P < 0.001), coronary artery disease , and hemodialysis compared with pre-emptive kidney transplantation  were the risk factors for early TRM. Older age , coronary artery disease , and hemodialysis  were the common independent risk factors for TRM. In contrast, cardiac arrhythmia  was associated only with early TRM, and fungal infection , and epoch of transplantation  were the factors associated with only TRM. The identified risk factors should be considered in patient counselling, selection, and management to prevent TRM.Mortality at an early stage after kidney transplantation is a catastrophic event. Treatment-related mortality (TRM) within 1 or 3 months after kidney transplantation has been seldom reported. We designed a retrospective observational cohort study using a national population-based database, which included information about all kidney recipients between 2003 and 2016. A total of 16,073 patients who underwent kidney transplantation were included. The mortality rates 1 month (early TRM) and 3 months (TRM) after transplantation were 0.5% (n = 74) and 1.0% (n = 160), respectively. Based on a multivariate analysis, older age (hazard ratio [HR] = 1.06;  After kidney transplantation, patients with end-stage renal disease (ESRD) had better survival, improved cognition, and less economic burden than those who continued with dialysis –3. KidneInvestigation of treatment-related mortality (TRM), which is a concept different from disease-related mortality, is important for improved survival after treatment. It provides information about factors that require intensive care and medical decisions during critical period ,6. In caThe present study was based on the use of a comprehensive database, which is operated by the National Health Insurance (NHI) of the Korean government. This database contains all the records of healthcare utilization among inpatients and outpatients particularly kidney recipients who were enrolled in the Rare Intractable Disease (RID) system and who received additional medical financial support. The registration is confirmed by a certified physician based on the RID criteria, which reflect international guidelines. Therefore, the use of this database was suitable for the investigation of TRM among kidney recipients.Using this database, we performed a comprehensive population-based analysis to investigate the risk factors and causes of TRM after kidney transplantation. It would facilitate pre- and post-transplantation assessment and management, which contributed to the improvement of the survival of kidney recipients.This was a retrospective and observational cohort study that used prospectively registered national data sets for reimbursement purposes. All patients who underwent kidney transplantation procedures  at any Korean medical center from January 2003 to December 2016 were included. We defined death within 1 and 3 months after kidney transplantation as early TRM and TRM, respectively. We investigated the risk factors related to early TRM and TRM and the causes of death.This study was approved by the independent institutional review board of Kosin University Gospel Hospital (KUGH 2017-12-009) and was conducted in accordance with the Declaration of Helsinki. Moreover, the need for informed consent was waived because anonymity of personal information was maintained.The study included all patients who have been listed for kidney transplantation from January 2003 to December 2016 in the Health Insurance Review and Assessment Service (HIRA). The patients were registered in the HIRA database after kidney transplantation, as defined by the ICD-10-CM code Z94.0. During this period, 18,822 patients were enrolled in the database. We excluded 2,726 patients who did not have complete demographic information and 59 patients who concurrently underwent other organ transplantations. The final cohort consisted of 16,037 patients. The records of medical visits, demographic characteristics, and death status were collected from the HIRA database for all kidney recipients.We collected the following demographic data and baseline characteristics of kidney recipients from the HIRA database: age, sex, medical comorbidities focusing on cardiac and cerebrovascular diseases reported to be important causes of early mortality , dialysiThe data used in this study were obtained from the HIRA database, which is based on the NHI system operated by the Korean government. Healthcare institutions submit the medical data of all inpatients and outpatients in electronic format to the HIRA for reimbursement purposes. The claims data integrated by HIRA include all healthcare utilization information on inpatients and outpatients. Data about the demographic characteristics of the patients, principal diagnosis, comorbidities, prescription history, and performed procedures based on ICD-10-CM codes are included in this database. In this study, we obtained all data about kidney recipients from the RID program of the HIRA database registered between January 2003 and the end of December 2016. The Korean government assigned kidney transplantation to the RID system for reducing the payments of the patients. The diagnosis must be reviewed by the corresponding healthcare institution before submission to the NHI. Therefore, the data registered in the RID registry are verified and reliable.The data for dialysis vintage, and donor state omitting in HIRA database were obtained from another database operated by the Korean Network for Organ Sharing system. In this database, the records of recipients who underwent kidney transplantation in 40 medical centers around the country were registered.We evaluated the TRM, risk factors, and causes of death of kidney recipients in Korea from 2003 to 2016. Descriptive statistics were used for patient characteristics correlated to early TRM and TRM. Comparisons of nominal and continuous variables between groups were assessed using chi-square test and Mann–Whitney U test, respectively. The median and inter-quartile range were used for non-normally distributed variables. Multivariate Cox proportional-hazards regression models adjusting age, sex, cardiac and cerebrovascular diseases, hemodialysis, infection, and epoch of transplantation were used to examine the variables correlated to TRM.P values less than 0.05 were considered statistically significant.Statistical analyses were performed using the R statistical software  and SAS statistical analysis software . The two-tailed A total of 16,073 patients who underwent kidney transplantation between 2003 and 2016 were included in our study cohort. The baseline characteristics of these patients are presented in P < 0.001). The number of patients with a history of cardiac disease, including coronary artery disease (CAD) (P < 0.001) and cardiac arrhythmia (P = 0.002), was significantly higher in the TRM groups than in the non-TRM groups. The recipients with TRM more frequently had undergone hemodialysis . Patients with anti-thymocyte globulin showed significant relation to TRM (P < 0.001), whereas those with basiliximab did not. CMV and fungal infections (P < 0.001) and the epoch of transplantation (P < 0.001), were associated with TRM at 3 months post-transplantation only.Of the 16,073 patients, 74 (0.5%) and 160 (1.0%) died within 1 and 3 months after kidney transplantation, respectively. The overall cumulative incidence of mortality is shown in P < 0.001), CAD , cardiac arrhythmia , and hemodialysis compared to pre-emptive kidney transplant  were independently associated with early TRM. Moreover, older age , CAD , and hemodialysis  were consistently independent risk factors of TRM at any time. However, fungal infection, , and the epoch of transplantation  were correlated to TRM only. Regarding to the epoch of transplantation, the aged between 50 and 59 years , the patients receiving basiliximab as induction therapy , and recipients with CMV infection  presented better outcome in 2010–2016, when compared to 2003–2009.The risk factors of early TRM and TRM are shown in Tables P < 0.001) and TRM . The effects of CAD and hemodialysis on cumulative incidences are shown in The effect of age on cumulative incidence of mortality is presented in In the present study, a comprehensive analysis of 1- and 3-month mortality after kidney transplantation in Korea was conducted. Older age, CAD, cardiac arrhythmia, and hemodialysis were risk factors for early TRM. For TRM, older age, CAD, and hemodialysis were common independent risk factors observed in both early TRM and TRM. In contrast, cardiac arrhythmia is a risk factor that associated with early TRM only. Fungal infection and the epoch of transplantation were factors associated with TRM only.Cardiovascular disease has been a well-known risk factor and cause of short- and long-term mortality after kidney transplantation ,24. MortPatients without previous hemodialysis showed more favorable outcomes based on our study, despite of discrepancies in preemptive kidney transplantation suggested in previous reports ,34. DialThe use of anti-thymocyte globulin has been greater in high-risk recipients such as highly sensitized patients, recipients from deceased donors, re-transplantations, and ABO incompatible transplants . AccordiFungal infections were not common (about 5%)  and usuaP < 0.001) for both early TRM and TRM. The significant association between old age and poor outcome was persistently reported in previous studies Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. 