Title: Identifying novel acute pancreatitis sub-phenotypes using total serum calcium trajectories
Version: 0 Date: 11 Dec 2023
Reviewer's report:
This research aims to delineate specific sub-phenotypes within Acute Pancreatitis patients by
analyzing longitudinal data for TSC levels, collected at one-hour intervals over a 24-hour period
following admission. The study successfully distinguishes four distinct phenotypic categories
among the hospitalized patient cohort. These identified subgroups exhibit variations in terms of
clinical outcomes and in-hospital mortality rates. The results of this investigation hold potential
for advancing the accuracy of prognosis in Acute Pancreatitis patient care.
Pros:
(1) In this study, a new and less invasive predictor biomarker has been developed. The readily
available and standardized reference ranges for a common routine test like serum calcium has
been used
(2) The study highlights the limitations of current indicators
(3) The research incorporates both the longitudinal TSC trajectory and individual point-in-time
TSC values into its analysis
(4) To ensure the reliability of the findings, two sensitivity analyses were conducted,
underscoring the robustness of the tests
(5) The outcomes of this research have the potential to serve as valuable drivers for targeted
treatment strategies tailored to different patient phenotypes
(6) I appreciated that the study is clear in its aim from the very beginning. It is succinct, discusses
relevant topics around its aim and presents clear and prominently highlighted results.
Revisions/ Some Thoughts:
(1) I don’t see any other referenced studies that have utilized calcium levels as prognostic
indicators for AP. A quick Google search reveals the works of Tian et al. (2021) and Gupta et
al. (2023), both of which employ TSC-related ratios as prognostic indicators for AP. It would be
beneficial to include a more comprehensive review of prior research exploring the associations
between TSC and AP in the literature review section.
(2) You’ve mentioned age in the Sources of Data section (16 years and above). Is there a reason
why this age bracket was considered? Could you add an explanation about your choice of data
subsegment?
(3) I'm having trouble understanding the comparison between Figure 2 and Figure 3. According
to Table 2, patient mortality is evident in all sub-phenotypes. Figure 2 shows that non-survivors
consistently exhibit lower TSC levels than survivors in the 24 hours post-admission period.
Conversely, Figure 3 depicts TSC trends over time for various phenotypes, and for those with
fluctuating high TSC (and even to some extent, for those with stable normal levels), the TSC
levels seem notably higher than those of non-survivors, despite the fact that some patients in
these sub-groups also did not survive. Can you provide additional clarification to address this
apparent discrepancy. Is Figure 3 exclusively representing the survivor group?
(4) Are there any concerns regarding potential data bias, considering that 3875 out of 4518
individuals belong to the stable normal group? Even if there are no such concerns, it would be
beneficial to have a discussion regarding the substantial disparity in group sizes resulting from
the GBTM analysis. Could stable normal calcium group itself also contain distinct sub-groups?
(5) In the results section, you've highlighted that "Non-survivors had higher rates of congestive
heart failure, chronic renal failure, metastatic cancer, and liver disease." Is it conceivable that
this outcome is, in some respects, anticipated due to the potential for compromised immunity in
individuals with pre-existing conditions, and in certain instances, mortality may not necessarily
be directly associated with AP? It would be nice to see your thoughts regarding this lack of a
direct link.
(6) Could you expand on the potential confounding factors discussed in model 3, as mentioned
in subsection "TSC Characteristics Within Phenotypes"?
(7) Please also ensure that throughout the document, all acronyms are accompanied by their full
forms before they are referenced.
Title: Identifying novel acute pancreatitis sub-phenotypes using total serum calcium trajectories
Version: 0 Date: 11 Dec 2023
Reviewer's report:
This research aims to delineate specific sub-phenotypes within Acute Pancreatitis patients by
analyzing longitudinal data for TSC levels, collected at one-hour intervals over a 24-hour period
following admission. The study successfully distinguishes four distinct phenotypic categories
among the hospitalized patient cohort. These identified subgroups exhibit variations in terms of
clinical outcomes and in-hospital mortality rates. The results of this investigation hold potential
for advancing the accuracy of prognosis in Acute Pancreatitis patient care.
Pros:
(1) In this study, a new and less invasive predictor biomarker has been developed. The readily
available and standardized reference ranges for a common routine test like serum calcium has
been used
(2) The study highlights the limitations of current indicators
(3) The research incorporates both the longitudinal TSC trajectory and individual point-in-time
TSC values into its analysis
(4) To ensure the reliability of the findings, two sensitivity analyses were conducted,
underscoring the robustness of the tests
(5) The outcomes of this research have the potential to serve as valuable drivers for targeted
treatment strategies tailored to different patient phenotypes
(6) I appreciated that the study is clear in its aim from the very beginning. It is succinct, discusses
relevant topics around its aim and presents clear and prominently highlighted results.
Revisions/ Some Thoughts:
(1) I don’t see any other referenced studies that have utilized calcium levels as prognostic
indicators for AP. A quick Google search reveals the works of Tian et al. (2021) and Gupta et
al. (2023), both of which employ TSC-related ratios as prognostic indicators for AP. It would be
beneficial to include a more comprehensive review of prior research exploring the associations
between TSC and AP in the literature review section.
