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The British Journal of Surgery logoLink to The British Journal of Surgery
. 2024 Oct 3;111(10):znae227. doi: 10.1093/bjs/znae227

Identification of patient characteristics that may improve procedure selection for the treatment of carotid stenosis

Andreas Kuehnl 1,, Christoph Knappich 2, Felix Kirchhoff 3, Bianca Bohmann 4, Vanessa Lohe 5, Shamsun Naher 6, Hans-Henning Eckstein 7, Michael Kallmayer 8
PMCID: PMC11448336  PMID: 39361152

Abstract

Background

Carotid endarterectomy and carotid artery stenting are common procedures for the treatment of carotid artery stenosis. The aim of this study was to identify factors that modify the effect between type of treatment and outcome, and could thus be used to refine the selection of treatment procedure.

Methods

All patients who underwent either carotid endarterectomy or carotid artery stenting between 2012 and 2018 in German hospitals were included. The analysis of effect modification was focused on baseline patient characteristics. The outcome was a composite of any stroke or death until discharge from hospital. For multivariable analyses, a generalized linear mixed regression model was used.

Results

Some 221 282 patients were included, of whom 68% were male. In patients who underwent carotid endarterectomy or carotid artery stenting, the risk of any stroke or death was 2.3% and 3.7% respectively. Patient age was statistically significantly associated with a higher risk of a composite outcome of any stroke or death (main effect of age: adjusted OR 1.21 (95% c.i. 1.17 to 1.26), P < 0.001). The age effect was stronger in patients treated with carotid artery stenting (interaction effect: adjusted OR 1.29 (95% c.i. 1.20 to 1.38), P < 0.001). Statistically significant interaction effects were identified for side of treatment, ASA grade, contralateral degree of stenosis, and the time interval between the index event and treatment.

Conclusion

This analysis shows that carotid artery stenting may be particularly disadvantageous in older patients, in patients with right-sided stenosis, and in symptomatic patients treated within the first 2 days after the index event. In patients with contralateral occlusion, carotid artery stenting appears equivalent to carotid endarterectomy.


The aim of this study was to identify factors that modify the effect between type of treatment and outcome, and could thus be used to refine the choice of treatment procedure. It was found that carotid artery stenting may be particularly disadvantageous in older patients and in patients with right-sided stenosis. In patients with contralateral occlusion and in symptomatic patients treated in the second week after the index event, it may be equivalent to carotid endarterectomy.

Introduction

Carotid endarterectomy (CEA) and carotid artery stenting (CAS) are the predominant procedures used for treating carotid artery stenosis. Therapy indications, diagnostic measures, and treatment types need to be established under international guideline recommendations1–3. In general, CEA is the standard therapy, whereas CAS may be considered an alternative in selected patients4, especially symptomatic patients at high surgical risk1. Regarding the choice of procedure (CEA or CAS), the decision should be based on patient-specific clinical and morphological variables, as well as the patient’s personal preferences (level of evidence/grading of recommendation: expert consensus, German–Austrian guideline1). The following characteristics and morphological variables are associated with higher risk when performing CAS (making CEA more beneficial): older age (greater than 70 years), a short time interval between the index event and treatment, difficult access for CAS, and morphological characteristics of long stenosis, heavy calcification, vessel elongation, and plaque ulceration (expert consensus based on Naylor et al.2 and Aboyans et al.5). In contrast, the following characteristics are associated with higher risk when performing CEA: restenosis, post-radiation stenosis, skull base near stenosis, tandem stenosis, and contralateral paresis of the recurrent laryngeal nerve (expert consensus1). However, all grades of the latter recommendations are expert consensus only, as higher-level evidence, for example direct head-to-head randomized studies, which justifies a higher grade of recommendation, remains unavailable. Regarding transfemoral CAS, a risk-calculating tool for the 30-day risk of stroke or death was developed based on a secondary data analysis of the Vascular Quality Initiative database6. This analysis directly associated the following factors with a higher risk in patients treated with CAS: age, race, diabetes, coronary artery disease, chronic heart failure, symptomatic status, and contralateral occlusion. In contrast, dual antiplatelet therapy and statin use were related to lower risk after CAS. Notably, these risk prediction models conducted the analysis either within a CEA or within a CAS cohort, but not simultaneously in both6,7.

The aim of this study was to identify factors that modify the effect between treatment types and outcomes, which can be used to refine the selection process of treatment type.

Methods

This was a pre-planned substudy analysis of the ISAR-IQ project (Integration and Spatial Analysis of Regional, site-specific, and patient-level factors for Improving the Quality of treatment for carotid artery stenosis).

