Analysis of Mortality Among Patients Attended by a Mobile Emergency Service in Paraná Between 2019 and 2020: An Observational Study

Article activity feed

1. 

   PREreview

   Jun 25, 2025

   This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/15741569.

   Analysis of Mortality Among Patients Attended by Mobile Emergency Service in Paraná Between 2019 and 2020 – Observational Study

   Authors: Erika F. S. B. Ludwig, Aroldo Gavioli, et al.

   DOI: https://doi.org/10.1590/SciELOPreprints.10275

   Date Posted: 31 October 2024

   Reviewed by Nyirabwimana FRANCOISE

   Study Design: Quantitative Observational, cross-sectional

   1. Summary of the Study

   This study investigates mortality among 13,326 patients assisted by the in Paraná from 2019 to 2020. It focuses on how response time, type of support, and regional service distribution affect outcomes, particularly prehospital mortality. Advanced statistical tools such as Kaplan-Meier survival curves and Cox regression were …

   This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/15741569.

   Analysis of Mortality Among Patients Attended by Mobile Emergency Service in Paraná Between 2019 and 2020 – Observational Study

   Authors: Erika F. S. B. Ludwig, Aroldo Gavioli, et al.

   DOI: https://doi.org/10.1590/SciELOPreprints.10275

   Date Posted: 31 October 2024

   Reviewed by Nyirabwimana FRANCOISE

   Study Design: Quantitative Observational, cross-sectional

   1. Summary of the Study

   This study investigates mortality among 13,326 patients assisted by the in Paraná from 2019 to 2020. It focuses on how response time, type of support, and regional service distribution affect outcomes, particularly prehospital mortality. Advanced statistical tools such as Kaplan-Meier survival curves and Cox regression were applied. Notably, mortality was higher in 2020 (vs. 2019).

   2. Strengths

   ✅ Timely and relevant topic, especially given the COVID-19 pandemic's impact on emergency services.

   ✅ Robust dataset: Over 13,000 service records analyzed.

   ✅ Statistical rigor: Use of Kaplan-Meier, Log-rank, Cox regression models.

   ✅ Policy relevance: Provides clear insights into regional inequalities and resource allocation.

   ✅ Well-defined variables: Includes prehospital mortality, response times, patient demographics, and system structure.

   3. Areas for Improvement

   🔹 A. Abstract

   The abstract is clear and well-structured, but the confidence intervals (CIs) in the hazard ratios should be fully reported (currently shown as IC95% only without actual values in some places).

   Include p-values for clarity on statistical significance.

   🔹 B. Introduction

   Very informative and thorough.

   Could be slightly more concise to better guide the reader to the problem and objective.

   🔹 C. Methods

   ·       Excellent detail about the structure of SAMU services and regional differences.

   ·       Limitations in data completeness were acknowledged, but it would be helpful to report how missing data were handled statistically.

   ·       Clarify if patients dead on arrival were excluded from the survival analysis, and if so, why.

   🔹 D. Results

   ·       Well-structured and statistically sound.

   🔹 E. Discussion

   The interpretation is insightful and supported by external literature.

   The section could benefit from a clearer structure: group the discussion under "Principal findings," "Comparison with other studies," "Implications," and "Limitations."

   🔹 F. Limitations

   Well-acknowledged (e.g., incomplete data, manual form filling).

   Consider discussing the generalizability of findings to other regions or contexts.

   4. Minor Suggestions

   Improve English grammar slightly in the translated abstract for fluency.

   Ensure consistency in units of time (e.g., minutes) across all tables and figures.

   Consider merging some long paragraphs for easier readability.

   5. Conclusion and Recommendation

   This preprint presents important evidence on how emergency medical response characteristics affect patient survival. It is especially valuable for health system managers in Brazil and other countries with regionalized prehospital systems. With minor revisions for clarity and structure, this work is publishable in a peer-reviewed journal.

   6. Final Recommendation

   ·       Clarifying CIs and p-values in the abstract

   ·       Enhancing readability and structure in the discussion

   ·       Explaining statistical treatment of missing data

   Competing interests

   Ensures transparency and integrity in the review process

   Read the original source
2. 

   PREreview

   Jun 17, 2025

   This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/15683404.

   Does the introduction explain the objective of the research presented in the preprint? Yes

   Are the methods well-suited for this research? Somewhat appropriate

   Are the conclusions supported by the data? Neither supported nor unsupported

   Are the data presentations, including visualizations, well-suited to represent the data? …

   This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/15683404.

   Does the introduction explain the objective of the research presented in the preprint? Yes

   Are the methods well-suited for this research? Somewhat appropriate

   Are the conclusions supported by the data? Neither supported nor unsupported

   Are the data presentations, including visualizations, well-suited to represent the data? Somewhat inappropriate or unclear There was no presentation of data visualization

   How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Somewhat clearly

   Is the preprint likely to advance academic knowledge? Somewhat likely

   Would it benefit from language editing? Yes

   Would you recommend this preprint to others? Yes, but it needs to be improved The English version needs to be made available for easy reading and comprehension, as using AI to translate may alter the originality of the work or paper

   Is it ready for attention from an editor, publisher or broader audience? Yes, after minor changes

   Competing interests

   The authors declare that they have no competing interests.

   Use of Artificial Intelligence (AI)

   The authors declare that they used generative AI to come up with new ideas for their review.

   Read the original source
3. 

   Version published to 10.1590/scielopreprints.10275 on SciELO Preprints

   Oct 31, 2024