Healthcare workload associated with transition onto kidney replacement therapy: a retrospective cohort study

Healthcare workload associated with transition onto kidney replacement therapy: a retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Healthcare workload associated with transition onto kidney replacement therapy: a retrospective cohort study Catrin H Jones, Benjamin Edgar, Peter C Thomson, Katie I Gallacher, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7557511/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Dec, 2025 Read the published version in BMC Nephrology → Version 1 posted 11 You are reading this latest preprint version Abstract Background and hypothesis. Transition onto kidney replacement therapy (KRT) is a complex, intensive phase for patients with advanced chronic kidney disease (CKD), characterised by high healthcare utilisation. Frequent outpatient visits, surgical and radiological procedures, hospitalisations and haemodialysis (HD) sessions impose a significant time burden on patients. The concept of time toxicity is widely described in oncology, and captures the disruption to patients’ lives due to treatment-related demands. We aimed to quantify time- based healthcare workload during the transition onto KRT and identify patient characteristics associated with increased workload. Methods. We conducted a retrospective cohort study including all consecutive adults initiating KRT (haemodialysis (HD), peritoneal dialysis (PD), or pre-emptive transplantation (KTx)) in the Glasgow Renal and Transplant Unit between January 2015 and December 2019. Routinely collected electronic health record data were used to estimate time spent per month on healthcare-related activities (outpatient appointments, radiology, inpatient admissions, HD sessions, and travel) from 6 months pre- to 36 months post-KRT initiation. Workload was analysed as a time-based outcome (hours/month). Univariate analysis used Kruskal-Wallis testing; multivariate modelling employed negative binomial regression. Results. A total of 1,022 patients (58.6% male; median age 61 years) contributed over 1.1 million patient-days. Median healthcare workload peaked around KRT initiation and was highest in HD patients. Kidney transplantation was associated with markedly lower workload post-initiation (IRR 0.04). Increased workload was associated with female sex, polypharmacy (> 15 medications), late referral, older age (in maintenance phase), and modality change or failed transplant. Socioeconomic deprivation and primary renal disease were not significantly associated with higher workload. Conclusion. Healthcare workload during KRT transition is substantial and varies widely. Transplantation is associated with significantly lower workload. These findings support timely transplant planning and underscore the importance of considering the time burden of healthcare experienced by patients when discussing treatment options. Chronic kidney disease healthcare workload kidney replacement therapy time toxicity treatment burden Figures Figure 1 Figure 2 Figure 3 Introduction Chronic kidney disease (CKD) is a global health priority ( 1 ) with an estimated prevalence of 850 million people worldwide( 2 ). The prevalence of both CKD and kidney replacement therapy (KRT) are both projected to increase considerably over the next 10 years( 3 ). Currently 8,254 adult patients start kidney replacement therapy every year in the UK, giving an incidence of 154 persons per million( 4 ). The transition from advanced CKD to KRT- either haemodialysis (HD), peritoneal dialysis (PD) or kidney transplantation (KTx)- is a complex phase in the patient journey with significant healthcare utilization ( 5 )( 6 ) ( 7 ). This has considerable economic and systemic resource allocation implications( 8 , 9 ), but also has a very human cost borne by the patients navigating this phase of their illness. The disruption caused by hospitalisations, frequent appointments and investigations, and attending dialysis are described as being particularly burdensome( 10 ). Treatment burden is the impact that fulfilling healthcare workload has on wellbeing( 11 ). There is growing recognition of the importance of recognising treatment burden but as it is the subjective experience of patient of the impact of healthcare workload, burden cannot be directly inferred by only quantifying workload( 12 ). Time toxicity is defined as the time impact of medical treatment, including the time spent co-ordinating care, attending clinics, inpatient stays, imaging, travel to and from healthcare facilities, seeking urgent care for side-effects or deteriorations, and follow up tests ( 13 , 14 ). It has been widely described in oncology, where it has been noted to be a patient centred measure that encompasses the temporal burden of treatment, the disruption of daily life, the opportunity cost of losing time to do other things such as spending quality time with loved ones, the cumulative impact of a consistently high temporal burden on wellbeing and the emotional and psychological strain of treatment which can impact the efficiency of healthcare utilization( 15 – 19 ). For some patients the impact of the time spent pursuing cancer treatments can be so considerable it offsets the modest survival gains offered by treatment( 14 ). The temporal burden of healthcare workload and time toxicity has not been explored for patients in the context of KRT transition. The aim of this study is to describe patterns of healthcare workload as measured by time per month spent in healthcare contact in the six months leading up to KRT initiation and in the first 36 months of KRT, and describe patient characteristics associated with higher workload. Materials and Methods Study Settings This was a retrospective cohort study of healthcare workload during transition onto KRT. All consecutive patients aged 18 or older that started any form of KRT in the Glasgow Renal and Transplant Unit, Glasgow, Scotland between 1st January 2015 and 31st December 2019 were included. The unit provides comprehensive renal services for NHS Greater Glasgow and Clyde and NHS Forth Valley health boards and renal transplant services for the West of Scotland, serving an estimated population of 1.5 million for general renal services and 2.6 million for renal transplantation. Participants were identified by interrogating the Strathclyde Electronic Renal Patient Record (SERPR, Vitalpulse, UK) system for all patients that had started KRT within the study period. Data were extracted for all recorded hospital based workload in SERPR from 6 months prior to starting KRT and for the first 36 months of KRT or until death, and categorised by which month in which they occurred relative to the KRT initiation date from Month − 6 to Month 36. Data collection ended on 31st December 2022. We elected to use 6 months prior to KRT initiation as it would capture most of the workload involved in KRT transition, and to follow up for 36 month as the average deceased donor kidney only transplant waitlist in the UK is 15.6 months( 20 ) and therefore a follow up period of 36 months would capture the majority of the workload experienced by patients pursuing their first renal transplant. For analysis we subdivided the study period to two phases: peri-initiation (Month-6 to Month 6) and early maintenance (Month 7 to 36). Caldicott approval was granted to access and analyse the anonymised data. Healthcare workload and predictor measurement Baseline demographic data were extracted including age at KRT initiation, sex, ethnicity, primary renal disease, and number of repeat prescription medications at time of initiation. Home postcodes at time of initiation were used to categorise socioeconomic status using Scottish Index of Multiple Deprivation (SIMD) quintiles. Initial contact with nephrology services were noted, and patients who presented to renal services less than 90 days prior to KRT initiation were classified as late presenters. The exact date of KRT start was noted as well as the starting modality: HD, PD or KTx. Data on modality changes in the first 36 months of KRT were extracted including number of modality changes and type of change: PD or HD to Transplant (Incident Transplantation) and Transplant to HD or PD (Failed Transplant). For patients that died during the 36 month follow period date of death was recorded and converted to month of death relative to KRT initiation. Because of the degree of incomplete data, ethnicity was excluded from the final analysis. All renal related clinic visits including general nephrology, vascular access, transplant assessment, transplant follow up or PD clinic were recorded. All hospital inpatient admissions and length of stay were recorded, as were all diagnostic and interventional radiology workload, and all HD sessions. Commute times for all episodes of care were estimated from domiciliary post code. The outcome of interest was average time per month in hours spent on healthcare workload. The decision to use time as outcome was done following consultation with a Patient and Public Involvement and Engagement (PPIE) group. The length of inpatient stay was calculated from the admission and discharge date recorded on SERPR, we estimated that an outpatient clinic appointment lasted 30 minutes, imaging appointment lasted 1 hour, and a HD session lasted 5 hours from average appointment duration. Travel times were estimated by querying the Google Maps application programme interface (API) using an anonymised list of postcodes to provide coordinates to enable geocoding. All coordinates were then geographically masked by a process known as ‘jittering’ to preserve patient anonymity. The API was then further queried for driving times between each set of coordinates and the hospital attended. These techniques are slightly less precise than using the exact street address for each patient, but were necessary to preserve anonymity( 21 , 22 ). Total time per month per participant from Month − 6 to Month 36 was calculated and this is our outcome measure. We censored the data for death to ensure accuracy and minimise bias from missing values. All variables were treated as categorical. Continuous variables were categorised for analysis. Age was categorised as 18–44, 45–64, 65–74 and 75 + in keeping with classification used by the Scottish Renal Registry( 23 ). Number of medications were categorised as < 10, 10–15, and 15 + as the average number of medications in our cohort was 12.5 and these categories reflect lower, average and higher medication burden. Statistical Analysis All statistical analysis were conducted using R Statistical Software. Skew was measured with Fisher G1 and Bowley quartile skew. Univariate statistical analysis was undertaken with Krukal-Wallis test and effect size was calculated using \(\:{\epsilon\:}^{2}\) . Negative binomial multiple regression models were fitted for both the peri-initiation and maintenance periods and Incidence Rate Ratios (IRRs) were calculated to compare workloads. Statistical significance was set as p < 0.05. As our dataset had low levels of missing data we conducted available case analysis. We censored the data for death so that average time per month was calculated only for the months patients were alive for in the analysis periods. Results Demographics 1022 consecutive patients that started KRT for the first time between 1st January 2015 and 31st December 2019 were recruited. Healthcare workload data were collected for all for the six months prior to KRT start and for 36 months after or until death, giving a total of 1,104,158 observed days. 317 patients (31%) died during the follow up period. The demographic characteristics of the patients are categorised in Table 1 . Median age at KRT start was 61 (IQR 50–71; range 18–90), 599/1,022 participants were male (58.6%) and 389/1,022 participants (38.2%) lived in Scottish Index of Multiple Deprivations (SIMD) 1 post codes which is the most deprived quintile. The most common primary renal disease (PRD) was diabetic nephropathy, reported in 319/1022 (31.2%) of participants. The median number of long-term medications at KRT start was 13 (IQR 9–16, range 0–36). Median distance from the hospital