Abstract
Background
Efficient arteriovenous vascular access (VA) surveillance is vital for early identification of dysfunctional access, allowing timely intervention to prevent thrombosis. This study compares the efficacy of adding remote software surveillance to standard clinical care across our units.
Methods
We conducted a 12-month prospective study on maintenance haemodialysis (HD) patients using Vasc-Alert software technology to assist clinical decision-making in 2 satellite HD units (group 1) and standard care in the remaining 3 HD units (group 2). Patients with Vasc-Alert-derived high Access Risk Score (ARS) (≥7) underwent clinical assessment and were referred for fistulogram based on relevant Kidney Disease Outcome Quality Initiative (KDOQI) criteria. Data on referrals for fistulogram, subsequent VA events, access abandonment, and complication-free days-extended (CFD-extended) were collected. VA survival analysis of post-intervention primary patency rate at 3 and 6 months was conducted.
Results
There were 23 (28.1%) pre-emptive correction of stenosis and 6 (7.3%) thrombosis episodes in group 1, compared to 40 (19.5%) and 21 (10.2%) in group 2 (p value 0.155, 0.587), respectively). Among the thrombotic episodes, 83% of cases in group 1 had been detected during surveillance and referred for diagnostic fistulogram ± angioplasty but developed thrombosis while awaiting elective intervention compared to 19% in group 2 (p = 0.004). Median time from fistulogram request to thrombosed VA was 26 days (interquartile range: 21–42 days). Group 1 exhibited better post-intervention primary patency rates and longer CFD compared to group 2 (p value <0.001, 0.002, respectively).
Conclusion
Incorporating Vasc-Alert technology into VA clinical surveillance pathway was associated with improved early detection of high-risk VA, higher primary patency rates, and longer CFD-extended compared to standard of care. Improving elective interventional radiology capacity for timely intervention (<3 weeks from referral) is crucial to materialise the benefits of enhanced surveillance in preventing acute thrombosis.
Keywords: Haemodialysis, Pre-emptive stenosis correction, Surveillance, Vascular access, Vasc-Alert technology
Introduction
Ensuring optimal arteriovenous vascular access (VA) function is paramount for haemodialysis (HD) patients, both clinically and as a research focus, with it being a core outcome in VA clinical trials [1]. VA stenosis and subsequent thrombosis are associated with significant patient morbidity and pose a heavy financial burden on healthcare systems [2]. Implementing a robust VA monitoring and surveillance program is crucial for maintaining access patency and reducing healthcare costs by pre-emptively addressing clinically significant stenosis and preventing VA thrombosis and subsequent loss [3].
Arteriovenous access flow dysfunction, as defined by Kidney Disease Outcome Quality Initiative (KDOQI), refers to clinically significant flow or patency abnormalities due to underlying stenosis or thrombosis [3]. Widely researched non-invasive methods for detecting significant VA stenosis include regular assessment of access blood flow either directly using colour Doppler US, or indirectly, with the ultrasound diluted technique [4]. These methods require additional dedicated staff resource and specialised equipment, the measurements are operator-dependent, and they have not shown to improve outcomes in VA survival and have not been recommended by KDOQI recommendations as primary means of VA surveillance [4]. KDOQI recommends regular physical examination to detect selected clinical indicators of flow dysfunction and specifies that additional surveillance techniques are supplementary and action should not be based solely on surveillance findings [3].
Vasc-Alert is an FDA-approved remote surveillance method for permanent VA [5]. It utilises pressure and flow measurements retrieved on regular intervals during each treatment session and can generate an Access Risk Score (ARS) without the need for additional trained personnel or equipment [6]. We previously conducted a retrospective evaluation of this technology in our centre [7]. In this prospective cohort study, we compared the supplementary use of Vasc-Alert technology to routine clinical monitoring, compared to routine clinical monitoring alone.
Patients and Methods
Study Design
This was a single-centre prospective observational cohort study over 12 months (2023).
