Evaluating the predictive value of frailty scores for critical care admission and hospital stay in elderly surgical patients: A comparison of the mFI-5 and CCI

Marc Lincoln; Liadán Tobin-Schnittger; Marianne Foley; Dulmi Nawartha; Pádraig Ó Scanaill

doi:10.1371/journal.pone.0322681

Peer Review History

Original SubmissionMarch 25, 2025
25 Mar 2025 Author Response https://doi.org/10.1371/journal.pone.0322681.r001
Jun 21 2025 Decision Letter - Pedro Curiati, Editor PONE-D-25-15888Evaluating the predictive value of frailty scores for critical care admission and hospital stay in elderly surgical patients: a comparison of the mFI-5 and CCIPLOS ONE Dear Dr. LINCOLN, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Jun 21 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This is a reasonable piece of work which could be improved with revisions. The conclusions are an accurate reflection of the result, showing that MFI-5 and CCI do not predict critical care or length of stay. However, it would be fair to say that neither of these tools were designed specifically for that purpose. Recommend a better explanation of the sample size. Why only 2 months’ patients when presumably more data was available by November 2024? It is possible that with a large sample, clearer results would have been obtained. Were ALL patients who attended the clinic over 65 included, or was there a patient opt-out or other exclusion criteria? Why was 5 days chosen as the cut-off for length of stay? Were other lengths considered and analysed? I infer that all the patients were elective admissions to hospital, but this could be made explicit. Not clear why HFRS (Gilbert https://doi.org/10.1016/S0140-6736(18)30668-8) was not mentioned. Also a recent paper (Kutrani https://doi.org/10.1371/journal.pone.0317234) showed that HFRS (or HFRS in conjunction with CCI) is effective at predicting LOS. The paper is not explicit on what statistical or machine learning technique was used for the predictive model. Was it logistic regression? Also, how were the confidence intervals and p-values obtained? The results show the demographics of the patients but not how many scored what mFI-5 or CCI scores (perhaps present this in suitable bands). The results show little to no predictive ability of the models and the discussion does make a good attempt at explaining why this might be the case. The sentence, "This discrepancy may be due to the homogeneity of the patient population and the lower physiological demands of the procedure compared to more complex surgeries." might be clearer if it compared the heterogeneity of THIS study with the homogeneity of other studies. In the discussion, other papers that the authors might wish to look at include: • Goshtasbi (https://doi.org/10.1177/01945998211010443) found that the mFI-5 was associated with longer length of stay, medical complications, and mortality. • Strigenz (https://doi.org/10.22603/ssrr.2022-0102) concluded that the mFI-5 was an independent predictor of morbidity, suggesting an increased risk of complication events (increased complications means longer LOS and more risk of admission to ICU). Reviewer #2: Overall: The study addresses an important topic, but the current manuscript has several limitations that limit its impact and interpretability. The negative findings are not surprising given the small sample size and heterogeneous surgical population, and the analysis lacks depth. Major Concerns: • The sample size (n=100) is underpowered to detect meaningful differences, particularly with only 20 ICU admissions. • The analysis relies solely on AUROC without exploring more clinically meaningful cutoffs (e.g., frail vs non-frail), limiting applicability. • The heterogeneity of surgical procedures likely masks any predictive signal; no subgroup or sensitivity analyses are provided. • The manuscript does not offer sufficient novel insight beyond prior studies that have shown mixed results for mFI-5 and CCI in specific surgeries. Reviewer #3: This is an automated report for PONE-D-25-15888. This report was solicited by the PLOS One editorial team and provided by ScreenIT. 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Attachments Attachment Submitted filename: report_10.1101+2025.03.27.25324817.pdf https://doi.org/10.1371/journal.pone.0322681.r002
Revision 1