was 5.4 miles (IQR 3.2–11.3; range 0.3–145 miles), with a median travel time of 21 minutes (IQR 15.2–30.6; range 2.5–479 minutes). Table 1 Demographic characteristics of participants Age 18–44: 176 (17.2%) 45–64: 403 (39.4%) 65–74: 225 (22.0%) 75+: 165 (16.1%) Not recorded: 53 (5.2%) Sex M 599 (58.6%) F 423 (41.4%) SIMD 1 389 (38.2%) 2 203 (19.9%) 3 166 (16.3%) 4 135 (13.2%) 5 126 (12.4%) Ethnicity White 287 (28.0%) Asian 38 (3.7%) Black 11 (1.1%) Mixed 3 (0.3%) Other 9 (0.8%) Not recorded 674 (65.9%) Primary Renal Disease Glomerular Disease 211 (20.7%) Tubulointerstitial Disease 148 (14.5%) Diabetes 319 (31.2%) HTN/Renovascular Disease 119 (11.7%) Other systemic disease affecting the kidney 33 (3.2%) Familial/ hereditary 86 (8.4%) Miscellaneous 100 (9.8%) Not recorded 5 (0.5%) Number of medications 15: 274 (26.8%) Distance from hospital < 10 miles: 749 (73.3%) 10–20 miles: 109 (10.7%) 20–30 miles: 116 (11.4%) 30 + miles: 42 (4.1%) Travel time < 15 minutes: 245 (24.0%) 15–30 minutes: 513 (50.2%) 30–60 minutes: 206 (20.2%) 60–120 minutes: 30 (2.9%) 120 + minutes: 22 (2.2%) Late presenter Late: 86 (8.4%) Not Late: 936 (91.6%) Starting Modality Haemodialysis 767 (75%) Peritoneal Dialysis122 (11.9%) Kidney Transplant 133 (13.0%) Modality changes No changes: 730 (71.4%) 1 change: 230 (22.5%) 2 + changes: 62 (6.1%) Exposure to transplant after PD/HD KRT start: Yes: 245 (24.0%) No:777 (76.0%) Exposure to failed transplant: Yes: 21 (2.0%) No: 1001 (98%) Status at 36 months Haemodialysis: 313 (30.6%) Peritoneal Dialysis: 6 (0.6%) Transplant: 386 (37.8%) Dead: 317 (31.0%) Most patient were known to nephrology services for more than 3 months prior to starting: only 86/1,022 (8.4%) were late presenters. HD was the most common starting modality with 767/1,022 (75%) starting on HD, 122 (11.9%) started on PD and 133 (13.0%) started KRT with a pre-emptive transplant. In the subsequent 36 months, 292 participants (28.6%) changed modality at least once and 317 (31%) died meaning that at 36 months post initiation 386 participants (37.8%) had a functioning transplant, 6 (0.6%) were on PD and 313 (30.6%) were on HD (Fig. 1 ). Temporal trends in workload Total time per month was calculated for every participant for every month from Month − 6 pre KRT to Month 36 post initiation or until death both overall and subdivided by type of workload (Outpatient, Radiology, Inpatient, HD, Commuting), as shown in Table 2 . Inpatient stays and HD sessions were the predominant drivers of workload. Overall time data had extreme right skew (Fisher g1 = 15.94, 95%CI 15.92–15.97; Bowley skew = 0.85, p < 0.001) signifying that a small number of patients had very high workload. Degree of skewness varied between workload type: inpatient care was extremely right skewed with Fisher g1 of 17.73, 95%CI 17.71-17-76, and an unquantifiable quartile skewness as more than 75% of patient-months had no inpatient stay. HD sessions had a borderline right skew on Fisher g1: 0.49, 95%CI 0.47–0.52) but strong right skew on Bowley quartile skew (1.00), which is in keeping with those not on HD not having any HD based workload but those on HD having consistently high and similar workloads. Similarly Radiology (Fisher g1 = 4.22, 95%CI 4.12–4.24; Bowley skew = unquantifiable, p < 0.001), Outpatient clinic (Fisher g1 = 2.96, 95%CI 2.93–2.98; Bowley skew = 1.0, p < 0.001) and Commute (Fisher g1 = 6.70, 95%CI 6.67–6.72; Bowley skew = 0.44, p < 0.001) workloads all demonstrated marked right skew, but less extreme than inpatient workload. Table 2 Total average death-censored time per month spent per activity (hours) Activity Peri-initiation (Month − 6 to 6) (Mean/SD; Median/IQR) Early Maintenance (Month 7 to 36) (Mean/SD; Median/IQR) Total Time Mean: 59.7 (164) Median: 3.53 (0.8–71.6) Mean: 50.5 (113) Median: 42.8 (0.0–71.0) Outpatient clinic Mean: 0.36 (0.54) Median: 0.0 (0.0-0.5) Mean:0.22 (0.47) Median:0.0 (0.0-0.5) Radiology Mean: 0.66 (1.36) Median:0.0 (0.0–1.0) Mean: 0.41(1.02) Median:0.0 (0.0–0.0) Inpatient care Mean: 36.4 (169.0) Median: 0.0 (0.0–0.0) Mean: 16.1 (106.0) Median: 0.0 (0.0–0.0) HD sessions Mean: 23.3 (32.6) Median: 0.0 (0.0–60) Mean: 36.8 (32.5) Median:55.0 (0–65.0) Commute Mean: 2.70 (4.79) Median:1.1 (0.3–3.7) Mean: 3.42 (4.89) Median:2.5 (0.4–4.6) When considering temporal patterns of workload, workload patterns differed depending on starting modality (Fig. 2 ). All modalities had an acute initiation workload spike at between Month − 1 and Month 1 mostly driven by inpatient stay, but this is less pronounced in those who stated on PD. The increase in inpatient workload starts earlier for HD and PD patients in the pre-KRT period as compared to transplant, likely representing inpatient admissions for vascular access creation, PD catheter insertion and medical optimisation. Post KRT initiation, transplant workload rapidly decreases over first six months and settles to a very low baseline. Haemodialysis workload also settles, but to a higher baseline with regular HD sessions. Peritoneal dialysis hospital-based workload is lower in the immediate initiation period but has ongoing spikes in inpatient stays and a slowly increasing rate of HD workload which is in keeping with patients experiencing PD complications and transitioning onto HD or being transplanted: of the 122 patients that start KRT on PD only 6 remain on PD at 36 months. Association between patient characteristics and workload On univariate analysis every categorical domain except sex for both peri-initiation and maintenance, and failed transplant for maintenance, had a signal for association with a difference in workload [Table 3 ]. Table 3 Patient characteristics associated with higher workload: Kruskal-Wallis univariate analysis Peri-initiation Maintenance \(\:{\epsilon\:}^{2}\) p-value \(\:{\epsilon\:}^{2}\) p-value Modality 0.39 < 0.001 0.34 < 0.001 PRD 0.07 < 0.001 0.12 < 0.001 Age 0.06 < 0.001 0.09 < 0.001 Late Presentation 0.05 < 0.001 < 0.01 0.04 Modality change 0.04 < 0.001 0.07 < 0.001 Incident Transplant 0.03 < 0.001 < 0.01 < 0.001 Medications 0.03 < 0.001 0.03 < 0.001 SIMD 0.02 < 0.001 0.02 < 0.001 Failed transplant < 0.01 0.031 < 0.01 0.985 Sex < 0.01 0.287 < 0.01 0.657 E 2 effect size: 0.14 large In the negative binomial multivariate regression model (Table 4 , Fig. 3 ) PD and Transplant were associated with significantly lower workloads compared to HD. The difference between Transplant and HD in Months 7–36 was particularly marked (IRR 0.04 (0.03–0.05)), which means that the average monthly workload was 96% lower in pre-emptive transplant patients compared to those who started on HD. Incident transplantation- being transplanted within the 36 month follow up period after starting KRT on either PD or HD- was also associated with lower workload (peri-initiation IRR 0.73 (0.57–0.92), maintenance 0.37 (0.28–0.49). Female sex was associated with a small increased workload (peri-initiation IRR 1.16 (1.07–1.24), early maintenance 1.17 (1.05–1.31)), and being on more than 15 long-term medications was also associated with a consistently higher workload (IRR 1.36 (1.20–1.55) peri-initiation, 1.35 (1.15–1.59) maintenance). Table 4 Association between patient characteristics and workload: a negative binomial model Variable (*=reference) Peri initiation Maintenance IRR (95%CI) p-value IRR (95%CI) p-value Sex Male * * * * Female 1.16 (1.07–1.24) < 0.001 1.17 (1.05–1.31) 0.006 SIMD 1–3 * * * * 4–5 0.97 (0.88–1.07) 0.539 1.10 (0.97–1.25) 0.122 PRD Glomerular * * * * Tubulointestitial 0.92 (0.79–1.07) 0.292 0.88 (0.73–1.07) 0.193 Diabetes 1.15 (1.01–1.31) 0.031 1.12 (0.96–1.32) 0.160 Hypertension 1.02 (0.87–1.20) 0.774 1.00 (0.82–1.22) 0.999 Other systemic 1.13 (0.88–1.46) 0.339 1.02 (0.75–1.42) 0.893 Familial 0.86 (0.72–1.03) 0.104 0.90 (0.72–1.13) 0.360 Miscellaneous 1.03 (0.87–1.22) 0.741 1.07 (0.87–1.33) 0.535 Unknown 0.83 (0.48–1.59) 0.537 0.41 (0.19–1.06) 0.043 Late Presentation Not Late * * * * Late 1.39 (1.18–1.65) < 0.001 1.01 (0.82–1.26) 0.905 Incident Transplant No * * * * Yes 0.73 (0.57–0.92) 0.007 0.37 (0.28–0.49) < 0.001 Failed Transplant No * * * * Yes 1.04 (0.77–1.44) 0.794 2.30 (1.61–3.41) < 0.001 Modality Change No * * * * Yes 0.98 (0.79–1.23) 0.888 1.44 (1.08–1.94) 0.008 Age 18–44 * * * * 45–64 1.06 (0.93–1.20) 0.382 1.16 (1.00-1.36) 0.055 65–74 1.12 (0.97–1.29) 0.127 1.24 (1.03–1.48) 0.028 75+ 1.16 (0.98–1.36) 0.082 1.27 (1.04–1.57) 0.023 Medications 15 1.36 (1.20–1.55) < 0.001 1.35 (1.15–1.59) < 0.001 Modality Haemodialysis * * * * Peritoneal 0.41 (0.35–0.47) < 0.001 0.47 (0.39–0.57) < 0.001 Transplant 0.36 (0.31–0.42) < 0.001 0.04 (0.03–0.05) < 0.001 Late presentation to nephrology (IRR 1.39 (1.18–1.65)) was associated with higher workload in the peri-initiation period but was not associated with a difference in workload in the maintenance period. Conversely, age had no significant effect on workload in the peri-initiation period but older age (65–74 (IRR 1.24(1.03–1.48)), 75+ (IRR 1.27(1.04–1.57))) was associated with higher workload in the maintenance period. Modality change (IRR 1.44(1.08–1.94)) and failed transplant (IRR 2.30 (1.61–3.41)) were also associated with higher workload in the maintenance period whilst having no significant effect on workload peri-initiation. There was no association between SIMD and workload, and with the exception of a small increase in workload for those with diabetic nephropathy peri-initiation (IRR 1.15(1.01–1.31)), there was no association between workload and PRD either. Discussion This study provides a detailed analysis of hospital-based healthcare workload derived from an EHR in the 6 months leading up to KRT initiation and the 36 months following. This allows for visualisation of the time burden of hospital based healthcare workload and how it evolves. We have demonstrated considerable variation in healthcare workload across the cohort; with haemodialysis, older age, high medication burden, late presentation, and complications such as modality changes and failed transplant all associated with higher workload. The use of time as a proxy measure for the burden of healthcare workload is novel in this population. High medication burden, which could be seen as a surrogate measure for multimorbidity( 24 – 27 ), was consistently associated with higher workload. The interaction between patient factors such as multimorbidity, frailty and older age with disease severity factors requiring more intensive treatment regimens creating subsets of patients with very high healthcare utilization is reflected in both renal specific( 28 ) and general ( 29 , 30 ) health economics literature. Frailty and severity of comorbidity could also curtail suitability for transplant and mark a high risk for ongoing high healthcare workload, and the data from this study could help delineate populations for whom the burden of ongoing kidney care outweighs benefit to their quality of life, and inform discussions around conservative care( 31 ). Patients who present ‘late’, defined as being referred to nephrology less than 3 months from KRT start, often miss out on outpatient pre-dialysis education and opportunities to prepare for optimal KRT starts such as pre-emptive transplantation, pre-emptive vascular access creation and PD counselling( 32 , 33 ). It is therefore not surprising that their peri-initiation workload is higher than those referred earlier. It is interesting that their workload in the maintenance period (7–36 months) is no longer higher, suggesting that the increased workload around initiation is being driven by the lateness of their presentation and clinicians and services should be mindful of the higher needs of those with unexpected KRT starts especially around the time of initiation. The most striking finding of this study is the marked reduction in healthcare workload associated with kidney transplantation. The beneficial effect of kidney transplantation on reducing healthcare utilisation and on improving quality of life is already known( 34 ), and this study contributes to the body of evidence that the timely pursuit of transplantation in potentially eligible patients is key in reducing workload and burden in advanced CKD patients. The use of time as a patient-centred aggregate