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. 2020 Feb 26;15(2):e0229531. doi: 10.1371/journal.pone.0229531

Frailty predicts surgical complications after kidney transplantation. A propensity score matched study

Milena dos Santos Mantovani 1, Nyara Coelho de Carvalho 1, Thomáz Eduardo Archangelo 1, Luis Gustavo Modelli de Andrade 2, Sebastião Pires Ferreira Filho 3, Ricardo de Souza Cavalcante 3, Paulo Roberto Kawano 4, Silvia Justina Papini 5, Nara Aline Costa 1, Ricardo Augusto Monteiro de Barros Almeida 3,*
Editor: Frank JMF Dor6
PMCID: PMC7043931  PMID: 32102091

Abstract

Background and objective

Surgical complications after kidney transplantation can lead to catastrophic outcomes. Frailty has been associated with important kidney transplantation outcomes; however, there are no studies assessing this measure of physiological reserve as a specific predictor of surgical complications in this population. Such an assessment was, therefore, the objective of the present study.

Methods

A total of 87 individuals aged ≥ 18 years who underwent kidney transplantation between March 2017 and March 2018 were included. At the time of admission for kidney transplantation, demographic, clinical, and kidney transplantation data were collected, and the frailty score was calculated according to Fried et al., which comprises five components: shrinking, weakness, exhaustion, low activity, and slowed walking speed. Urological, vascular, and general surgical complications were assessed three months later, or until graft loss or death. The propensity score was used to achieve a better homogeneity of the sample, and new analyses were performed in this new, balanced sample.

Results

Of the 87 individuals included, 30 (34.5%) had surgical complications. After propensity score matching, the risk of surgical complications was significantly higher among the frail individuals (RR 2.14; 95% CI 1.01–4.54; p = 0.035); specifically, the risk of noninfectious surgical complications was significantly higher among these individuals (RR 2.50; 95% CI 1.11–5.62; p = 0.017).

Conclusion

The results showed that individuals with some degree of frailty before kidney transplantation were more subject to surgical complications. The calculation of the frailty score for transplant candidates and the implementations of measures to increase the physiological reserve of these patients at the time of kidney transplantation may possibly reduce the occurrence of surgical complications.

Introduction

Despite advances in surgical techniques and the use of new technologies, kidney transplantation (KTx) is still associated with various clinical and surgical complications due to the high complexity of this procedure [1–3]. Although the overall incidence of surgical complications is relatively low in KTx, especially when compared to other organs such as the liver or pancreas, they are usually present in approximately 2.5–15% of cases and, if not diagnosed and treated properly, can lead to catastrophic outcomes [3–5].

Although several classifications have been proposed, surgical complications can typically be divided into urological and vascular complications. The most common urological complications, usually present in up to 15% of patients, are urinary leak, ureteral obstruction/stricture, lithiasis, and vesicoureteral reflux, whose treatments will depend on the time of onset and severity of the condition, among other variables [4,6,7]. In turn, vascular complications, observed in 3 to 15% of cases, tend to have less favorable outcomes. With the exception of lymphocele and renal artery stenosis, pseudoaneurysms and vascular thromboses (of either the renal artery or vein) typically progress to graft loss, regardless of the diagnosis and/or applied treatment [8–10]. Other complications of KTx can be classified as general complications, and these involve mainly surgical wound dehiscence/infection [3,4].

The identification of predictors of outcomes in the kidney-transplanted population is essential, aiming to more adequately guide the inclusion and maintenance of patients on the waiting list and to enable the most adequate control of these predictor factors before KTx. However, most models studied have little effectiveness in predicting the most relevant outcomes of KTx [11,12].

Frailty is a measure of physiological reserve, initially validated for the geriatric population [13]. Although the frailty score has not been formally validated for patients with end-stage renal disease (ESRD) and for kidney-transplanted patients, it has been shown to be applicable to these populations. These patients appear to share many pathogenic mechanisms of frailty, such as a pro-inflammatory state, with an exacerbated production of inflammatory cytokines, and dysregulation of the immune, neuroendocrine, and neuromuscular systems, resulting in accelerated ageing [12,14–16]. Frailty is considered highly prevalent in patients at any stage of chronic kidney disease (CKD) and may reach up to two-thirds in ESRD cases [17]. The use of the frailty score has progressively increased in the ESRD and transplant population. A recent systematic review [18] evaluating the use of the frailty score in the population of patients with CKD found that 72% of the studies used the Fried et al. score [13].

Frailty has been studied as a predictor of KTx outcomes. To date, frailty has been shown to be an independent risk factor for delayed graft function [12], post-transplant delirium [19], longer initial length of hospital stay [20], early hospital readmission [21], adverse effects from immunosuppressive drugs [22], and death [23]. Importantly, the studies that have been conducted thus far are limited to only one transplant center in the United States.

Studies have shown an association between frailty and general postoperative complications related to KTx [24] and to other types of surgery [25–29], but to the best of our knowledge, no studies have evaluated frailty as a specific predictor of surgical complications after KTx.

The relevance of surgical complications, the need to identify their predictive factors, and the need for scientific evidence regarding the efficacy of frailty as a good predictor of KTx outcomes justified the present study.

Materials and methods

Study design

A prospective and longitudinal study was conducted that included 87 KTx recipients whose transplants were performed by the Kidney Transplant Program of Botucatu Medical School Clinics Hospital, located in the city of Botucatu, São Paulo, Brazil. Botucatu Medical School Clinics Hospital is a tertiary-level care, education and research center with 417 beds, covering approximately 75 municipalities and 2 million people. Annually, approximately 140 KTx procedures are performed in this center, with 80% of these using deceased donors.

The study included individuals aged ≥ 18 years who underwent KTx between March 2017 and March 2018. Individuals undergoing transplantation of other organs along with the kidney were excluded. Individuals with amputations or other physical conditions that prevented the walk test or the handgrip strength test and the patients with significant cognitive impairment who were unable to understand and respond to the frailty score questionnaires were also excluded from the study.