Study Population
All adult patients over 18 years, on maintenance HD (>3 months on HD) receiving their dialysis via a permanent VA (arteriovenous fistula or graft) at all the 5 dialysis units of our centre were included. Patients dialysing via central venous catheter (temporary or long-term lines) were excluded. Demographic and clinical data were collected from the electronic patient record, including prior access stenosis (identified as previous access angioplasty), date of referral for VA angiogram/plasty, subsequent VA events (pre-emptive correction of stenosis or thrombosis), and access abandonment (i.e., unsalvageable access loss).
Study Groups
Vasc-Alert technology was used as a supplementary technique to routine clinical care consisting of bimonthly clinical review in 2 HD satellite units (group 1) and routine care continued in the remaining 3 HD units (group 2).
VA Pathway Routine Clinical Care
Routine clinical care is based on clinical examination and review of dialysis access parameters. In all 5 HD units, a vascular access multidisciplinary team (VA MDT) meets every month consisting of a HD consultant from the respective unit, a VA specialist nurse, and HD nurses. Medical and nursing staff refer cases for review at the MDT and patients are planned for fistulogram based on KDIGO criteria. Patients are reviewed routinely every 2 months by the medical team. Consultants can also refer directly for fistulogram if they deem appropriate without prior discussion at the MDT. Complex cases are discussed at a separate MDT with the VA surgeons.
VA Pathway Routine Clinical Care with Supplementary Remote Surveillance
A dedicated biweekly meeting was established to review patients showing positive alerts, considering clinical findings, dialysis parameters, and routine blood tests. Only patients with positive clinical indicators as defined by KDOQI [3] were referred for diagnostic fistulogram ± angioplasty.
Vasc-Alert Software Technology
Vasc-Alert software retrieves flow and pressure measurements every 30 min during each HD treatment session, applies an adjustment for haematocrit and systemic blood pressure, and produces a risk score that ranges from 1 to 10. For the purpose of this study, high ARS was defined as ≥7 previously described [6, 7].
Study Definitions
Complication-free days (CFD)-extended over 1 year was defined as days without serious VA events, radiological or surgical intervention, VA infection, VA-related hospitalisation or use of central venous catheter [8]. Serious vascular events were defined as significant VA stenosis requiring intervention and VA thrombosis post-intervention primary patency rate was conducted at 3 and 6 months defined as the time from the index procedure until the next access thrombosis or reintervention [9]. Avoidable thrombosis was defined as VA access referred for elective correction of stenosis that developed thrombosis while on the waiting list for the procedure.
Statistical Analysis
The Statistical Package for Social Sciences (IBM SPSS Statistics), version 26 for Windows (IBM Corp., Armonk, NY, USA), was used for data analysis licenced to the University of Manchester. Categorical variables are presented as counts and percentages, and continuous variables are presented as mean ± standard deviation or median and interquartile range (IQR) 25–75% depending for normally and non-normally distributed data respectively. Comparisons were performed using chi-squared test. The distribution of continuous numerical variables was assessed with Shapiro-Wilk test. Comparisons of parametric and non-parametric data were performed with independent samples t test and Mann-Whitney U test, respectively.
For analysis of time-to-event data, Kaplan-Meier curve was constructed, and log-rank test was used to compare between the renal units. The overall primary patency percentage was calculated at 3 and 6 months with standard errors and 95% confidence intervals. A p value <0.05 was adopted to interpret the significance of the statistical analysis.