Data source

This study was based on the nationwide German statutory quality assurance measures according to § 136 SGB V of the Federal Joint Committee operated by the Institute for Quality Assurance and Transparency in Healthcare (Institut für Qualitätssicherung und Transparenz im Gesundheitswesen (IQTIG)). The IQTIG statutorily collected data on carotid revascularization procedures (CEA and CAS) in all German hospitals. Data were collected for all CEA and CAS procedures, except for those performed at military hospitals and outpatient clinics, because of legal obligations. The Ethics Committee of the Medical Faculty, Technical University of Munich approved this study (Reference Number 107/20S). The analysis was conducted in accordance with the Good Practice of Secondary Data Analysis guidelines8. REporting of studies Conducted using Observational Routinely-collected Data (RECORD) reporting guidelines were applied; this was appropriate because this was an observational study using routinely collected health data9. All data were saved on IQTIG servers, following the respective data protection regulations. Controlled remote data processing was used to permit data access. The ISAR-IQ study protocol was submitted to the IQTIG and the Gemeinsamer Bundesausschuss, Germany’s Federal Joint Committee (G-BA) during the application procedure, but was not published separately. Further details on methods have already been published1,10–21.

Inclusion and exclusion criteria

This study included all patients who underwent either CEA or CAS for carotid stenosis (asymptomatic, symptomatic, emergency, and other indications) from 2012 to 2018 in German hospitals (Fig. 1). Patients who underwent procedures other than CEA/CAS, as well as patients who underwent combined/converted procedures, patients who underwent combined carotid-coronary or carotid-peripheral artery procedures, and patients who underwent CAS procedures to primarily gain access for an intracranial intervention were excluded; in addition, patients with unknown or diverse sex were excluded. The latter was required to avoid extensive output blocking due to data protection issues. Patients were categorized as asymptomatic, symptomatic, or others. Symptomatic patients were subcategorized as symptomatic ‘elective’ (amaurosis fugax, transient ischaemic attack (TIA), stroke, or other elective symptoms) or symptomatic ‘emergency’ (crescendo TIA, stroke-in-evolution, or other emergency symptoms) based on the urgency of the care provided. In total, 221 282 patients were finally included.

Fig. 1.

Fig. 1

Patient flow chart illustrating inclusion and exclusion criteria

*Excluding combined/converted procedures (CAS and CEA) and CAS procedures performed for the primary purpose of gaining access for an intracranial intervention. Special conditions include simultaneous cardiac, aortic, or peripheral vascular surgical procedures. CEA, carotid endarterectomy; CAS, carotid artery stenting.

Grouping variables and outcome

The patients were mainly categorized based on the procedure they underwent (CEA versus CAS as a comparative variable) and the occurrence of the outcome event (OE). The OE was the compound endpoint of ‘any stroke or death’, which is used in many major studies and guidelines and is crucial for the patient1,2,5. This endpoint refers to the interval up to discharge from the hospital, as the statutory quality assurance system recorded no data after discharge.

Statistical analyses

Categorical variables are presented as n (%) and continuous variables are presented as median (interquartile range).

R function ‘glmer’ with logit link function was used for multilevel multivariable regression analysis. The pre-procedural and post-procedural neurological-clinical assessments were included in the model as fixed effects by default because they were the strongest confounders in all previous analyses.

The procedure type (CEA versus CAS) was included as a fixed effect, as were the clinical variables age, sex, ASA grade, side of treatment, ipsilateral degree of stenosis, contralateral degree of stenosis, type of index event (initial neurological symptoms), time interval between the index event and treatment (only for electively treated symptomatic patients), morphological characteristics (for example ulcerated plaques and aneurysmal changes in addition to the stenosis), and centre annual caseload. The models involved an interaction term between the form of therapy and the respective clinical variable.

Hospital identifier and year of treatment were entered as random factors into the model (intercept only) to adjust for clustering effects and temporal trends respectively22–24.

The chi-squared test was used to analyse differences regarding intra- and post-procedural variables. R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria) was utilized for data processing and statistical analysis, with extension packages ‘tidyverse’, ‘epitools’, ‘lme4’, ‘expss’, and ‘ggplot2’ used for cross-classified tables, chi-squared tests, and multivariable regression analyses.

Scatter plots with individual patient data points must not be created for data protection reasons. The differential effects of age and hospital caseload were visualized using microsimulation (n = 10 000) based on the parameters calculated by the abovementioned multivariable regression models for an easily understandable graphical depiction of interaction effects. Graphic processing of the data was conducted using Microsoft Excel. A two-tailed level of significance of α = 5% was used for all tests. For further details on the statistical methods please see the Supplementary material.

Results

Characteristics of patients

This study included 221 282 patients, of whom 68% were male. Of the patients, 179 724 (81%) and 41 558 (19%) underwent CEA and CAS respectively. The majority of patients were asymptomatic (55%). Table 1 shows details on baseline characteristics of patients on hospital admission. Among patients who underwent CEA, general anaesthesia was predominantly used (71%), followed by local anaesthesia (27%) and combined/modified measures (2.5%). Revascularization success was controlled by intraoperative completion study in 74% of patients; imaging techniques, such as angiography or ultrasonography, were used in 56% of patients. Table 2 shows details on perioperative and intraoperative management.

Table 1.