All participants were evaluated at admission (M0) and at three months after the KTx procedure, or until graft loss or death (M1). At time M0, demographic, clinical, and KTx data were collected, including age, sex, race/ethnicity, etiology of chronic kidney disease, comorbidities, body mass index (BMI), cardiovascular risk, type of dialysis and time on dialysis, number of previous kidney transplants, type of donor, donor data, compatibility and immunological risk, cold ischemia time, and immunosuppressive regimens, and the frailty score was calculated according to Fried et al. [13], as described below. Data related to surgical complication outcomes were collected at time M1.

The data above were collected from electronic medical records and from interviews with the patients.

Surgical protocol, prophylaxis against surgical site infections, and prevention of vascular complications of KTx

The surgical protocol, prophylaxis against surgical site infections, and the vascular complication prevention regimen used by the KTx unit are described in detail in the (S1 Appendix).

Frailty

The frailty score used was based on Fried et al. [13], and was validated for the Brazilian population [30,31]. The score is divided into five components: shrinking (self-report of unintentional weight loss ≥ 10 lb in the previous year and/or BMI < 18.5 kg/m2); weakness (using a hand-held dynamometer, considering sex and BMI); feeling of exhaustion (self-reported); slow walking speed (time taken to walk 15 ft, considering height and sex); and low weekly physical activity, considering the patient’s sex. Fried et al. [13] score was calculated considering only the dry weight loss. More detailed descriptions of the five components of the frailty score can be found in the (S2 Appendix).

The frailty score is calculated by summing the scores of the components, with each component corresponding to one point, where 1 corresponds to the presence of the component and 0 corresponds to its absence. A score of 0 to 1 indicates the absence of frailty, 2 indicates intermediate frailty, and 3 to 5 indicate frailty.

Statistical analysis

Sample size was estimated based on the study of Araújo et al. [32]. We assumed a frequency of surgical complications of 45% in the frail group and 15% in the non-frail group. Considering a power of 0.80, and alpha of 0.05, we calculated a minimum sample size of 68 patients [33].

Univariate analysis was performed using the variables of the recipient and donor, grouped by the presence of frailty. Frailty was divided into two categories: non-frail and frail (the latter grouping intermediate frailty and frailty). The t-test was used for the parametric continuous variables, and the Mann-Whitney test was used for the nonparametric variables. For the categorical variables, the chi-squared test or Fisher’s exact test were used, as appropriate.

The propensity score was used to achieve a better homogeneity of the sample. The variables related to the presence or absence of surgical complications were used to calculate the propensity score using the logistic regression method. The variables selected for this score were age, sex, presence of diabetes, time on dialysis before KTx, cardiovascular risk, BMI classification, panel reactive antibodies, type of donor, expanded criteria donor, and cold ischemia time. After calculating the propensity score, the group selection (matching) method used was the k-nearest neighbor (KNN) method, with a caliper width of 0.2. A visual analysis of the normal quantile-quantile (QQ) plots was performed to confirm that the groups were adequately balanced. The statistical analyses were performed on ‘before matching’ and ‘after matching’. The analyses after matching were performed using the balanced sample.

All analyses were performed using R (R Foundation for Statistical Computing, Vienna, Austria) version 3.4.2 with the MatchIt package to match and package pwr to sample size (S3 and S4 Appendices).

We considered statistical significance p value < 0.05. All analyses considered two-tailed hypothesis test.

Ethics in research

The present study was approved by the Research Ethics Committee of Botucatu Medical School (protocol number 1.782.708).

Results

Study population

A total of 131 KTx procedures were performed between March 2017 and March 2018 at the Botucatu Medical School Clinics Hospital. Of these, 87 (66.4%) patients were included in the study. The reasons for not including the other 44 patients are shown in Fig 1. The non-inclusion of patients due to logistical difficulties occurred mainly due to communication difficulties between transplant and research teams at the time of admission for kidney transplantation.

Fig 1. Patient disposition.

Fig 1

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Baseline characteristics

Table 1 shows the general characteristics of the 87 patients included in the study and of the deceased donors, with a group of 32 (36.8%) individuals considered frail [frail (n = 14; 16.1%) or with intermediate frailty (n = 18; 20.7%)] and a group of 55 (63.2%) non-frail individuals, before and after matching.

Table 1. Patient and donor characteristics.

