Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study

Daiki Takekawa; Hideki Endo; Eiji Hashiba; Kazuyoshi Hirota

doi:10.1371/journal.pone.0269737

Peer Review History

Original SubmissionJanuary 18, 2022
30 Mar 2022 Decision Letter - Yu Ru Kou, Editor PONE-D-22-01670Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort studyPLOS ONE Dear Dr. Takekawa, 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. Reviewer #2 was very critical in evaluating your work, while reviewer #1 gave some helpful comments. If you choose to resubmit your work, you need to fully addressed the concerns raised by the reviewers. Please submit your revised manuscript by May 14 2022 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. 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Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: 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: Thank you for giving me good opportunity to read Dr. Takekawa’s excellent paper entitled “Predict model for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study. ”. This author clearly showed the risk factors for prolonged ICU stay in Japan based on JIPAD database, and this result would be very important to consider the contents of intensive care for risk patients, and also re-set up the health insurance service. So I think this paper would be appropriate enough for the publish in the PLOS ONE journal, however, to improve its perfection as a scientific paper, I request the author to add minor revision as following. I’m looking forward to reading revised version shortly. Again, thank you for giving me such a nice opportunity to review such an excellent paper.” Major 1．Table 1 looks so long and contained too many information. I recommend to divide the table 1 appropriately like backgrounds including number, male, age, BMI, kinds of admission, outcome as 1 table, and diagnosis and chronic disease as 1 table, interventions as 1 table, and independent 1 table for about APACHE2, 3, and SAPSII. 2．The author succussed to approve models for predicting prolonged stays in Japanese ICU with appropriate statistical analysis, however there are too many long tables to understand not easy. I recommend two figures to show AUC for predicting prolonged ICU stay and hospital death with each model, if the author will accept and consider looking better. It’s up to the author. Minor 1．Please add more detail explanation about JIPAD like as the number of participated facilities, on line-based input system, and past achievements, in page 4, lines 25 to Page4, line 2. 2．Please add full spell of MV as “mechanical ventilation” in the Page5, line 6. 3．Please re-check the expression of page in each reference of NO. 6 and 18. Reviewer #2: This article entitled　“Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study.” reported by Daiki Takekawa et al. Author analyzed predict model for prolong ICU stay. I agree this retrospective multicenter cohort study showed some new factors regarding to prolonged ICU stay. However, there are so many significant factors to predict the prolonged ICU stay. So, we can not recognize the specific factor to predict the prolonged ICU stay. Major comments 1.First, author should mention about the definition of prolonged ICU stay. Why did you chose 14 days ? Author must show the definition and its reason, not only referring just citations. 2. It is too difficult for clinician to understand usefuleness for this predictive models. After all, which combination of factors is the best for predicting? 3.Author should use more figures for understanding. I think that ROC analysis is suitable for this study. Please show visually ROC analysis by figure. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". 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Revision 1