measure of healthcare workload in kidney disease is novel. The impact of the time commitments involved in commuting to treatment and the considerable time burden of hospitalisation for the minority that require it is similar to that found for metastatic breast cancer care( 35 ) and multiple myeloma( 16 ). The negative impact of hospitalisation on patients’ psychological wellbeing is well documented( 36 ). However, care must be taken in inferring that all time used on healthcare workload is detrimental or that lack of time is necessarily superior: kidney failure is a life-threatening disease state that requires extensive healthcare input. Difficulty accessing healthcare could be a detrimental reason for less time spent on healthcare workload. Premature discharge from hospital or insufficient clinic appointments could constitute an inappropriate transfer of work from hospital clinicians to patients or to primary care( 37 , 38 ). Further qualitative work is required to understand what aspects of healthcare workload are most burdensome, how patient capacity affects experiences of workload, and how the burden of treatment could be mitigated. The use of SERPR as a data source brought both strengths and limitations. The use of SERPR as a renal specific EPR provides highly granular and accurate data for healthcare workload within the Glasgow renal services which is a strength of this study. However, it does not capture outpatient clinics with other specialities, hospital workload in health boards other than NHS GGC and NHS FV, healthcare contact with primary care and other community services, or work undertaken at home which is a particular limitation when considering PD or home HD. SERPR also only captures the number, date and type of healthcare episode and does not capture the exact time spent by the patient in the hospital and therefore we needed to extrapolate estimated time from the SERPR data which introduced a degree of imprecision into our study. SERPR also does not capture healthcare workload that takes place in the home, which could lead to the workload associated with home therapies such as peritoneal dialysis and haemodialysis being severely underestimated. This is a single-centre study, albeit covering a wide geographical area with multiple sites and teams, and this potentially limits its generalisability. In conclusion, this study is a comprehensive exploration of healthcare workload associated with transition onto kidney replacement therapy. A key finding is the profound protective effect of transplantation on workload, reinforcing the importance of timely and proactive pursuit of transplantation for potentially eligible patients and the vital importance of strategies improving the availability of both live donor transplantation and organ availability and utilisation in deceased donor transplantation. Secondly, there are a group of older multimorbid patients on haemodialysis who have a much higher than average workload. This study could help inform discussions around wishes around care, and if the benefits of undertaking time consuming treatment still outweighs the burden. Abbreviations CKD Chronic Kidney Disease HD Haemodialysis IRR Incidence Rate Ratios KRT Kidney Replacement Therapy KTx Kidney Transplant PD Peritoneal Dialysis PPIE Patient and Public Involvement and Engagement SERPR Strathclyde Electronic Renal Patient Record SIMD Scottish Index of Multiple Deprivation Declarations Consent to participate and ethics statement As this study was based on retrospective secondary analysis of anonymised routinely collected clinical data, IRB review was waivered and permission was granted to access the data and for governance from the NHS Greater Glasgow and Clyde Caldicott Guardian and the study was conducted in line with the Declaration of Helsinki. Also as a result of this study being secondary analysis of routinely collected anonymised data individual consent for participation was deemed not to be required in line with MRC guidelines ‘Using information about people in health research”. Consent for publication Not applicable. This study used only anonymised, routinely collected data, and no identifiable individual data are presented. Clinical Trial Number: Not applicable. Availability of data and materials: The data that supports the findings of this study are available from the corresponding author upon reasonable request. Due to the nature of the data and participant confidentiality, restrictions apply to the availability of these data. Competing interests: PM received grants from AstraZeneca and Boehringer Ingelheim, consulting fees from AstraZeneca, Boehringer Ingelheim, Pharmacosmos, and Vifor, honoraria for lectures from AstraZeneca, Boehringer Ingelheim, and Vifor and participates in advisory boards for Vertex and NovoNordisk. PT has received speaker fees from W.L. Gore & Associates. All other authors have no conflicts of interest to declare. Funding: CJ holds a Clinical Academic Fellowship from the Chief Scientist Office (Scotland), fellowship number CAF/23/03. SK holds a post-doctoral clinical lectureship from the Chief Scientist Office (Scotland), grant number PCL/24/04. Authors‘ contributions: Conceptualization: CJ, KS, KG, PM, BJ, PT Methodology: CJ, KS, KG, PM, BJ Formal Analysis: CJ, KS, KG, PM, BE, BJ Investigation: CJ, PT Data curation: CJ, PT Writing- original draft: CJ Writing- review and editing: CJ, BE, SK, KS,KG, PT, PM, DK, BJ Supervision: BJ, KS, KG, PM Project administration: KG, BJ Funding acquisition: CJ All authors read and approved the final manuscript. Acknowledgements: We would like to acknowledge the valuable contribution made by the Public and Patient Involvement and Engagement group in the conceptualisation of this study. References Francis A, Harhay MN, Ong ACM, Tummalapalli SL, Ortiz A, Fogo AB, et al. Chronic kidney disease and the global public health agenda: an international consensus. Nat Rev Nephrol. 2024;20(7):473–85. Jager KJ, Kovesdy C, Langham R, Rosenberg M, Jha V, Zoccali C. A single number for advocacy and communication—worldwide more than 850 million individuals have kidney diseases. Kidney International. Volume 96. Elsevier B.V.; 2019. pp. 1048–50. Brown S, Garcia Sanchez JJ, Guiang H, Priest S, Wheeler DC, Moura AF et al. IMPACT CKD: Holistic Disease Model Projecting 10-Year Population Burdens. Kidney Int Rep. 2024. UK Renal Registry. (2022) UK Renal Registry 24th Annual Report – data to 31/12/2020, Bristol, UK. Available from https://ukkidney.org/audit-research/annual-report Murray E, Eid M, Traynor JP, Stevenson KS, Kasthuri R, Kingsmore DB, et al. The first 365 days on haemodialysis: Variation in the haemodialysis access journey and its associated burden. Nephrol Dialysis Transplantation. 2018;33(7):1244–50. Crowe K, Murray E, Macleod J, Thomson P, #4909 THE HEALTHCARE ACTIVITY BURDEN OF A HOME-BASED. TREATMENT: A SUMMARY OF THE FIRST 365 DAYS OF PERITONEAL DIALYSIS [Internet]. Available from: https://www.nice.org.uk/guidance/ta1035 Weeda ER, Su Z, Taber DJ, Bian J, Morinelli TA, Pilch NA et al. Hospital admissions and emergency department visits among kidney transplant recipients. Clin Transpl. 2019;33(5). Chadban S, Arıcı M, Power A, Wu MS, Mennini FS, Javier J et al. Projecting the economic burden of chronic kidney disease at the patient level (Inside CKD): a microsimulation modelling study [Internet]. 2024. Available from: Wong CKH, Chen J, Fung SKS, Mok MMY, Cheng YL, Kong I, et al. Direct and indirect costs of end-stage renal disease patients in the first and second years after initiation of nocturnal home haemodialysis, hospital haemodialysis and peritoneal dialysis. Nephrol Dialysis Transplantation. 2019;34(9):1565–76. Thomas ST, Sav A, Thomas R, Cardona M, Michaleff Z, Titus TT et al. Patient and physician perspectives on treatment burden in end-stage kidney disease: a nominal group technique study. BMJ Open. 2022;12(12). Mair FS, May CR. Thinking about the burden of treatment. Vol. 349, BMJ (Clinical research ed.). 2014. p. g6680. Lee JE, Lee J, Shin R, Oh O, Lee KS. Treatment burden in multimorbidity: an integrative review. BMC Primary Care [Internet]. 2024 Dec 1 [cited 2025 Jul 22];25(1):1–22. Available from: https://bmcprimcare.biomedcentral.com/articles/ 10.1186/s12875-024-02586-z Gupta A, Jensen EH, Virnig BA, Beg MS. Time-Related Burdens of Cancer Care. 18. Available from: https://doi.org/10.1200/OP.21.00662 Gupta A, Eisenhauer EA, Booth CM. The Time Toxicity of Cancer Treatment [Internet]. 2022. Available from: https://doi.org/10. Nwozichi C, Omolabake S, Ojewale MO, Faremi F, Brotobor D, Olaogun E, et al. Time toxicity in cancer care: A concept analysis using Walker and Avant’s method. Asia-Pacific Journal of Oncology Nursing. Volume 11. Asian Onscology Nursing Society; 2024. Banerjee R, Cowan AJ, Ortega M, Missimer C, Carpenter PA, Oshima MU, et al. Financial Toxicity, Time Toxicity, and Quality of Life in Multiple Myeloma. Clin Lymphoma Myeloma Leuk. 2024;24(7):446–e4543. Sentana-Lledo D, Morgans AK. Time’s up: the urgency to investigate time toxicity in patients with genitourinary malignancies. Therapeutic Advances in Medical Oncology. Volume 16. SAGE Publications Inc.; 2024. Nindra U, Shivasabesan G, Childs S, Yoon R, Haider S, Hong M et al. Time toxicity associated with early phase clinical trial participation. ESMO Open. 2023;8(6). Johnson WV, Blaes AH, Booth CM, Ganguli I, Gupta A. The unequal burden of time toxicity. Trends in Cancer. Volume 9. Cell; 2023. pp. 373–5. NHS Blood and Transplant. (2024). Annual Report and Accounts 2023-24 https://assets.publishing.service.gov.uk/media/66df23b99210ba34a3ebabdc/nhsbt-annual-report-and-accounts-2023-to-2024-accessible-version.pdf Cheng AC, Mem M, Levy MA. Determining Burden of Commuting for Treatment Using Online Mapping Services-A Study of Breast Cancer Patients. Zandbergen PA. Ensuring Confidentiality of Geocoded Health Data: Assessing Geographic Masking Strategies for Individual-Level Data. Adv Med. 2014;2014:1–14. Health Scotland P. Scottish Renal Registry Annual report 2024 A Management Information release for Scotland [Internet]. 2024. Available from: www.publichealthscotland.scot. Loeppenthin K, Dalton SO, Johansen C, Andersen E, Christensen MB, Pappot H et al. Total burden of disease in cancer patients at diagnosis—a Danish nationwide study of multimorbidity and redeemed medication. British Journal of Cancer 2020 123:6 [Internet]. 2020 Jul 7 [cited 2025 Jul 22];123(6):1033–40. Available from: https://www.nature.com/articles/s41416-020-0950-3 Christensen LD, Reilev M, Juul-Larsen HG, Jørgensen LM, Kaae S, Andersen O, et al. Use of prescription drugs in the older adult population-a nationwide pharmacoepidemiological study. Eur J Clin Pharmacol. 2019;75(8):1125–33. Turner JP, Shakib S, Singhal N, Hogan-Doran J, Prowse R, Johns S, et al. Prevalence and factors associated with polypharmacy in older people with cancer. Support Care Cancer. 2014;22(7):1727–34. Nicholson K, Liu W, Fitzpatrick D, Hardacre KA, Roberts S, Salerno J et al. Prevalence of multimorbidity and polypharmacy among adults and older adults: a systematic review. Lancet Healthy Longev [Internet]. 2024 Apr 1 [cited 2025 Jul 22];5(4):e287–96. Available from: https://www.thelancet.com/action/showFullText?pii=S2666756824000072 Lee CC, Hsu CC, Lin MH, Sung JM, Kuo TH. Healthcare utilization and expenditure among individuals with end-stage kidney disease in Taiwan. J Formos Med Assoc. 2022;121:S47–55. Jones CH, Dolsten M. Healthcare on the brink: navigating the challenges of an aging society in the United States. npj Aging 2024;10(1). Wammes JJG, Van Der Wees PJ, Tanke MAC, Westert GP, Jeurissen PPT. Systematic review of high-cost patients’ characteristics and healthcare utilisation. Volume 8. BMJ Open: BMJ Publishing Group; 2018. Jongejan M, de Lange S, Bos WJW, Pieterse AH, Konijn WS, van Buren M et al. Choosing conservative care in advanced chronic kidney disease: a scoping review of patients’ perspectives. Nephrology Dialysis Transplantation [Internet]. 2024 Mar 27 [cited 2025 Jul 22];39(4):659–68. Available from: https://dx.doi.org/10.1093/ndt/gfad196 Mendelssohn DC, Curtis B, Yeates K, Langlois S, MacRae JM, Semeniuk LM, et al. Suboptimal initiation of dialysis with and without early referral to a nephrologist. Nephrol Dialysis Transplantation. 