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: Partly**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes**********3. Have the authors made all data underlying the findings in their manuscript fully available?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.The Reviewer #1: 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**********5. Review Comments to the AuthorPlease 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. Reviewer #1: In this paper submitted by Jeong et al, an investigation about the risk factors causes of TRM after kidney transplantation, focusing on vascular diseases was presented.The paper is written in a correct and fluent English, and statistical analyses are correctly described and presented by the authors.Nevertheless, the paper presents several limitations, apart the retrospective design, which make oit unsuitable for the publication in this form. First of all, several important data are missing and in my opinion crucial for the aim of the study: dialysis vintage, prevalence of deceased/living donor (if not considered explain why), basic nephropathy, and steroid therapy before therapy, donor characteristics. All those factors might impact also on the global results of the study that at the moment does not add any novel knowledge on the problem.In addition many topics need a better clarification and explanation: definition of CMD disease, prevalence of CMV serum-negativity. The cause of death classification is absolutely unreasonable, - “chronic kidney disease was the main cause of both early TRM and TRM, followed cystic kidney disease” ??????**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  3 May 20201. Thank you for providing the following Data Availability Statement:https://nhiss.nhis.or.kr/bd/ay/bdaya001iv.do."The repository data for public release is not available because of the personally dentifiable information. The full dataset includes clinic centers in which they attend, insurance conditions. Therefore, concerning privacy risks, the data is managed by authorized executive supervisor. If one researcher asks to access data, the person in charge releases data with blind identification for the discrete requirements and the data should be analyzed only in permitted rooms in centers of National Health Insurance Service. Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article . Contact information for a data access committee is listed as follows: National Health Insurance Sharing Service, Tel: 82-33-736-2432; Official internet site: Before we proceed, please confirm the following:1) Please give the full name of the organization that has imposed the data restictions .� We submitted the security memorandum and pledge to the Institutional Review Board of National Health Insurance Sharing Service when we access these data. The original files of security memorandum and pledge have been uploaded for this revision. The translated contents include “Any data obtained from National Health Insurance Sharing Service will not be taken out externally or used for any other purpose. I pledge to take any civil and criminal penalties.”. Your kind consideration for this security situation would be greatly appreciated. We have inserted additional explanation in to the revised Data Availability Statement  as follows. “If one researcher asks to access data, the researcher should submit the security memorandum and pledge to the Institutional Review Board of National Health Insurance Sharing Service. After approval, the person in charge releases data with blind identification for the discrete requirements and the data should be analyzed only in permitted rooms in centers of National Health Insurance Service.”2) Please confirm that others would be able to access these data in the same manner as the authors. Please also confirm that the authors did not have any special access privileges that others would not have.� We confirmed that others could access these data in the same manner as the authors and the authors did not have any special access privileges. We also have added these statement to the revised Data Availability Statement  as follows.“The other researchers could access these data in the same manner as the authors and the authors did not have any special access privileges.”https://journals.plos.org/plosone/s/data-availability#loc-minimal-data-set-definition3) Please confirm that the data that researchers can access fits our definition of "minimal data set" as outlined here: � We have provided maximally permitted data for meeting the requirements of “minimal data set”. Although entire data sets of kidney recipients were not permitted, the anonymisable data for recipients with treatment-related mortality focused on this manuscript and used for tables and graphs were provided in S1 Table.Journal requirements: http://www.plosone.org/attachments/PLOSOne_formatting_sample_main_body.pdf and http://www.plosone.org/attachments/PLOSOne_formatting_sample_title_authors_affiliations.pdf1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at � We have checked the PLOS ONE style templates and corrected the location of References section. The revised References section has been listed after the main text, before the supporting information. The file naming also checked and corrected.http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.2. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see In your revised cover letter, please address the following prompts:a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail  and who has imposed them . Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see We will update your Data Availability statement on your behalf to reflect the information you provide.� We provided the minimal data set, which had anonymisable information in S1 Table. Therefore, we have corrected the sentence from “Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article  and are available from the corresponding author upon reasonable request.” to “Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article .” in the revised Data accessibility statement section . Because National Health Insurance Sharing Service restricts to share full dataset concerning privacy risks, minimal anonymized data set focusing on recipients with treatment-related mortality after kidney transplantation was provided. Contact information for a data access committee and the way for obtaining the data were described in the Data accessibility statement section. We have added these statement to the revised cover letter.Response to the reviewer’s comments1. Is the manuscript technically sound, and do the data support the conclusions?Reviewer #1: Partly� We have corrected and checked that the revised manuscript described a technically sound piece of scientific research and that the data supported the conclusions. We also responded to the reviewer #1’s comments sincerely.2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes� We have checked that the statistical analysis has been conducted appropriately and rigorously.3. Have the authors made all data underlying the findings in their manuscript fully available?Reviewer #1: Yes� According to the journal requirements, we provided the minimal data set focusing on recipients with treatment-related mortality after kidney transplantation. Contact information for a data access committee and the way for obtaining the data were described in the Data accessibility statement section. We have added these statement to the revised cover letter.“We collected the following demographic data and baseline characteristics of kidney recipients from the HIRA database: age, sex, medical comorbidities focusing on cardiac and cerebrovascular diseases reported to be important causes of early mortality [16], dialysis status, cytomegalovirus (CMV) and fungal infection, and year of transplantation (S1 Table).”S1 Table. Data set of recipients with TRM after kidney transplantation.4. Is the manuscript presented in an intelligible fashion and written in standard English?Reviewer #1: Yes� We used manuscript editing service before submission.5. Review Comments to the AuthorPlease 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. Response to reviewer #1’s commentsComment 1: In this paper submitted by Jeong et al, an investigation about the risk factors causes of TRM after kidney transplantation, focusing on vascular diseases was presented.The paper is written in a correct and fluent English, and statistical analyses are correctly described and presented by the authors.Nevertheless, the paper presents several limitations, apart the retrospective design, which make oit unsuitable for the publication in this form. First of all, several important data are missing and in my opinion crucial for the aim of the study: dialysis vintage, prevalence of deceased/living donor (if not considered explain why), basic nephropathy, and steroid therapy before therapy, donor characteristics. All those factors might impact also on the global results of the study that at the moment does not add any novel knowledge on the problem.