14 Apr 2022 Author Response April 4, 2022 Submission no: PONE-D-22-01670 Submission title: Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study Dear Academic Editor Yu Ru Kou, PhD Thank you for your letter of March 30 regarding the above manuscript. We are pleased to know that our manuscript will be reconsidered after revision according to your reviewers’ comments. Our responses to the reviewers’ comments are noted below. Reviewer #1: Major Q1. Table 1 looks so long and contained too many information. I recommend to divide the table 1 appropriately like backgrounds including number, male, age, BMI, kinds of admission, outcome as 1 table, and diagnosis and chronic disease as 1 table, interventions as 1 table, and independent 1 table for about APACHE2, 3, and SAPSII. R1. As suggested, we divided the Table 1 to Table 1–4. Q2．The author succussed to approve models for predicting prolonged stays in Japanese ICU with appropriate statistical analysis, however there are too many long tables to understand not easy. I recommend two figures to show AUC for predicting prolonged ICU stay and hospital death with each model, if the author will accept and consider looking better. It’s up to the author. R2. As suggested, we added Fig 3, 4 to show ROC curves for predicting prolonged ICU stay and hospital death with each model. Minor Q1．Please add more detail explanation about JIPAD like as the number of participated facilities, on line-based input system, and past achievements, in page 4, lines 25 to Page4, line 2. R1. As suggested, we added more detail explanation about JIPAD in the materials and methods section (page 4, line 15–21). Detail explanation about JIPAD is below. JIPAD was established by the Japanese Society of Intensive Care Medicine in 2014. 94 ICUs participate in JIPAD as of December 31, 2021. Each participating ICU submits data of their ICU patients, such as characteristics, severity scores at ICU admission, therapies in the ICU and outcomes, using on-line data system. Submitted data are routinely monitored and corrected by members of the JIPAD working group to improve the credibility of data. A recent study developed a mortality prediction model for adult patients admitted to ICU in Japan using JIPAD [13]. Further information about JIPAD can be found elsewhere [12]. 12. Irie H, Okamoto H, Uchino S, Endo H, Uchida M, Kawasaki T, et al.; JIPAD Working Group in the Japanese Society of Intensive Care Medicine. The Japanese Intensive care PAtient Database (JIPAD): A national intensive care unit registry in Japan. J Crit Care. 2020; 55: 86-94. doi: 10.1016/j.jcrc.2019.09.004. 13. Endo H, Uchino S, Hashimoto S, Aoki Y, Hashiba E, Hatakeyama J, Hayakawa K, Ichihara N, Irie H, Kawasaki T, Kumasawa J, Kurosawa H, Nakamura T, Ohbe H, Okamoto H, Shigemitsu H, Tagami T, Takaki S, Takimoto K, Uchida M, Miyata H. Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures. J Intensive Care. 2021; 9(1): 18. doi: 10.1186/s40560-021-00533-z. Q2. Please add full spell of MV as “mechanical ventilation” in the Page5, line 6. R2. We are sorry for this mistake. We added it. Q3. Please re-check the expression of page in each reference of NO. 6 and 18. R3. We are sorry for this mistake. We corrected it. Reviewer #2: Major comments Q1. First, author should mention about the definition of prolonged ICU stay. Why did you chose 14 days ? Author must show the definition and its reason, not only referring just citations. R1. As suggested, we added the reason why we chose this definition in the materials and methods section (page 4, line 26 to page 5, line 3). The reason is below. It is because special fees for critical care are limited to a period of 14 days in the Japanese health insurance system, even if the status of the patient remains serious for more than 14 days. Additionally, previous studies about prolonged ICU stay that conducted in other countries also used this definition [2,14,15]. 2. Arabi Y, Venkatesh S, Haddad S, Al Shimemeri A, Al Malik S. A prospective study of prolonged stay in the intensive care unit: predictors and impact on resource utilization. Int J Qual Health Care. 2002; 14(5): 403-10. doi: 10.1093/intqhc/14.5.403. 14. Laupland KB, Kirkpatrick AW, Kortbeek JB, Zuege DJ. Long-term mortality outcome associated with prolonged admission to the ICU. Chest. 2006; 129(4): 954-9. doi: 10.1378/chest.129.4.954. 