Before matching After matching
Patient characteristics Non-frail (n = 55) Frail (n = 32) P Non-frail (n = 32) Frail (n = 32) P
Age, mean (SD), y 44 (12) 46 (13) 0.5191 48 (12) 46 (13) 0.5351
Male (%) 67.3 43.8 0.0322 56.2 43.8 0.3172
Caucasian (%) 47.3 59.4 0.2762 43.8 59.4 0.2112
Cause of ESRD (%)
 Diabetes mellitus 9.1 12.5 0.9042 12.5 12.5 0.8462
 Hypertension 23.6 18.8 25.0 18.8
 Glomerulonephritis 5.5 9.4 3.1 9.4
 Undefined 32.7 34.4 31.2 34.4
 Other 29.1 25.0 28.1 25.0
Retransplantation (%) 3.6 3.1 1.0003 3.1 3.1 1.0003
BMI classification (%)
 Underweight 3.6 9.4 0.4002 3.1 9.4 0.1902
 Normal weight + overweight 80.0 68.8 87.5 68.8
 Obesity 16.4 21.9 9.4 21.9
Cardiovascular risk (%)
 Low 74.5 62.5 0.2372 62.5 62.5 1.0002
 Moderate + High 25.5 37.5 37.5 37.5
Pre-KTx diabetes (%) 12.7 15.6 0.7052 15.6 15.6 1.0002
Time on dialysis, median [IQR], m 26 [12–41] 29 [21–57] 0.2654 31 [15–49] 29 [21–57] 0.7424
Dialysis modality (%)
 None (preemptive) 3.6 3.1 0.2142 3.1 3.1 0.4842
 Hemodialysis 76.4 90.6 81.2 90.6
 Peritoneal 20.0 6.2 15.6 6.2
PRA, median [IQR], % 0 [0–0] 0 [0–67] 0.0304 0 [0–0] 0 [0–67] 0.0894
HLA mismatches, median [IQR], n 3 [2–4] 3 [3–3] 0.4974 3 [2–4] 3 [3–3] 0.9164
Deceased donor (%) 74.5 84.4 0.2852 71.9 84.4 0.2262
Induction therapy (%)
 No induction 3.6 3.1 0.9002 6.2 3.1 0.5542
 Anti-thymocyte globulin 96.4 96.9 93.8 96.9
Maintenance therapy (%)
 FK+mTORi+PDN* 65.5 59.4 0.6702 62.5 59.4 0.7632
 FK+MPS+PDN 29.1 37.5 31.2 37.5
 Other 5.5 3.1 6.2 3.1
Cold ischemia time, median [IQR], h 21 [8–24] 23 [20–26] 0.1074 21 [2–24] 23 [20–26] 0.1454
Deceased donor characteristics
Age, mean (SD), y 37 (14) 43 (15) 0.0771 38 (15) 43 (15) 0.1511
Cause of death (%)
 Stroke 48.8 59.3 0.5412 52.2 59.3 0.4762
 Traumatic brain injury 41.5 37.0 34.8 37.0
 Other 9.8 3.7 13.0 3.7
Serum creatinine median [IQR], mg/dL 1.0 [0.8–1.2] 1.0 [0.8–1.3] 0.8314 1.0 [0.8–1.0] 1.0 [0.8–1.3] 0.5164
Diabetes mellitus (%) 3.6 9.4 0.2673 0.0 9.4 0.0763
Hypertension (%) 18.2 21.9 0.6752 18.8 21.9 0.7562
Expanded Criteria Donor (%) 16.4 28.1 0.3232 18.8 28.1 0.4122
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SD, standard deviation; ESRD, end-stage renal disease; BMI, body mass index; KTx, kidney transplantation; IQR, interquartile range; PRA, panel reactive antibody; HLA, Human leukocyte antigen; FK, tacrolimus; mTORi, mammalian target of rapamycin inhibitor; MPS, mycophenolate sodium; PDN, prednisone.

*Tacrolimus+everolimus+prednisone, 87.3%; tacrolimus+sirolimus+prednisone, 12.7%.

1 t-test.

2 Pearson´s Chi-squared test.

3 Fisher’s exact test.

4 Mann-Whitney test.

Before matching, there was a significant difference between the frail and non-frail groups only with respect to sex, with female patients being considered more frail, and regarding panel reactive antibodies, whose levels were higher in the frail group. After matching, there was no significant difference for the study variables between the two groups. The post-matching analysis showed a homogeneous distribution of the propensity scores between 0.2 and 0.8, with the outliers being removed (S5 Appendix).

No patient had a serological test positive for human immunodeficiency virus (HIV), a positive PCR result for hepatitis C virus (HCV), or the presence of hepatitis B surface antigen (HBsAg).

Frailty and surgical complications

Of the 87 individuals included, 30 (34.5%) had surgical complications during the evaluated period—four (4.6%) patients developed infectious complications and 29 (33.3%) developed noninfectious complications. Table 2 lists the surgical complications identified in the study.

Table 2. Post-transplant surgical complications.

Surgical complications n patients (%)
Urological
Urinary leak 7 (8.0)
Hydronephrosis 2 (2.3)
Distal ureteral necrosis 1 (1.1)
Vascular
Renal artery stenosis 1 (1.1)
Renal vein thrombosis 4 (4.6)
Perigraft bleeding 4 (4.6)
Perigraft hematoma 5 (5.7)
Lymphocele 5 (5.7)
Infected lymphocele 1 (1.1)
General
Abdominal wall seroma 2 (2.3)
Abdominal wall hematoma 2 (2.3)
Surgical wound dehiscence 3 (3.4)
Superficial surgical site infection 2 (2.3)
Abdominal wall infection 1 (1.1)
Perigraft infection 1 (1.1)
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Table 3, Figs 2 and 3 show the occurrence of surgical complications after KTx, according to the frail and non-frail groups, before and after matching. Before matching, the risk of noninfectious surgical complications was significantly higher among the frail individuals (RR 1.84; 95% CI 1.03–3.30; p = 0.041). After matching, according to the propensity score, the risk of surgical complications was significantly higher among the frail individuals (RR 2.14; 95% CI 1.01–4.54; p = 0.035); specifically, the risk of noninfectious surgical complications was significantly higher among these individuals (RR 2.50; 95% CI 1.11–5.62; p = 0.017).

Table 3. Surgical complications after kidney transplantation, according to the frail and non-frail groups, before and after matching.

Before matching After matching
Non-frail (n = 55) Frail (n = 32) P RR (95% CI) Non-frail (n = 32) Frail (n = 32) P RR (95% CI)
Surgical complications n (%) 15 (27.3) 15 (46.9) 0.0641 1.72 (0.97–3.03) 7 (21.9) 15 (46.9) 0.0351 2.14 (1.01–4.54)
Infectious n (%) 2 (3.6) 2 (6.2) 0.5752 1.72 (0.25–11.62) 2 (6.2) 2 (6.2) 1.0002 1.00 (0.15–6.67)
Noninfectious n (%) 14 (25.5) 15 (46.9) 0.0411 1.84 (1.03–3.30) 6 (18.8) 15 (46.9) 0.0171 2.50 (1.11–5.62)
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RR: relative risk; CI: confidence interval.

