Revolving Door in Older Patients: An Observational Study of Risk Assessment of Rehospitalization Using the BRASS Scale

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This is an interesting and timely study that aims to assess the risk of rehospitalization and mortality among elderly patients, including the evaluation of the BRASS Scale's effectiveness in objectively identifying elderly patients at risk of difficult discharge and hospitalization. This study undoubtedly underscores the usefulness and validity of the BRASS Scale as an objective tool for assessing the risk of rehospitalization among elderly patients, supporting the implementation of targeted post-discharge care strategies aimed at reducing the incidence of the "revolving door" phenomenon among frail elderly people. However, further revisions are needed for the manuscript to be considered for publication.

1. In the introduction, from lines 73 to 78, the authors write: "To the best of our knowledge, this is one of the first studies attempting to highlight the validity of the BRASS Scale in objectively assessing the risk of rehospitalization and mortality among older patients, implementing targeted interventions to mitigate this phenomenon. Given the increasing aging index of society, with a growing population in need of prolonged care, this research aligns with the current demands and healthcare needs of the modern population." Frankly, this comment is more appropriate for a concluding paragraph than an introductory paragraph. In this sense, the authors should more appropriately revise the key concepts to be included in the introduction.

2. From lines 173 to 182, the authors briefly describe the contents of Figures 1 to 4, making it difficult to understand. The authors should comment more extensively on the results depicted in the graphs, figure by figure.

3. Figures 3 and 4 can be improved by including the results of a log-rank analysis to assess any statistically significant differences between the survival curves in Figure 3 and the rehospitalization curves in Figure 4.

 

Comments on the Quality of English Language

The English form should be corrected in several places in the text, perhaps with the assistance of a native speaker.

Author Response

Reviewer 1

Comments 1. In the introduction, from lines 73 to 78, the authors write: "To the best of our knowledge, this is one of the first studies attempting to highlight the validity of the BRASS Scale in objectively assessing the risk of rehospitalization and mortality among older patients, implementing targeted interventions to mitigate this phenomenon. Given the increasing aging index of society, with a growing population in need of prolonged care, this research aligns with the current demands and healthcare needs of the modern population." Frankly, this comment is more appropriate for a concluding paragraph than an introductory paragraph. In this sense, the authors should more appropriately revise the key concepts to be included in the introduction.

Response 1. Thank you. We agree that the original wording in the introduction (lines 73–78) was more appropriate for the concluding section. Accordingly, we have revised the paragraph to focus on the study’s background and rationale. The revised introduction now emphasizes the clinical need for reliable tools to assess the risk of rehospitalization and mortality among older patients, setting the stage for the objectives of our study without anticipating its outcomes:

“Older adults represent a population at particularly high risk of rehospitalization and mortality, especially in the context of prolonged care needs. Identifying reliable tools to assess this risk objectively is therefore essential for improving patient outcomes and guiding appropriate interventions. Among the available instruments, the BRASS Scale has gained attention as a potential tool for risk stratification in older patients, although further research is needed to confirm its validity in this setting.”

Comments 2. From lines 173 to 182, the authors briefly describe the contents of Figures 1 to 4, making it difficult to understand. The authors should comment more extensively on the results depicted in the graphs, figure by figure.

Response 2. Thank you. We added more details about the contents of Figure 1, 2,3 and 4. The text now reports:

“Figure 1 shows the distribution of the main causes of hospitalization by clinical area: infectious diseases represented the first cause (27.9%), followed by cardiac diseases (12.8%), gastroenterological diseases (11.7%) and Surgical causes (10.6%).  Figure 2 illustrates the main causes of rehospitalization by clinical area: in this picture Surgical causes and cardiac diseases became the main reason (both 18.7%), then infectious disease (17.3%), pulmonary disease (9.7%) and nefrological and gastroenterological diseases (8 % both), showing how there was a great decrease in infectious diseases (-14.2%) and an important increase in surgical causes (+8.1%) and cardiac diseases (+ 5.9%).  Figure 3 presents the Kaplan-Meier survival curves stratified according to BRASS risk categories. As shown, patients classified in the high-risk group experienced a markedly lower probability of survival over the entire follow-up period compared to those in the medium- and low-risk categories. The survival probability for high-risk patients declined steeply within the first months and remained consistently below that of the other groups throughout the observation period. In contrast, the low-risk group demonstrated the most favorable survival outcomes, with survival probabilities remaining consistently high and stable over time, while the medium-risk group exhibited intermediate survival patterns, falling between the two extremes.  Figure 4 depicts the Kaplan-Meier curves for rehospitalization events across the same BRASS risk categories. Interestingly, in this analysis, the intermediate-risk group showed a significantly greater probability of rehospitalization compared to both the low- and high-risk groups throughout the follow-up period. The low-risk group maintained the most favorable trajectory, with the lowest cumulative risk of rehospitalization over time. The unexpectedly higher rehospitalization rate in the intermediate-risk group, relative even to the high-risk group, may indicate distinct clinical or social factors influencing rehospitalization risk beyond those captured by the BRASS score alone, warranting further investigation.”

Comments 3. Figures 3 and 4 can be improved by including the results of a log-rank analysis to assess any statistically significant differences between the survival curves in Figure 3 and the rehospitalization curves in Figure 4.

Response 3. Good idea. We also included in our analysis the results of a log-rank analysis to assess any statistically significant differences between the survival curves in Figure 3 and the rehospitalization curves in Figure 4:

The differences among the survival curves were statistically significant according to the log-rank test (low vs. high risk: p < 0.0001; intermediate vs. high risk: p < 0.001; intermediate vs. low risk: p = 0.82).”

