The outcomes of a consecutive cohort of all ecAVG (Gore® Acuseal™) placed in a single-centre (2/2012–12/2019) with a minimum one-year follow-up were retrospectively analysed from a prospectively recorded electronic patient record (ePR). Data included demographics, complications and outcomes. Functional patency was used as the most meaningful outcome measure for patients and was defined as the interval between first cannulation and abandonment or the time of measurement of patency including occurrence of a censored event (death, elective change of modality, loss of follow-up)22. Other than 2 patients that were lost to follow-up after more than one year, all data was complete for the remaining patients. A multidisciplinary team meeting ran weekly with attendance from representatives of the vascular access specialist nursing team, interventional radiology, ultrasonography, nephrology and surgery, at which all imaging and planning was discussed. The technical aspects of AVG placement were consistent throughout the period with all data pertaining to one surgical team (DBK, KS, AJ).
Factors Related to Functional Patency:
Patient Factors: Details of patient co-morbidity were obtained from the documentation of past medical history and included co-existent disease (diabetes mellitus, previous coronary artery disease, stroke, hypertension, cardiac failure, peripheral vascular disease, malignancy), underlying aetiology of renal failure (diabetic nephropathy, glomerular nephritis, interstitial nephritis, unknown, multisystem diseases, other miscellaneous causes), smoking (active or not), body mass index (BMI, as a continuous and categorical variable), and medication (anti-coagulation, antiplatelets). The implantation site and configuration was recorded.
Renal Replacement Therapy (RRT): Data on previous RRT were recorded: time on RRT, previous RRT modality, previous vascular access (at time of operation for ecAVG, prior TCVC, prior AVF).
Indication for an ecAVG: The indications previously reported in case-series included poor native options for elective creation of an AVF, central vein stenosis requiring lower limb ecAVG or HeRO (hemodialysis reliable outflow graft, ®Merritt Medical), patient choice, TCVC complications including infection and dysfunction, salvage of failed AVF for thrombosis or aneurysm, and urgent – where dialysis was required before AVF creation had been achieved (Table 1). The primary indication for ecAVG was taken as the fundamental reason to receive an ecAVG rather than alternative vascular access. For example, an acutely occluded aneurysmal AVF that was excised and a replaced with an AVG in the same arm was categorised as AVF failure. However, if the AVG had been placed in the contra-lateral arm due that had no option for an AVF, then the indication was poor native options. Central vein stenosis as an indication was based on the need for either HeRO or lower limb ecAVG with the central venous stenosis was present in the SVC or being bilateral. Poor native options was based on ultrasound measurements of brachial artery or cephalic vein less than 3 mm. An ecAVG was categorised as urgent if there was an acute need for dialysis with no vascular access ready. Thus a late-presenter would have the option of ecAVG or TCVC and may elect for an ecAVG and would be classified as ‘urgent’. If there was time before HD was required and an AVF was a viable option but the patient chose an ecAVG, then the indication would be patient choice. Importantly, the allocation to indication was made prior to the analysis of outcomes and obtained from the pre-operative documentation.
Table 1
Case-Mix of Case-Reports of Early-Cannulation Arteriovenous Grafts
Article
|
Demographic Factors
|
Vascular Access History
|
|
Mean
Age
|
DM
|
BMI
|
Sex
%male
|
Renal
Disease
|
% Incident
|
Years HD
|
TCVC at op
|
AV at op
|
% Leg /HeRO
|
Aitken7
N = 37
|
42
|
97%
|
31
|
54
|
✕
|
11%
|
3.2
|
46%
|
8%
|
70%
|
Glickman16
N = 138
|
63
|
60%
|
30
|
49
|
✕
|
17%
|
2
|
89%
|
9%
|
0%
|
Maytham11
N = 55
|
64
|
38%
|
|
51
|
✕
|
20%
|
|
|
49%
|
0%
|
Tozzi8
N = 30
|
60
|
40%
|
|
60
|
✕
|
|
8.4mo
|
57%
|
|
10%
|
Aitken12
N = 60
|
54
|
37%
|
17%
obese
|
53
|
✓
|
27%
|
3.4
|
22%
|
30%
|
3%
|
Chemla27
N = 16
|
56
|
47%
|
|
47
|
✕
|
0
|
|
|
|
0%
|
Chiang28
N = 45
|
52
|
60%
|
|
51
|
✕
|
62
|
|
|
|
0%
|
Schild9
N = 33
|
< 70
|
60%
|
|
48%
|
✕
|
0
|
|
|
|
0%
|
Lioupis14
N = 48
|
59
|
40%
|
|
65
|
✓
|
35
|
|
|
|
0%
|
Berard15
N = 46
|
63
|
39%
|
24
|
61%
|
✓
|
17%
|
1.3
|
74%
|
24%
|
22%
|
Scarrit13
N = 78
|
59
|
40%
|
|
65%
|
✕
|
35%
|
|
|
|
0%
|
Sutaria6