� Response 1: As indicated by reviewer, we have provided available information in the revised manuscript. Dialysis vintage: We have requested additional data from another database operated by the Korean Network for Organ Sharing system in order to analyze dialysis vintage. In this database, the records of recipients who underwent kidney transplantation in 40 medical centers around the country have been registered. We have provided the results of dialysis vintage, time from dialysis to transplantation, in the revised Tables 1-3 as follows. The source of data was also described in revised Materials and Methods section as follows.ResultsTable 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.Characteristicsa Early TRM TRM Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valuebNumber (%) 15,999 74 　 15,913 160 　Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.00150–59 4,830 (30.2) 32 (43.2) 　 4,792 (30.1) 70 (43.8) 　60–69 1,838 (11.5) 18 (24.3) 　 1,819 (11.4) 37 (23.1) 　70–79 143 (0.9) 5 (6.8) 　 139 (0.9) 9 (5.6) 　Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684 Cause of ESRD Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485Underlying diseasec 　 　 　 　 　 　 Cardiac disease 　 　 　 　 　 　 Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001 Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014  Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002  Cerebrovascular disease 　 　 　 　 　 　 Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460  Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763 Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001 Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000Infection 　 　 　 　 　 　 CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001 Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001Epoch of transplantation 　 　 　 　 　 　 2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001 2010–2016 11,365 (71.0) 47 (63.5) 　 11,319 (71.1) 93 (58.1) 　a Data were expressed as number (%) or median (interquartile range).b P value was calculated using chi-square test or Mann–Whitney U test.c In case of the presence of underlying diseases, multiple diseases were designated to one patient.d Data were obtained from the Korean Network for Organ Sharing system.e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.10) < 0.001 1.07 (1.05-1.10) < 0.001 < 50 Reference 　 　 　 50–59 3.21 (1.82-5.66) < 0.001 　 　 60–69 4.74 (2.49-9.03) < 0.001 　 　 70–79 16.66 (6.22-44.62) < 0.001 　 　Sex, male 0.98 (0.62-1.56) 0.944 　 　Cause of ESRD  Diabetes mellitus 1.22 (0.89-1.75) 0.451  Hypertension 0.80 (0.58-1.12) 0.672  Glomerulonephritis 0.93 (0.52-2.15) 0.591  Cystic kidney disease 1.19 (0.78-2.32) 0.854 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 5.51 (2.74-11.06) < 0.001 2.81 (1.37-5.78) 0.005  Acute myocardial infarction 1.51 (0.37-6.15) 0.566 　 　 Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.99 (1.09-3.64) 0.025  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.87 (0.12-6.26) 0.890 　 　Hemodialysis 3.00 (1.21-7.45) 0.018 2.58 (1.04-6.42) 0.041 Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086 Before steroid used 0.55 (0.17-1.74) 0.307 Infection 　 　 　 　 CMV infection 1.26 (0.46-3.45) 0.652 　 　 Fungal infection 0.66 (0.16-2.71) 0.569 　 　Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168 　 　a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.09) < 0.001 1.08 (1.06-1.09) < 0.001 < 50 　 　 　 　 50–59 3.05 (2.09-4.44) < 0.001 　 　 60–69 4.24 (2.74-6.57) < 0.001 　 　 70–79 13.16 (6.43-26.96) < 0.001 　 　Sex, female 1.07 (0.78-1.46) 0.690 　 　Cause of ESRD  Diabetes mellitus 1.25 (0.92-1.59) 0.273  Hypertension 0.86 (0.68-1.10) 0.463  Glomerulonephritis 0.91 (0.49-1.75) 0.385  Cystic kidney disease 1.23 (0.87-2.41) 0.526 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.53 (1.49-4.31) 0.001  Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.70 (0.78-3.69) 0.183  Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.43 (0.91-2.24) 0.117  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.80 (0.20-3.23) 0.755 　 　Hemodialysis 2.69 (1.49-4.85) 0.001 2.32 (1.28-4.19) 0.005 Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179 Before steroid used 0.95 (0.52-1.76) 0.882 Infection 　 　 　 　 CMV infection 2.19 (1.51-3.16) < 0.001 1.65 (1.12-2.42) 0.012  Fungal infection 3.57 (2.47-5.15) < 0.001 2.48 (1.69-3.65) < 0.001Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.43 (0.31-0.60) < 0.001a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.Materials and Methods section The data for dialysis vintage, and donor state omitting in HIRA database were obtained from another database operated by the Korean Network for Organ Sharing system. In this database, the records of recipients who underwent kidney transplantation in 40 medical centers around the country were registered.Prevalence of deceased/living donor (if not considered explain why):We have also requested data of donor state from the Korean Network for Organ Sharing system since donor information was not included in the Health Insurance Review and Assessment Service (HIRA). The results of living, deceased, and non-heart beating donors are presented in the revised Results section as follows. These variables did not insert into the Tables because the direct combination of data was not available for the multivariate analyses.ResultsCharacteristics of patients “Most patients received kidney from living donor (62.2%), followed by deceased (37.5%) and non-heart beating (0.3%) donors.”Treatment-related mortality “The rates of recipients who died 1 month  and 3 months  after transplantation showed significant difference according to the donor state (P < 0.001).”Discussion “Donor status has been a well-known important factor for short- and long-term mortality after kidney transplantation . According to previous studies, kidney allograft recipients that died within the first year after transplantation were more likely to be recipients of deceased donor kidneys . It was difficult to compare TRM of our cohort with those of other countries directly because of lack of available data. More intensive care for recipients from deceased donors at early point after transplantation is recommended.”Basic nephropathy: We have added the results of basic nephropathy including diabetes mellitus, hypertension, glomerulonephritis, and cystic kidney disease to the revised Tables 1-3 as follows. Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.Characteristicsa Early TRM TRM Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valuebNumber (%) 15,999 74 　 15,913 160 　Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.00150–59 4,830 (30.2) 32 (43.2) 　 4,792 (30.1) 70 (43.8) 　60–69 1,838 (11.5) 18 (24.3) 　 1,819 (11.4) 37 (23.1) 　70–79 143 (0.9) 5 (6.8) 　 139 (0.9) 9 (5.6) 　Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684 Cause of ESRD Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485Underlying diseasec 　 　 　 　 　 　 Cardiac disease 　 　 　 　 　 　 Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001 Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014  Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002  Cerebrovascular disease 　 　 　 　 　 　 Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460  Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763 Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001 Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000Infection 　 　 　 　 　 　 CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001 Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001Epoch of transplantation 　 　 　 　 　 　 2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001 2010–2016 11,365 (71.0) 47 (63.5) 　 11,319 (71.1) 93 (58.1) 　a Data were expressed as number (%) or median (interquartile range).b P value was calculated using chi-square test or Mann–Whitney U test.c In case of the presence of underlying diseases, multiple diseases were designated to one patient.d Data were obtained from the Korean Network for Organ Sharing system.e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.10) < 0.001 1.07 (1.05-1.10) < 0.001 < 50 Reference 　 　 　 50–59 3.21 (1.82-5.66) < 0.001 　 　 60–69 4.74 (2.49-9.03) < 0.001 　 　 70–79 16.66 (6.22-44.62) < 0.001 　 　Sex, male 0.98 (0.62-1.56) 0.944 　 　Cause of ESRD  Diabetes mellitus 1.22 (0.89-1.75) 0.451  