Cost Analysis
Costs related to VA-associated admissions (admissions while waiting for thrombectomy and admissions for surgical interventions of the VA) or VA interventions (line insertion, elective fistulogram/plasty performed in our hospital) were calculated by the hospital’s finance department. The estimated costs of the VA-related outpatient and inpatients admission episodes are based on the costs of admission episodes for each of the patients between the dates of admission and discharge and include the direct costs of treating each patient (e.g., the costs of medical and nursing staff time and any materials and disposable items used) and the overhead costs associated with the running of the wider organization (the Northern Care Alliance NHS Foundation Trust) such as maintenance costs, the depreciation of buildings and equipment, and the costs of non-patient-facing departments such as human resources, information, and finance. All the costs have been extracted from the Trust’s Service Line Reporting information for the relevant periods and expressed in Great Britain Pound (GBP). The cost of thrombectomy procedures was not included because these procedures are performed at another hospital and relevant financial information could not be retrieved. The total cost in each group was divided by the number of patients with permanent VA to calculate the average per patient cost.
Study Registration
This study was registered with the Northern Care Alliance Research and Innovation department (Ref: ID 21HIP02).
Results
In January 2023, there were 490 patients in total undergoing maintenance HD, among whom 287 patients had permanent VA (279 AVFs and 8 AVGs), with 82 patients in group 1, and 205 in group 2 (study flowchart presented in Fig. 1). Comparative analysis of baseline data between the two groups is presented in Table 1. Group 1 included more Asians and fewer white British patients compared to group 2 (53.7% and 39% compared to 10.2% & 74.1%, respectively, p value <0.001). Group 1 also had significantly longer VA and HD vintage compared to group 2. No other statistically significant difference between the 2 groups was detected. The characteristics of patients who experienced vascular events (correction of stenosis or thrombosis) are presented in Table 2.
Fig. 1.
Flowchart of the study group. CVC, central venous catheter, HD, haemodialysis, n, number; VA, vascular access.
Table 1.
Comparative analysis between demographic, VA, and dialysis data between the study groups
| Characteristic | Overall, N = 287 | Group 1, N = 82 | Group 2, N = 205 | p value |
|---|---|---|---|---|
| Age, median [IQR] (range), years | 63 [50–73] (21–89) | 62 [48–68] (21–87) | 64 [51–75] (22–89) | 0.1581 |
| Gender, n (%) | 0.4182 | |||
| Male | 199.0 (69.3) | 54.0 (65.9) | 145.0 (70.7) | |
| Female | 88.0 (30.7) | 28.0 (34.1) | 60.0 (29.3) | |
| Ethnicity, n (%) | <0.001 3 | |||
| British | 184.0 (64.1) | 32.0 (39.0) | 152.0 (74.1) | |
| Asian | 65.0 (22.6) | 44.0 (53.7) | 21.0 (10.2) | |