Baseline characteristics of patients on hospital admission by type of treatment, primary outcome event, and raw risks

Clinical variable Overall OE occurred OE did not occur P (chi-squared)
CEA CAS CEA CAS
Patients 221 282 (100) 4099 (1.9) 1524 (0.7) 175 625 (79) 40 034 (18) <0.001
Age (years), median (interquartile range) 72 (64–77) 74 (67–79) 75 (67–80) 72 (65–78) 70 (63–77)
Sex
 Male 150 734 (68) 2768 (68) 1020 (67) 119200 (68) 27 746 (69) <0.001
 Female 70 548 (32) 1331 (32) 504 (33) 56 425 (32) 12 288 (31) <0.001
Side of treatment
 Right 110 910 (50) 1780 (43) 703 (46) 88 610 (51) 19 817 (50) <0.001
 Left 110 372 (50) 2319 (57) 821 (54) 87 015 (49) 20 217 (50) <0.001
ASA grade*
 I/II 72 169 (33) 614 (15) 538 (36) 48 211 (28) 22 806 (59) <0.001
 III 139 822 (64) 3022 (74) 649 (43) 121 591 (70) 14 560 (38) <0.001
 IV/V 7206 (3.3) 449 (11) 314 (21) 5027 (2.9) 1416 (3.7) <0.001
Ipsilateral degree of stenosis†
 Mild (<50%) 3753 (1.7) 132 (3.2) 53 (3.5) 2599 (1.5) 969 (2.4) 0.657
 Moderate (50–69%) 11 400 (5.2) 286 (7.0) 95 (6.2) 8839 (5.0) 2180 (5.5) 0.013
 Severe (70–99%) 203 025 (92) 3551 (87) 1123 (74) 162 972 (93) 35 379 (88) <0.001
 Occlusion (100%) 3104 (1.4) 130 (3.2) 253 (17) 1215 (0.7) 1506 (3.8) <0.001
Contralateral degree of stenosis†
 Mild (<50%) 150 898 (68) 2525 (62) 1075 (71) 119 068 (68) 28 230 (71) <0.001
 Moderate (50–69%) 30 507 (14) 606 (15) 116 (7.6) 25 848 (15) 3937 (9.8) 0.026
 Severe (70–99%) 26 022 (12) 557 (14) 180 (12) 21 070 (12) 4215 (11) <0.001
 Occlusion (100%) 13 855 (6.3) 411 (10) 153 (10) 9639 (5.5) 3652 (9.1) 0.855
Neurological symptoms
 Asymptomatic 122 363 (55) 1461 (36) 374 (25) 99 454 (57) 21 074 (53) 0.001
 Amaurosis fugax 12 375 (5.6) 140 (3.4) 24 (1.6) 10 374 (5.9) 1837 (4.6) 0.884
 TIA 23 257 (11) 481 (12) 107 (7.0) 19 718 (11) 2951 (7.4) <0.001
 Stroke (minor/major/NA) 39 571 (18) 1137 (28) 326 (21) 31 249 (18) 6859 (17) <0.001
 Other elective symptoms 3764 (1.7) 80 (2.0) 28 (1.8) 2673 (1.5) 983 (2.5) 0.824
 cTIA/SIE 9962 (4.5) 414 (10) 417 (27) 5662 (3.2) 3469 (8.7) <0.001
 Other emergency symptoms 9990 (4.5) 386 (9.4) 248 (16) 6495 (3.7) 2861 (7.1) <0.001
Time interval (days)‡
 0–2 8023 (11) 260 (15) 104 (23) 6152 (11) 1507 (13) <0.001
 3–7 27 323 (38) 652 (38) 149 (32) 22 723 (39) 3799 (33) <0.001
 8–14 15 169 (21) 381 (22) 71 (15) 12 393 (21) 2324 (20) 0.962
 15–180 21 920 (30) 443 (26) 137 (30) 17 564 (30) 3776 (33) <0.001
Morphological characteristics§
 Ulcerated plaque 22 276 (10) 591 (14) 96 (6.3) 19 962 (11) 1627 (4.1) <0.001
 Aneurysmal change¶ 1418 (0.6) 68 (1.7) 27 (1.8) 891 (0.5) 432 (1.1) 0.394
 Coiling 1648 (0.8) 59 (1.4) 13 (0.9) 1449 (0.8) 127 (0.3) <0.001
 Multiple lesions 6354 (2.9) 239 (5.8) 211 (14) 3634 (2.1) 2270 (5.7) <0.001

Values are n (%) unless otherwise indicated. *ASA grade missing for 2085 patients. †Degree of stenosis is in accordance with the North American Symptomatic Carotid Endarterectomy Trial (NASCET) standard. ‡Only available for symptomatic patients treated electively (not available for 148 847 patients). §Each yes versus no. ¶Aneurysmal change in addition to the atherosclerotic stenosis. OE, outcome event; CEA, carotid endarterectomy; CAS, carotid artery stenting; TIA, transient ischaemic attack; NA, information not available; cTIA, crescendo transient ischaemic attack; SIE, stroke-in-evolution.

