Title: Which scoring systems are useful for predicting the prognosis of lower gastrointestinal
bleeding? Old and New
Version: 2 Date: 06 Dec 2024
Reviewer:  Chikamasa Ichita
Reviewer's report:
This study validated prediction scores for lower gastrointestinal bleeding (LGIB) in an
emergency setting. The outcomes were  all cause mortality and prolonged hospital stay (#10
days). The validation conducted at a single center in South Korea demonstrated that the AIMS
65, CHAMPS, and ABC scoring systems exhibited superior performance for predicting 30-day
mortality. For predicting prolonged hospital stay, the SHA2PE score demonstrated the highest
accuracy among all evaluated systems.
The true aim of this study appears to be to accurately identify which patients with LGIB are at
risk of worsening outcomes. However, several issues need to be addressed:
1. Inappropriate outcome selection: prolonged hospital stay
Prolonged hospital stay is influenced by a variety of factors, such as social adjustments and
comorbidities, rather than solely reflecting the impact of bleeding. It serves as a surrogate
outcome rather than a direct measure of disease severity. In studies of LGIB, mortality rates are
generally below 1% (PMID: 34388140), making rebleeding the most critical outcome. The study
should reconsider (30-day) rebleeding as the primary outcome instead of prolonged hospital stay.
2. Suitability of mortality as a primary outcome
While mortality is rare in LGIB, with rates generally below 1%, it is undeniably an important
clinical endpoint. However, its use as a primary outcome in this study raises questions about its
appropriateness. As shown in this study, risk factors for mortality, such as hypoalbuminemia and
underlying cancer, are often unrelated to bleeding itself. These factors strongly correlate with
scores that identify frail patients rather than the severity of bleeding. Given the low mortality
rate, (30-day) rebleeding would be a more appropriate primary outcome, with mortality assessed
as a secondary outcome.
3. Lack of inclusion of relevant scoring systems
This study aimed to predict severe outcomes, such as mortality and prolonged hospital stay, in
LGIB patients. However, it did not include the NOBLADS score (PMID: 27311620,29698506),
which was specifically developed for predicting the severity of LGIB. Given the study's
objectives, NOBLADS should have been included as one of the evaluated scoring systems.
4. Absence of calibration assessment
The performance of predictive scores and models should be evaluated based on both
discrimination (e.g., AUROC) and calibration (PMID: 25560730, Item 10d. Specify all measures
used to assess model performance and, if relevant, to compare multiple models. ). This study
assessed only discrimination, which is insufficient for a comprehensive evaluation of the scores.
Calibration data or figures comparing predicted and observed outcomes for each score and
outcome should be presented.
5. Unclear focus on risk factor exploration
Although the primary purpose of this study is the validation of scoring systems, it also explores
risk factors for each outcome, which may confuse readers. Moreover, the study selected variables
for analysis from the scoring systems themselves, but the rationale for this selection is unclear.
Since this study does not aim to develop a new prediction model but rather to validate existing
ones, it would be better to omit the risk factor analysis to avoid confusion.
Title: Which scoring systems are useful for predicting the prognosis of lower gastrointestinal
bleeding? Old and New
Version: 2 Date: 06 Dec 2024
Reviewer:  Chikamasa Ichita
Reviewer's report:
This study validated prediction scores for lower gastrointestinal bleeding (LGIB) in an
emergency setting. The outcomes were  all cause mortality and prolonged hospital stay (#10
days). The validation conducted at a single center in South Korea demonstrated that the AIMS
65, CHAMPS, and ABC scoring systems exhibited superior performance for predicting 30-day
mortality. For predicting prolonged hospital stay, the SHA2PE score demonstrated the highest
accuracy among all evaluated systems.
The true aim of this study appears to be to accurately identify which patients with LGIB are at
risk of worsening outcomes. However, several issues need to be addressed:
1. Inappropriate outcome selection: prolonged hospital stay
Prolonged hospital stay is influenced by a variety of factors, such as social adjustments and
comorbidities, rather than solely reflecting the impact of bleeding. It serves as a surrogate
outcome rather than a direct measure of disease severity. In studies of LGIB, mortality rates are
generally below 1% (PMID: 34388140), making rebleeding the most critical outcome. The study
should reconsider (30-day) rebleeding as the primary outcome instead of prolonged hospital stay.