| African | 12.0 (4.2) | 1.0 (1.2) | 11.0 (5.4) | |
| Caribbean | 4.0 (1.4) | 1.0 (1.2) | 3.0 (1.5) | |
| Mixed/any/unknown | 22.0 (7.7) | 4.0 (4.9) | 18.0 (8.8) | |
| BMI, median [IQR] (range), kg/m2 | 26 [23–30] (11–46) | 26 [23–29] (19–46) | 27 [23–31] (11–46) | 0.4011 |
| Primary kidney disease, n (%) | 0.9702 | |||
| DN | 71.0 (24.7) | 22.0 (26.8) | 49.0 (23.9) | |
| HTN/RVD | 43.0 (15.0) | 10.0 (12.2) | 33.0 (16.1) | |
| ON/inf | 31.0 (10.8) | 9.0 (11.0) | 22.0 (10.7) | |
| GN | 54.0 (18.8) | 15.0 (18.3) | 39.0 (19.0) | |
| CKD | 29.0 (10.1) | 9.0 (11.0) | 20.0 (9.8) | |
| Unknown/miscellaneous | 59.0 (20.6) | 17.0 (20.7) | 42.0 (20.5) | |
| Prior stenosis, n (%) | 13 | |||
| Yes | 286.0 (99.7) | 29 (35.8) | 74 (36) | |
| Hypertension, n (%) | 0.2692 | |||
| Yes | 261.0 (90.9) | 77.0 (93.9) | 184.0 (89.8) | |
| DM, n (%) | 0.3232 | |||
| Yes | 96.0 (33.4) | 31.0 (37.8) | 65.0 (31.7)1 | |
| 1 | ||||
| CVS, n (%) | 0.9402 | |||
| Yes | 127.0 (44.3) | 36.0 (43.9) | 91.0 (44.4) | |
| Site of anastomosis, n (%) | 0.2283 | |||
| Radio-cephalic | 140.0 (48.8) | 45.0 (54.9) | 95.0 (46.3) | |
| Radio-brachial | 4.0 (1.4) | 2.0 (2.4) | 2.0 (1.0) | |
| Brachio-cephalic | 104.0 (36.2) | 29.0 (35.4) | 75.0 (36.6) | |
| Brachio-basilic | 36.0 (12.5) | 6.0 (7.3) | 30.0 (14.6) | |
| Brachio-axillary | 3.0 (1.0) | 0.0 (0.0) | 3.0 (1.5) | |
| VA, n (%) | 0.4473 | |||
| AVF | 279.0 (97.2) | 81.0 (98.8) | 198.0 (96.6) | |
| AVG | 8.0 (2.8) | 1.0 (1.2) | 7.0 (3.4) | |
| VA vintage, median [IQR] (range) | 2 [1–5] (0–19) | 3 [2–6] (0–19) | 2 [1–5] (0–17) | 0.011 1 |
| HD vintage, median [IQR] (range) | 3 [1–5] (0–58) | 3 [2–5] (0–21) | 2 [1–4] (0–58) | 0.009 1 |
Bold values are statistically significant (p < 0.05).
AVF/G, arteriovenous fistula/graft; BMI, body mass index; CVS, cardio/cerebrovascular disease; DN, diabetic nephropathy; GN, glomerulonephritis; HD, haemodialysis; HTN, hypertension; inf, infection; RVD, reno-vascular disease; ON, obstructive nephropathy.
1Wilcoxon rank sum test.
2Pearson’s chi-squared test.
3Fisher’s exact test.
Table 2.
Comparative analysis between demographic, VA, and dialysis data of cases who experienced vascular events (correction of stenosis or thrombosis)
| Characteristic | Overall, N = 80 | Group 1, N = 29 | Group 2, N = 51 | p value |
|---|---|---|---|---|
| Age, median [IQR] (range), years | 63 [49–73] (22–89) | 59 [45–67] (28–80) | 66 [50–78] (22–89) | 0.037 1 |
| Gender, n (%) | 0.7752 | |||
| Male | 54.0 (67.5) | 19.0 (65.5) | 35.0 (68.6) | |
| Female | 26.0 (32.5) | 10.0 (34.5) | 16.0 (31.4) | |
| Ethnicity, n (%) | 0.004 3 | |||
| British | 50.0 (62.5) | 12.0 (41.4) | 38.0 (74.5) | |
| Asian | 24.0 (30.0) | 15.0 (51.7) | 9.0 (17.6) | |
| African | 2.0 (2.5) | 0.0 (0.0) | 2.0 (3.9) | |
| Caribbean | 4.0 (5.0) | 2.0 (6.9) | 2.0 (3.9) | |
| Mixed/any/unknown | 0.0 (0.0) | 0.0 (0.0) | 0.0 (0.0) | |
| BMI, median [IQR] (range), kg/m2 | 26 [23–29] (11–46) | 26 [24–28] (19–46) | 26 [23–30] (11–44) | 11 |