15. Zampieri FG, Ladeira JP, Park M, Haib D, Pastore CL, Santoro CM, et al. Admission factors associated with prolonged (>14 days) intensive care unit stay. J Crit Care. 2014; 29(1): 60-5. doi: 10.1016/j.jcrc.2013.09.030. Q2. It is too difficult for clinician to understand usefuleness for this predictive models. After all, which combination of factors is the best for predicting? R2. Thank you for your variable comment. As you pointed out, there are a lot of variables in our models. Thus, we performed backward deletion to reduce variables in a stepwise manner. The results are shown in below table (Model 1–3). However, only “Male” was removed from each model, so our models still contained seven variables. Generally, predict models are not simple. Indeed, although previous studies also developed predict models for prolonged ICU stay, their models contain a lot of variables as well as the present study (2, 16). It is because these studies didn't intend to develop simple predict models but intended to develop accurate predict models as well as our study. Indeed, the AUC values for all our predict models were more than 0.8, which means that the discrimination abilities of these models were good. So, we did not change the table 5. The present models look complicated due to many categories, particularly in diagnosis, but there are only eight variables in these models. It is not so complicated. Model 1 aOR 95% CI P value (Intercept) 0.007 0.006, 0.010 <0.001* APACHE II –10 reference 11–20 3.650 2.910, 4.590 <0.001* 21–30 12.60 9.940, 15.90 <0.001* 31–40 17.90 13.80, 23.00 <0.001* 41+ 9.050 6.500, 12.60 <0.001* BMI (kg/m2) 18.5 ≤, < 25 reference < 18.5 0.953 0.848, 1.070 0.419 25 ≤, < 35 1.140 1.030, 1.270 0.013* 35 ≤ 1.330 0.936, 1.890 0.111 RRT/MET 1.240 1.060, 1.470 <0.001* Postresuscitation 1.330 1.090, 1.610 <0.001* Readmisson 1.290 1.100, 1.500 <0.001* LOS before ICU admission (days) 0 reference 1–7 0.757 0.674, 0.850 <0.001* 8–14 0.970 0.821, 1.150 0.724 15+ 1.280 1.120, 1.470 <0.001* Diagnosis -Post-operative Cardiovascular disease reference Respiratory disease 0.209 0.146, 0.301 <0.001* Digestive disease 0.550 0.466, 0.650 <0.001* Neurological disease 0.675 0.556, 0.820 <0.001* Trauma 1.260 0.879, 1.800 0.208 Metabolic/hematological disease 0.425 0.158, 1.140 0.091 Urinary disease 0.145 0.071, 0.293 <0.001* Muscle/bone/skin disease 0.282 0.185, 0.430 <0.001* Obstetrics/gynecological disease 0.177 0.073, 0.429 <0.001* -Non-operative Cardiovascular disease 0.894 0.755, 1.060 0.200 Respiratory disease 2.080 1.790, 2.410 <0.001* Digestive disease 1.170 0.950, 1.440 0.140 Neurological disease 1.280 1.040, 1.570 0.022* Sepsis 1.020 0.807, 1.280 0.882 Trauma 1.490 1.080, 2.050 0.014* Metabolic disease 0.333 0.214, 0.518 <0.001* Hematological disease 1.133 0.698, 1.820 0.622 Urinary disease 0.779 0.456, 1.330 0.359 Muscle/bone/skin disease 2.030 1.380, 2.980 <0.001* Others 1.260 0.790, 2.010 0.331 Model 2 aOR 95% CI P value (Intercept) 0.005 0.003, 0.006 <0.001* APACHE III score –40 reference 41–80 6.270 4.820, 8.160 <0.001* 81–120 21.20 16.20, 27.80 <0.001* 121–160 28.50 21.30, 38.20 <0.001* 161+ 12.50 8.530, 18.30 <0.001* BMI (kg/m2) 18.5≤, < 25 reference <18.5 0.952 0.847, 1.070 0.410 25 ≤, < 35 1.160 1.040, 1.290 0.006* 35 ≤ 1.370 0.965, 1.950 0.078 RRT/MET 1.250 1.060, 1.480 0.007* Postresuscitation 1.250 1.020, 1.520 0.030* Readmisson 1.240 1.060, 1.440 0.007* LOS before ICU admission (days) 0 reference 1–7 0.774 0.689, 0.869 <0.001* 8–14 0.955 0.808, 1.130 0.593 15+ 1.290 1.130, 1.480 <0.001* Diagnosis -Post-operative Cardiovascular disease reference Respiratory disease 0.231 0.161, 0.332 <0.001* Digestive disease 0.513 0.434, 0.607 <0.001* Neurological disease 0.846 0.695, 1.030 0.095 Trauma 1.470 1.020, 2.100 0.004* Metabolic/hematological disease 0.511 0.189, 1.380 0.185 Urinary disease 0.156 0.078, 0.316 <0.001* Muscle/bone/skin disease 0.285 0.187, 0.435 <0.001* Obstetrics/gynecological disease 0.193 0.080, 0.468 <0.001* -Non-operative Cardiovascular disease 0.969 0.817, 1.150 0.717 Respiratory disease 2.270 1.950, 2.630 <0.001* Digestive disease 1.200 0.972, 1.480 0.091 Neurological disease 1.430 1.160, 1.760 <0.001* Sepsis 1.050 0.835, 1.330 