1 Pearson´s Chi-squared test.

2 Fisher’s exact test.

Fig 2. Surgical complications after kidney transplantation, according to the frail and non-frail groups, before and after matching.

Fig 2

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Fig 3. Noninfectious surgical complications after kidney transplantation, according to the frail and non-frail groups, before and after matching.

Fig 3

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The incidence of graft loss (3.1% vs. 15.6%, p = 0.086) and death (9.4% vs. 12.5%, p = 0.689) were not statistically different after matching, respectively, between non-frail and frail groups.

Discussion

Until the present study, no studies evaluating the frailty score as a specific predictor of surgical complications after KTx have been identified.

In general, the frequency of urological, vascular, and general surgical complications in the studied sample was in agreement with the literature [3,4,6–10]. Urinary leak was the most frequent complication, accounting for 8.0% of the total. Also noteworthy is the low incidence of arterial stenosis observed in this study (1.1%), which is lower than that reported in the literature. Notably, mammalian target of rapamycin (mTOR) inhibitors with low tacrolimus levels was the most frequently used immunosuppressive maintenance regimen in the present study, and this combination has been associated with slightly higher risk of wound healing complications [34].

The percentage of frail individuals in the study sample (16.1%) was slightly lower compared to the literature. McAdams-DeMarco et al. [35] found 19.5% of frail individuals at admission for KTx using the Fried et al. score [13], whereas another multicenter study found 18.4% of frail individuals on the waiting list for KTx [36]. When considering the frequency of patients with intermediate frailty, the percentages found in these two studies increase to 31.7% [35] and 62.7% [36], respectively—much higher than that identified in the present study (20.7%). Differences among the studied populations, especially the higher age range of the KTx recipients included in the studies cited above, may explain such discrepant frequencies.

Fried et al. [13] found a higher prevalence of frailty among elderly women compared to elderly men in the same age group, corroborating the results of the present study. However, this difference was not detected in large-scale studies that evaluated populations that were more similar to the population studied here [35–37].

After matching, the risk of surgical complications, more specifically of noninfectious complications, was 2.5 times greater among individuals with some degree of frailty. Although this association may seem intuitive, this was the first time that this association was scientifically evidenced.

Studies have shown the association between frailty and general postoperative complications related to other types of surgery using specific population groups and various tools to measure frailty [25–29]. However, those studies selected a broader range of postoperative complications as outcomes, using classifications such as the one proposed by Clavien et al. or according to the criteria proposed by the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) [29,38,39], and not specifically surgical complications, as evaluated for the first time in the present study.

Schopmeyer et al. [24] associated the occurrence of postoperative complications (30 days after KTx) with the frailty score calculated at admission for KTx using a different tool than that proposed by Fried et al. [13]. However, the study also evaluated general postoperative complications as the outcome using the Comprehensive Complication Index (CCI) [40], and not specifically surgical complications.

Because the present study evaluates an unprecedented outcome in the population of kidney-transplanted patients, it is not possible to compare its results with the literature.

The present study has relevant limitations. The collection of data from a single center makes it difficult to extrapolate the results to other populations with characteristics different from our center. Increasing the number of patients in the sample would be desired to better evaluate the association between frailty and the different categories of post-KTx surgical complications. The exclusion of patients due to logistical difficulties may have resulted in a systematic bias. However, we believe that this potential bias does not represent a relevant risk, as we cannot anticipate the frail condition without applying the Fried score [13].

However, the present study also has its strengths. This study is a prospective and unprecedented study. Although there is still no ideal method for calculating the frailty score in patients who undergo KTx [41], the tool of Fried et al. [13] is certainly the most used, and it was validated for the Brazilian population. Importantly, the frailty data was collected at patient admission, reflecting the patients’ physiological reserve for KTx at the most appropriate time possible. Finally, it is also noteworthy that this is the first study evaluating the association between frailty and KTx in the Brazilian population.

The results of the present study showed that individuals with some degree of frailty before KTx were more subject to surgical complications, more specifically, to noninfectious complications. The calculation of the frailty score for transplant candidates and the implementations of measures to increase the physiological reserve of these patients at the time of KTx may possibly reduce the occurrence of surgical complications.

Studies evaluating the association between frailty and surgical complications should be performed in different populations of KTx recipients, using a larger sample.

Supporting information

S1 Appendix. Surgical protocol, prophylaxis against surgical site infections, and prevention of vascular complications in the kidney transplant unit.

(PDF)

Click here for additional data file. (54.7KB, pdf)
S2 Appendix. Frailty score components.

(PDF)

Click here for additional data file. (68.8KB, pdf)
S3 Appendix. Code R related to data and statistics.

(R)

Click here for additional data file. (9.7KB, R)
S4 Appendix. Tabulated data.

(XLSX)

Click here for additional data file. (24.6KB, xlsx)
S5 Appendix. Distribution of propensity scores after matching.

(PDF)

Click here for additional data file. (47.9KB, pdf)

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This study was supported by grant from São Paulo Research Foundation (FAPESP) # 2016/24745-3 (http://www.fapesp.br/en/) and was also financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 (https://www.capes.gov.br/). TEA received a scientific initiation scholarship from the National Council for Scientific and Technological Development (CNPq), RT - Bolsa Reitoria, project 42014 (http://www.cnpq.br/).

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Decision Letter 0

Frank JMF Dor

13 Dec 2019

PONE-D-19-31205

Frailty predicts surgical complications after kidney transplantation. A propensity score matched study.

PLOS ONE

Dear Dr. Monteiro de Barros Almeida,

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.

Timely and important topic in the field of kidney transplantation. One statistical reviewer and two experts in the field have raised several issues on methodology and execution of the study, as well as interpretation of the results. These concerns will have to be adressed thoroughly. Also, quite a few clarifications are needed by the authors. Please make a real effort to revise the MS accordingly. This is no guarantee that the revised MS will be accepted, though.