| Primary kidney disease, n (%) | 0.7003 | |||
| DN | 20.0 (25.0) | 6.0 (20.7) | 14.0 (27.5) | |
| HTN/RVD | 12.0 (15.0) | 5.0 (17.2) | 7.0 (13.7) | |
| ON/inf | 6.0 (7.5) | 2.0 (6.9) | 4.0 (7.8) | |
| GN | 15.0 (18.8) | 8.0 (27.6) | 7.0 (13.7) | |
| Cystic kidney disease | 12.0 (15.0) | 3.0 (10.3) | 9.0 (17.6) | |
| Unknown/miscellaneous | 15.0 (18.8) | 5.0 (17.2) | 10.0 (19.6) | |
| Prior stenosis, n (%) | 44 (55) | 14 (48.3) | 30(58.8) | 0.3621 |
| Hypertension, n (%) | 0.4763 | |||
| Yes | 71.0 (88.8) | 27.0 (93.1) | 44.0 (86.3) | |
| DM, n (%) | 0.6992 | |||
| Yes | 27.0 (33.8) | 9.0 (31.0) | 18.0 (35.3) | |
| CVS, n (%) | 0.3072 | |||
| Yes | 30.0 (37.5) | 13.0 (44.8) | 17.0 (33.3) | |
| Site of anastomosis, n (%) | 0.9733 | |||
| Radio-cephalic | 31.0 (38.8) | 11.0 (37.9) | 20.0 (39.2) | |
| Radio-brachial | 3.0 (3.8) | 1.0 (3.4) | 2.0 (3.9) | |
| Brachio-cephalic | 30.0 (37.5) | 12.0 (41.4) | 18.0 (35.3) | |
| Brachio-basilic | 15.0 (18.8) | 5.0 (17.2) | 10.0 (19.6) | |
| Brachio-axillary | 1.0 (1.3) | 0.0 (0.0) | 1.0 (2.0) | |
| VA, n (%) | 0.5503 | |||
| AVF | 77.0 (96.3) | 29.0 (100.0) | 48.0 (94.1) | |
| AVG | 3.0 (3.8) | 0.0 (0.0) | 3.0 (5.9) | |
| VA vintage, median [IQR] (range) | 2 [1–4] (0–16) | 4 [2–6] (0–16) | 2 [1–3] (0–16) | 0.002 1 |
| HD vintage, median [IQR] (range) | 2 [1–4] (0–19) | 3 [2–6] (0–19) | 2 [1–4] (0–15) | <0.001 1 |
| CFD-extended, median (IQR), days | 363 (356–364) | 364 (363–364) | 362 (354–363) | 0.002 4 |
| Access abandonment, n (%) | 10 (12.5) | 3 (10.3) | 7 (13.7) | 0.7403 |
Bold values are statistically significant (p < 0.05).
AVF/G, arteriovenous fistula/graft; BMI, body mass index; CVS, cardio/cerebrovascular disease; CFD, complications-free days; DN, diabetic nephropathy; GN, glomerulonephritis; HD, haemodialysis; HTN, hypertension; inf, infection; RVD, reno-vascular disease; ON, obstructive nephropathy.
1Wilcoxon rank sum test.
2Pearson’s chi-squared test.
3Fisher’s exact test.
4Mann-Whitney test.
Over a period of 12 months, we recorded 23 (28.1%) episodes of pre-emptive correction of stenosis and 6 (7.3%) episodes of thrombosis in group 1. There were 40 (19.5%) episodes of elective stenosis corrections and 21 (10.2%) episodes of thrombosis in group 2 (p value 0.155 and 0.587, respectively) (Table 2).
Among the episodes of thrombosis 5/6 (83%) cases had been pre-emptively referred for diagnostic fistulogram ± angioplasty but developed thrombosis while awaiting elective intervention in group 1, compared with 4/21 (19%) in group 2 (p value = 0.004) (Table 3). In group 2, 11 stenosis episodes (5.4%) underwent repeated pre-emptive correction of stenosis (all were AVFs) and 2 (1%) repeated thrombosis episode (1 AVF and 1 AVG), while there were no episodes of repeated stenosis or thrombosis in group 1 during the period of the study (p value = 0.038, 1, respectively) (Table 2). The median time interval from the date of fistulogram request until the date of thrombosed VA was 26 days (IQR: 21–42 days).
Table 3.