Table 2.

Perioperative and intraoperative management

Overall OE occurred OE did not occur P (chi-squared)
CEA CAS CEA CAS
Neurological assessment*
 Pre-procedural 161 069 (73) 3211 (78) 1341 (88) 124 088 (71) 32 429 (81) <0.001
 Post-procedural 138 556 (63) 3469 (85) 1393 (91) 104 419 (60) 29 275 (73) <0.001
 Pre- and post-procedural 128 510 (58) 2914 (71) 1289 (85) 96 118 (55) 28 189 (70) <0.001
Preoperative diagnostic procedures*†‡
 Duplex ultrasonography 152 681 (96) 2784 (97) 702 (71) 124 661 (98) 24 534 (88) <0.001
 Transcranial Doppler 45 833 (29) 956 (33) 415 (42) 34 348 (27) 10 114 (36) <0.001
 CT angiography 83 861 (53) 1899 (66) 681 (69) 66 739 (53) 14 542 (52) <0.001
 MRI angiography 74 976 (47) 1301 (45) 419 (42) 60 729 (48) 12 527 (45) <0.001
Perioperative antiplatelet medication
 None 13 361 (6.0) 332 (8.1) 148 (9.7) 11 577 (6.6) 1304 (3.3) <0.001
 ASS monotherapy 163 612 (74) 3464 (85) 477 (31) 149 984 (85) 9687 (24) <0.001
 Clopidogrel monotherapy 5781 (2.6) 94 (2.3) 53 (3.5) 4392 (2.5) 1242 (3.1) <0.001
 Other monotherapy 1078 (0.5) 8 (0.2) 33 (2.2) 767 (0.4) 270 (0.7) <0.001
 Dual antiplatelet medication 37 450 (17) 201 (4.9) 813 (53) 8905 (5.1) 27 531 (69) 0.001
Type of anaesthesia‡
 Local 34 775 (27) 589 (21) 34 186 (27)
 General 91 562 (71) 2194 (76) 89 368 (71)
 Combined§ 3265 (2.5) 97 (3.4) 3168 (2.5)
Intra-procedural monitoring‡¶
 Electroencephalography 8209 (5.2) 149 (5.2) 8 (0.8) 7903 (6.2) 149 (0.5) 0.008
 Transcranial cerebral oximetry 24 417 (15) 401 (14) 239 (24) 16 383 (13) 7394 (27) 0.001
 SSEP 36 417 (23) 756 (26) 8 (0.8) 35 320 (28) 333 (1.2) 0.900
 Other methods 36 780 (23) 576 (20) 186 (19) 30 234 (24) 5784 (21) <0.001
Operation technique‡
 TEA direct suture 2017 (1.6) 64 (2.2) 1953 (1.5)
 TEA with patch 44 944 (35) 1004 (35) 43 940 (35)
 Eversion CEA 53 149 (41) 963 (33) 52 186 (41)
 Interposition 2478 (1.9) 144 (5.0) 2334 (1.8)
 Other techniques# 27 014 (21) 705 (25) 26 309 (21)
Intra-arterial shunt use*‡ 55 681 (35) 16 040 (56) 54 077 (43)
Intraoperative completion study‡
 Any type 116 715 (74) 1960 (68) 933 (94) 88 196 (70) 25 626 (92) <0.001
 Imaging technique only 88 085 (56) 1329 (46) 917 (92) 60 700 (48) 25 139 (91) <0.001
Duration of operation (min), median (interquartile range) 80 (60–103) 94 (74–122) 60 (42–90) 86 (68–107) 45 (40–60) <0.001
Duration of hospital stay after procedure (days), median (interquartile range)
 All patients 5 (3–6) 9 (5–16) 8 (4–14) 5 (4–6) 2 (2–5) <0.001
 Asymptomatic patients 4 (3–6) 9 (5–16) 7 (3–14) 5 (4–6) 2 (2–4) <0.001
 Symptomatic patients 5 (4–7) 10 (5–16) 8 (4–14) 5 (4–7) 3 (2–6) <0.001

Values are n (%) unless otherwise indicated. *Yes versus no. †Multiple answers possible. ‡Only available from 2012 to 2016. §Patients who received a combination of local and general anaesthesia were likely to have predominantly undergone conversion from local to general anaesthesia. †,¶Multiple answers possible; information on percentages of subcategories refers to the cohort of patients who received intra-procedural neurophysiological monitoring; other methods include local anaesthesia in combination with the duck squeezing test, transcranial Doppler sonography, and measurement of stump pressure. #Other techniques include, for example, transposition of the carotid bifurcation, as well as procedures documented as ‘other’. OE, outcome event; CEA, carotid endarterectomy; CAS, carotid artery stenting; ASS, Acetylsalicylic acid; SSEP, Somatosensory evoked potential.

