Title: A nomogram to predict pulmonary complications after gastrointestinal surgery: a
retrospective study
Version: 2 Date: 28 Sep 2024
Reviewer's report:
This is a well-conducted retrospective study that aims to identify risk factors for postoperative
pulmonary complications (PPCs) after gastrointestinal surgery and develop a predictive
nomogram model. The study provides valuable insights into the factors associated with PPCs
and has the potential to aid in clinical decision-making. However, there are some areas that
require revision to improve the clarity and accuracy of the conclusions.
Although this study constructs a nomogram model, offering a novel approach and method for
predicting postoperative PPCs following gastrointestinal surgery, it is necessary to compare this
model with other representative existing models to highlight the advantages of the nomogram
model in predicting PPCs after gastrointestinal surgery. On the other hand, the source code of
the nomogram model needs to be supplemented, ensuring that the code is clear, complete, and
easy to understand for other researchers to validate and replicate. It’s recommended that the
authors refer to the practices of other related studies, submit the source code as supplementary
material, and provide detailed instructions and the operating environment in the paper or in the
supplementary materials.
Title: A nomogram to predict pulmonary complications after gastrointestinal surgery: a
retrospective study
Version: 2 Date: 28 Sep 2024
Reviewer's report:
This is a well-conducted retrospective study that aims to identify risk factors for postoperative
pulmonary complications (PPCs) after gastrointestinal surgery and develop a predictive
nomogram model. The study provides valuable insights into the factors associated with PPCs
and has the potential to aid in clinical decision-making. However, there are some areas that
require revision to improve the clarity and accuracy of the conclusions.
Although this study constructs a nomogram model, offering a novel approach and method for
predicting postoperative PPCs following gastrointestinal surgery, it is necessary to compare this
model with other representative existing models to highlight the advantages of the nomogram
model in predicting PPCs after gastrointestinal surgery. On the other hand, the source code of
the nomogram model needs to be supplemented, ensuring that the code is clear, complete, and
easy to understand for other researchers to validate and replicate. It’s recommended that the
authors refer to the practices of other related studies, submit the source code as supplementary
material, and provide detailed instructions and the operating environment in the paper or in the
supplementary materials.
Please review this paper.
user
Title: A nomogram to predict pulmonary complications after gastrointestinal surgery: a
retrospective study
Version: 2 Date: 28 Sep 2024
Reviewer's report:
This is a well-conducted retrospective study that aims to identify risk factors for postoperative
pulmonary complications (PPCs) after gastrointestinal surgery and develop a predictive
nomogram model. The study provides valuable insights into the factors associated with PPCs
and has the potential to aid in clinical decision-making. However, there are some areas that
require revision to improve the clarity and accuracy of the conclusions.
Although this study constructs a nomogram model, offering a novel approach and method for
predicting postoperative PPCs following gastrointestinal surgery, it is necessary to compare this
model with other representative existing models to highlight the advantages of the nomogram
model in predicting PPCs after gastrointestinal surgery. On the other hand, the source code of
the nomogram model needs to be supplemented, ensuring that the code is clear, complete, and
easy to understand for other researchers to validate and replicate. It’s recommended that the
authors refer to the practices of other related studies, submit the source code as supplementary
material, and provide detailed instructions and the operating environment in the paper or in the
supplementary materials.
assistant