(2) You’ve mentioned age in the Sources of Data section (16 years and above). Is there a reason
why this age bracket was considered? Could you add an explanation about your choice of data
subsegment?
(3) I'm having trouble understanding the comparison between Figure 2 and Figure 3. According
to Table 2, patient mortality is evident in all sub-phenotypes. Figure 2 shows that non-survivors
consistently exhibit lower TSC levels than survivors in the 24 hours post-admission period.
Conversely, Figure 3 depicts TSC trends over time for various phenotypes, and for those with
fluctuating high TSC (and even to some extent, for those with stable normal levels), the TSC
levels seem notably higher than those of non-survivors, despite the fact that some patients in
these sub-groups also did not survive. Can you provide additional clarification to address this
apparent discrepancy. Is Figure 3 exclusively representing the survivor group?
(4) Are there any concerns regarding potential data bias, considering that 3875 out of 4518
individuals belong to the stable normal group? Even if there are no such concerns, it would be
beneficial to have a discussion regarding the substantial disparity in group sizes resulting from
the GBTM analysis. Could stable normal calcium group itself also contain distinct sub-groups?
(5) In the results section, you've highlighted that "Non-survivors had higher rates of congestive
heart failure, chronic renal failure, metastatic cancer, and liver disease." Is it conceivable that
this outcome is, in some respects, anticipated due to the potential for compromised immunity in
individuals with pre-existing conditions, and in certain instances, mortality may not necessarily
be directly associated with AP? It would be nice to see your thoughts regarding this lack of a
direct link.
(6) Could you expand on the potential confounding factors discussed in model 3, as mentioned
in subsection "TSC Characteristics Within Phenotypes"?
(7) Please also ensure that throughout the document, all acronyms are accompanied by their full
forms before they are referenced.
Please review this paper.
user
Title: Identifying novel acute pancreatitis sub-phenotypes using total serum calcium trajectories
Version: 0 Date: 11 Dec 2023
Reviewer's report:
This research aims to delineate specific sub-phenotypes within Acute Pancreatitis patients by
analyzing longitudinal data for TSC levels, collected at one-hour intervals over a 24-hour period
following admission. The study successfully distinguishes four distinct phenotypic categories
among the hospitalized patient cohort. These identified subgroups exhibit variations in terms of
clinical outcomes and in-hospital mortality rates. The results of this investigation hold potential
for advancing the accuracy of prognosis in Acute Pancreatitis patient care.
Pros:
(1) In this study, a new and less invasive predictor biomarker has been developed. The readily
available and standardized reference ranges for a common routine test like serum calcium has
been used
(2) The study highlights the limitations of current indicators
(3) The research incorporates both the longitudinal TSC trajectory and individual point-in-time
TSC values into its analysis
(4) To ensure the reliability of the findings, two sensitivity analyses were conducted,
underscoring the robustness of the tests
(5) The outcomes of this research have the potential to serve as valuable drivers for targeted
treatment strategies tailored to different patient phenotypes
(6) I appreciated that the study is clear in its aim from the very beginning. It is succinct, discusses
relevant topics around its aim and presents clear and prominently highlighted results.
Revisions/ Some Thoughts:
(1) I don’t see any other referenced studies that have utilized calcium levels as prognostic
indicators for AP. A quick Google search reveals the works of Tian et al. (2021) and Gupta et
al. (2023), both of which employ TSC-related ratios as prognostic indicators for AP. It would be
beneficial to include a more comprehensive review of prior research exploring the associations
between TSC and AP in the literature review section.
(2) You’ve mentioned age in the Sources of Data section (16 years and above). Is there a reason
why this age bracket was considered? Could you add an explanation about your choice of data
subsegment?
(3) I'm having trouble understanding the comparison between Figure 2 and Figure 3. According
to Table 2, patient mortality is evident in all sub-phenotypes. Figure 2 shows that non-survivors
consistently exhibit lower TSC levels than survivors in the 24 hours post-admission period.
Conversely, Figure 3 depicts TSC trends over time for various phenotypes, and for those with
fluctuating high TSC (and even to some extent, for those with stable normal levels), the TSC
levels seem notably higher than those of non-survivors, despite the fact that some patients in
these sub-groups also did not survive. Can you provide additional clarification to address this
apparent discrepancy. Is Figure 3 exclusively representing the survivor group?
(4) Are there any concerns regarding potential data bias, considering that 3875 out of 4518
individuals belong to the stable normal group? Even if there are no such concerns, it would be
beneficial to have a discussion regarding the substantial disparity in group sizes resulting from
the GBTM analysis. Could stable normal calcium group itself also contain distinct sub-groups?
(5) In the results section, you've highlighted that "Non-survivors had higher rates of congestive
heart failure, chronic renal failure, metastatic cancer, and liver disease." Is it conceivable that
this outcome is, in some respects, anticipated due to the potential for compromised immunity in
individuals with pre-existing conditions, and in certain instances, mortality may not necessarily
be directly associated with AP? It would be nice to see your thoughts regarding this lack of a
direct link.
(6) Could you expand on the potential confounding factors discussed in model 3, as mentioned
in subsection "TSC Characteristics Within Phenotypes"?
(7) Please also ensure that throughout the document, all acronyms are accompanied by their full
forms before they are referenced.
assistant