furthermore, while the results are presented, they lack adequate context and comparison with previous studies, limiting their interpretive value. Expanding the discussion to include comparisons with existing literature will contextualize the findings and highlight their significance.

Although the figures and tables present relevant data, they lack clear labeling, legends, and statistical annotations. Enhancing the clarity and presentation of visual elements is essential for effective communication of results. Additionally, while the introduction provides background information, it fails to clearly articulate the novelty and objectives of the study, which diminishes its impact. The discussion section also does not sufficiently address the broader implications of the findings or their potential translational relevance, which are desirable improvements to consider.

Lastly, the manuscript’s English, though understandable, could be improved to streamline verbose sentences and enhance overall readability. A thorough review of the language and the addition of supplementary analyses or data could further strengthen the manuscript's scientific quality and presentation. Addressing these necessary and desirable corrections will significantly improve the manuscript’s rigor and impact.

Response 2:

We appreciate the reviewer’s insightful comments and suggestions. Below, we address the points raised and provide details on the revisions made in the manuscript.

COVID-19 is primarily diagnosed based on pulmonary involvement; however, cardiovascular complications play a critical role in in-hospital events and mortality.

We added this to discussion section as;

The disease can lead to various cardiovascular conditions, including acute coronary syndrome (ACS), heart failure (HF), stroke, myocarditis, arrhythmia, and cardiac arrest.

Regarding the existing scoring systems for predicting mortality in hospitalized patients, widely used models such as SIRS, NEWS, MEWS, 4C Mortality, and qSOFA were primarily developed for sepsis and septic shock. Although some scoring models have been specifically designed for COVID-19, our study is distinct in incorporating cardiac biomarkers and coronary/aortic calcification, both of which are significant contributors to mortality. [page 12, line 327-335].

Revisions and Clarifications:

We have made the following revisions to enhance the clarity and comprehensiveness of our study:

1.     Study Population and Methodology:

• We have clarified the inclusion and exclusion criteria for patient selection. The study included hospitalized patients aged 18 years or older with a confirmed COVID-19 PCR test result, provided that relevant clinical, laboratory, and imaging data were accessible via the hospital information system or direct contact with the patient or their relatives.
• Patients with an expected life expectancy of less than one year, a negative COVID-19 PCR test, no thoracic CT imaging, or those lost to follow-up were excluded. [page 2, line 60-70].

2.     Patient Screening and Data Collection:

• Between March 1, 2020, and December 31, 2021, hospitalized COVID-19 patients were screened. Outpatients (n=531) were excluded due to the inability to monitor hs-troponin levels and other laboratory parameters. Patients whose initial imaging was performed using chest X-ray rather than thoracic CT (n=159) were also excluded, as calcification scoring could not be performed. Additionally, 53 hospitalized patients with incomplete data were excluded. [page 2, line 60-70].

3.     Sample Size Determination:

o   We have elaborated on the statistical justification for our sample size calculation. Using G*Power 3.1.9.7 software, we determined the required sample size based on a dependent two-sample t-test, assuming a power of 95%, an α error probability of 0.05, and a medium effect size (Cohen’s d = 0.5). While the minimum required sample size was 95 patients, we included 325 patients in our study, utilizing their most recent thoracic CT scans for analysis. [page 2, line 71-75].

4.     Validation of the Scoring System:

o   The primary limitation of our study is the small sample size. The effect of the HEARTT-C score on mortality was assessed using a post hoc power analysis with G*Power 3.1.9.7. When comparing the HEARTT-C scores of patients with and without mortality, the effect size was determined to be 0.8, and the power analysis result was 0.91. In conclusion, our study represents a preliminary report, and further validation through larger-scale, prospective studies is required. We added this to limitations section. [page 13, line 351-355].

We have made the necessary revisions in the manuscript. We appreciate the reviewer’s valuable feedback, which has helped strengthen the clarity and rigor of our study.

4. Response to Comments on the Quality of English Language

Point 1:
The English could be improved to more clearly express the research.

Response 1: We sought assistance from AI to improve the English language quality of our manuscript, and the necessary revisions have been made accordingly.

5. Additional clarifications: Please see the attachment*