N = 141
|
61
|
46%
|
|
41
|
✕
|
26
|
|
51%
|
37%
|
2%
8%
|
Key: DM – diabetes mellitus; BMI – body mass index; Years HD – years on haemodialysis prior to ecAVG; TCVC at op – presence of a TCVC at time of ecAVG operation; AV at op – arteriovenous fistula at time of ecAVG operation; HeRO – haemodialysis reliable outflow device |
Article
|
Indication For AVG
|
Prev
TCVC
|
Prev AVF
|
Factors in model
|
|
Urgent
|
AVF/G dys
|
TCVC dys
|
PNO
|
CVS
|
|
|
|
Aitken7
N = 37
|
11%
|
8%
|
32%
|
9%
|
68%
|
65%
|
Mean 2
|
5/6
|
Glickman16
N = 138
|
9%
|
7%
|
27%
|
20%
|
38%
|
53%
|
85%
|
5/6
|
Maytham11
N = 55
|
0
|
25% / 31%
|
0%
|
51%
|
0
|
|
25%
|
3/6
|
Tozzi8
N = 30
|
|
|
|
|
0
|
|
|
2/6
|
Aitken12
N = 60
|
12%
|
38%
|
21%
|
|
0
|
Mean 2
|
Mean 2
|
6/6
|
Chemla27
N = 16
|
|
|
|
|
|
100%
|
100%
|
3/6
|
Chiang28
N = 45
|
|
13%AVF
24%AVG
|
|
|
|
|
13%
|
2/6
|
Schild9
N = 33
|
|
|
|
|
|
|
100%
|
3/6
|
Lioupis14
N = 48
|
|
|
|
|
|
|
100%
|
3/6
|
Berard15
N = 46
|
|
24%
|
|
74%
|
|
74%
|
43%
|
6/6
|
Scarrit13
N = 78
|
|
19%
|
|
|
|
|
Median 1
|
3/6
|
Sutaria6
N = 141
|
20%
|
33%
|
4%
|
|
8%
|
|
|
3/6
|
Key: Shading = predictors in multi-variate model |
DM – diabetes mellitus; BMI – body mass index; Primary diagnosis – underlying cause of renal disease; HD – hemodialysis; TCVC – tunnelled central venous catheter; Op – operation to implant ecAVG; AV – arteriovenous fistula or graft; LL – lower limb; HeRO – hemodialysis reliable outflow device; AVF/G Dys = dysfunction of an existing AVF or AVG; TCVC Dys = dysfunction of a previously functioning TCVC; PNO = poor native options; CVS = central vein stenosis ; Factors in model = number of factors documented in methods in the predictive model |
Analysis:
Initially the data was analysed to detect normality of distribution. Data that were not normally distributed included age and sex with greatly differing event rates. Age was included as a continuous variable in the multivariate analysis. As variables to be analysed were both quantitative and categorical, and with likely interaction, a Cox proportional Hazards analysis was performed. Predictors of poor outcome were sought using univariate analysis. There was no evidence of informative censoring as very few patients were lost to follow-up. The Wilcoxon test was used to test for significance rather than the log-rank due to the number of censored events.
To create the multivariate model, up to 10 predictors found significant on univariate analysis could be reliably fitted to the data, accepting the limitations to this particularly for time dependent outcomes23,24. A Cox proportional hazards model was performed based on continuous variable (age, number of TCVC) and categorical variables (sex, age in cohorts, smoking, presence/absence of co-morbid conditions, aetiology of ESRF, modality of vascular access at time of procedure, number of catheters, aetiology of ESRF, and indication).
The analysis was complicated due to the high level of censored events as it is assumed in the model that censored patients will have similar outcomes to non-censored which may or may not be true. The validity of the proportional-hazards assumption was made by making an interaction of the variable with time, with the significance of the time-dependent variable (T-cov) calculated when included in a Cox Model25. Schoenfeld residual analysis could not be performed to check the assumptions of proportionality due to the high intercurrent censored event rates which would be excluded using this method. There was a significant non-proportionality for sex (p < 0.04), with all other variables showing proportionality. The survival curves by sex demonstrated that up to 300 days, females had slightly poorer functional patency, whereas after this time period, males had poorer patency. Thus in the multi-variate analysis, a time-dependent model was used with this included.
All p-values were derived from two-tailed tests with p < 0.05 considered statistically significant. Data were analysed using SPSS software (IBM® SPSS® Statistics, Version 27).
The study was registered with the appropriate regional committee – The Renal Services Clinical Effectiveness Group. In the UK (NHS-Health Research Authority), formal research ethics approval was not required due to the retrospective, observational study of established practice within accepted guidelines with no additional tests performed for the purposes of research for which patient permission is included in the consent forms, with no patient identification. All methods were carried out in accordance with relevant guidelines and regulations.