Title: Association between Estimated Plasma Volume Status and the Risk of 30-day Mortality
in Patients with Severe Acute Pancreatitis: A Retrospective Study Based on the MIMIC-IV
Database
Version: 0 Date: 07 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While the MIMIC-IV database is large and robust, it is still a retrospective cohort study. This
limits the ability to establish causal relationships, as associations observed may be influenced
by unmeasured confounders.
-There may be inherent biases in the database, such as incomplete documentation or data entry
errors, although the authors did attempt to address these issues.
-The study uses data from a single medical center, which may limit the generalizability of the
findings to other populations. Patient demographics and treatment practices may vary in other
institutions or regions.
-The inclusion of only ICU patients may not reflect the full spectrum of SAP cases, as some
patients may not require intensive care.
-The study primarily investigates ePVS but does not compare this variable directly with other
common markers of SAP severity (e.g., APACHE II, BISAP, CT severity index). A comparison
with these scoring systems could have provided additional context for the clinical usefulness
of ePVS.
-The ePVS is calculated based on hematocrit and hemoglobin levels, which are influenced by
multiple factors (e.g., anemia, dehydration). This could limit the specificity of ePVS as a sole
predictor of mortality in SAP patients.
-Although the authors adjust for several confounders, the treatment interventions themselves
(such as norepinephrine, statins, or mechanical ventilation) could influence patient outcomes.
The complex interplay between ePVS and treatment could be a source of residual confounding.
-The study includes only the first test results after ICU admission; however, changes in ePVS
over time could provide additional insights into the relationship between plasma volume status
and prognosis.
-Although the study uses statistical techniques like cross-validation for model selection, there
is no mention of external validation of the results on an independent cohort. This would help
confirm whether the findings are replicable in other datasets.
-The Strauss formula used to estimate ePVS assumes a direct relationship between hematocrit,
hemoglobin, and plasma volume, but this simplification might not fully capture the complexity
of plasma volume dynamics in critically ill patients, especially those with severe pancreatitis.
Additional validation and refinement of this formula in the context of SAP could be beneficial.
-The study design is not critically discussed in relation to the potential biases inherent in
retrospective studies, such as selection bias, measurement bias, or the inability to control for all
confounding variables. A more thorough discussion on the retrospective nature of the study and
its limitations would strengthen the overall validity of the study's conclusions.
-The discussion mentions the use of multivariate Cox regression analysis and RCS analysis but
does not fully explain the significance of these analyses or how they were integrated with the
overall results. For instance, it would have been helpful to discuss the specific variables that
were most strongly associated with mortality and how they were accounted for in the models.
Title: Association between Estimated Plasma Volume Status and the Risk of 30-day Mortality
in Patients with Severe Acute Pancreatitis: A Retrospective Study Based on the MIMIC-IV
Database
Version: 0 Date: 07 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While the MIMIC-IV database is large and robust, it is still a retrospective cohort study. This
limits the ability to establish causal relationships, as associations observed may be influenced
by unmeasured confounders.
-There may be inherent biases in the database, such as incomplete documentation or data entry
errors, although the authors did attempt to address these issues.
-The study uses data from a single medical center, which may limit the generalizability of the
findings to other populations. Patient demographics and treatment practices may vary in other
institutions or regions.
-The inclusion of only ICU patients may not reflect the full spectrum of SAP cases, as some
patients may not require intensive care.
-The study primarily investigates ePVS but does not compare this variable directly with other
common markers of SAP severity (e.g., APACHE II, BISAP, CT severity index). A comparison
with these scoring systems could have provided additional context for the clinical usefulness
of ePVS.
-The ePVS is calculated based on hematocrit and hemoglobin levels, which are influenced by
multiple factors (e.g., anemia, dehydration). This could limit the specificity of ePVS as a sole
predictor of mortality in SAP patients.
-Although the authors adjust for several confounders, the treatment interventions themselves
(such as norepinephrine, statins, or mechanical ventilation) could influence patient outcomes.