“Here too, the differences between curves were statistically significant (low vs. high risk: p < 0.0001; intermediate vs. high risk: p < 0.001; intermediate vs. low risk: p = 0.52).”

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

Your manuscript describes a novel and interesting study, showing results that can be very useful in clinical practice and for future studies.

I have only a few comments/suggestions:

Discussion

Lines 224-228 The Authors underlined the fact that chronological age alone is not enough to predict patient clinical outcomes. Frailty assessment can help to better characterise patient complexity. The Authors should discuss this part, adding some more lines.

Supplementary File

The Authors should replace the following words:

“Nutrition”: Eating

“Hygiene”: Bathing

“Transfers”: Transferring

“Disoriented in”: Disoriented to

“Number of preious”: Number of previous

“Needing continuity of care, likely requiring rehabilitation…”: requiring continuity of care, need for rehabilitation…

Author Response

Reviewer 2:

Comments 1. Lines 224-228 The Authors underlined the fact that chronological age alone is not enough to predict patient clinical outcomes. Frailty assessment can help to better characterise patient complexity. The Authors should discuss this part, adding some more lines.

Response 1. Thank you for your comment. We now discussed more this part adding more details:

“This result highlights a key point: while age is often considered a primary risk factor, it alone does not capture the complexity of older patients' health status. Frailty assessment offers a more comprehensive evaluation, incorporating functional, cognitive, and social dimensions that are not reflected by age alone. Previous studies have similarly demonstrated that frailty indices outperform chronological age in predicting adverse outcomes, including mortality and rehospitalization. Our findings therefore support the growing consensus that clinical decision-making in older adults should be guided by frailty assessment rather than age alone.”

 

Comments 2. Supplementary File

The Authors should replace the following words:

“Nutrition”: Eating

“Hygiene”: Bathing

“Transfers”: Transferring

“Disoriented in”: Disoriented to

“Number of preious”: Number of previous

“Needing continuity of care, likely requiring rehabilitation…”: requiring continuity of care, need for rehabilitation…

Response 2. Thank you. We thank the reviewer for the suggestion. All the requested changes in the Supplementary File have been made as follows:

• “Nutrition” has been replaced with “Eating.”
• “Hygiene” has been replaced with “Bathing.”
• “Transfers” has been replaced with “Transferring.”
• “Disoriented in” has been replaced with “Disoriented to.”
• “Number of preious” has been corrected to “Number of previous.”
• “Needing continuity of care, likely requiring rehabilitation…” has been replaced with “Requiring continuity of care, need for rehabilitation…”

Reviewer 3 Report

Comments and Suggestions for Authors

The BRASS Index is one of the original risk prediction models  utilizing functional assessment, historical utilization data, and limited medical information to predict risk for length of stay, discharge planning needs, and post-discharge institutional care along hospitalized patients.

Recent reviews of risk prediction models for hospital readmission include newer tools which incorporate medical comorbidities, prior utilization, functional status, and social determinants of health.  Reporting use of the older BRASS Index to identify patients at high risk of readmission is therefore not novel.

The real gap in the literature involves identifying actionable items that can be utilized to reduce risk of hospital readmission, and demonstrating effectiveness. Unfortunately this study does not contribute to this need.

Author Response

Reviewer 3

Comments 1. The BRASS Index is one of the original risk prediction models  utilizing functional assessment, historical utilization data, and limited medical information to predict risk for length of stay, discharge planning needs, and post-discharge institutional care along hospitalized patients.

Recent reviews of risk prediction models for hospital readmission include newer tools which incorporate medical comorbidities, prior utilization, functional status, and social determinants of health.  Reporting use of the older BRASS Index to identify patients at high risk of readmission is therefore not novel.

The real gap in the literature involves identifying actionable items that can be utilized to reduce risk of hospital readmission, and demonstrating effectiveness. Unfortunately this study does not contribute to this need.

 

Response 1.We thank the reviewer for this important observation. We agree that the BRASS Index is one of the earlier risk prediction models and that more recent tools incorporating additional variables have been developed. However, the purpose of our study was not only to assess the predictive performance of the BRASS Index for readmission and mortality risk in an older patient population but also to validate its applicability within our specific clinical context, where it remains widely used for discharge planning.

While we acknowledge that identifying actionable interventions to reduce readmission risk is an important next step, we believe that confirming the validity of widely implemented tools like the BRASS Index is a necessary foundation for designing such interventions. Our findings provide evidence that, even with newer models available, the BRASS Index can still stratify patients according to risk, thereby helping clinicians target high-risk groups for potential future interventions aimed at reducing readmission rates.

We have clarified these points in the revised discussio to better emphasize the role and relevance of our study within the broader literature:

 

“Although several newer risk prediction models for hospital readmission have been proposed, incorporating medical comorbidities, prior utilization, functional status, and social determinants of health, the BRASS Index remains widely used in clinical practice for discharge planning, particularly in older populations. Our study aimed to validate the BRASS Index in our specific setting, demonstrating that it continues to stratify patients effectively according to risk of readmission and mortality. We acknowledge that the identification of actionable interventions to reduce readmission risk represents the next critical step; however, establishing the validity and utility of existing tools is essential before such interventions can be meaningfully designed and implemented. Our findings therefore provide a foundation for future studies aimed at linking risk stratification with targeted strategies to improve patient outcomes.”

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors responded comprehensively and promptly to all comments. The manuscript may be considered for publication.

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for this novel and interesting study.

Reviewer 3 Report

Comments and Suggestions for Authors

The BRASS Index is one of the original risk prediction models utilizing functional assessment, historical utilization data, and limited medical information to predict risk for length of stay, discharge planning needs, and post-discharge institutional care along hospitalized patients.

Regrets the manuscript validates use of the BRASS scale for a specific inpatient population, but does not provide new information.