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We look forward to receiving your revised manuscript.

Kind regards,

Frank JMF Dor, M.D., Ph.D., FEBS, FRCS

Academic Editor

PLOS ONE

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Reviewer #3: Partly

**********

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Reviewer #1: Yes

Reviewer #2: I Don't Know

Reviewer #3: Yes

**********

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Reviewer #1: Yes

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Reviewer #3: Yes

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Reviewer #1: The manuscript entitled 'Frailty predicts surgical complications after kidney transplantation. A propensity score matched study. ' with the aim to determine of frailty are predictive of surgical complications following kidney transplant.

This is quite an interesting study. The manuscript can be further improved.

Comments

Methods

It would be good to have sample size calculation for the study.

Figure 1, more detail information to be provided to describe the study i.e. flow, grouping, M0, M1 etc

Statistical analysis

Statement on statistical analysis were performed on 'before matching' and 'after matching' to be added. 1 or 2 tailed for the statistical test(s) to be stated.

Results

Table 1, statistical test to be denoted in the table footnote.

Line 212- 220, the figure of RR, 95%CI to be placed in Table 3. 95% CI or 95% confidence interval (CI) to be standardized.

Table 3, individual n and total complications for both before and after matching to be added. Statistical test to be denoted in the table footnote.

Figure 2, 3, n (%) to be labelled in the graph for easy visualization.

Reviewer #2: Predicting complications and hence making the decision as to whether to proceed with transplantation is a complex process. There having been a growing number of publication looking at some for frailty index and this study adds to that body of work and hence is timely. The frailty methodology (Fried) used here is a well validated method of calculating frailty in renal patients.

There are some major questions that need clarification:

1. There were 131 transplants during this period but only 88 were included in the study. The area of concerns is that a total of 24 of the 44 exclusions were attributed to either researcher not informed or logistical difficulties. This needs further to be explained in more detail as there is a real risk of systematic bias.

2. It is stated that iatrogenic surgical complications were excluded from the analysis. It is not clear how it was determined if a complication was iatrogenic. Of note the commonest complication was urinary fistula. Under certain circumstances this could be considered an iatrogenic complication. Similarly it would be useful to know what complications were excluded from consideration as they were thought to be iatrogenic.

Reviewer #3: Thank you for the opportunity to review this paper which is of huge relevance and significance within the current transplant climate. I think it has been relatively well written and raises some interesting points.

My main issue with the study is that the measure used to assess frailty does not appear to have been validated for the renal failure population. The measure used (Fried et al) was written "To develop and operationalize a phenotype of frailty in older adults" and was validated based on a sample of patients who were all aged over 65. To use the same measure in the renal failure population awaiting transplantation is problematic for a number of reasons. Firstly, they are, on average, 20 years younger. Secondly, many of the sequela of ESRD are similar to that of frailty and therefore it is impossible to know whether the scores from the questionnaire are demonstrating true frailty or symptoms of ESRD. For example, weight loss is a difficult factor to consider within the dialysis population due to issues with fluid retention, whether patients are on a fluid restriction, whether they had been dialysed prior to admission and so on. It is therefore imperative that a measure of this kind is validated within the population in which you wish to use it.

With regard to the conclusions of the study, I agree that the finding of non-infective complications being at a higher rate in the more frail population is of interest, however I am unsure (given the reasons outlined above) how reliable this data is. Reason being, symptoms or signs that may be labelled as 'frailty' may actually be signs of something else related to the renal failure that would also have put the patient at higher risk of complications.

More minor points:

Abstract - I would expand the results and discussion sections. A single line for these parts of the abstract are not really adequate in my opinion

I would not class a lymphocele as a urological complication

I am unsure what a urinary fistula is - please explain what is meant by this

Exclusion criteria - you say that 'those whose physical or congnitive conditions prevented the calculation of the frailty score were excluded from the study' however you do not expand on what these are.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PLoS One. 2020 Feb 26;15(2):e0229531. doi: 10.1371/journal.pone.0229531.r002

Author response to Decision Letter 0

5 Jan 2020

Dear Editor,

We really appreciate all the comments made about our manuscript. Below we answer the questions and suggestions made by the reviewers.

Dear reviewers,

Thank you very much for the comments. They were extremely helpful. We are available to answer any further questions or suggestions you might have.

Reviewer #1: The manuscript entitled 'Frailty predicts surgical complications after kidney transplantation. A propensity score matched study. ' with the aim to determine of frailty are predictive of surgical complications following kidney transplant.

This is quite an interesting study. The manuscript can be further improved.

Comments

Methods

It would be good to have sample size calculation for the study.

Answer: We provided the sample size calculation in ‘Statistical analysis’ section.

Figure 1, more detail information to be provided to describe the study i.e. flow, grouping, M0, M1 etc

Answer: Done as suggested. Please see the new figure 1 attached.

Statistical analysis

Statement on statistical analysis were performed on 'before matching' and 'after matching' to be added. 1 or 2 tailed for the statistical test(s) to be stated.

Answer: Done as suggested.

Results

Table 1, statistical test to be denoted in the table footnote.

Answer: Statistical tests were denoted in the Table 1 footnote.

Line 212- 220, the figure of RR, 95%CI to be placed in Table 3. 95% CI or 95% confidence interval (CI) to be standardized.

Answer: Confidence interval was standardized in the text. The 95% CI was provided in Table 3.

Table 3, individual n and total complications for both before and after matching to be added. Statistical test to be denoted in the table footnote.

Answer: Done as suggested.

Figure 2, 3, n (%) to be labelled in the graph for easy visualization.

Answer: We modified the figures 2 and 3 for easy visualization.

Reviewer #2: Predicting complications and hence making the decision as to whether to proceed with transplantation is a complex process. There having been a growing number of publication looking at some for frailty index and this study adds to that body of work and hence is timely. The frailty methodology (Fried) used here is a well validated method of calculating frailty in renal patients.