12 May 2025 Author Response Reviewer #1: Many thanks for taking the time to review this paper. I hope you will find the ammendments and responses satisfactory. Marc • The conclusions are an accurate reflection of the result, showing that MFI-5 and CCI do not predict critical care or length of stay. However, it would be fair to say that neither of these tools were designed specifically for that purpose. Response: This is a fair point and I have included a sentence in the discussion which now addresses this. • Recommend a better explanation of the sample size. Why only 2 months’ patients when presumably more data was available by November 2024? It is possible that with a large sample, clearer results would have been obtained. Response: We limited data collection to a two-month period (November–December 2023) to reflect a practical snapshot of patient flow through the preoperative assessment clinic, based on available resources and feasibility. A retrospective power analysis using an anticipated event rate of 30% and AUROC threshold of 0.7 suggested that a sample size of approximately 100 patients would provide sufficient power to detect moderate predictive ability, consistent with similar published studies in this field as referenced in the article. However, we acknowledge that this sample size is modest, and the wide confidence intervals observed in our AUROC results likely reflect this. It is possible that with a larger sample size, clearer patterns may have emerged regarding the predictive value of the frailty indices. Future prospective studies with larger cohorts could offer more definitive conclusions and allow for subgroup analysis by surgical specialty or urgency. I have added a short paragraph into the discussion section which acknowledge this limitation to our study. • Were ALL patients who attended the clinic over 65 included, or was there a patient opt-out or other exclusion criteria? Response: Yes every patient over the age of 65 was included and there were no exclusion criteria. I have exmphaised in the amended manuscript for clarity. • Why was 5 days chosen as the cut-off for length of stay? Were other lengths considered and analysed? Response: We selected a length of stay cut-off of 5 days prior to conducting the study, based on local clinical expectations and its use as a marker of prolonged admission in similar surgical cohorts. We did not test multiple thresholds post hoc, due to concern over false positive results. • I infer that all the patients were elective admissions to hospital, but this could be made explicit. Response: I have included a sentence on this in the methods section for clarity. • Not clear why HFRS (Gilbert https://doi.org/10.1016/S0140-6736(18)30668-8) was not mentioned. Also a recent paper (Kutrani https://doi.org/10.1371/journal.pone.0317234) showed that HFRS (or HFRS in conjunction with CCI) is effective at predicting LOS. Response: I agree that the Hospital Frailty Risk Score (HFRS) is an important tool in the assessment of frailty, particularly in large administrative datasets. However, our study was based on clinical data collection rather than ICD coding, which the HFRS relies upon, and thus we didn’t feel it was feasible to implement in our setting. Furthermore, we felt that CCI and MFI-5 are more useful in the point of care surgical setting like the per-operative care setting in which are study takes place rather than HFRS. I haven’t included reference to this in the amended manuscript as it stands but happy to reference it if you feel it would improve the validity of the paper. • The paper is not explicit on what statistical or machine learning technique was used for the predictive model. Was it logistic regression? Also, how were the confidence intervals and p-values obtained? Response: To assess the predictive ability of the frailty scores we performed AUROC analysis. This method was used to evaluate the discriminatory ability of each score in predicting outcomes. No logistic regression or machine learning models were used in this analysis. SPSS was used for all statistical analysis and I did this myself. The 95% confidence intervals and p values for AUROC on SPSS is calculated based off the Hanley and Mcneil mtehod. P-values were derived from the comparison of AUROC values with the null hypothesis that the score has no discriminative ability (i.e., AUROC = 0.5). A p-value of less than 0.05 was considered statistically significant, although none of the tests reached significance. I feel I have included enough information in the methods section on the statistical analysis to be in line with other papers on similar topics but I am more than happy to go into more detail in the manuscript if you feel it is necessary for clarity. • The results show the demographics of the patients but not how many scored what mFI-5 or CCI scores (perhaps present this in suitable bands). Response: I have added in a table into the methods section for this. • The results show little to no predictive ability of the models and the discussion does make a good attempt at explaining why this might be the case. The sentence, "This discrepancy may be due to the homogeneity of the patient population and the lower physiological demands of the procedure compared to more complex surgeries." might be clearer if it compared the heterogeneity of THIS study with the homogeneity of