Outcomes and interaction effects

A total of 5623 events occurred, which corresponded to an overall raw risk of stroke or death until hospital discharge of 2.5%. The risk of OE was 2.3% and 3.7% in patients who underwent CEA and CAS respectively (Table 3). Patient age was statistically significantly associated with higher OE risk (main effect of age by 10-year steps: adjusted OR 1.21 (95% c.i. 1.17 to 1.26), P < 0.001). The age effect was statistically significantly stronger in patients treated with CAS (interaction effect: adjusted OR 1.29 (95% c.i. 1.20 to 1.38), P < 0.001) (Table 3). Figure 2a illustrates the association between age, treatment type, and risk of OE. Higher annual centre volume (all CEA and CAS procedures) was associated with lower risk of OE (main effect of hospital volume per 1 log point: adjusted OR 0.84 (95% c.i. 0.80 to 0.89), P < 0.001). However, the volume–outcome effect was not different between CEA and CAS (interaction effect: adjusted OR 1.02 (95% c.i. 0.95 to 1.11), P = 0.549). Figure 2b shows the volume–outcome association. Multilevel multivariable regression analysis revealed statistically significant interaction effects for the side of treatment, ASA grade, contralateral degree of stenosis, the time interval between the index event and treatment, and aneurysmal change of the ipsilateral internal carotid artery (Table 3).

Table 3.

Adjusted ORs for the interaction effect between the index clinical variable, treatment type, and outcome

Clinical variable Raw risk (%) Raw relative risk, CAS versus CEA Interaction effect, CAS versus CEA
CEA CAS RR (95% c.i.) P aOR (95% c.i.) P
Overall cohort 2.3 3.7 1.61 (1.52,1.70) <0.001
Age (10-year steps) 1.29 (1.20,1.38) <0.001*
Centre annual caseload 1.02 (0.95,1.11) 0.549
Sex
 Male (reference) 2.3 3.5 1.56 (1.46,1.68) <0.001 1.11 (0.97,1.26) 0.123
 Female 2.3 3.9 1.71 (1.55,1.89) <0.001
Side of treatment
 Right 2.0 3.4 1.74 (1.59,1.90) <0.001 1.17 (1.03,1.32) 0.011*
 Left (reference) 2.6 3.9 1.50 (1.39,1.63) <0.001
ASA grade
 I + II 1.3 2.3 1.83 (1.63,2.06) <0.001 Reference
 III 2.4 4.3 1.76 (1.61,1.91) <0.001 1.05 (0.91,1.22) 0.495
 IV + V 8.2 18.2 2.21 (1.94,2.53) <0.001 1.35 (1.09,1.65) 0.004*
Ipsilateral degree of stenosis†
 Mild (<50%) 4.8 5.2 1.07 (0.79,1.46) 0.657 0.75 (0.54,1.05) 0.091
 Moderate (50–69%) 3.1 4.2 1.33 (1.06,1.67) 0.013 0.89 (0.70,1.15) 0.377
 Severe (70–99%) 2.1 3.1 1.44 (1.35,1.54) <0.001 Reference
 Occlusion (100%) 9.7 14.4 1.49 (1.22,1.82) <0.001 0.95 (0.74,1.21) 0.657
Contralateral degree of stenosis†
 Mild (<50%) 2.1 3.7 1.77 (1.65,1.90) <0.001 1.15 (0.95,1.38) 0.152
 Moderate (50–69%) 2.3 2.9 1.25 (1.03,1.52) 0.026 0.80 (0.61,1.05) 0.104
 Severe (70–99%) 2.6 4.1 1.59 (1.35,1.88) <0.001 Reference
 Occlusion (100%) 4.1 4.0 0.98 (0.82,1.18) 0.856 0.61 (0.47,0.79) <0.001*
Neurological symptoms
 Asymptomatic 1.4 1.7 1.20 (1.08,1.35) 0.001 Reference
 Symptomatic
  Amaurosis fugax 1.3 1.3 0.97 (0.63,1.49) 0.884 0.72 (0.45,1.16) 0.182
  TIA 2.4 3.5 1.47 (1.20,1.81) <0.001 1.04 (0.81,1.34) 0.734
  Stroke (minor/major/NA) 3.5 4.5 1.29 (1.15,1.46) <0.001 1.02 (0.84,1.23) 0.866
  Other elective symptoms 2.9 2.8 0.95 (0.62,1.46) 0.824 0.79 (0.49,1.27) 0.330
  cTIA/SIE 6.8 10.7 1.57 (1.38,1.79) <0.001 1.09 (0.88,1.34) 0.427
  Other emergency symptoms 5.6 8.0 1.42 (1.21,1.66) <0.001 1.03 (0.82,1.28) 0.819
Time interval (days)‡
 0–2 4.1 6.5 1.59 (1.28,1.99) <0.001 1.71 (1.21,2.43) 0.003*
 3–7 2.8 3.8 1.35 (1.14,1.61) <0.001 1.38 (0.87,2.19) 0.170
 8–14 3.0 3.0 0.99 (0.77,1.28) 0.962 Reference
 15–180 2.5 3.5 1.42 (1.18,1.72) <0.001 1.50 (0.94,2.39) 0.090
Morphological characteristics
 Ulcerated plaque 2.9 5.6 1.94 (1.57,2.39) <0.001 1.15 (0.91,1.46) 0.235
 Aneurysmal change§ 7.1 5.9 0.83 (0.54,1.28) 0.396 0.49 (0.31,0.78) 0.002*
 Coiling 3.9 9.3 2.37 (1.34,4.22) 0.003 1.38 (0.74,2.56) 0.311
 Multiple lesions 6.2 8.5 1.38 (1.15,1.65) <0.001 0.86 (0.70,1.06) 0.169