2011;26(9):2959–65. Zhang Y, Baharani J. Dialysis education and options for late presenters—An ongoing dilemma. Hemodialysis International [Internet]. 2023 Jul 1 [cited 2025 Jul 22];27(3):224–30. Available from: https://onlinelibrary.wiley.com/doi/full/ 10.1111/hdi.13082 Tonelli M, Wiebe N, Knoll G, Bello A, Browne S, Jadhav D, et al. Systematic review: Kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant. 2011;11(10):2093–109. Rocque GB, Williams CP, Ingram SA, Azuero A, Mennemeyer ST, Young Pierce J, et al. Health care-related time costs in patients with metastatic breast cancer. Cancer Med. 2020;9(22):8423–31. Alzahrani N. The effect of hospitalization on patients’ emotional and psychological well-being among adult patients: An integrative review. Appl Nurs Res. 2021;61. Shippee ND, Shah ND, May CR, Mair FS, Montori VM. Cumulative complexity: A functional, patient-centered model of patient complexity can improve research and practice. J Clin Epidemiol. 2012;65(10):1041–51. Shippee ND, Allen SV, Leppin AL, May CR, Montori VM. Attaining minimally disruptive medicine: Context, challenges and a roadmap for implementation. J Royal Coll Physicians Edinb. 2015;45(2):118–22. Additional Declarations Competing interest reported. PM received grants from AstraZeneca and Boehringer Ingelheim, consulting fees from AstraZeneca, Boehringer Ingelheim, Pharmacosmos, and Vifor, honoraria for lectures from AstraZeneca, Boehringer Ingelheim, and Vifor and participates in advisory boards for Vertex and NovoNordisk. PT has received speaker fees from W.L. Gore & Associates. All other authors have no conflict of interest to declare. Cite Share Download PDF Status: Published Journal Publication published 23 Dec, 2025 Read the published version in BMC Nephrology → Version 1 posted Editorial decision: Revision requested 21 Oct, 2025 Reviews received at journal 20 Oct, 2025 Reviews received at journal 09 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviewers agreed at journal 01 Oct, 2025 Reviewers invited by journal 25 Sep, 2025 Editor assigned by journal 25 Sep, 2025 Editor invited by journal 22 Sep, 2025 Submission checks completed at journal 19 Sep, 2025 First submitted to journal 13 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7557511","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":525583851,"identity":"77adf14e-a71b-489b-81ae-6eb51e09fbe6","order_by":0,"name":"Catrin H 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14:37:12","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":134386,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7557511/v1/4c4a598dfa058c5d04f5736f.html"},{"id":93240334,"identity":"619b2394-2ae4-415a-8376-f0d995255e34","added_by":"auto","created_at":"2025-10-10 14:45:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108914,"visible":true,"origin":"","legend":"\u003cp\u003eSankey diagram demonstrating changes in modality over 36 months\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7557511/v1/f798354335f3b32ab0f216c8.png"},{"id":93239042,"identity":"a7a3a0ee-3dfc-4faf-8a8b-14eac19becc3","added_by":"auto","created_at":"2025-10-10 14:37:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":139319,"visible":true,"origin":"","legend":"\u003cp\u003eDeath censored average workload per month by modality\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7557511/v1/7f17abedc97dc3b32c13f270.png"},{"id":93239044,"identity":"4242def1-91e8-4e83-b377-a717ad1c5f2e","added_by":"auto","created_at":"2025-10-10 14:37:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":116961,"visible":true,"origin":"","legend":"\u003cp\u003eIncidence rate ratios for healthcare workload during peri-initiation and maintenance phases for KRT patients\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7557511/v1/c0ee492e4a780bf4c075ae64.png"},{"id":99172419,"identity":"06ddf8d9-dddf-4421-b6e9-bc8fa8c5537d","added_by":"auto","created_at":"2025-12-29 16:09:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1506813,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7557511/v1/e5ab2edd-3c59-4a06-a600-f0447f2b0e37.pdf"}],"financialInterests":"Competing interest reported. PM received grants from AstraZeneca and Boehringer Ingelheim, consulting fees from AstraZeneca, Boehringer Ingelheim, Pharmacosmos, and Vifor, honoraria for lectures from AstraZeneca, Boehringer Ingelheim, and Vifor and participates in advisory boards for Vertex and NovoNordisk.\nPT has received speaker fees from W.L. Gore \u0026 Associates.\nAll other authors have no conflict of interest to declare.","formattedTitle":"\u003cp\u003eHealthcare workload associated with transition onto kidney replacement therapy: a retrospective cohort study\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic kidney disease (CKD) is a global health priority (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) with an estimated prevalence of 850\u0026nbsp;million people worldwide(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The prevalence of both CKD and kidney replacement therapy (KRT) are both projected to increase considerably over the next 10 years(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Currently 8,254 adult patients start kidney replacement therapy every year in the UK, giving an incidence of 154 persons per million(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The transition from advanced CKD to KRT- either haemodialysis (HD), peritoneal dialysis (PD) or kidney transplantation (KTx)- is a complex phase in the patient journey with significant healthcare utilization (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This has considerable economic and systemic resource allocation implications(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), but also has a very human cost borne by the patients navigating this phase of their illness. The disruption caused by hospitalisations, frequent appointments and investigations, and attending dialysis are described as being particularly burdensome(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTreatment burden is the impact that fulfilling healthcare workload has on wellbeing(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). There is growing recognition of the importance of recognising treatment burden but as it is the subjective experience of patient of the impact of healthcare workload, burden cannot be directly inferred by only quantifying workload(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Time toxicity is defined as the time impact of medical treatment, including the time spent co-ordinating care, attending clinics, inpatient stays, imaging, travel to and from healthcare facilities, seeking urgent care for side-effects or deteriorations, and follow up tests (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). It has been widely described in oncology, where it has been noted to be a patient centred measure that encompasses the temporal burden of treatment, the disruption of daily life, the opportunity cost of losing time to do other things such as spending quality time with loved ones, the cumulative impact of a consistently high temporal burden on wellbeing and the emotional and psychological strain of treatment which can impact the efficiency of healthcare utilization(\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). For some patients the impact of the time spent pursuing cancer treatments can be so considerable it offsets the modest survival gains offered by treatment(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The temporal burden of healthcare workload and time toxicity has not been explored for patients in the context of KRT transition.\u003c/p\u003e\u003cp\u003eThe aim of this study is to describe patterns of healthcare workload as measured by time per month spent in healthcare contact in the six months leading up to KRT initiation and in the first 36 months of KRT, and describe patient characteristics associated with higher workload.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Settings\u003c/h2\u003e\u003cp\u003eThis was a retrospective cohort study of healthcare workload during transition onto KRT. All consecutive patients aged 18 or older that started any form of KRT in the Glasgow Renal and Transplant Unit, Glasgow, Scotland between 1st January 2015 and 31st December 2019 were included. The unit provides comprehensive renal services for NHS Greater Glasgow and Clyde and NHS Forth Valley health boards and renal transplant services for the West of Scotland, serving an estimated population of 1.5\u0026nbsp;million for general renal services and 2.6\u0026nbsp;million for renal transplantation. Participants were identified by interrogating the Strathclyde Electronic Renal Patient Record (SERPR, Vitalpulse, UK) system for all patients that had started KRT within the study period. Data were extracted for all recorded hospital based workload in SERPR from 6 months prior to starting KRT and for the first 36 months of KRT or until death, and categorised by which month in which they occurred relative to the KRT initiation date from Month \u0026minus;\u0026thinsp;6 to Month 36. Data collection ended on 31st December 2022. We elected to use 6 months prior to KRT initiation as it would capture most of the workload involved in KRT transition, and to follow up for 36 month as the average deceased donor kidney only transplant waitlist in the UK is 15.6 months(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) and therefore a follow up period of 36 months would capture the majority of the workload experienced by patients pursuing their first renal transplant. For analysis we subdivided the study period to two phases: peri-initiation (Month-6 to Month 6) and early maintenance (Month 7 to 36). Caldicott approval was granted to access and analyse the anonymised data.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eHealthcare workload and predictor measurement\u003c/h3\u003e\n\u003cp\u003eBaseline demographic data were extracted including age at KRT initiation, sex, ethnicity, primary renal disease, and number of repeat prescription medications at time of initiation. Home postcodes at time of initiation were used to categorise socioeconomic status using Scottish Index of Multiple Deprivation (SIMD) quintiles. Initial contact with nephrology services were noted, and patients who presented to renal services less than 90 days prior to KRT initiation were classified as late presenters. The exact date of KRT start was noted as well as the starting modality: HD, PD or KTx. Data on modality changes in the first 36 months of KRT were extracted including number of modality changes and type of change: PD or HD to Transplant (Incident Transplantation) and Transplant to HD or PD (Failed Transplant). For patients that died during the 36 month follow period date of death was recorded and converted to month of death relative to KRT initiation. Because of the degree of incomplete data, ethnicity was excluded from the final analysis. All renal related clinic visits including general nephrology, vascular access, transplant assessment, transplant follow up or PD clinic were recorded. All hospital inpatient admissions and length of stay were recorded, as were all diagnostic and interventional radiology workload, and all HD sessions. Commute times for all episodes of care were estimated from domiciliary post code.\u003c/p\u003e\u003cp\u003eThe outcome of interest was average time per month in hours spent on healthcare workload. The decision to use time as outcome was done following consultation with a Patient and Public Involvement and Engagement (PPIE) group. The length of inpatient stay was calculated from the admission and discharge date recorded on SERPR, we estimated that an outpatient clinic appointment lasted 30 minutes, imaging appointment lasted 1 hour, and a HD session lasted 5 hours from average appointment duration. Travel times were estimated by querying the Google Maps application programme interface (API) using an anonymised list of postcodes to provide coordinates to enable geocoding. All coordinates were then geographically masked by a process known as \u0026lsquo;jittering\u0026rsquo; to preserve patient anonymity. The API was then further queried for driving times between each set of coordinates and the hospital attended. These techniques are slightly less precise than using the exact street address for each patient, but were necessary to preserve anonymity(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Total time per month per participant from Month \u0026minus;\u0026thinsp;6 to Month 36 was calculated and this is our outcome measure. We censored the data for death to ensure accuracy and minimise bias from missing values.