other studies. Response: Many thanks for this comment. I agree it is not clear, and I have amended it in the discussion to draw a more clear comparison between the heterogeneity of this study population and the homogeneity of other studies. • In the discussion, other papers that the authors might wish to look at include: • Goshtasbi (https://doi.org/10.1177/01945998211010443) found that the mFI-5 was associated with longer length of stay, medical complications, and mortality. • Strigenz (https://doi.org/10.22603/ssrr.2022-0102) concluded that the mFI-5 was an independent predictor of morbidity, suggesting an increased risk of complication events (increased complications means longer LOS and more risk of admission to ICU). Response: I have included reference in the discussion to the paper by Goshtasbi. I agree that Stigenz’s paper conluded that MFI-5 was a predictor of morbidity but given it didn’t specifically look at ICU admission or length of stay I didn’t include it in the reference list if that’s okay. Reviewer #2: Many thanks for taking the time to review this paper, I hope you will find the responses and subsequent ammendments to the manuscript acceptable. Marc • The sample size (n=100) is underpowered to detect meaningful differences, particularly with only 20 ICU admissions. Repsonse: Thank you for this important comment. A power analysis was conducted prior to study initiation to ensure adequate planning; however, we acknowledge that the final sample size remains modest, particularly in relation to the relatively small number of ICU admissions. We have now addressed this limitation explicitly in the discussion section, and we note that larger sample sizes in future studies may improve the stability and generalizability of predictive estimates. • The analysis relies solely on AUROC without exploring more clinically meaningful cutoffs (e.g., frail vs non-frail), limiting applicability. Response: Thank you for this valuable observation. We chose AUROC as our primary analytic tool because it offers a comprehensive measure of a model’s overall discriminative ability across all possible thresholds. While we recognize that dichotomous classifications (e.g., frail vs. non-frail) may have clinical relevance, our intent was to assess the overall predictive value of these indices which can be generalised across diverse surgical populations. • The heterogeneity of surgical procedures likely masks any predictive signal; no subgroup or sensitivity analyses are provided. Response: We appreciate this comment and agree that procedural heterogeneity may have reduced the predictive signal of frailty indices and the modest sample size constrained our ability to conduct formal subgroup analyses with sufficient power. We have now addressed this in the discussion section pointing out how the heterogeneity of our sample population is an explanation for the lack of predictive value of the scoring systems in this paper compared with other papers which show predictive value of them in much more homogenous populations, such as specific surgeries. • The manuscript does not offer sufficient novel insight beyond prior studies that have shown mixed results for mFI-5 and CCI in specific surgeries. Response: Thank you for this feedback. While we acknowledge prior studies have examined mFI-5 and CCI in specific surgical contexts, our study aimed to assess the feasibility and predictive utility of these indices in a general perioperative clinic setting, where patient populations are diverse and decisions about preoperative optimization must often be made in the absence of procedure-specific data. This broader approach adds practical insight into how frailty tools perform in real-world, mixed-cohort settings. We have revised the discussion adding a short paragraph which better articulate this distinction and to clarify how our findings contribute to the ongoing evaluation of frailty measures in everyday perioperative practice. Reviewer #3 ScreenIT has been reviewed, and suitable ammendments to manuscript have been made. Attachments Attachment Submitted filename: Reviewer PLOS one response.docx https://doi.org/10.1371/journal.pone.0322681.r003
Decision Letter - Pedro Curiati, Editor Evaluating the predictive value of frailty scores for critical care admission and hospital stay in elderly surgical patients: a comparison of the mFI-5 and CCI PONE-D-25-15888R1 Dear Dr. LINCOLN, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Pedro Kallas Curiati, M.D., Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0322681.r004
Formally Accepted
Acceptance Letter - Pedro Curiati, Editor PONE-D-25-15888R1 PLOS ONE Dear Dr. LINCOLN, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Pedro Kallas Curiati Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0322681.r005

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