Hypertension 0.80 (0.58-1.12) 0.672  Glomerulonephritis 0.93 (0.52-2.15) 0.591  Cystic kidney disease 1.19 (0.78-2.32) 0.854 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 5.51 (2.74-11.06) < 0.001 2.81 (1.37-5.78) 0.005  Acute myocardial infarction 1.51 (0.37-6.15) 0.566 　 　 Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.99 (1.09-3.64) 0.025  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.87 (0.12-6.26) 0.890 　 　Hemodialysis 3.00 (1.21-7.45) 0.018 2.58 (1.04-6.42) 0.041 Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086 Before steroid used 0.55 (0.17-1.74) 0.307 Infection 　 　 　 　 CMV infection 1.26 (0.46-3.45) 0.652 　 　 Fungal infection 0.66 (0.16-2.71) 0.569 　 　Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168 　 　a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.09) < 0.001 1.08 (1.06-1.09) < 0.001 < 50 　 　 　 　 50–59 3.05 (2.09-4.44) < 0.001 　 　 60–69 4.24 (2.74-6.57) < 0.001 　 　 70–79 13.16 (6.43-26.96) < 0.001 　 　Sex, female 1.07 (0.78-1.46) 0.690 　 　Cause of ESRD  Diabetes mellitus 1.25 (0.92-1.59) 0.273  Hypertension 0.86 (0.68-1.10) 0.463  Glomerulonephritis 0.91 (0.49-1.75) 0.385  Cystic kidney disease 1.23 (0.87-2.41) 0.526 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.53 (1.49-4.31) 0.001  Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.70 (0.78-3.69) 0.183  Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.43 (0.91-2.24) 0.117  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.80 (0.20-3.23) 0.755 　 　Hemodialysis 2.69 (1.49-4.85) 0.001 2.32 (1.28-4.19) 0.005 Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179 Before steroid used 0.95 (0.52-1.76) 0.882 Infection 　 　 　 　 CMV infection 2.19 (1.51-3.16) < 0.001 1.65 (1.12-2.42) 0.012  Fungal infection 3.57 (2.47-5.15) < 0.001 2.48 (1.69-3.65) < 0.001Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.43 (0.31-0.60) < 0.001a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.Steroid therapy before therapy:We have inserted the results of steroid therapy before transplantation into the revised Tables 1-3 as follows. The recipients with the use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation were designated and described in the revised footnotes of Tables.Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.Characteristicsa Early TRM TRM Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valuebNumber (%) 15,999 74 　 15,913 160 　Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.00150–59 4,830 (30.2) 32 (43.2) 　 4,792 (30.1) 70 (43.8) 　60–69 1,838 (11.5) 18 (24.3) 　 1,819 (11.4) 37 (23.1) 　70–79 143 (0.9) 5 (6.8) 　 139 (0.9) 9 (5.6) 　Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684 Cause of ESRD Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485Underlying diseasec 　 　 　 　 　 　 Cardiac disease 　 　 　 　 　 　 Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001 Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014  Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002  Cerebrovascular disease 　 　 　 　 　 　 Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460  Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763 Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001 Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000Infection 　 　 　 　 　 　 CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001 Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001Epoch of transplantation 　 　 　 　 　 　 2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001 2010–2016 11,365 (71.0) 47 (63.5) 　 11,319 (71.1) 93 (58.1) 　a Data were expressed as number (%) or median (interquartile range).b P value was calculated using chi-square test or Mann–Whitney U test.c In case of the presence of underlying diseases, multiple diseases were designated to one patient.d Data were obtained from the Korean Network for Organ Sharing system.e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.10) < 0.001 1.07 (1.05-1.10) < 0.001 < 50 Reference 　 　 　 50–59 3.21 (1.82-5.66) < 0.001 　 　 60–69 4.74 (2.49-9.03) < 0.001 　 　 70–79 16.66 (6.22-44.62) < 0.001 　 　Sex, male 0.98 (0.62-1.56) 0.944 　 　Cause of ESRD  Diabetes mellitus 1.22 (0.89-1.75) 0.451  Hypertension 0.80 (0.58-1.12) 0.672  Glomerulonephritis 0.93 (0.52-2.15) 0.591  Cystic kidney disease 1.19 (0.78-2.32) 0.854 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 5.51 (2.74-11.06) < 0.001 2.81 (1.37-5.78) 0.005  Acute myocardial infarction 1.51 (0.37-6.15) 0.566 　 　 Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.99 (1.09-3.64) 0.025  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.87 (0.12-6.26) 0.890 　 　Hemodialysis 3.00 (1.21-7.45) 0.018 2.58 (1.04-6.42) 0.041 Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086 Before steroid used 0.55 (0.17-1.74) 0.307 Infection 　 　 　 　 CMV infection 1.26 (0.46-3.45) 0.652 　 　 Fungal infection 0.66 (0.16-2.71) 0.569 　 　Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168 　 　a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.09) < 0.001 1.08 (1.06-1.09) < 0.001 < 50 　 　 　 　 50–59 3.05 (2.09-4.44) < 0.001 　 　 60–69 4.24 (2.74-6.57) < 0.001 　 　 70–79 13.16 (6.43-26.96) < 0.001 　 　Sex, female 1.07 (0.78-1.46) 0.690 　 　Cause of ESRD  Diabetes mellitus 1.25 (0.92-1.59) 0.273  Hypertension 0.86 (0.68-1.10) 0.463  Glomerulonephritis 0.91 (0.49-1.75) 0.385  Cystic kidney disease 1.23 (0.87-2.41) 0.526 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.53 (1.49-4.31) 0.001  Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.70 (0.78-3.69) 0.183  Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.43 (0.91-2.24) 0.117  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.80 (0.20-3.23) 0.755 　 　Hemodialysis 2.69 (1.49-4.85) 0.001 2.32 (1.28-4.19) 0.005 Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179 Before steroid used 0.95 (0.52-1.76) 0.882 Infection 　 　 　 　 CMV infection 2.19 (1.51-3.16) < 0.001 1.65 (1.12-2.42) 0.012  Fungal infection 3.57 (2.47-5.15) < 0.001 2.48 (1.69-3.65) < 0.001Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.43 (0.31-0.60) < 0.001a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.Donor characteristics:Unfortunately, the donor characteristics were not provided by National Health Insurance Sharing Service. We have described this limitation in the revised Discussion section  as follows. “This study had several limitations. The lack of detailed clinical information, such as donor’s characteristics and laboratory data , led to restrictions on the analysis of wider variables for TRM.”Comment 2: In addition many topics need a better clarification and explanation: definition of CMD disease, prevalence of CMV serum-negativity. The cause of death classification is absolutely unreasonable, - “chronic kidney disease was the main cause of both early TRM and TRM, followed cystic kidney disease” ??????� Response 2: We have added explanation for the definition of CMV disease to the revised Materials Methods section  as follows. “The ICD-10-CM codes for CMV disease were B27.1, B25.0, B25.1, B25.8, and B25.9.”The prevalence of CMV serum-negativity could not be provided because laboratory values for CMV infection were not included in the datasets provided by National Health Insurance Sharing Service. We have described this limitation in the revised Discussion section  as follows. “This study had several limitations. The lack of detailed clinical information, such as donor’s characteristics and laboratory data , led to restrictions on the analysis of wider variables for TRM.”We have eliminated the contents for the cause of death throughout the revised manuscript .https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, � We have uploaded our figure files  to the PACE digital diagnostic tool to meet PLOS requirements. The preview files  were generated and checked.AttachmentResponse to Reviewers.docSubmitted filename: Click here for additional data file. 25 May 2020PONE-D-20-03919R1The risk factors associated with treatment-related mortality in 16,073 kidney transplantation - A nationwide cohort studyPLOS ONEDear Dr. Jeong,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. 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Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. 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 addressedReviewer #2: 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: (No Response)Reviewer #2: Yes**********3. 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At the moment the paper is suitable for publication.Reviewer #2: Treatment-related mortality (TRM) after renal transplantation is a concept different from disease-related mortality and appeared to be a very prevalent entity.This article would be a valuable contribution to the medical literature to encourage further discussion on this entity.The writing is clear and easily understandable.The Authors have worked hard to improve this article, and they have met all criticisms raised by refereesStrengths:- There are scarce data in scientific literature about TRM within 1 or 3 months after kidney transplantation.