\u003c/p\u003e\u003cp\u003eAll variables were treated as categorical. Continuous variables were categorised for analysis. Age was categorised as 18\u0026ndash;44, 45\u0026ndash;64, 65\u0026ndash;74 and 75\u0026thinsp;+\u0026thinsp;in keeping with classification used by the Scottish Renal Registry(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Number of medications were categorised as \u0026lt;\u0026thinsp;10, 10\u0026ndash;15, and 15\u0026thinsp;+\u0026thinsp;as the average number of medications in our cohort was 12.5 and these categories reflect lower, average and higher medication burden.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analysis were conducted using R Statistical Software. Skew was measured with Fisher G1 and Bowley quartile skew. Univariate statistical analysis was undertaken with Krukal-Wallis test and effect size was calculated using \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e. Negative binomial multiple regression models were fitted for both the peri-initiation and maintenance periods and Incidence Rate Ratios (IRRs) were calculated to compare workloads. Statistical significance was set as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. As our dataset had low levels of missing data we conducted available case analysis. We censored the data for death so that average time per month was calculated only for the months patients were alive for in the analysis periods.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eDemographics\u003c/h2\u003e\u003cp\u003e1022 consecutive patients that started KRT for the first time between 1st January 2015 and 31st December 2019 were recruited. Healthcare workload data were collected for all for the six months prior to KRT start and for 36 months after or until death, giving a total of 1,104,158 observed days. 317 patients (31%) died during the follow up period.\u003c/p\u003e\u003cp\u003eThe demographic characteristics of the patients are categorised in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Median age at KRT start was 61 (IQR 50\u0026ndash;71; range 18\u0026ndash;90), 599/1,022 participants were male (58.6%) and 389/1,022 participants (38.2%) lived in Scottish Index of Multiple Deprivations (SIMD) 1 post codes which is the most deprived quintile. The most common primary renal disease (PRD) was diabetic nephropathy, reported in 319/1022 (31.2%) of participants. The median number of long-term medications at KRT start was 13 (IQR 9\u0026ndash;16, range 0\u0026ndash;36). Median distance from the hospital was 5.4 miles (IQR 3.2\u0026ndash;11.3; range 0.3\u0026ndash;145 miles), with a median travel time of 21 minutes (IQR 15.2\u0026ndash;30.6; range 2.5\u0026ndash;479 minutes).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic characteristics of participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u0026ndash;44: 176 (17.2%)\u003c/p\u003e\u003cp\u003e45\u0026ndash;64: 403 (39.4%)\u003c/p\u003e\u003cp\u003e65\u0026ndash;74: 225 (22.0%)\u003c/p\u003e\u003cp\u003e75+: 165 (16.1%)\u003c/p\u003e\u003cp\u003eNot recorded: 53 (5.2%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eM 599 (58.6%)\u003c/p\u003e\u003cp\u003eF 423 (41.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSIMD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 389 (38.2%)\u003c/p\u003e\u003cp\u003e2 203 (19.9%)\u003c/p\u003e\u003cp\u003e3 166 (16.3%)\u003c/p\u003e\u003cp\u003e4 135 (13.2%)\u003c/p\u003e\u003cp\u003e5 126 (12.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhite 287 (28.0%)\u003c/p\u003e\u003cp\u003eAsian 38 (3.7%)\u003c/p\u003e\u003cp\u003eBlack 11 (1.1%)\u003c/p\u003e\u003cp\u003eMixed 3 (0.3%)\u003c/p\u003e\u003cp\u003eOther 9 (0.8%)\u003c/p\u003e\u003cp\u003eNot recorded 674 (65.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary Renal Disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlomerular Disease 211 (20.7%)\u003c/p\u003e\u003cp\u003eTubulointerstitial Disease 148 (14.5%)\u003c/p\u003e\u003cp\u003eDiabetes 319 (31.2%)\u003c/p\u003e\u003cp\u003eHTN/Renovascular Disease 119 (11.7%)\u003c/p\u003e\u003cp\u003eOther systemic disease affecting the kidney 33 (3.2%)\u003c/p\u003e\u003cp\u003eFamilial/ hereditary 86 (8.4%)\u003c/p\u003e\u003cp\u003eMiscellaneous 100 (9.8%)\u003c/p\u003e\u003cp\u003eNot recorded 5 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of medications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;10: 263 (25.7%)\u003c/p\u003e\u003cp\u003e10\u0026ndash;15: 485 (47.5%)\u003c/p\u003e\u003cp\u003e\u0026gt;\u0026thinsp;15: 274 (26.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDistance from hospital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;10 miles: 749 (73.3%)\u003c/p\u003e\u003cp\u003e10\u0026ndash;20 miles: 109 (10.7%)\u003c/p\u003e\u003cp\u003e20\u0026ndash;30 miles: 116 (11.4%)\u003c/p\u003e\u003cp\u003e30\u0026thinsp;+\u0026thinsp;miles: 42 (4.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTravel time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;15 minutes: 245 (24.0%)\u003c/p\u003e\u003cp\u003e15\u0026ndash;30 minutes: 513 (50.2%)\u003c/p\u003e\u003cp\u003e30\u0026ndash;60 minutes: 206 (20.2%)\u003c/p\u003e\u003cp\u003e60\u0026ndash;120 minutes: 30 (2.9%)\u003c/p\u003e\u003cp\u003e120\u0026thinsp;+\u0026thinsp;minutes: 22 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLate presenter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLate: 86 (8.4%)\u003c/p\u003e\u003cp\u003eNot Late: 936 (91.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStarting Modality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaemodialysis 767 (75%)\u003c/p\u003e\u003cp\u003ePeritoneal Dialysis122 (11.9%)\u003c/p\u003e\u003cp\u003eKidney Transplant 133 (13.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModality changes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo changes: 730 (71.4%)\u003c/p\u003e\u003cp\u003e1 change: 230 (22.5%)\u003c/p\u003e\u003cp\u003e2\u0026thinsp;+\u0026thinsp;changes: 62 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExposure to transplant after PD/HD KRT start:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes: 245 (24.0%)\u003c/p\u003e\u003cp\u003eNo:777 (76.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExposure to failed transplant:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes: 21 (2.0%)\u003c/p\u003e\u003cp\u003eNo: 1001 (98%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStatus at 36 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHaemodialysis: 313 (30.6%)\u003c/p\u003e\u003cp\u003ePeritoneal Dialysis: 6 (0.6%)\u003c/p\u003e\u003cp\u003eTransplant: 386 (37.8%)\u003c/p\u003e\u003cp\u003eDead: 317 (31.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMost patient were known to nephrology services for more than 3 months prior to starting: only 86/1,022 (8.4%) were late presenters. HD was the most common starting modality with 767/1,022 (75%) starting on HD, 122 (11.9%) started on PD and 133 (13.0%) started KRT with a pre-emptive transplant. In the subsequent 36 months, 292 participants (28.6%) changed modality at least once and 317 (31%) died meaning that at 36 months post initiation 386 participants (37.8%) had a functioning transplant, 6 (0.6%) were on PD and 313 (30.6%) were on HD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eTemporal trends in workload\u003c/h2\u003e\u003cp\u003eTotal time per month was calculated for every participant for every month from Month \u0026minus;\u0026thinsp;6 pre KRT to Month 36 post initiation or until death both overall and subdivided by type of workload (Outpatient, Radiology, Inpatient, HD, Commuting), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Inpatient stays and HD sessions were the predominant drivers of workload. Overall time data had extreme right skew (Fisher g1\u0026thinsp;=\u0026thinsp;15.94, 95%CI 15.92\u0026ndash;15.97; Bowley skew\u0026thinsp;=\u0026thinsp;0.85, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) signifying that a small number of patients had very high workload. Degree of skewness varied between workload type: inpatient care was extremely right skewed with Fisher g1 of 17.73, 95%CI 17.71-17-76, and an unquantifiable quartile skewness as more than 75% of patient-months had no inpatient stay. HD sessions had a borderline right skew on Fisher g1: 0.49, 95%CI 0.47\u0026ndash;0.52) but strong right skew on Bowley quartile skew (1.00), which is in keeping with those not on HD not having any HD based workload but those on HD having consistently high and similar workloads. Similarly Radiology (Fisher g1\u0026thinsp;=\u0026thinsp;4.22, 95%CI 4.12\u0026ndash;4.24; Bowley skew\u0026thinsp;=\u0026thinsp;unquantifiable, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Outpatient clinic (Fisher g1\u0026thinsp;=\u0026thinsp;2.96, 95%CI 2.93\u0026ndash;2.98; Bowley skew\u0026thinsp;=\u0026thinsp;1.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Commute (Fisher g1\u0026thinsp;=\u0026thinsp;6.70, 95%CI 6.67\u0026ndash;6.72; Bowley skew\u0026thinsp;=\u0026thinsp;0.44, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) workloads all demonstrated marked right skew, but less extreme than inpatient workload.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTotal average death-censored time per month spent per activity (hours)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActivity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeri-initiation (Month \u0026minus;\u0026thinsp;6 to 6)\u003c/p\u003e\u003cp\u003e\u003cem\u003e(Mean/SD; Median/IQR)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEarly Maintenance (Month 7 to 36)\u003c/p\u003e\u003cp\u003e\u003cem\u003e(Mean/SD; Median/IQR)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal Time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean: 59.7 (164)\u003c/p\u003e\u003cp\u003eMedian: 3.53 (0.8\u0026ndash;71.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean: 50.5 (113)\u003c/p\u003e\u003cp\u003eMedian: 42.8 (0.0\u0026ndash;71.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutpatient clinic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean: 0.36 (0.54)\u003c/p\u003e\u003cp\u003eMedian: 0.0 (0.0-0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean:0.22 (0.47)\u003c/p\u003e\u003cp\u003eMedian:0.0 (0.0-0.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRadiology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean: 0.66 (1.36)\u003c/p\u003e\u003cp\u003eMedian:0.0 (0.0\u0026ndash;1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean: 0.41(1.02)\u003c/p\u003e\u003cp\u003eMedian:0.0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInpatient care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean: 36.4 (169.0)\u003c/p\u003e\u003cp\u003eMedian: 0.0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean: 16.1 (106.0)\u003c/p\u003e\u003cp\u003eMedian: 0.0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHD sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean: 23.3 (32.6)\u003c/p\u003e\u003cp\u003eMedian: 0.0 (0.0\u0026ndash;60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean: 36.8 (32.5)\u003c/p\u003e\u003cp\u003eMedian:55.0 (0\u0026ndash;65.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCommute\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean: 2.70 (4.79)\u003c/p\u003e\u003cp\u003eMedian:1.1 (0.3\u0026ndash;3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean: 3.42 (4.89)\u003c/p\u003e\u003cp\u003eMedian:2.5 (0.4\u0026ndash;4.