0.663 Trauma 1.710 1.250, 2.360 <0.001* Metabolic disease 0.360 0.232, 0.560 <0.001* Hematological disease 1.210 0.749, 1.960 0.434 Urinary disease 0.817 0.478, 1.400 0.459 Muscle/bone/skin disease 2.080 1.410, 3.060 <0.001* Others 1.450 0.906, 2.310 0.122 Model 3 aOR 95% CI P value (Intercept) 0.004 0.003, 0.005 <0.001* SAPS II score –25 reference 26–50 7.590 6.200, 9.300 <0.001* 51–75 22.60 18.30, 28.00 <0.001* 76–100 21.30 16.60, 27.30 <0.001* 101+ 6.830 4.090, 11.40 <0.001* BMI (kg/m2) 18.5 ≤, < 25 reference < 18.5 0.963 0.856, 1.080 0.523 25 ≤, < 35 1.150 1,030, 1.270 0.001* 35 ≤ 1.370 0.965, 1.960 0.078 RRT/MET 1.220 1.030, 1.430 0.019* Postresuscitation 1.360 1.120, 1.660 0.002* Readmisson 1.200 1.030, 1.400 0.020* LOS before ICU admission (days) 0 reference 1–7 0.905 0.807, 1.010 0.086 8–14 1.120 0.945, 1.320 0.194 15+ 1.520 1.320, 1.740 <0.001* Diagnosis -Post-operative Cardiovascular disease reference Respiratory disease 0.298 0.207, 0.429 <0.001* Digestive disease 0.575 0.486, 0.680 <0.001* Neurological disease 0.862 0.707, 1.050 0.141 Trauma 1.270 0.885, 1.810 0.197 Metabolic/hematological disease 0.591 0.218, 1.600 0.300 Urinary disease 0.223 0.110, 0.450 <0.001* Muscle/bone/skin disease 0.351 0.230, 0.537 <0.001* Obstetrics/gynecological disease 0.267 0.110, 0.647 <0.001* -Non-operative Cardiovascular disease 0.915 0.774, 1.080 0.301 Respiratory disease 2.330 2.010, 2.700 <0.001* Digestive disease 1.300 1.050, 1.590 0.014* Neurological disease 1.340 1.090, 1.650 0.006* Sepsis 1.150 0.913, 1.450 0.236 Trauma 1.620 1.180, 2.230 0.003* Metabolic disease 0.384 0.247, 0.597 <0.001* Hematological disease 1.300 0.802, 2.100 0.289 Urinary disease 0.946 0.554, 1.620 0.840 Muscle/bone/skin disease 2.400 1.630, 3.540 <0.001* Others 1.540 0.966, 2.450 0.069 2. Arabi Y, Venkatesh S, Haddad S, Al Shimemeri A, Al Malik S. A prospective study of prolonged stay in the intensive care unit: predictors and impact on resource utilization. Int J Qual Health Care. 2002; 14(5): 403-10. doi: 10.1093/intqhc/14.5.403. 16. Kramer AA, Zimmerman JE. A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay. BMC Med Inform Decis Mak. 2010; 10: 27. doi: 10.1186/1472-6947-10-27. Q3. Author should use more figures for understanding. I think that ROC analysis is suitable for this study. Please show visually ROC analysis by figure. R3. As suggested (reviewer 1 also suggested), we added Fig 3, 4 to show ROC curves for predicting prolonged ICU stay and hospital death with each model. We thank the reviewers for their comments and hope that this paper is now suitable for publication in PLOS ONE. Sincerely yours, Daiki Takekawa, M.D, PhD. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0269737.r002
27 May 2022 Decision Letter - Yu Ru Kou, Editor Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study PONE-D-22-01670R1 Dear Dr. Takekawa, 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 for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, 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, Yu Ru Kou, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 6. 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: Thank you for the prompt reply for revising your excellent paper. The second version was fully revised appropriately, especially, additional figure and revised tables looks excellent, so I think now this paper would be good enough to be published in PLOS ONE journal. Finally, thank you for giving me good opportunity to review your paper. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No https://doi.org/10.1371/journal.pone.0269737.r003
Formally Accepted
31 May 2022 Acceptance Letter - Yu Ru Kou, Editor PONE-D-22-01670R1 Predict models for prolonged ICU stay using APACHE II, APACHE III and SAPS II scores: A Japanese multicenter retrospective cohort study Dear Dr. Takekawa: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. 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 plosone@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. Yu Ru Kou Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0269737.r004

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