2. Suitability of mortality as a primary outcome
While mortality is rare in LGIB, with rates generally below 1%, it is undeniably an important
clinical endpoint. However, its use as a primary outcome in this study raises questions about its
appropriateness. As shown in this study, risk factors for mortality, such as hypoalbuminemia and
underlying cancer, are often unrelated to bleeding itself. These factors strongly correlate with
scores that identify frail patients rather than the severity of bleeding. Given the low mortality
rate, (30-day) rebleeding would be a more appropriate primary outcome, with mortality assessed
as a secondary outcome.
3. Lack of inclusion of relevant scoring systems
This study aimed to predict severe outcomes, such as mortality and prolonged hospital stay, in
LGIB patients. However, it did not include the NOBLADS score (PMID: 27311620,29698506),
which was specifically developed for predicting the severity of LGIB. Given the study's
objectives, NOBLADS should have been included as one of the evaluated scoring systems.
4. Absence of calibration assessment
The performance of predictive scores and models should be evaluated based on both
discrimination (e.g., AUROC) and calibration (PMID: 25560730, Item 10d. Specify all measures
used to assess model performance and, if relevant, to compare multiple models. ). This study
assessed only discrimination, which is insufficient for a comprehensive evaluation of the scores.
Calibration data or figures comparing predicted and observed outcomes for each score and
outcome should be presented.
5. Unclear focus on risk factor exploration
Although the primary purpose of this study is the validation of scoring systems, it also explores
risk factors for each outcome, which may confuse readers. Moreover, the study selected variables
for analysis from the scoring systems themselves, but the rationale for this selection is unclear.
Since this study does not aim to develop a new prediction model but rather to validate existing
ones, it would be better to omit the risk factor analysis to avoid confusion.
Please review this paper.
user
Title: Which scoring systems are useful for predicting the prognosis of lower gastrointestinal
bleeding? Old and New
Version: 2 Date: 06 Dec 2024
Reviewer:  Chikamasa Ichita
Reviewer's report:
This study validated prediction scores for lower gastrointestinal bleeding (LGIB) in an
emergency setting. The outcomes were  all cause mortality and prolonged hospital stay (#10
days). The validation conducted at a single center in South Korea demonstrated that the AIMS
65, CHAMPS, and ABC scoring systems exhibited superior performance for predicting 30-day
mortality. For predicting prolonged hospital stay, the SHA2PE score demonstrated the highest
accuracy among all evaluated systems.
The true aim of this study appears to be to accurately identify which patients with LGIB are at
risk of worsening outcomes. However, several issues need to be addressed:
1. Inappropriate outcome selection: prolonged hospital stay
Prolonged hospital stay is influenced by a variety of factors, such as social adjustments and
comorbidities, rather than solely reflecting the impact of bleeding. It serves as a surrogate
outcome rather than a direct measure of disease severity. In studies of LGIB, mortality rates are
generally below 1% (PMID: 34388140), making rebleeding the most critical outcome. The study
should reconsider (30-day) rebleeding as the primary outcome instead of prolonged hospital stay.
2. Suitability of mortality as a primary outcome
While mortality is rare in LGIB, with rates generally below 1%, it is undeniably an important
clinical endpoint. However, its use as a primary outcome in this study raises questions about its
appropriateness. As shown in this study, risk factors for mortality, such as hypoalbuminemia and
underlying cancer, are often unrelated to bleeding itself. These factors strongly correlate with
scores that identify frail patients rather than the severity of bleeding. Given the low mortality
rate, (30-day) rebleeding would be a more appropriate primary outcome, with mortality assessed
as a secondary outcome.
3. Lack of inclusion of relevant scoring systems
This study aimed to predict severe outcomes, such as mortality and prolonged hospital stay, in
LGIB patients. However, it did not include the NOBLADS score (PMID: 27311620,29698506),
which was specifically developed for predicting the severity of LGIB. Given the study's
objectives, NOBLADS should have been included as one of the evaluated scoring systems.
4. Absence of calibration assessment
The performance of predictive scores and models should be evaluated based on both
discrimination (e.g., AUROC) and calibration (PMID: 25560730, Item 10d. Specify all measures
used to assess model performance and, if relevant, to compare multiple models. ). This study
assessed only discrimination, which is insufficient for a comprehensive evaluation of the scores.
Calibration data or figures comparing predicted and observed outcomes for each score and
outcome should be presented.
5. Unclear focus on risk factor exploration
Although the primary purpose of this study is the validation of scoring systems, it also explores
risk factors for each outcome, which may confuse readers. Moreover, the study selected variables
for analysis from the scoring systems themselves, but the rationale for this selection is unclear.
Since this study does not aim to develop a new prediction model but rather to validate existing
ones, it would be better to omit the risk factor analysis to avoid confusion.
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