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen considering temporal patterns of workload, workload patterns differed depending on starting modality (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). All modalities had an acute initiation workload spike at between Month \u0026minus;\u0026thinsp;1 and Month 1 mostly driven by inpatient stay, but this is less pronounced in those who stated on PD. The increase in inpatient workload starts earlier for HD and PD patients in the pre-KRT period as compared to transplant, likely representing inpatient admissions for vascular access creation, PD catheter insertion and medical optimisation. Post KRT initiation, transplant workload rapidly decreases over first six months and settles to a very low baseline. Haemodialysis workload also settles, but to a higher baseline with regular HD sessions. Peritoneal dialysis hospital-based workload is lower in the immediate initiation period but has ongoing spikes in inpatient stays and a slowly increasing rate of HD workload which is in keeping with patients experiencing PD complications and transitioning onto HD or being transplanted: of the 122 patients that start KRT on PD only 6 remain on PD at 36 months.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssociation between patient characteristics and workload\u003c/h3\u003e\n\u003cp\u003eOn univariate analysis every categorical domain except sex for both peri-initiation and maintenance, and failed transplant for maintenance, had a signal for association with a difference in workload [Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePatient characteristics associated with higher workload: Kruskal-Wallis univariate analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePeri-initiation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMaintenance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.39\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.34\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePRD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.07\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.12\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.06\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.09\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLate Presentation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModality change\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.07\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncident Transplant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSIMD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFailed transplant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.985\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.657\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eE\u003csup\u003e2\u003c/sup\u003e effect size: \u0026lt;0.01 neglible, 0.01\u0026ndash;0.06 small, 0.06\u0026ndash;0.14 moderate, \u0026gt;\u0026thinsp;0.14 large\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the negative binomial multivariate regression model (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) PD and Transplant were associated with significantly lower workloads compared to HD. The difference between Transplant and HD in Months 7\u0026ndash;36 was particularly marked (IRR 0.04 (0.03\u0026ndash;0.05)), which means that the average monthly workload was 96% lower in pre-emptive transplant patients compared to those who started on HD. Incident transplantation- being transplanted within the 36 month follow up period after starting KRT on either PD or HD- was also associated with lower workload (peri-initiation IRR 0.73 (0.57\u0026ndash;0.92), maintenance 0.37 (0.28\u0026ndash;0.49). Female sex was associated with a small increased workload (peri-initiation IRR 1.16 (1.07\u0026ndash;1.24), early maintenance 1.17 (1.05\u0026ndash;1.31)), and being on more than 15 long-term medications was also associated with a consistently higher workload (IRR 1.36 (1.20\u0026ndash;1.55) peri-initiation, 1.35 (1.15\u0026ndash;1.59) maintenance).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociation between patient characteristics and workload: a negative binomial model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable (*=reference)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePeri initiation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMaintenance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIRR (95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIRR (95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.16 (1.07\u0026ndash;1.24)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.17 (1.05\u0026ndash;1.31)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSIMD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u0026ndash;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.97 (0.88\u0026ndash;1.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.539\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.10 (0.97\u0026ndash;1.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePRD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlomerular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTubulointestitial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.92 (0.79\u0026ndash;1.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.292\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.88 (0.73\u0026ndash;1.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.193\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.15 (1.01\u0026ndash;1.31)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.12 (0.96\u0026ndash;1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.160\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.02 (0.87\u0026ndash;1.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00 (0.82\u0026ndash;1.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther systemic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.13 (0.88\u0026ndash;1.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02 (0.75\u0026ndash;1.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.893\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamilial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.86 (0.72\u0026ndash;1.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.90 (0.72\u0026ndash;1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.360\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiscellaneous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.03 (0.87\u0026ndash;1.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.07 (0.87\u0026ndash;1.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.535\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnknown\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.83 (0.48\u0026ndash;1.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.537\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.41 (0.19\u0026ndash;1.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLate Presentation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot Late\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.39 (1.18\u0026ndash;1.65)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01 (0.82\u0026ndash;1.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.905\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncident Transplant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.73 (0.57\u0026ndash;0.92)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.37 (0.28\u0026ndash;0.49)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFailed Transplant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.04 (0.77\u0026ndash;1.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.794\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e2.30 (1.61\u0026ndash;3.41)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModality Change\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.98 (0.79\u0026ndash;1.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.44 (1.08\u0026ndash;1.94)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.06 (0.93\u0026ndash;1.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.16 (1.00-1.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e65\u0026ndash;74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.12 (0.97\u0026ndash;1.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.24 (1.03\u0026ndash;1.48)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e75+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.16 (0.98\u0026ndash;1.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.27 (1.04\u0026ndash;1.57)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026ndash;15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.09 (0.98\u0026ndash;1.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.07 (0.92\u0026ndash;1.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.380\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e1.36 (1.20\u0026ndash;1.55)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1.35 (1.15\u0026ndash;1.59)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHaemodialysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeritoneal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.41 (0.35\u0026ndash;0.47)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.47 (0.39\u0026ndash;0.57)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTransplant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e0.36 (0.31\u0026ndash;0.42)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.04 (0.03\u0026ndash;0.05)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eLate presentation to nephrology (IRR 1.39 (1.18\u0026ndash;1.65)) was associated with higher workload in the peri-initiation period but was not associated with a difference in workload in the maintenance period. Conversely, age had no significant effect on workload in the peri-initiation period but older age (65\u0026ndash;74 (IRR 1.24(1.03\u0026ndash;1.48)), 75+ (IRR 1.27(1.04\u0026ndash;1.57))) was associated with higher workload in the maintenance period. Modality change (IRR 1.44(1.08\u0026ndash;1.94)) and failed transplant (IRR 2.30 (1.61\u0026ndash;3.41)) were also associated with higher workload in the maintenance period whilst having no significant effect on workload peri-initiation.\u003c/p\u003e\u003cp\u003eThere was no association between SIMD and workload, and with the exception of a small increase in workload for those with diabetic nephropathy peri-initiation (IRR 1.15(1.01\u0026ndash;1.31)), there was no association between workload and PRD either.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides a detailed analysis of hospital-based healthcare workload derived from an EHR in the 6 months leading up to KRT initiation and the 36 months following. This allows for visualisation of the time burden of hospital based healthcare workload and how it evolves. We have demonstrated considerable variation in healthcare workload across the cohort; with haemodialysis, older age, high medication burden, late presentation, and complications such as modality changes and failed transplant all associated with higher workload. The use of time as a proxy measure for the burden of healthcare workload is novel in this population.\u003c/p\u003e\u003cp\u003eHigh medication burden, which could be seen as a surrogate measure for multimorbidity(\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), was consistently associated with higher workload. The interaction between patient factors such as multimorbidity, frailty and older age with disease severity factors requiring more intensive treatment regimens creating subsets of patients with very high healthcare utilization is reflected in both renal specific(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) and general (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) health economics literature. Frailty and severity of comorbidity could also curtail suitability for transplant and mark a high risk for ongoing high healthcare workload, and the data from this study could help delineate populations for whom the burden of ongoing kidney care outweighs benefit to their quality of life, and inform discussions around conservative care(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePatients who present \u0026lsquo;late\u0026rsquo;, defined as being referred to nephrology less than 3 months from KRT start, often miss out on outpatient pre-dialysis education and opportunities to prepare for optimal KRT starts such as pre-emptive transplantation, pre-emptive vascular access creation and PD counselling(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). It is therefore not surprising that their peri-initiation workload is higher than those referred earlier. It is interesting that their workload in the maintenance period (7\u0026ndash;36 months) is no longer higher, suggesting that the increased workload around initiation is being driven by the lateness of their presentation and clinicians and services should be mindful of the higher needs of those with unexpected KRT starts especially around the time of initiation.