Comparison between the vascular events’ episodes between the study groups
| Total | Group 1 | Group 2 | p value | |
|---|---|---|---|---|
| Total population | 287 | 82 | 205 | |
| Thrombosis | 27 (9.4%) | 6 (7.3%) | 21 (10.2%) | 0.5871 |
| Repeated thrombosis | 2 | 0 | 2 | 1.0002 |
| Avoidable thrombosis/total thrombosis3 | 9/27 (33%) | 5/6 (83%) | 4/21 (19%) | 0.0041 |
| Pre-emptive stenosis correction | 63 (21.9%) | 23 (28.1%) | 40 (19.5%) | 0.1551 |
| Repeated stenosis | 11 | 0 | 11 | 0.0381 |
1Fisher’s exact test.
2χ2: Pearson’s chi-squared test, significant at p < 0.05.
3Avoidable thrombosis, i.e., referred for pre-emptive stenosis of correction but thrombosed while waiting for intervention.
Patients in group 1 had significantly higher CFD-extended compared to those in group 2 (group 1; median 364, IQR: 363–364 – group 2; median 362, IQR: 354–363, p = 0.002) (Table 2). The overall VA post-intervention primary patency rates at 3 and 6 months were 100% versus 80% and 100% versus 62.2%, respectively, p value of the log-rank test <0.001 (Fig. 2).
Fig. 2.
Kaplan-Meier curve for post-intervention primary patency rate, group 1 with Vasc-Alert, group 2 without Vasc-Alert (control).
Within group 1, we detected high ARS not fulfilling the KDOQI clinical criteria for referral for diagnostic intervention in 3 patients (3.6%). All patients who were referred for angiogram based on KDOQI criteria underwent therapeutic angioplasty for significant stenosis, except 1 patient with AVF who was only found to have an elongated tortuous vein and endovascular intervention was not performed. This patient was subsequently reviewed by vascular surgeons and was planned for corrective surgery for vein straightening. Total hospitalisation and VA intervention (excluding thrombectomy) cost was calculated at GBP 129,655 for group 1 and GBP 375,556 for group 2 corresponding to an average VA-related cost per patient with VA access GBP 1,600 for group 1 and GBP 1868 GBP for group 2.
Discussion
This study demonstrates that the implementation of the Vasc-Alert surveillance technology to assist early detection of malfunctioning VA was associated with improved clinical detection rate of high-risk VA requiring intervention compared to standard care alone in our unit. Patients in the remote surveillance supported clinical pathway experienced better post-intervention primary patency rates, more complication-free days-extended, and did not suffer from recurrent stenosis or thrombosis. Furthermore, implementation of the software as a supplementary tool in VA MDTs identified 83% of cases who unfortunately developed thrombosis while on the waiting list for elective angioplasty compared to 19% in the group receiving standard care.
In our routine care only group (group 2), the annual thrombosis rate was 10.4% (0.104 thromboses/AVF per year) compared to 7.4% (0.074 thromboses/AVF per year) in the software assisted surveillance group; however, the difference was not statistically significant. The thrombosis rates in both groups are within the range reported in previous observational studies (0.03–0.17 thromboses/AVF-year) [10–13]. Based on our findings, adequate capacity for elective radiological intervention delivered within 3 weeks of referral could have reduced the thromboses rate to 1.2% (0.012 thromboses/AVF per year) in group 1.
Our study highlights the impact of lack of adequate elective capacity in interventional radiology in our centre. In turn, this increases the need for urgent interventional radiology intervention (thrombectomy), which is more challenging to deliver in a timely fashion, and associated with less favourable VA outcomes [14].
Our findings support the KDOQI recommendation that surveillance methods should only be used as supplementary tools for clinical assessment. Fortnightly review of electronic alerts enabled the MDT to identify clinical indicators of dysfunctional fistula earlier and in more cases compared to standard of care. Clinical assessment prevented unnecessary interventions in 3.6% patients with false-positive alerts in group 1.