There are some major questions that need clarification:

1. There were 131 transplants during this period but only 88 were included in the study. The area of concerns is that a total of 24 of the 44 exclusions were attributed to either researcher not informed or logistical difficulties. This needs further to be explained in more detail as there is a real risk of systematic bias.

Answer: We combined the terms ‘researcher not informed’, ‘logistical difficulties’, and ‘no available time for collection’ into a single term named ‘logistical difficulties’ because they represent similar reasons for non-inclusion in the study. Logistical difficulties occurred mainly due to communication difficulties between the transplantation team and the research team at patient admission. However, we believe that this potential bias does not represent a relevant risk, as it is not possible to identify patients as frail or non-frail without applying the methodology of Fried et al., nor can we anticipate kidney transplant outcomes at the time patients are hospitalized. We added a statement in the ‘Results’ section that explains in more detail the logistical difficulties.

2. It is stated that iatrogenic surgical complications were excluded from the analysis. It is not clear how it was determined if a complication was iatrogenic. Of note the commonest complication was urinary fistula. Under certain circumstances this could be considered an iatrogenic complication. Similarly it would be useful to know what complications were excluded from consideration as they were thought to be iatrogenic.

Answer: We have initially proposed to define ‘iatrogenic surgical complications’ as organ and tissue injuries that accidentally occur at the surgical site during the procedure. However, we agree with the reviewer that the definition of ‘iatrogenic surgical complications’ is rather inaccurate. That’s why we removed this statement from the manuscript. Additionally, no patients were excluded due to this condition.

Reviewer #3: Thank you for the opportunity to review this paper which is of huge relevance and significance within the current transplant climate. I think it has been relatively well written and raises some interesting points.

My main issue with the study is that the measure used to assess frailty does not appear to have been validated for the renal failure population. The measure used (Fried et al) was written "To develop and operationalize a phenotype of frailty in older adults" and was validated based on a sample of patients who were all aged over 65. To use the same measure in the renal failure population awaiting transplantation is problematic for a number of reasons. Firstly, they are, on average, 20 years younger. Secondly, many of the sequela of ESRD are similar to that of frailty and therefore it is impossible to know whether the scores from the questionnaire are demonstrating true frailty or symptoms of ESRD. For example, weight loss is a difficult factor to consider within the dialysis population due to issues with fluid retention, whether patients are on a fluid restriction, whether they had been dialysed prior to admission and so on. It is therefore imperative that a measure of this kind is validated within the population in which you wish to use it.

Answer: Frailty has been shown to be applicable in end-stage renal disease patients (ESRD) and in kidney-transplanted patients. These populations appear to share many pathogenic mechanisms of frailty, such as a pro-inflammatory state, with an exacerbated production of inflammatory cytokines, and dysregulation of the immune, neuroendocrine, and neuromuscular systems, resulting in accelerated ageing [1-4]. Frailty is considered highly prevalent in patients at any stage of chronic kidney disease (CKD) and may reach up to two-thirds in ESRD cases [5]. The use of the frailty score has progressively increased in the ESRD and transplant population. A recent systematic review [6] evaluating the use of the frailty score in the population of patients with CKD found that 72% of the studies used the Fried et al. score.

In kidney transplantation, frailty has been shown to be an independent risk factor for delayed graft function [1], post-transplant delirium [7], longer initial length of hospital stay [8], early hospital readmission [9], adverse effects from immunosuppressive drugs [10], and death [11]. In the ‘Report from the American Society of Transplantation on frailty in solid organ transplantation’, 98.9% of transplant surgeons responded that frailty in transplant candidates is a risk factor for adverse outcomes after transplantation [12].

We think that the measure of weight loss when calculating the Fried score in dialysis population was not a significant limitation because we only considered self-report of unintentional dry weight loss, reducing this limitation. Beside that, the Fried score has been used as a robust marker of outcomes in ESRD patients.

We added the two following statements in the ‘Introduction’ and ‘Material and methods’ sections, respectively, to emphasize the topics discussed above:

- ‘Frailty is considered highly prevalent in patients at any stage of chronic kidney disease (CKD), and may reach up to two-thirds in ESRD cases [Kojima G. Prevalence of frailty in end-stage renal disease: a systematic review and meta-analysis. Int Urol Nephrol. 2017;49 (11):1989–1997]. The use of the frailty score has progressively increased in the ESRD and transplant population. A recent systematic review [Chowdhury R, Peel NM, Krosch M, Hubbard RE. Frailty and chronic kidney disease: A systematic review. Arch Gerontol Geriatr. 2017;68:135–142] evaluating the use of the frailty score in the population of patients with CKD found that 72% of the studies used the Fried et al. score.’

- ‘Fried et al. score was calculated considering only the dry weight loss.’

References

1. Garonzik-Wang JM, Govindan P, Grinnan JW, Liu M, Ali HM, Chakraborty A, et al. Frailty and delayed graft function in kidney transplant recipients. Arch Surg. 2012;147(2):190-193.

2. Exterkate L, Slegtenhorst BR, Kelm M, Seyda M, Schuitenmaker JM, Quante M, et al. Frailty and transplantation. Transplantation. 2016;100(4):727-733.

3. McAdams-DeMarco MA, Suresh S, Law A, Salter ML, Gimenez LF, Jaar BG, et al. Frailty and falls among adult patients undergoing chronic hemodialysis: A prospective cohort study. BMC Nephrol. 2013;214:224.

4. McAdams‐DeMarco MA, Law A, Salter ML, Boyarsky B, Gimenez L, Jaar BG, et al. Frailty as a novel predictor of mortality and hospitalization in individuals of all ages undergoing hemodialysis. J Am Geriatr Soc. 2013;61(6):896-901.