\u003c/p\u003e\u003cp\u003eThe most striking finding of this study is the marked reduction in healthcare workload associated with kidney transplantation. The beneficial effect of kidney transplantation on reducing healthcare utilisation and on improving quality of life is already known(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), and this study contributes to the body of evidence that the timely pursuit of transplantation in potentially eligible patients is key in reducing workload and burden in advanced CKD patients.\u003c/p\u003e\u003cp\u003eThe use of time as a patient-centred aggregate measure of healthcare workload in kidney disease is novel. The impact of the time commitments involved in commuting to treatment and the considerable time burden of hospitalisation for the minority that require it is similar to that found for metastatic breast cancer care(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and multiple myeloma(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The negative impact of hospitalisation on patients\u0026rsquo; psychological wellbeing is well documented(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). However, care must be taken in inferring that all time used on healthcare workload is detrimental or that lack of time is necessarily superior: kidney failure is a life-threatening disease state that requires extensive healthcare input. Difficulty accessing healthcare could be a detrimental reason for less time spent on healthcare workload. Premature discharge from hospital or insufficient clinic appointments could constitute an inappropriate transfer of work from hospital clinicians to patients or to primary care(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Further qualitative work is required to understand what aspects of healthcare workload are most burdensome, how patient capacity affects experiences of workload, and how the burden of treatment could be mitigated.\u003c/p\u003e\u003cp\u003eThe use of SERPR as a data source brought both strengths and limitations. The use of SERPR as a renal specific EPR provides highly granular and accurate data for healthcare workload within the Glasgow renal services which is a strength of this study. However, it does not capture outpatient clinics with other specialities, hospital workload in health boards other than NHS GGC and NHS FV, healthcare contact with primary care and other community services, or work undertaken at home which is a particular limitation when considering PD or home HD. SERPR also only captures the number, date and type of healthcare episode and does not capture the exact time spent by the patient in the hospital and therefore we needed to extrapolate estimated time from the SERPR data which introduced a degree of imprecision into our study. SERPR also does not capture healthcare workload that takes place in the home, which could lead to the workload associated with home therapies such as peritoneal dialysis and haemodialysis being severely underestimated. This is a single-centre study, albeit covering a wide geographical area with multiple sites and teams, and this potentially limits its generalisability.\u003c/p\u003e\u003cp\u003eIn conclusion, this study is a comprehensive exploration of healthcare workload associated with transition onto kidney replacement therapy. A key finding is the profound protective effect of transplantation on workload, reinforcing the importance of timely and proactive pursuit of transplantation for potentially eligible patients and the vital importance of strategies improving the availability of both live donor transplantation and organ availability and utilisation in deceased donor transplantation. Secondly, there are a group of older multimorbid patients on haemodialysis who have a much higher than average workload. This study could help inform discussions around wishes around care, and if the benefits of undertaking time consuming treatment still outweighs the burden.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCKD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eChronic Kidney Disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHaemodialysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIRR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIncidence Rate Ratios\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eKRT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eKidney Replacement Therapy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eKTx\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eKidney Transplant\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePeritoneal Dialysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePPIE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePatient and Public Involvement and Engagement\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSERPR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStrathclyde Electronic Renal Patient Record\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSIMD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eScottish Index of Multiple Deprivation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConsent to participate and ethics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs this study was based on retrospective secondary analysis of anonymised routinely collected clinical data, IRB review was waivered and permission was granted to access the data and for governance from the NHS Greater Glasgow and Clyde Caldicott Guardian and the study was conducted in line with the Declaration of Helsinki. Also as a result of this study being secondary analysis of routinely collected anonymised data individual consent for participation was deemed not to be required in line with MRC guidelines \u0026lsquo;Using information about people in health research\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThis study used only anonymised, routinely collected data, and no identifiable individual data are presented.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that supports the findings of this study are available from the corresponding author upon reasonable request. Due to the nature of the data and participant confidentiality, restrictions apply to the availability of these data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePM received grants from AstraZeneca and Boehringer Ingelheim, consulting fees from AstraZeneca, Boehringer Ingelheim, Pharmacosmos, and Vifor, honoraria for lectures from AstraZeneca, Boehringer Ingelheim, and Vifor and participates in advisory boards for Vertex and NovoNordisk.\u003c/p\u003e\n\u003cp\u003ePT has received speaker fees from W.L. Gore \u0026amp; Associates.\u003c/p\u003e\n\u003cp\u003eAll other authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCJ holds a Clinical Academic Fellowship from the Chief Scientist Office (Scotland), fellowship number CAF/23/03.\u003c/p\u003e\n\u003cp\u003eSK holds a post-doctoral clinical lectureship from the Chief Scientist Office (Scotland), grant number PCL/24/04.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026lsquo; contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: CJ, KS, KG, PM, BJ, PT\u003c/p\u003e\n\u003cp\u003eMethodology: CJ, KS, KG, PM, BJ\u003c/p\u003e\n\u003cp\u003eFormal Analysis: CJ, KS, KG, PM, BE, BJ\u003c/p\u003e\n\u003cp\u003eInvestigation: CJ, PT\u003c/p\u003e\n\u003cp\u003eData curation: CJ, PT\u003c/p\u003e\n\u003cp\u003eWriting- original draft: CJ\u003c/p\u003e\n\u003cp\u003eWriting- review and editing: CJ, BE, SK, KS,KG, PT, PM, DK, BJ\u003c/p\u003e\n\u003cp\u003eSupervision: BJ, KS, KG, PM\u003c/p\u003e\n\u003cp\u003eProject administration: KG, BJ\u003c/p\u003e\n\u003cp\u003eFunding acquisition: CJ\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge the valuable contribution made by the Public and Patient Involvement and Engagement group in the conceptualisation of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFrancis A, Harhay MN, Ong ACM, Tummalapalli SL, Ortiz A, Fogo AB, et al. Chronic kidney disease and the global public health agenda: an international consensus. Nat Rev Nephrol. 2024;20(7):473\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJager KJ, Kovesdy C, Langham R, Rosenberg M, Jha V, Zoccali C. A single number for advocacy and communication\u0026mdash;worldwide more than 850 million individuals have kidney diseases. Kidney International. Volume 96. Elsevier B.V.; 2019. pp. 1048\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrown S, Garcia Sanchez JJ, Guiang H, Priest S, Wheeler DC, Moura AF et al. IMPACT CKD: Holistic Disease Model Projecting 10-Year Population Burdens. Kidney Int Rep. 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUK Renal Registry. (2022) UK Renal Registry 24th Annual Report \u0026ndash; data to 31/12/2020, Bristol, UK. Available from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ukkidney.org/audit-research/annual-report\u003c/span\u003e\u003cspan address=\"https://ukkidney.org/audit-research/annual-report\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMurray E, Eid M, Traynor JP, Stevenson KS, Kasthuri R, Kingsmore DB, et al. The first 365 days on haemodialysis: Variation in the haemodialysis access journey and its associated burden. Nephrol Dialysis Transplantation. 2018;33(7):1244\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCrowe K, Murray E, Macleod J, Thomson P, #4909 THE HEALTHCARE ACTIVITY BURDEN OF A HOME-BASED. TREATMENT: A SUMMARY OF THE FIRST 365 DAYS OF PERITONEAL DIALYSIS [Internet]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nice.org.uk/guidance/ta1035\u003c/span\u003e\u003cspan address=\"https://www.nice.org.uk/guidance/ta1035\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWeeda ER, Su Z, Taber DJ, Bian J, Morinelli TA, Pilch NA et al. Hospital admissions and emergency department visits among kidney transplant recipients. Clin Transpl. 2019;33(5).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChadban S, Arıcı M, Power A, Wu MS, Mennini FS, Javier J et al. Projecting the economic burden of chronic kidney disease at the patient level (Inside CKD): a microsimulation modelling study [Internet]. 2024. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.thelancet.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWong CKH, Chen J, Fung SKS, Mok MMY, Cheng YL, Kong I, et al. Direct and indirect costs of end-stage renal disease patients in the first and second years after initiation of nocturnal home haemodialysis, hospital haemodialysis and peritoneal dialysis. Nephrol Dialysis Transplantation. 2019;34(9):1565\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThomas ST, Sav A, Thomas R, Cardona M, Michaleff Z, Titus TT et al. Patient and physician perspectives on treatment burden in end-stage kidney disease: a nominal group technique study. BMJ Open. 2022;12(12).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMair FS, May CR. Thinking about the burden of treatment. Vol. 349, BMJ (Clinical research ed.). 2014. p. g6680.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee JE, Lee J, Shin R, Oh O, Lee KS. Treatment burden in multimorbidity: an integrative review. BMC Primary Care [Internet]. 2024 Dec 1 [cited 2025 Jul 22];25(1):1\u0026ndash;22. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bmcprimcare.biomedcentral.com/articles/\u003c/span\u003e\u003cspan address=\"https://bmcprimcare.biomedcentral.com/articles/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12875-024-02586-z\u003c/span\u003e\u003cspan address=\"10.1186/s12875-024-02586-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGupta A, Jensen EH, Virnig BA, Beg MS. Time-Related Burdens of Cancer Care. 18. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1200/OP.21.00662\u003c/span\u003e\u003cspan address=\"10.1200/OP.21.00662\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGupta A, Eisenhauer EA, Booth CM. The Time Toxicity of Cancer Treatment [Internet]. 2022. Available from: https://doi.org/10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNwozichi C, Omolabake S, Ojewale MO, Faremi F, Brotobor D, Olaogun E, et al. Time toxicity in cancer care: A concept analysis using Walker and Avant\u0026rsquo;s method. Asia-Pacific Journal of Oncology Nursing. Volume 11. Asian Onscology Nursing Society; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBanerjee R, Cowan AJ, Ortega M, Missimer C, Carpenter PA, Oshima MU, et al. Financial Toxicity, Time Toxicity, and Quality of Life in Multiple Myeloma. Clin Lymphoma Myeloma Leuk. 2024;24(7):446\u0026ndash;e4543.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSentana-Lledo D, Morgans AK. Time\u0026rsquo;s up: the urgency to investigate time toxicity in patients with genitourinary malignancies. Therapeutic Advances in Medical Oncology. Volume 16. SAGE Publications Inc.; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNindra U, Shivasabesan G, Childs S, Yoon R, Haider S, Hong M et al. Time toxicity associated with early phase clinical trial participation. ESMO Open. 2023;8(6).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJohnson WV, Blaes AH, Booth CM, Ganguli I, Gupta A. The unequal burden of time toxicity. Trends in Cancer. Volume 9. Cell; 2023. pp. 373\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNHS Blood and Transplant. (2024). Annual Report and Accounts 2023-24 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://assets.publishing.service.gov.uk/media/66df23b99210ba34a3ebabdc/nhsbt-annual-report-and-accounts-2023-to-2024-accessible-version.pdf\u003c/span\u003e\u003cspan address=\"https://assets.publishing.service.gov.uk/media/66df23b99210ba34a3ebabdc/nhsbt-annual-report-and-accounts-2023-to-2024-accessible-version.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng AC, Mem M, Levy MA. Determining Burden of Commuting for Treatment Using Online Mapping Services-A Study of Breast Cancer Patients.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZandbergen PA. Ensuring Confidentiality of Geocoded Health Data: Assessing Geographic Masking Strategies for Individual-Level Data. Adv Med. 2014;2014:1\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHealth Scotland P. Scottish Renal Registry Annual report 2024 A Management Information release for Scotland [Internet]. 2024. Available from: www.publichealthscotland.scot.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLoeppenthin K, Dalton SO, Johansen C, Andersen E, Christensen MB, Pappot H et al. Total burden of disease in cancer patients at diagnosis\u0026mdash;a Danish nationwide study of multimorbidity and redeemed medication. British Journal of Cancer 2020 123:6 [Internet]. 2020 Jul 7 [cited 2025 Jul 22];123(6):1033\u0026ndash;40. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nature.com/articles/s41416-020-0950-3\u003c/span\u003e\u003cspan address=\"https://www.nature.com/articles/s41416-020-0950-3\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChristensen LD, Reilev M, Juul-Larsen HG, J\u0026oslash;rgensen LM, Kaae S, Andersen O, et al. Use of prescription drugs in the older adult population-a nationwide pharmacoepidemiological study. Eur J Clin Pharmacol. 2019;75(8):1125\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTurner JP, Shakib S, Singhal N, Hogan-Doran J, Prowse R, Johns S, et al. Prevalence and factors associated with polypharmacy in older people with cancer. Support Care Cancer. 2014;22(7):1727\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNicholson K, Liu W, Fitzpatrick D, Hardacre KA, Roberts S, Salerno J et al. Prevalence of multimorbidity and polypharmacy among adults and older adults: a systematic review. Lancet Healthy Longev [Internet]. 2024 Apr 1 [cited 2025 Jul 22];5(4):e287\u0026ndash;96. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.thelancet.com/action/showFullText?pii=S2666756824000072\u003c/span\u003e\u003cspan address=\"https://www.thelancet.com/action/showFullText?pii=S2666756824000072\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee CC, Hsu CC, Lin MH, Sung JM, Kuo TH. Healthcare utilization and expenditure among individuals with end-stage kidney disease in Taiwan. J Formos Med Assoc. 2022;121:S47\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJones CH, Dolsten M. Healthcare on the brink: navigating the challenges of an aging society in the United States. npj Aging 2024;10(1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWammes JJG, Van Der Wees PJ, Tanke MAC, Westert GP, Jeurissen PPT. Systematic review of high-cost patients\u0026rsquo; characteristics and healthcare utilisation. Volume 8. BMJ Open: BMJ Publishing Group; 2018.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJongejan M, de Lange S, Bos WJW, Pieterse AH, Konijn WS, van Buren M et al. Choosing conservative care in advanced chronic kidney disease: a scoping review of patients\u0026rsquo; perspectives. Nephrology Dialysis Transplantation [Internet]. 2024 Mar 27 [cited 2025 Jul 22];39(4):659\u0026ndash;68. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dx.doi.org/10.1093/ndt/gfad196\u003c/span\u003e\u003cspan address=\"10.1093/ndt/gfad196\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMendelssohn DC, Curtis B, Yeates K, Langlois S, MacRae JM, Semeniuk LM, et al. Suboptimal initiation of dialysis with and without early referral to a nephrologist. Nephrol Dialysis Transplantation. 2011;26(9):2959\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Y, Baharani J. Dialysis education and options for late presenters\u0026mdash;An ongoing dilemma. Hemodialysis International [Internet]. 2023 Jul 1 [cited 2025 Jul 22];27(3):224\u0026ndash;30. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://onlinelibrary.wiley.com/doi/full/\u003c/span\u003e\u003cspan address=\"https://onlinelibrary.wiley.com/doi/full/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/hdi.13082\u003c/span\u003e\u003cspan address=\"10.1111/hdi.13082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTonelli M, Wiebe N, Knoll G, Bello A, Browne S, Jadhav D, et al. Systematic review: Kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant. 2011;11(10):2093\u0026ndash;109.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRocque GB, Williams CP, Ingram SA, Azuero A, Mennemeyer ST, Young Pierce J, et al. Health care-related time costs in patients with metastatic breast cancer. Cancer Med. 2020;9(22):8423\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlzahrani N. The effect of hospitalization on patients\u0026rsquo; emotional and psychological well-being among adult patients: An integrative review. Appl Nurs Res. 2021;61.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShippee ND, Shah ND, May CR, Mair FS, Montori VM. Cumulative complexity: A functional, patient-centered model of patient complexity can improve research and practice. J Clin Epidemiol. 2012;65(10):1041\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShippee ND, Allen SV, Leppin AL, May CR, Montori VM. Attaining minimally disruptive medicine: Context, challenges and a roadmap for implementation. J Royal Coll Physicians Edinb. 2015;45(2):118\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Chronic kidney disease, healthcare workload, kidney replacement therapy, time toxicity, treatment burden","lastPublishedDoi":"10.21203/rs.3.rs-7557511/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7557511/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and hypothesis.\u003c/h2\u003e\u003cp\u003eTransition onto kidney replacement therapy (KRT) is a complex, intensive phase for patients with advanced chronic kidney disease (CKD), characterised by high healthcare utilisation. Frequent outpatient visits, surgical and radiological procedures, hospitalisations and haemodialysis (HD) sessions impose a significant time burden on patients. The concept of time toxicity is widely described in oncology, and captures the disruption to patients\u0026rsquo; lives due to treatment-related demands. We aimed to quantify time- based healthcare workload during the transition onto KRT and identify patient characteristics associated with increased workload.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e\u003cp\u003eWe conducted a retrospective cohort study including all consecutive adults initiating KRT (haemodialysis (HD), peritoneal dialysis (PD), or pre-emptive transplantation (KTx)) in the Glasgow Renal and Transplant Unit between January 2015 and December 2019. Routinely collected electronic health record data were used to estimate time spent per month on healthcare-related activities (outpatient appointments, radiology, inpatient admissions, HD sessions, and travel) from 6 months pre- to 36 months post-KRT initiation. Workload was analysed as a time-based outcome (hours/month). Univariate analysis used Kruskal-Wallis testing; multivariate modelling employed negative binomial regression.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e\u003cp\u003eA total of 1,022 patients (58.6% male; median age 61 years) contributed over 1.1\u0026nbsp;million patient-days. Median healthcare workload peaked around KRT initiation and was highest in HD patients. Kidney transplantation was associated with markedly lower workload post-initiation (IRR 0.04). Increased workload was associated with female sex, polypharmacy (\u0026gt;\u0026thinsp;15 medications), late referral, older age (in maintenance phase), and modality change or failed transplant. Socioeconomic deprivation and primary renal disease were not significantly associated with higher workload.\u003c/p\u003e\u003ch2\u003eConclusion.\u003c/h2\u003e\u003cp\u003eHealthcare workload during KRT transition is substantial and varies widely. Transplantation is associated with significantly lower workload. These findings support timely transplant planning and underscore the importance of considering the time burden of healthcare experienced by patients when discussing treatment options.\u003c/p\u003e","manuscriptTitle":"Healthcare workload associated with transition onto kidney replacement therapy: a retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-10 14:37:07","doi":"10.21203/rs.3.rs-7557511/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-21T10:40:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-20T22:47:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-10T01:03:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28148043154227735842345819216833418222","date":"2025-10-06T19:36:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71440463549108667616759671952568252053","date":"2025-10-06T16:33:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"249986431700155127274597377482111890050","date":"2025-10-01T05:28:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-26T03:43:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-26T03:36:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-22T11:51:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-19T11:00:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2025-09-13T17:02:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10a669a3-170a-4a73-b598-3427e2a4ccda","owner":[],"postedDate":"October 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T16:03:18+00:00","versionOfRecord":{"articleIdentity":"rs-7557511","link":"https://doi.org/10.1186/s12882-025-04693-0","journal":{"identity":"bmc-nephrology","isVorOnly":false,"title":"BMC Nephrology"},"publishedOn":"2025-12-23 15:57:24","publishedOnDateReadable":"December 23rd, 2025"},"versionCreatedAt":"2025-10-10 14:37:07","video":"","vorDoi":"10.1186/s12882-025-04693-0","vorDoiUrl":"https://doi.org/10.1186/s12882-025-04693-0","workflowStages":[]},"version":"v1","identity":"rs-7557511","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7557511","identity":"rs-7557511","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}