We did not observe any episode of recurrent stenosis or thrombosis in group 1 but detected 11 episodes of restenosis and 2 episodes of re-thrombosis in group 2. There were significant differences in ethnic background between the groups. Variation in VA outcomes depending on ethnicity has been described in US HD patients, with poorer VA outcomes in African Americans [15], but not in a study reporting on UK HD patients with ethnic minority population consisting predominantly of South Asians similar to our study [16]. It could be speculated that timely and appropriate treatment of clinically significant stenosis may have reduced the risk of recurrent stenosis in group 1.
The main limitations of the study are the relatively small population size, the lack of randomisation and insufficient statistical power to detect differences in thrombotic events between the groups. This was a feasibility pilot study evaluating prospectively the use of the surveillance technology to assist clinical decision-making within the existing insufficient resources for radiological intervention. Consequently, the results should be interpreted cautiously due to the exploratory nature of the study. In post hoc statistical power calculation related to the outcome of avoidable thrombosis (83% in the study group vs. 19% in the control group), the study was adequately powered assuming a significance level of 0.05 and 80% power. In addition, our study included mostly arteriovenous fistulas and our results cannot be generalised for arteriovenous grafts. Furthermore, our cost analysis was limited to VA-associated admissions while waiting for thrombectomy and for elective surgical or radiological interventions of the VA in our hospital, and did not include cost of urgent thrombectomy which is performed in the neighbouring centre due to lack of relevant financial information. We also did not include the cost of additional VA MDT which was performed biweekly at the intervention group. Due to the relevant small sample size, we also did not calculate the additional financial and clinical benefit of potentially improved patency rates which could decrease the need for subsequent surgical creation of arteriovenous fistulas.
This study shows that the addition of remote software surveillance to routine clinical monitoring improves timely detection of clinically high-risk VA and highlights the need for elective interventional radiology capacity to improve outcomes. Prospective multicentre randomised controlled studies are required with adequate elective radiological interventional capacity to investigate the impact on outcomes from the integration of this technology into the clinical pathway and its cost effectiveness.
Statement of Ethics
The study protocol was approved and registered (Ref: ID 21HIP02) by the Research and Innovation Committee of the Northern Care Alliance NHS Group and the need for individual patient consent was waived by the Research and Innovation Committee of the Northern Care Alliance NHS group as this was a service evaluation using routinely collected data in an anonymised fashion and as indicated by the NHS Health Research Authority online tool (http://www.hradecisiontools.org.uk/research) did not require Research Ethics Committee review and thus did not require individual patient consent.
Conflict of Interest Statement
The authors have no conflicts of interest to declare.
Funding Sources
This study was not supported by any sponsor or funder.
Author Contributions
Alshymaa Eltahan conducted the data collection and analysis, writing the original draft, review, and editing. Dimitrios Poulikakos performed conceptualisation, study design, data analysis, review, and editing. Rosemary Donne, David Lewis, Maharajan Raman, Zulfikar Pondor, Jan Cowperthwaite, Marinela Liliana Resiga, Paul Hinchliffe, Paula Gleave, and Jazzle Lim contributed to data reviewing and editing. Jonathan Allsopp calculated all vascular access-related episodes cost.
Funding Statement
This study was not supported by any sponsor or funder.
Data Availability Statement
Data will be available upon request.