- Authors collected an important amount of data from a very large cohort of patients using a national population based database, which included information about a total of 16,073 kidney recipients.Specific comments:- Abstract. Authors should clearly explain the following sentence: “Based on a multivariate analysis, older age , coronary artery disease , and hemodialysis  were the risk factors for early TRM.” What do you mean with hemodialysis as a risk factor for early TRM? Patients who underwent to hemodialysis immediately after renal transplant for a DGF, o hemodialysis compared with peritoneal dialysis or pre-emptive renal transplant? This is not clear.- Introduction, page 4, line 16. Supporting references at the end of the following sentence are needed: “however, studies about 1- or 3-month mortality were extremely limited.”- Introduction, page 5, line 2. Authors should clearly explain the following sentence: “… to investigate the risk factors and causes of TRM after kidney transplantation focusing on vascular diseases.” Are Authors focused on vascular diseases in this analysis?- Methods. Authors collected data of the post-transplant administration of antiviral agent, but there is no mention to induction (basiliximab vs thymoglobuline) immunosuppressive therapy, that is supposed to strongly impact on treatment related mortality. This is an important point that Authors should add into the analysis. Otherwise this will represent an important limitation.- Results. A sub-analysis might be performed distinguishing TRM analysis between transplantation cases performed in different epoch (2003-2009 vs 2010-2016). This might be interesting even if this factor did not reach statistical significance at univariate analysis. In fact, “Epoch of transplantation 2010–2016” showed a trend towards statistical significance.- Results. In the following sentence, Authors should specify the number of recipients who died among the total number of recipients for each type of transplantation, and only after the percentage value in parentheses: “The rates of recipients who died 1 month  and 3 months  after transplantation showed significant differenceaccording to the donor state (P < 0.001).”**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  23 Jun 2020Response to the reviewer’s commentsResponse to reviewer #1’s comments1. I thank the authors to have addressed all my recommendations. At the moment the paper is suitable for publication.� We thank the reviewer for the constructive review of our manuscript. Response to reviewer #2’s commentsTreatment-related mortality (TRM) after renal transplantation is a concept different from disease-related mortality and appeared to be a very prevalent entity.This article would be a valuable contribution to the medical literature to encourage further discussion on this entity.The writing is clear and easily understandable.The Authors have worked hard to improve this article, and they have met all criticisms raised by refereesStrengths:- There are scarce data in scientific literature about TRM within 1 or 3 months after kidney transplantation.- Authors collected an important amount of data from a very large cohort of patients using a national population based database, which included information about a total of 16,073 kidney recipients.Specific comments:1. Abstract. Authors should clearly explain the following sentence: “Based on a multivariate analysis, older age , coronary artery disease , and hemodialysis  were the risk factors for early TRM.” What do you mean with hemodialysis as a risk factor for early TRM? Patients who underwent to hemodialysis immediately after renal transplant for a DGF, o hemodialysis compared with peritoneal dialysis or pre-emptive renal transplant? This is not clear.� We have provided detailed description of hemodialysis in the revised Abstract section as follows for clarification. In addition, we have also inserted this description into the revised Results section as follows.Abstract section “Based on a multivariate analysis, older age , coronary artery disease , and hemodialysis compared with pre-emptive kidney transplantation  were the risk factors for early TRM.”Results section “Based on the Cox multivariate analysis, older age , CAD , cardiac arrhythmia , and hemodialysis compared to pre-emptive kidney transplant  were independently associated with early TRM.”2. Introduction, page 4, line 16. Supporting references at the end of the following sentence are needed: “however, studies about 1- or 3-month mortality were extremely limited.”� To the best of our knowledge, mortality after kidney transplantation within 1- or 3- months has been seldom reported. There was one report comparing mortality risk between deceased-donor kidney allograft recipients and wait-listed transplant candidates from time of listing published in 1993. Relative risk of mortality within the first 30 days, days 31-365 and more than 365-days post transplantation were 2.43, 0.96 and 0.36, respectively. Another report recently published was dealt with 30-day mortality and compared mostly the ethnic difference of England, and New York State. We have cited these two articles at the end of the sentence in the revised Introduction section as follows. These articles have been presented in the revised Reference section as follows.Introducton section “Most reports have shown the results of kidney transplantation after 1 [18], 5 [16], and greater than 10 years [19]; however, studies about 1- or 3-month mortality were extremely limited .”Reference section “20. Port FK, Wolfe RA, Mauger EA, Berling DP, Jiang K. Comparison of survival probabilities for dialysis patients vs cadaveric renal transplant recipients. JAMA. 1993;270: 1339-1343.21. Tahir S, Gillott H, Jackson-Spence F, Nath J, Mytton J, Evison F, et al. Do outcomes after kidney transplantation differ for black patients in England versus New York State? A comparative, population-cohort analysis. BMJ Open. 2017;7: e014069.”3. Introduction, page 5, line 2. Authors should clearly explain the following sentence: “… to investigate the risk factors and causes of TRM after kidney transplantation focusing on vascular diseases.” Are Authors focused on vascular diseases in this analysis?� As indicated by the reviewer, various risk factors related to treatment-related mortality (TRM) were identified in our manuscript. Therefore, we have eliminated “focusing on vascular diseases” in the revised Introduction section  as follows.“Using this database, we performed a comprehensive population-based analysis to investigate the risk factors and causes of TRM after kidney transplantation.”4. Methods. Authors collected data of the post-transplant administration of antiviral agent, but there is no mention to induction (basiliximab vs thymoglobuline) immunosuppressive therapy, that is supposed to strongly impact on treatment related mortality. This is an important point that Authors should add into the analysis. Otherwise this will represent an important limitation.� As suggested by the reviewer, we have extracted the information about induction regimens and provided the results, and discussion in the revised manuscript. Because the recipients receiving anti-thymocyte globulin were significantly associated with 1- and 3-month mortalities in the multivariate analyses, the results of other variables such as age, coronary artery disease, cardiac arrhythmia, and hemodialysis in the early TRM, and age, coronary artery disease, acute myocardial infarction, cardiac arrhythmia, hemodialysis, and cytomegalovirus and fungal infections in TRM were also revised throughout the manuscript. In particular, the contents for CMV infection related to TRM including Fig 2B were eliminated because the P value was changed from 0.012 to 0.106 in the revised manuscript.Abstract section “Based on a multivariate analysis, older age , coronary artery disease , and hemodialysis compared with pre-emptive kidney transplantation  were the risk factors for early TRM. Older age , coronary artery disease , and hemodialysis  were the common independent risk factors for TRM. In contrast, cardiac arrhythmia  was associated only with early TRM, and fungal infection , and epoch of transplantation  were the factors associated with only TRM.”Materials and Methods section “The induction regimens such as basiliximab, and anti-thymocyte globulin were also extracted.”Results section “Regarding to induction therapy, basiliximab, and anti-thymocyte globulin were administered to 79.0%, and 11.4% of recipients, respectively.”Results section “Patients with anti-thymocyte globulin showed significant relation to TRM (P < 0.001), whereas those with basiliximab did not.”Results section “The risk factors of early TRM and TRM are shown in Tables 2 and 3, respectively. Based on the Cox multivariate analysis, older age , CAD , cardiac arrhythmia , and hemodialysis compared to pre-emptive kidney transplant  