5. Kojima G. Prevalence of frailty in end-stage renal disease: a systematic review and meta-analysis. Int Urol Nephrol. 2017;49(11):1989–1997.

6. Chowdhury R, Peel NM, Krosch M, Hubbard RE. Frailty and chronic kidney disease: A systematic review. Arch Gerontol Geriatr. 2017;68:135–142.

7. Haugen CE, Mountford A, Warsame F, Berkowitz R, Bae S, Thomas AG, et al. Incidence, risk factors, and sequelae of post‐kidney transplant delirium. J Am Soc Nephrol. 2018;29(6):1752-1759.

8. McAdams‐DeMarco MA, King EA, Luo X, Haugen C, DiBrito S, Shaffer A, et al. Frailty, length of stay, and mortality in kidney transplant recipients: a national registry and prospective cohort study. Ann Surg. 2016;266(6):1084‐1090.

9. McAdams-DeMarco MA, Law A, Salter ML, Chow E, Grams M, Walston J, et al. Frailty and early hospital readmission after kidney transplantation. Am J Transplant. 2013;13(8):2091-2095.

10. McAdams-De Marco MA, Law A, Tan J, Delp C, King EA, Orandi, et al. Frailty, mycophenolate reduction, and graft loss in kidney transplant recipients. Transplantation. 2015;15(1):149-154.

11. Mc Adams-De Marco MA, Law A, King E, Orandi B, Salter M, Gupta N, et al. Frailty and mortality in Kidney transplant recipients. Am J Transplant. 2015;15(1):149-154.

12. Kobashigawa J, Dadhania D, Bhorade S, Adey D, Berger J, Bhat G, et al. Report from the American Society of Transplantation on frailty in solid organ transplantation. Am J Transplant. 2019;19(4): 984-994.

With regard to the conclusions of the study, I agree that the finding of non-infective complications being at a higher rate in the more frail population is of interest, however I am unsure (given the reasons outlined above) how reliable this data is. Reason being, symptoms or signs that may be labelled as 'frailty' may actually be signs of something else related to the renal failure that would also have put the patient at higher risk of complications.

Answer: According to the discussion and the literature above, we believe that Fried et al. frailty score is indeed applicable to ESRD and transplant populations. Frailty score can be a robust marker that predicts important outcomes after transplantation. The most important is that the Fried et al. score can capture higher risk patients in kidney transplantation.

More minor points:

Abstract - I would expand the results and discussion sections. A single line for these parts of the abstract are not really adequate in my opinion

Answer: We agree with the reviewer. The results and discussion sections in the abstract were expanded.

I would not class a lymphocele as a urological complication

Answer: Some references classified the lymphocele as vascular and others as urological complication. We agree to reclassify lymphocele as a vascular complication.

I am unsure what a urinary fistula is - please explain what is meant by this

Answer: We refered urinary leak as urinary fistula. We changed the terms in the text.

Exclusion criteria - you say that 'those whose physical or congnitive conditions prevented the calculation of the frailty score were excluded from the study' however you do not expand on what these are.

Answer: We changed the phrase to ‘Individuals with amputations or other physical conditions that prevented the walk test or the handgrip strength test and the patients with significant cognitive impairment who were unable to understand and respond to the frailty score questionnaires were also excluded from the study’.

Attachment

Submitted filename: Response To Reviewers.docx

Click here for additional data file. (33KB, docx)

Decision Letter 1

Frank JMF Dor

30 Jan 2020

PONE-D-19-31205R1

Frailty predicts surgical complications after kidney transplantation. A propensity score matched study.

PLOS ONE

Dear Dr. Monteiro de Barros Almeida,

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.

==============================

ACADEMIC EDITOR:

The authors have addressed most of the point raised by the reviewers, but there are still a few outstanding points that would warrant careful revision. Please see detailed responses by the three reviewers.

==============================

We would appreciate receiving your revised manuscript by Mar 15 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Frank JMF Dor, M.D., Ph.D., FEBS, FRCS

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

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

Reviewer #2: (No Response)

Reviewer #3: 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: Partly

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: I Don't Know

Reviewer #3: 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: (No Response)

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: 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: Minor comments

Page 7 Line 161, alfa to be written as alpha.

Page 7 Line 162, to state clearly sample size 56 for whole group or each group. Also to add discussion on power of study.

Page 12 Table 3, CI 95% to be written as 95%CI.

Reviewer #2: I raised 2 questions when originally reviewing this paper. The authors have answered question 2 satisfactorily in my opinion. As for question 1, they have partly addressed my concerns but not fully. I think it is worth their including a statement raising the possibility that the exclusion of patients due to logicistical difficulties may have resulted in a systematic bias. Perhaps the clinical team did not try as hard to contact the Research team for a certain "type" of patient. I think a statement addressing this and a comment of why they do not think it relevant would satisfy me. If the editors are happy with the changes made I do not need to see the manuscript again

Reviewer #3: Thank you for providing a detailed response to my comments and for making appropriate adjustments to the manuscipt.

My main comment is with regard to the statement about questionnaire validation. I think it is entirely reasonable to make a statement saying that frailty is being increasingly assessed within this population and that the Fried score appears to be the most popular rating scale being used. However, I still think there also needs to be a statement that says something akin to "The Fried frailty index has not been formally validated within the end-stage renal failure population, however it is currently the most popular / frequently used questionnaire".

This is important because the reader needs to be aware that whilst this is the most popular scale, it has not undergone the formal validation process that a lot of questionnaires should have done when being used in certain populations. The crossover of symptoms between those with frailty due to renal disease and general frailty is significant and the fact that this has not specifically been considered as part of validity testing is hugely relevant within this context.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: 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". If this link does not appear, there are no attachment files to be viewed.]