References
- 1. Viecelli AK, Tong A, O’Lone E, Ju A, Hanson CS, Sautenet B, et al. Report of the standardized outcomes in nephrology-hemodialysis (SONG-HD) consensus workshop on establishing a core outcome measure for hemodialysis vascular access. Am J Kidney Dis. 2018;71(5):690–700. [DOI] [PubMed] [Google Scholar]
- 2. Manns B, Tonelli M, Yilmaz S, Lee H, Laupland K, Klarenbach S, et al. Establishment and maintenance of vascular access in incident hemodialysis patients: a prospective cost analysis. J Am Soc Nephrol. 2005;16(1):201–9. [DOI] [PubMed] [Google Scholar]
- 3. Lok CE, Huber TS, Lee T, Shenoy S, Yevzlin AS, Abreo K, et al. KDOQI clinical practice guideline for vascular access: 2019 update United States. Am J Kidney Dis; 2020. 75(4 Suppl 2). S1–164. [DOI] [PubMed] [Google Scholar]
- 4. Tonelli M, James M, Wiebe N, Jindal K, Hemmelgarn B; Alberta Kidney Disease Network . Ultrasound monitoring to detect access stenosis in hemodialysis patients: a systematic review. Am J Kidney Dis. 2008;51(4):630–40. [DOI] [PubMed] [Google Scholar]
- 5. Frinak S, Zasuwa G, Dunfee T, Besarab A, Yee J. Dynamic venous access pressure ratio test for hemodialysis access monitoring. Am J Kidney Dis. 2002;40(4):760–8. [DOI] [PubMed] [Google Scholar]
- 6. Astor BC, Hirschman K, Kennedy J, Frinak S, Besarab A. Development and validation of a risk score to prioritize patients for evaluation of access stenosis. Semin Dial. 2022;35(3):236–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Eltahan AR, Pondor Z, Donne RL, Lewis D, Raman M, Hinchliffe P, et al. Remote surveillance technology of dialysis arteriovenous access. Retrospective Eval a UK Ren centre Nephron. 2024;1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Lee T, Mokrzycki M, Moist L, Maya I, Vazquez M, Lok CE, et al. Standardized definitions for hemodialysis vascular access. Semin Dial. 2011;24(5):515–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Sidawy AN, Gray R, Besarab A, Henry M, Ascher E, Silva MJ, et al. Recommended standards for reports dealing with arteriovenous hemodialysis accesses. J Vasc Surg. 2002;35(3):603–10. [DOI] [PubMed] [Google Scholar]
- 10. Tessitore N, Lipari G, Poli A, Bedogna V, Baggio E, Loschiavo C, et al. Can blood flow surveillance and pre-emptive repair of subclinical stenosis prolong the useful life of arteriovenous fistulae? A randomized controlled study. Nephrol Dial Transpl. 2004;19(9):2325–33. [DOI] [PubMed] [Google Scholar]
- 11. Tessitore N, Bedogna V, Poli A, Mantovani W, Lipari G, Baggio E, et al. Adding access blood flow surveillance to clinical monitoring reduces thrombosis rates and costs, and improves fistula patency in the short term: a controlled cohort study. Nephrol Dial Transpl. 2008;23(11):3578–84. [DOI] [PubMed] [Google Scholar]
- 12. Sands JJ, Jabyac PA, Miranda CL, Kapsick BJ. Intervention based on monthly monitoring decreases hemodialysis access thrombosis. Am Soc Artif Intern Organs Trans J. 1999;45(3):147–50. [DOI] [PubMed] [Google Scholar]
- 13. Roca-Tey R, Samon R, Ibrik O, Roda E, González-Oliva JC, Martínez-Cercós R, et al. Five years of vascular access stenosis surveillance by blood flow rate measurements during hemodialysis using the Delta-H method. J Vasc Access. 2012;13(3):321–8. [DOI] [PubMed] [Google Scholar]
- 14. Sands JJ, Miranda CL. Prolongation of hemodialysis access survival with elective revision. Clin Nephrol. 1995;44(5):329–33. [PubMed] [Google Scholar]
- 15. Woo K, Gascue L, Goldman DP, Romley JA. Variations in outcomes of hemodialysis vascular access by race/ethnicity in the elderly. J Vasc Surg. 2017;65(3):783–92.e4, [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Wilmink T, Wijewardane A, Lee K, Murley A, Hollingworth L, Powers S, et al. Effect of ethnicity and socioeconomic status on vascular access provision and performance in an urban NHS hospital. Clin Kidney J. 2017;10(1):62–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data will be available upon request.