Raw risks for age and volume are shown in Fig. 2. *Statistically significant. †Degree of stenosis is in accordance with the North American Symptomatic Carotid Endarterectomy Trial (NASCET) standard. ‡Only available for symptomatic patients treated electively. §Aneurysmal change in addition to the atherosclerotic stenosis. CAS, carotid artery stenting; CEA, carotid endarterectomy; RR, relative risk; aOR, adjusted OR (statistical interaction effect between the index variable, treatment (CAS versus CEA), and the risk of any stroke or death until discharge (primary outcome event)); TIA, transient ischaemic attack; NA, information not available; cTIA, crescendo transient ischaemic attack; SIE, stroke-in-evolution.

Fig. 2.

Fig. 2

Visualized association between the type of treatment, the risk of stroke or death until discharge from hospital, and patient age or annual hospital volume

a Patient age. b Annual hospital volume. Data derived from microsimulation (see the Methods section). Absolute risk of stroke or death until discharge was simulated based on the parameters derived from the multivariable regression models. A microsimulation was necessary because a direct display of data points of individual patients was prohibited for data protection reasons. Carotid endarterectomy = blue and carotid artery stenting = red. CEA, carotid endarterectomy; CAS, carotid artery stenting.

Discussion

This analysis of nationwide real-world data reveals the generally higher in-hospital risk of stroke or death after CAS. Therefore, this analysis highlights that CEA is the treatment of choice, as recommended by current guidelines. Based on this study, CAS may be particularly disadvantageous in older patients, in patients with right-sided stenosis, and in symptomatic patients treated within the first 2 days after the index event. It may be equivalent to CEA in patients with contralateral occlusion, as well as symptomatic patients treated in the second week after the index event. Greater than 40 000 CAS procedures were performed from 2012 to 2018, of which 21 000 were in asymptomatic patients, despite the recommendations in the German–Austrian guideline (first published in 2012). The reasons for method selection cannot be substantiated based on the available data, but widespread compliance with the guideline recommendations still appears inadequate in Germany. This should encourage national educational measures to improve guideline-compliant care.

The overall risk of OE was generally higher in CAS compared with CEA (3.7% versus 2.3% respectively), which corresponds well with other reports4,25 and a comprehensive Cochrane systematic review26. The latter meta-analysis included 5396 patients from 10 RCTs. The risk of any stroke or death within 30 days in asymptomatic patients in this Cochrane review was 1.4% for CEA and 2.5% for CAS (OR 1.72 (95% c.i. 1.00 to 2.97)). In symptomatic patients, these figures were 4.4% versus 7.2% respectively (OR 1.70 (95% c.i. 1.31 to 2.19)). In comparison, the specific risks for CEA and CAS in this study were 1.4% and 1.7% respectively in asymptomatic patients and 3.3% and 5.7% respectively in symptomatic patients (elective or emergency treatment). These values are generally somewhat lower compared with the Cochrane review cited above and other studies. The German quality assurance data are exclusively inpatient data, whereas the risks reported in RCTs are usually associated with an interval of up to 30 days; consequently, the risks determined in this study are probably too low, with the actual risks being higher. Information bias can be assumed, as statutory quality assurance in Germany relates exclusively to the inpatient sector, with no association with other social data to date. The different duration of hospital stay needs to be considered, which is statistically significantly shorter for CAS (2 days) than for CEA (5 days). This results in a shorter interval ‘under observation’ for CAS in which an OE could be recorded for quality assurance purposes. Therefore, the actual outcome risks may be even higher after CAS compared with CEA and the size of the differential effects found in this study is probably underestimated.