The complex interplay between ePVS and treatment could be a source of residual confounding.
-The study includes only the first test results after ICU admission; however, changes in ePVS
over time could provide additional insights into the relationship between plasma volume status
and prognosis.
-Although the study uses statistical techniques like cross-validation for model selection, there
is no mention of external validation of the results on an independent cohort. This would help
confirm whether the findings are replicable in other datasets.
-The Strauss formula used to estimate ePVS assumes a direct relationship between hematocrit,
hemoglobin, and plasma volume, but this simplification might not fully capture the complexity
of plasma volume dynamics in critically ill patients, especially those with severe pancreatitis.
Additional validation and refinement of this formula in the context of SAP could be beneficial.
-The study design is not critically discussed in relation to the potential biases inherent in
retrospective studies, such as selection bias, measurement bias, or the inability to control for all
confounding variables. A more thorough discussion on the retrospective nature of the study and
its limitations would strengthen the overall validity of the study's conclusions.
-The discussion mentions the use of multivariate Cox regression analysis and RCS analysis but
does not fully explain the significance of these analyses or how they were integrated with the
overall results. For instance, it would have been helpful to discuss the specific variables that
were most strongly associated with mortality and how they were accounted for in the models.
Please review this paper.
user
Title: Association between Estimated Plasma Volume Status and the Risk of 30-day Mortality
in Patients with Severe Acute Pancreatitis: A Retrospective Study Based on the MIMIC-IV
Database
Version: 0 Date: 07 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-While the MIMIC-IV database is large and robust, it is still a retrospective cohort study. This
limits the ability to establish causal relationships, as associations observed may be influenced
by unmeasured confounders.
-There may be inherent biases in the database, such as incomplete documentation or data entry
errors, although the authors did attempt to address these issues.
-The study uses data from a single medical center, which may limit the generalizability of the
findings to other populations. Patient demographics and treatment practices may vary in other
institutions or regions.
-The inclusion of only ICU patients may not reflect the full spectrum of SAP cases, as some
patients may not require intensive care.
-The study primarily investigates ePVS but does not compare this variable directly with other
common markers of SAP severity (e.g., APACHE II, BISAP, CT severity index). A comparison
with these scoring systems could have provided additional context for the clinical usefulness
of ePVS.
-The ePVS is calculated based on hematocrit and hemoglobin levels, which are influenced by
multiple factors (e.g., anemia, dehydration). This could limit the specificity of ePVS as a sole
predictor of mortality in SAP patients.
-Although the authors adjust for several confounders, the treatment interventions themselves
(such as norepinephrine, statins, or mechanical ventilation) could influence patient outcomes.
The complex interplay between ePVS and treatment could be a source of residual confounding.
-The study includes only the first test results after ICU admission; however, changes in ePVS
over time could provide additional insights into the relationship between plasma volume status
and prognosis.
-Although the study uses statistical techniques like cross-validation for model selection, there
is no mention of external validation of the results on an independent cohort. This would help
confirm whether the findings are replicable in other datasets.
-The Strauss formula used to estimate ePVS assumes a direct relationship between hematocrit,
hemoglobin, and plasma volume, but this simplification might not fully capture the complexity
of plasma volume dynamics in critically ill patients, especially those with severe pancreatitis.
Additional validation and refinement of this formula in the context of SAP could be beneficial.
-The study design is not critically discussed in relation to the potential biases inherent in
retrospective studies, such as selection bias, measurement bias, or the inability to control for all
confounding variables. A more thorough discussion on the retrospective nature of the study and
its limitations would strengthen the overall validity of the study's conclusions.
-The discussion mentions the use of multivariate Cox regression analysis and RCS analysis but
does not fully explain the significance of these analyses or how they were integrated with the
overall results. For instance, it would have been helpful to discuss the specific variables that
were most strongly associated with mortality and how they were accounted for in the models.
assistant