were independently associated with early TRM. Moreover, older age , CAD , and hemodialysis  were consistently independent risk factors of TRM at any time. However, fungal infection, , and the epoch of transplantation  were correlated to TRM only.”Results section “Fungal infection  affected TRM (after early TRM). The protective effect of transplantation in 2010–2016 is illustrated in Fig 2C.”Discussion section “The use of anti-thymocyte globulin has been greater in high-risk recipients such as highly sensitized patients, recipients from deceased donors, re-transplantations, and ABO incompatible transplants [36]. According to a prospective, randomized study, patients receiving anti-thymocyte globulin presented a greater incidence of infection (85.8%) compared to those with basiliximab (75.2%) at 12 months after transplantation [37]. However, there was no significant difference in patient survival, similar to the results of a recent study using a network meta-analysis [38]. In Korea, the one-year patient survival in the anti-thymocyte globulin group (89.4%) was compared to the basiliximab group (93.8%), and presented no significant difference [39]. Based on our data, the high-risk recipients receiving anti-thymocyte globulin were significantly associated with early mortality. Further studies for the premature mortality are necessary to validate our results, and intensive care for the high-risk patients receiving anti-thymocyte globulin is important for improving outcomes.”Figure Fig 2. Cumulative incidence of mortality according to the factors associated 1- or 3-month mortality after kidney transplantation. (A) Cardiac arrhythmia was related to a worse outcome 1 month after transplantation. (B) Fungal infection were a risk factor of 3-month mortality after transplantation. (C) Recent epoch of transplantation (2010–2016) was a protective factor of 3-month mortality compared to the treatment-related mortality of previous epoch (2003–2009). Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.Characteristicsa Early TRM TRM Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valuebNumber (%) 15,999 74 　 15,913 160 　Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.00150–59 4,830 (30.2) 32 (43.2) 　 4,792 (30.1) 70 (43.8) 　60–69 1,838 (11.5) 18 (24.3) 　 1,819 (11.4) 37 (23.1) 　70–79 143 (0.9) 5 (6.8) 　 139 (0.9) 9 (5.6) 　Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684 Cause of ESRD Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485Underlying diseasec 　 　 　 　 　 　 Cardiac disease 　 　 　 　 　 　 Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001 Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014  Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002  Cerebrovascular disease 　 　 　 　 　 　 Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460  Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763 Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001 Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000Induction therapy Basiliximab 12,637 (79.0) 55 (74.3) 0.402 12,569 (79.0) 123 (76.9) 0.579Anti-thymocyte globulin 1,818 (11.4) 22 (29.7) < 0.001 1,799 (11.3) 41 (25.6) < 0.001Infection 　 　 　 　 　 　 CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001 Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001Epoch of transplantation 　 　 　 　 　 　 2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001 2010–2016 11,365 (71.0) 47 (63.5) 　 11,319 (71.1) 93 (58.1) 　a Data were expressed as number (%) or median (interquartile range).b P value was calculated using chi-square test or Mann–Whitney U test.c In case of the presence of underlying diseases, multiple diseases were designated to one patient.d Data were obtained from the Korean Network for Organ Sharing system.e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.10) < 0.001 1.06 (1.04-1.09) < 0.001 < 50 Reference 　 　 　 50–59 3.21 (1.82-5.66) < 0.001 　 　 60–69 4.74 (2.49-9.03) < 0.001 　 　 70–79 16.66 (6.22-44.62) < 0.001 　 　Sex, male 0.98 (0.62-1.56) 0.944 　 　Cause of ESRD  Diabetes mellitus 1.22 (0.89-1.75) 0.451  Hypertension 0.80 (0.58-1.12) 0.672  Glomerulonephritis 0.93 (0.52-2.15) 0.591  Cystic kidney disease 1.19 (0.78-2.32) 0.854 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 5.51 (2.74-11.06) < 0.001 3.02 (1.48-6.17) 0.002  Acute myocardial infarction 1.51 (0.37-6.15) 0.566 　 　 Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.98 (1.08-3.62) 0.027  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.87 (0.12-6.26) 0.890 　 　Hemodialysis 3.00 (1.21-7.45) 0.018 2.53 (1.02-6.28) 0.046 Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086 Before steroid used 0.55 (0.17-1.74) 0.307 Induction therapy Basiliximab 0.77 (0.46-1.30) 0.326 Anti-thymocyte globulin 3.31 (2.01-5.45) < 0.001 2.62 (1.59-4.32) < 0.001Infection 　 　 　 　 CMV infection 1.26 (0.46-3.45) 0.652 　 　 Fungal infection 0.66 (0.16-2.71) 0.569 　 　Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168 　 　a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.Variable Univariate Multivariate HR (95% CI) P-value HR (95% CI) P-valueAge, yearsa 1.07 (1.05–1.09) < 0.001 1.07 (1.05-1.09) < 0.001 < 50 　 　 　 　 50–59 3.05 (2.09-4.44) < 0.001 　 　 60–69 4.24 (2.74-6.57) < 0.001 　 　 70–79 13.16 (6.43-26.96) < 0.001 　 　Sex, female 1.07 (0.78-1.46) 0.690 　 　Cause of ESRD  Diabetes mellitus 1.25 (0.92-1.59) 0.273  Hypertension 0.86 (0.68-1.10) 0.463  Glomerulonephritis 0.91 (0.49-1.75) 0.385  Cystic kidney disease 1.23 (0.87-2.41) 0.526 Underlying disease 　 　 　 　 Cardiac disease 　 　 　 　 Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.88 (1.71-4.84) < 0.001  Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.75 (0.81-3.80) 0.157  Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.40 (0.89-2.18) 0.145  Cerebrovascular disease 　 　 　 　 Cerebral hemorrhage NA 　 　 　 Cerebral infarction 0.80 (0.20-3.23) 0.755 　 　Hemodialysis 2.69 (1.49-4.85) 0.001 2.35 (1.30-4.25) 0.004 Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179 Before steroid used 0.95 (0.52-1.76) 0.882 Induction therapy Basiliximab 0.88 (0.61-1.28) 0.514 Anti-thymocyte globulin 2.73 (1.92-3.90) < 0.001 2.38 (1.62-3.49) < 0.001Infection 　 　 　 　 CMV infection 2.19 (1.51-3.16) < 0.001 1.39 (0.93-2.08) 0.106  Fungal infection 3.57 (2.47-5.15) < 0.001 2.61 (1.79-3.82) < 0.001Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.34 (0.24-0.48) < 0.001a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.c Data were obtained from the Korean Network for Organ Sharing system.d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.5. Results. A sub-analysis might be performed distinguishing TRM analysis between transplantation cases performed in different epoch (2003-2009 vs 2010-2016). This might be interesting even if this factor did not reach statistical significance at univariate analysis. In fact, “Epoch of transplantation 2010–2016” showed a trend towards statistical significance.� We have conducted the sub-analysis for the two epoch of transplantation and added the results to the revised Results and Discussion sections as follows. Results section “Regarding to the epoch of transplantation, the aged between 50 and 59 years , the patients receiving basiliximab as induction therapy , and recipients with CMV infection  presented better outcome in 2010-2016, when compared to 2003-2009.”Discussion section “In particular, relatively low- or intermediate-risk patients such as aged 50 to 59 years, and patients receiving basiliximab were influence by the improved protocols, and showed better outcome than high-risk recipients . Further, more aggressive and sophisticated infection controls on CMV such as monitoring quantitative levels, and high dose of antiviral therapy [47] may protect more recipients in 2010-2016 than those in 2003-2009.”6. Results. In the following sentence, Authors should specify the number of recipients who died among the total number of recipients for each type of transplantation, and only after the percentage value in parentheses: “The rates of recipients who died 1 month  and 3 months  after transplantation showed significant difference according to the donor state (P < 0.001).”� We have applied these results to our cohort and presented the number of recipients in the revised Results section  as follows. The calculation errors were also corrected.“The rates of recipients who died 1 month  and 3 months  after transplantation showed significant difference according to the donor state (P < 0.001).”Response to the editor’s commenthttps://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. 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The preview files  were generated and checked.AttachmentResponse to Reviewers.docSubmitted filename: Click here for additional data file. 6 Jul 2020The risk factors associated with treatment-related mortality in 16,073 kidney transplantation - A nationwide cohort studyPONE-D-20-03919R2Dear Dr. Jeong,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.