The association between age and the risk of OE was stronger in CAS compared with CEA (Fig. 2a). The different slopes for CEA and CAS can be used to identify the effect modification. This indicates that, the older the patients, the lower the relative risk of CEA compared with CAS under otherwise identical conditions. These results are congruent with earlier publications from Germany16,17, an individual patient meta-analysis of the Carotid Stenting Trialists’ Collaboration (CSTC; data from the International Carotid Stenting Study (ICSS), the Carotid Revascularization Endarterectomy versus Stent Trial (CREST), the Endarterectomy versus Angioplasty in Patients with Symptomatic Severe Carotid Stenosis (EVA-3S) trial, and the Stent-Protected Angioplasty versus Carotid Endarterectomy (SPACE) trial)27,28, and a systematic review of international observational studies29. The aforementioned CSTC meta-analysis identified age as a statistically significant effect modifier, but all other subgroups analysed demonstrated no evidence of effect modification. These divergent results may be due to several variations between the CSTC data and the mandatory nationwide German carotid database. In particular, the CSTC included considerably fewer patients (3433 versus 221 282), only symptomatic patients, only patients who were eligible for both procedures, only patients in participating centres, only patients who consented to study participation, and only patients who met all inclusion criteria, and participating centres and physicians had to meet all minimum requirements for participation. Conversely, the CSTC included patients who were randomized (but only for the CEA–CAS head-to-head comparison), patients who were from different countries, and, most importantly, patients who were prospectively documented, resulting in very low information bias. Notably, the external validity of RCTs is heterogeneous and may vary from clinical practice, for example concerning age, co-morbidities and medication, as analysed in detail by Kallmayer et al.30. A higher risk in older patients could be caused by increasing vascular calcification with age, especially in patients with calcification of the access routes to the carotid artery16,17. A retrospective analysis of the Vascular Quality Initiative database that included 11 342 patients who underwent transfemoral CAS or transcarotid artery revascularization (TCAR) supported this notion; this study revealed that marked carotid artery calcification was associated with worse outcomes in patients who underwent transfemoral CAS, whereas this was not the case with TCAR31. Additionally, the formation of unfavourable aortic arch anatomy during ageing may cause a higher risk in old patients who undergo CAS26,32. Further, the negative effects of an unfavourable or longer access route could cause a higher risk of right-sided stenosis in CAS than in CEA, as the present study reveals. A higher risk of right-sided CAS was also found in the systematic review by Touzé et al.29, which included greater than 30 000 patients from 12 studies.

The risk of OE was comparable in both CEA (4.1%) and CAS (4.0%) in the subgroup of patients with contralateral carotid occlusion (CCO). In contrast, Krawisz et al.33 analysed 58 423 patients from the USA and reported that the risk of in-hospital stroke or death in patients with CCO was 3.0% for CEA and 1.9% for CAS. These results are congruent with the findings of Touzé et al.29, demonstrating that CEA was statistically significantly associated with a higher risk of stroke or death in patients with CCO (risk ratio 1.56 (95% c.i. 1.31 to 1.86)), whereas CAS exhibited no increased risk in patients with CCO. Additionally, contralateral occlusion was determined to be a statistically significant predictor of the 30-day stroke or death rate after CEA and was thus included in the Ontario Carotid Endarterectomy Registry risk model34. A large external validation study identified the Ontario Carotid Endarterectomy Registry risk model as providing the most reliable predictions of stroke or death rates after CEA7; unfortunately, the study did not conduct a direct comparison with CAS. In summary, more consideration may be given to CAS in the presence of a CCO.

A comprehensive review of 71 studies including greater than 230 000 symptomatic patients summarized that early CEA within 2 or up to 7 days after the index event was safer than transfemoral CAS regarding the timing of treatment35. This is congruent with the results of the present study and an earlier secondary data analysis of the German statutory quality assurance database19. The present analysis considers CAS to be equivalent only in the second week after the index event, and otherwise inferior to CEA, especially in the first 2 days after the index event. In summary, the current real-world data support the recommendations of the guidelines, including those of the European Society for Vascular Surgery (ESVS): patients who are undergoing revascularization within the first 14 days after the onset of symptoms are recommended to undergo CEA, rather than carotid stenting2.

A detailed discussion of the limitations can be found in the Supplementary material and elsewhere10–13,15–21,36–39. In summary, this is a secondary data analysis and thus all difficulties associated with observational studies using routine data must be considered. This is a retrospective study with the observation interval only covering the inpatient stay. All information in the database is self-reported, but the reporting of data on all CEA and CAS procedures was mandatory and required by law in a standardized manner for all of Germany. Only the variables available in the mandatory documentation form could be analysed; thus, risk adjustment was limited and residual confounding could not be excluded.

Supplementary Material

znae227_Supplementary_Data

Acknowledgements

The authors would like to thank Dr Eva Knipfer, MHBA, Mrs Lan Zang, MD, and Dr Stefan Saicic, MD, all from the Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich. Additionally, the authors thank Prof. Volker Schmid, PhD, from the Department of Statistics, Ludwig-Maximilians-University of Munich. Furthermore, the authors thank Thomas Lang, MSc, Michael Salvermoser, MSc, Joana Huber, MSc, Sofie Lückerath, MD, and Simon Heuberger, PhD, all former employees of the Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich. Finally, the authors thank Peter Hermanek, Julian Böhm, and Rebecca Moser, all from the Landesarbeitsgemeinschaft zur datengestützten, einrichtungsübergreifenden Qualitätssicherung in Bayern (LAG Bayern), and the employees from the IQTIG, for their valuable support regarding data extraction.

Contributor Information

Andreas Kuehnl, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Christoph Knappich, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Felix Kirchhoff, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Bianca Bohmann, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Vanessa Lohe, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Shamsun Naher, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Hans-Henning Eckstein, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Michael Kallmayer, Department for Vascular and Endovascular Surgery, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.