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PLoS One. 2020 Feb 26;15(2):e0229531. doi: 10.1371/journal.pone.0229531.r004

Author response to Decision Letter 1

3 Feb 2020

Dear Editor,

We sincerely appreciate all valuable comments and suggestions. We have made a great effort to take into account all the suggestions proposed by the reviewers. We are available to answer any further questions or suggestions you might have.

Reviewer #1: Minor comments.

Page 7 Line 161, alfa to be written as alpha.

Answer: Thank you very much. We changed to “alpha”.

Page 7 Line 162, to state clearly sample size 56 for whole group or each group. Also to add discussion on power of study.

Answer: The reviewer is correct. We apologize about the mistake. In fact, we assumed a frequency of surgical complications of 45% in the frail group and 15% in the non-frail group. Considering a power of 0.80, and alpha of 0.05, we calculated a minimum sample size of 68 patients. This information was corrected in the ‘Statistical analysis’ section. We also calculated the post hoc power of the study considering the incidence of surgical complications after matching and it reached 0.71. However, it is important to notice that there was a significant difference between the groups, thus type I error and not type II is the most important in our study.

Page 12 Table 3, CI 95% to be written as 95%CI.

Answer: Done as suggested.

Reviewer #2: I raised 2 questions when originally reviewing this paper. The authors have answered question 2 satisfactorily in my opinion. As for question 1, they have partly addressed my concerns but not fully. I think it is worth their including a statement raising the possibility that the exclusion of patients due to logicistical difficulties may have resulted in a systematic bias. Perhaps the clinical team did not try as hard to contact the Research team for a certain "type" of patient. I think a statement addressing this and a comment of why they do not think it relevant would satisfy me. If the editors are happy with the changes made I do not need to see the manuscript again

Answer: We added the following statement in the ‘Discussion’ section: ‘The exclusion of patients due to logistical difficulties may have resulted in a systematic bias. However, we believe that this potential bias does not represent a relevant risk, as we cannot anticipate the frail condition without applying the Fried score [13]’.

Reviewer #3: Thank you for providing a detailed response to my comments and for making appropriate adjustments to the manuscipt.

My main comment is with regard to the statement about questionnaire validation. I think it is entirely reasonable to make a statement saying that frailty is being increasingly assessed within this population and that the Fried score appears to be the most popular rating scale being used. However, I still think there also needs to be a statement that says something akin to "The Fried frailty index has not been formally validated within the end-stage renal failure population, however it is currently the most popular / frequently used questionnaire".

This is important because the reader needs to be aware that whilst this is the most popular scale, it has not undergone the formal validation process that a lot of questionnaires should have done when being used in certain populations. The crossover of symptoms between those with frailty due to renal disease and general frailty is significant and the fact that this has not specifically been considered as part of validity testing is hugely relevant within this context.

Answer: Thank you very much for the comments. In the ‘Introduction’ section we changed the phrase ‘Frailty is a measure of physiological reserve, initially validated for the geriatric population [13]. However, it has been shown to be applicable in end-stage renal disease (ESRD) patients and in kidney-transplanted patients. These populations appear to share many pathogenic mechanisms of frailty, such as a pro-inflammatory state, with an exacerbated production of inflammatory cytokines, and dysregulation of the immune, neuroendocrine, and neuromuscular systems, resulting in accelerated ageing [12,14-16]’ to ‘Frailty is a measure of physiological reserve, initially validated for the geriatric population [13]. Although the frailty score has not been formally validated for patients with end-stage renal disease (ESRD) and for kidney-transplanted patients, it has been shown to be applicable to these populations. These patients appear to share many pathogenic mechanisms of frailty, such as a pro-inflammatory state, with an exacerbated production of inflammatory cytokines, and dysregulation of the immune, neuroendocrine, and neuromuscular systems, resulting in accelerated ageing [12,14-16]’.

We think this statement has clarified the fact that frailty score has not yet undergone the formal validation process within ESRD and kidney-transplanted populations.

Attachment

Submitted filename: Response To Reviewers v2.docx

Click here for additional data file. (25.1KB, docx)

Decision Letter 2

Frank JMF Dor

10 Feb 2020

Frailty predicts surgical complications after kidney transplantation. A propensity score matched study.

PONE-D-19-31205R2

Dear Dr. Monteiro de Barros Almeida,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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With kind regards,

Frank JMF Dor, M.D., Ph.D., FEBS, FRCS

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

Reviewer #2: All comments have been addressed

Reviewer #3: 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

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #2: I Don't Know

Reviewer #3: 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: (No Response)

Reviewer #2: Yes

Reviewer #3: 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

Reviewer #2: Yes

Reviewer #3: 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: (No Response)

Reviewer #2: (No Response)

Reviewer #3: All my comments have now been addressed, thank you.

**********

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.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Acceptance letter

Frank JMF Dor

13 Feb 2020

PONE-D-19-31205R2

Frailty predicts surgical complications after kidney transplantation. A propensity score matched study.

Dear Dr. Monteiro de Barros Almeida:

I am 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 notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, 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.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Frank JMF Dor

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Appendix. Surgical protocol, prophylaxis against surgical site infections, and prevention of vascular complications in the kidney transplant unit.

    (PDF)

    Click here for additional data file. (54.7KB, pdf)
    S2 Appendix. Frailty score components.

    (PDF)

    Click here for additional data file. (68.8KB, pdf)
    S3 Appendix. Code R related to data and statistics.

    (R)

    Click here for additional data file. (9.7KB, R)
    S4 Appendix. Tabulated data.

    (XLSX)

    Click here for additional data file. (24.6KB, xlsx)
    S5 Appendix. Distribution of propensity scores after matching.

    (PDF)

    Click here for additional data file. (47.9KB, pdf)
    Attachment

    Submitted filename: Response To Reviewers.docx

    Click here for additional data file. (33KB, docx)
    Attachment

    Submitted filename: Response To Reviewers v2.docx

    Click here for additional data file. (25.1KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.

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