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. 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At the moment thepaper is suitable for publicationReviewer #2: Treatment-related mortality (TRM) after renal transplantation is a concept different from disease-related mortality and appeared to be a very prevalent entity.Strengths:- There are scarce data in scientific literature about TRM within 1 or 3 months after kidney transplantation.- Authors collected an important amount of data from a very large cohort of patients using a national population based database, which included information about a total of 16,073 kidney recipients.This article would be a valuable contribution to the medical literature to encourage further discussion on this entity.The writing is clear and easily understandable.The Authors have worked hard to improve this article, and they have met all criticisms raised by referees.I feel the manuscript is now suitable for publication in Plos One.**********what does this mean?). If published, this will include your full peer review and any attached files.7. 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Uremic toxins (UTs) generally accumulate in patients developing end-stage renal disease (ESRD). Although some kinds of UTs cause early death after starting hemodialysis (HD), it remains unknown whether the degree of excessive accumulation of various UTs is associated with worsening of prognosis. We retrospectively conducted this cohort study consisting of adult patients developing ESRD who initiated HD at the National Center for Global Health and Medicine from 2010 to 2019. We created a new uremic score, which was defined as the aggregate score of the following variables reflecting uremic state: elevated blood urea nitrogen, β2-microglobulin, and anion gap before starting HD. The primary outcome was early mortality within 1-year after HD commencement. The hazard ratio (HR) and 95% confidence interval (CI) for a one-point increase in uremic score was calculated with Cox proportional hazard models adjusted by baseline conditions. We included 230 participants, 16 of whom experienced the primary outcome of early mortality after HD commencement. Uremic score was significantly associated with the primary outcome . Our novel uremic score, reflecting accumulation of specific UTs, more precisely predicts early mortality after HD commencement. One of the main roles of the kidney is to excrete harmful metabolites and toxins produced by various metabolic activities in the body ,2. AlthoMany UTs have been newly identified using integrative metabolomic and proteomic approaches in the past few years . HoweverIn the present study, we focused on β2-microglobulin (β2MG) and anion gap (AG) along with BUN, as easily measurable biomarkers reflecting the uremic state in patients with pre-dialysis ESRD in clinical practice. β2MG, which is a well-known representative marker of smaller mid-size UTs in patients undergoing maintenance dialysis, has recently been rediscovered as a novel filtration marker predicting CKD progression and mortality . AdditioIn the present study, to evaluate uremic state multilaterally using a composite indicator, we assessed the patients’ uremic score, which was defined as the aggregate score of three variables related to uremia: elevated BUN, β2MG, and AG before starting HD. We evaluated whether uremic score was related to 1-year mortality after HD commencement in adult ESRD patients. Furthermore, we unraveled the characteristics of patients with elevated BUN, β2MG, and AG.Kaplan-Meier analysis indicated that patients with higher uremic scores had a lower survival rate . EvaluatIn multivariate logistic regression analysis, all variables related to uremia were strongly associated with hyperphosphatemia . ElevateIn the present study, we found that uremic score, defined as the aggregate score of three variables reflecting the uremic state, i.e., elevated BUN, β2MG, and AG before HD commencement, was related to 1-year mortality after HD commencement in adult ESRD patients. Moreover, elevated BUN mainly correlated with cardiovascular problems, including blood pressure and comorbid cardiovascular diseases, elevated β2MG levels mainly correlated with malnutrition and inflammation in patients with more advanced impairment of residual kidney function, and elevated AG mainly correlated with inflammation unaccompanied by malnutrition.UTs are defined as many different substances that accumulate in the body with CKD progression, and which adversely affect biological functions . ExcessiBUN is the first UT to be identified and can be easily removed by dialysis, although the toxicity of BUN remains unclear. It is thought that uremic syndrome is related to the effects of other UTs, but not to BUN per se. On the other hand, BUN has more recently been found to directly increase reactive oxygen species and oxidative stress, leading to various types of tissue damage . It has β2MG, which is a well-known surrogate for smaller mid-size UTs, consists of non-variable light chains from the major histocompatibility complex (MHC) class I, and has recently been able to be efficiently removed from the blood due to advances in dialysis technology . It has AG is a simple indicator calculated by measuring anions and cations that is easily corrected by dialysis but is not a direct indicator reflecting the accumulation of UTs. However, an increase in AG is proven to be exacerbated by retention of unmeasured anionic UTs related to progression of uremia, and is related to 1-year mortality after HD commencement, particularly in the elderly . While tIn this study, we focused on β2MG and AG rather than BUN, as easily measurable indicators reflecting the uremic state in patients with ESRD in clinical practice that are corrected by commencement of dialysis. In fact, it is easy and useful to evaluate these three indicators in the clinical setting, compared with many other UTs, which can only be measured in the laboratory. However, it might be possible that there are other critical toxins that are not evaluated by using only these three indicators. Therefore, further research is needed to clarify the characteristics of each UT and establish a practical evaluation method assessing the accumulation of harmful UTs.This study has some limitations. First, this study was conducted in a single-center. Therefore, the results, in this study, need to be validated by further studies conducted in multi-center. Second, confounding factors might have influenced variables reflecting the uremic state before starting HD, as the present study was an observational study. Third, this study likely had insufficient power because of the small sample size. Fourth, the measurement methods of serum bicarbonate level are not unified. In this study, the serum bicarbonate level was measured by blood gas analysis using either arterial, venous, or mixed venous blood. Fifth, AG is influenced by various factors such as serum protein concentration and the methodology used for measuring ion activities ,22. SincIn conclusion, the novel uremic score defined as the aggregate score of each of the three indicators related to uremia: BUN, β2MG, and AG before HD commencement is related to 1-year mortality after HD commencement. While many indicators reflecting the accumulation of UTs in patients with ESRD have recently been identified as predictors of poor prognosis, each indicator has different individual characteristics. It is thus necessary to evaluate the uremic state multilaterally using composite indicators before starting HD.The protocol of this study was approved by the ethical review board of the National Center for Global Health and Medicine (NCGM) ,23. The 2 in spite of sufficient optimal conservative treatment. However, the decision of starting hemodialysis should be determined based on a comprehensive assessment of renal failure symptoms, daily life activities, and nutritional status, which are not relievable without hemodialysis”.All patients who had complete data on BUN, AG, and β2MG, and started HD for ESRD at the NCGM from 2010 to 2019 were included in this study. Among them, participants with missing follow-up data, use of peritoneal dialysis, or comorbid unhealed cancer were excluded. Participants were followed up for a year after HD commencement or until the time of death, whichever came earlier. In addition, we decided the timing of HD commencement according to the section of “Hemodialysis Initiation for Maintenance Hemodialysis” in the Japanese Society for Dialysis Therapy Clinical Guideline . The guiThe primary outcome of this study was 1-year mortality after HD commencement. To evaluate this primary outcome, the following data were extracted from medical records: demographic information including body mass index (BMI), clinical status, blood pressure, laboratory analyses, medications, and comorbidities. Values of the most recent laboratory data for the following items were recorded: BUN, AG, β2MG, eGFR, hemoglobin level, and serum levels of albumin, phosphate, and CRP. In this study, eGFR was evaluated by the estimation formula according to the Japanese Society of Nephrology . In this2) and clinical status; Model 2, Model 1 and laboratory data ; Model 3, Model 2 and comorbidities and medications. Moreover, we used logistic regression to unravel the characteristics of patients with elevated BUN, AG, or β2MG levels. Multivariate analysis was conducted using covariates that demonstrated a p-value of <0.05 in univariate analysis. We used SPSS software, version 25  for statistical analyses. In this study, statistically significance was determined by two-sided p-values < 0.05.We divided patients into four groups based on their uremic scores. Baseline conditions of this cohort were demonstrated as mean ± standard deviation (SD) for continuous variables, and frequency and percentage for categorical variables. We compared the incidence of death within a year after HD commencement between these four groups using the Kaplan-Meier surviving curves and the log-rank test. The HR and 95% CI for a one-point increase in uremic score was calculated using Cox proportional hazard models. Adjusted HR was calculated by multivariate analyses using baseline covariates as following: Model 1, demographic data (age ≥ 75 years, sex, BMI < 20 kg/m


Cardiopulmonary exercise testing (CPET) is of great interest and utility for clinicians dealing Pulmonary Hypertension (PH) in several ways, including: helping with differential diagnosis, evaluating exercise intolerance and its underpinning mechanisms, accurately assessing exertional dyspnea and unmasking its underlying often non-straightforward mechanisms, generating prognostic indicators. Pathophysiologic anomalies in PH can range from reduced cardiac output and aerobic capacity, to inefficient ventilation, dyspnea, dynamic hyperinflation, and locomotor muscle dysfunction. CPET can magnify the PH-related pathophysiologic anomalies and has a major role in the management of PH patients. Pulmonary arterial hypertension (PAH) is characterized by anomalies in pulmonary arteries  which results in cardiovascular anomalies such as increase in pulmonary vascular resistance (PVR) and finally right ventricular failure . PAH mayCardiopulmonary exercise testing (CPET) is of great interest and utility for clinicians dealing PH in evaluating exercise intolerance and its underpinning mechanisms, accurately assessing exertional dyspnea and unmasking its underlying mechanisms, which are often not straightforward. Previous studies have shown that PAH management at an early stage of the disease translates into better outcomes . TherefoCPET can magnify the PH-related pathophysiologic anomalies and has a major role in the management of PH patients. Pathophysiologic anomalies in PH can widely range from reduced cardiac output and aerobic capacity, to pulmonary gas exchange and ventilatory efficiency anomalies, dyspnea, dynamic hyperinflation and locomotor muscle dysfunction .Pulmonary vascular obstruction along with concurrent increased mean PAP and PVR and reduced pulmonary capillary bed and recruitment give rise to three different pathophysiologic anomalies: (1) ventilation/perfusion (V/Q) inequalities; (2) pulmonary gas exchange anomalies; (3) increased right ventricle (RV) afterload and concomitant reduced left ventricle (LV) filling. These three major pathophysiologic derangements are responsible of characteristic anomalies observed during CPET that can ultimately explain exertional dyspnea and exercise intolerance .E) of poorly perfused air spaces (2), high dead space to tidal volume fraction (VD/VT) and widening of the alveolar-arterial pressure difference of oxygen [P(A-a)O2] and of the arterial-end-tidal pressure difference of carbon dioxide [P(a-ET)CO2]. These anomalies can stimulate an excessive V’E response to exercise along with altered chemosensitivity and inefficient ventilation mirrored by the increased steepness with which V’E rises with respect to CO2 production (V’CO2)   and hypocapnia   or high V/Q ratios caused by increased minute ventilation (V’r spaces  V/Q mism2 slope) . Ineffic, PaCO2) .2 with enlargement of P(A-a)O2 during CPET.The reduced pulmonary capillary bed and recruitment at rest can be amplified during CPET and translated in pulmonary gas exchange anomalies such as a relative low alveolar-capillary diffusing capacity; this can be mirrored by a reduced diffusing capacity or transfer factor of the lung for carbon monoxide (DLCO or TLCO) at rest and a reduced PaO2), which results in reduced aerobic capacity with attendant reduced anaerobic threshold (AT) and oxygen consumption (V’O2). Reduced oxygen delivery also causes early onset of lactic acidosis and increased V’CO2, which further contributes to the excessive V’E response to CPET  along with peripheral muscle dysfunction and deconditioning  result i to CPET . The redT) expansion and dynamic lung hyperinflation can also play a crucial role into the genesis of exertional dyspnea and therefore exercise intolerance  has the advantage of being an effort independent measure of exercise tolerance , or plateau (early or late during exercise) of the oxygen pulse , or an abnormal HR/V’O2 slope (>50) may be typical CO2 which fails to became negative during exercise and, sometimes, a P(A-a)O2 which widens on exertion (E/V’CO2 at AT (≥34–35) and low PETCO2 at AT (≤30 mmHg) without an alternative explanation in patients presenting with unexplained dyspnea and exercise limitation should prompt further diagnostic testing to exclude PAH or CTEPH  and reduced resting PaCO2 (hypocapnia) are frequent in pulmonary vascular disease such as PAH, chronic thromboembolic pulmonary hypertension (CTEPH) and pulmonary veno-occlusive disease (PVOD)  value between the AT and respiratory compensation point where PETCO2 is constant and, therefore, is supposed to truly reflect the real PaCO2 set-point  had worse cardiac function and more severe gas exchange anomalies during CPET   and corre (PVOD) . Abnormas in PAH . Howeveret-point . The evaet-point . Recentling CPET . High chexercise . Taken tE to MVV , other indicators of ventilatory limitation to exercise can be appreciated: constraints on dynamic VT expansion relative to resting or dynamic decrease in inspiratory capacity (IC) used also to appreciate a critical reduction in inspiratory reserve volume (IRV)  . More reme (IRV)  and some disease . Figure Exertional dyspnea is most frequent and cumbersome symptom in patients with idiopathic PAH, CTEPH, and PVOD .Although researchers have worked hard to try to explain this symptom, its underpinning mechanisms remain at present not completely understood . PreviouT expansion and attainment of a critical IRV in at least 60% of these patients (75%) where VT occurs; this predisposes to dynamic decrease in IC and limitation of VT expansion with concomitant attainment of a critical IRV in some of these PAH and CTEPH patients, as it may occur in some patients with asthma , we can say that some features are the development of EFL and dynamic lung hyperinflation  with concurrent limitation of Vpatients . Of courpatients , even inpatients ; what ish asthma , 2013a, h asthma  and chroh asthma . The senh asthma , as is th asthma , 2013a, h asthma .T expansion nor attainment of a critical IRV during CPET . The occurrence of fatigue or the overt presence of weakness of inspiratory muscle in PAH patients have been questioned by two studies from E in PAH , (2) sniE in PAH  and (3) E in PAH , 2015. TE in PAH , 2015 anE in PAH .2 >15 mL.min–1.kg–1 or > 65% predicted and a V’E/V’CO2 slope of <36  and PVR >16 Wood units had a particularly dismal prognosis, while patients with peak V’O2 ≥ 46.3% predicted and a PVR < 11.6 Wood units had >90% 5-year survival. Echocardiographic assessment of RV function in combination with CPET may provide incremental prognostic utility. Badagliacca and colleagues found that RV fractional area change on echocardiogram, in conjunction with the O2 pulse from CPET, which reflect RV function and stroke volume, were independent predictors of outcome in patients with idiopathic PAH  is of great interest and utility for clinicians dealing with Pulmonary Hypertension (PH) in several ways such as: helping orienting diagnosis, evaluating exercise intolerance and its underpinning mechanisms, accurately assessing exertional dyspnea and unmasking its underlying often non straightforward mechanisms, generating prognostic indicators. Pathophysiologic anomalies in PH can range from reduced cardiac output and aerobic capacity, to inefficient ventilation, dyspnea, dynamic hyperinflation and locomotor muscle dysfunction. CPET can magnify the PH-related pathophysiologic anomalies and has a major role in the management of PH patients.PL and JW equally contributed to the writing and revision of the manuscript. Both authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.