Funding

The present analysis was a pre-planned substudy of the ISAR-IQ project (Integration and Spatial Analysis of Regional, site-specific, and patient-level factors for Improving the Quality of treatment for carotid artery stenosis) that was funded by Germany’s Federal Joint Committee Innovation Fund (G-BA Innovationsfonds, 01VSF19016 ISAR-IQ).

Disclosure

The authors declare no conflict of interest.

Supplementary material

Supplementary material is available at BJS online.

Data availability

The datasets analysed during the current study are available on request from the IQTIG, (https://iqtig.org/qs-verfahren-uebersicht/sekundaere-datennutzung/).

Author contributions

Andreas Kuehnl (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing), Christoph Knappich (Conceptualization, Data curation, Investigation, Supervision, Writing—review & editing), Felix Kirchhoff (Data curation, Validation, Writing—review & editing), Bianca Bohmann (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing—review & editing), Vanessa Lohe (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing—review & editing), Shamsun Naher (Data curation, Formal analysis, Investigation, Methodology, Validation, Writing—review & editing), Hans-Henning Eckstein (Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing—review & editing), and Michael Kallmayer (Conceptualization, Investigation, Project administration, Resources, Supervision, Validation, Writing—original draft, Writing—review & editing)

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Associated Data

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

Supplementary Materials

znae227_Supplementary_Data

Data Availability Statement

The datasets analysed during the current study are available on request from the IQTIG, (https://iqtig.org/qs-verfahren-uebersicht/sekundaere-datennutzung/).

Author contributions

Andreas Kuehnl (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing), Christoph Knappich (Conceptualization, Data curation, Investigation, Supervision, Writing—review & editing), Felix Kirchhoff (Data curation, Validation, Writing—review & editing), Bianca Bohmann (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing—review & editing), Vanessa Lohe (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing—review & editing), Shamsun Naher (Data curation, Formal analysis, Investigation, Methodology, Validation, Writing—review & editing), Hans-Henning Eckstein (Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing—review & editing), and Michael Kallmayer (Conceptualization, Investigation, Project administration, Resources, Supervision, Validation, Writing—original draft, Writing—review & editing)

References

  • 1. Eckstein  HH, Kuhnl  A, Berkefeld  J, Lawall  H, Storck  M, Sander  D. Diagnosis, treatment and follow-up in extracranial carotid stenosis. Dtsch Arztebl Int  2020;117:801–807 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Naylor  R, Rantner  B, Ancetti  S, de Borst  GJ, De Carlo  M, Halliday  A  et al.  Editor’s Choice—European Society for Vascular Surgery (ESVS) 2023 clinical practice guidelines on the management of atherosclerotic carotid and vertebral artery disease. Eur J Vasc Endovasc Surg  2023;65:7–111 [DOI] [PubMed] [Google Scholar]
  • 3. AbuRahma  AF, Avgerinos  ED, Chang  RW, Darling  RC  III, Duncan  AA, Forbes  TL  et al.  Society for Vascular Surgery clinical practice guidelines for management of extracranial cerebrovascular disease. J Vasc Surg  2022;75:4S–22S [DOI] [PubMed] [Google Scholar]
  • 4. Bogiatzi  C, Azarpazhooh  MR, Spence  JD. Choosing the right therapy for a patient with asymptomatic carotid stenosis. Expert Rev Cardiovasc Ther  2020;18:53–63 [DOI] [PubMed] [Google Scholar]
  • 5. Aboyans  V, Ricco  JB, Bartelink  MEL, Bjorck  M, Brodmann  M, Cohnert  T  et al.  2017 ESC guidelines on the diagnosis and treatment of peripheral arterial diseases, in collaboration with the European Society for Vascular Surgery (ESVS): document covering atherosclerotic disease of extracranial carotid and vertebral, mesenteric, renal, upper and lower extremity arteries. Eur Heart J  2018;39:763–816 [DOI] [PubMed] [Google Scholar]
  • 6. Dakour-Aridi  H, Faateh  M, Kuo  PL, Zarkowsky  DS, Beck  A, Malas  MB. The Vascular Quality Initiative 30-day stroke/death risk score calculator after transfemoral carotid artery stenting. J Vasc Surg  2020;71:526–534 [DOI] [PubMed] [Google Scholar]
  • 7. Poorthuis  MHF, Herings  RAR, Dansey  K, Damen  JAA, Greving  JP, Schermerhorn  ML  et al.  External validation of risk prediction models to improve selection of patients for carotid endarterectomy. Stroke  2022;53:87–99 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Swart  E, Gothe  H, Geyer  S, Jaunzeme  J, Maier  B, Grobe  TG  et al.  [Good Practice of Secondary Data Analysis (GPS): guidelines and recommendations]. Gesundheitswesen  2015;77:120–126 [DOI] [PubMed] [Google Scholar]
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