Risk Assessment in the CLI Patient: Who is Likely to Benefit from Revascularization and Who is Not? Easy 89 yo Non-ambulatory Multiple failed interventions Forefoot and heel gangrene Andres Schanzer, MD University of Massachusetts Medical School UCSF Vascular Symposium 77 yo Dialysis dependent Tissue loss Not so Easy CABG 2 years prior Lives at home independently Contralateral GSV present 7.5 Months Postop Angiogram: Mild iliac/cfa disease, occluded SFA/Pop with reconstitution of anterior tibial runoff to the foot 1
Predicting Outcomes Risk Stratification CLI is associated with a high risk of cardiovascular events including major limb loss, myocardial infarction, stroke and death. Decision Making Alternative Treatment Strategies Open surgical bypass traditionally has been the gold standard method for revascularization. 1. Endovascular techniques 2. Primary amputation 3. Conservative management 2
Goal: To develop and validate a prognostic risk index for patients with CLI considered for bypass surgery Research Design and Methods Study Design Retrospective review of three prospectively collected databases to derive and then validate a risk prediction model Data Sources PREVENT III 14 CLI patients from 83 hospitals External validation cohort * 716 CLI patients from 3 hospitals (BWH, USF, Sarasota Memorial) VSGNE 1166 CLI patients from 11 hospitals Schanzer et al, JVS, 9. *Schanzer et al, JVS,. Schanzer et al, JVS, 11. PIII CLI Risk Score Development 1. PREVENT III cohort randomly divided into a derivation set and a validation set Two-Thirds: PIII Derivation Set 14 patients One-Third: PIII Validation Set 953 patients 451 patients PIII CLI Risk Score Development 1. Derivation Multivariable model converted to a standard integer score system 2. Validation Internal validation (PIII validation set, n=451) External validation (External multicenter cohort, n=716) External validation (VSGNE, n=1166) External validation (Finland, n=1425) 3
Results Multivariable Model for 1-Year AFS COVARIATES Dialysis CLI criterion Age 75 years Hematocrit < History of advanced CAD Integer score 4 3 2 2 1 PIII Derivation Set Stratified by Risk Score COVARIATES Dialysis CLI criterion Age 75 years Hematocrit < History of advanced CAD β HR coefficient (95% CI) 2.81 1.3 (1.97, 3.99) <.1 4 2.22.8 (1.43, 3.44).4 1.6.5 (1.21-2.22).1 1.61.48 (1.11, 2.34).12 1.41.34 (1.5, 1.88).21 Risk Score Amputation-Free Survival (%) Integer P-Value score 1 93.1 2 89.7 3 86.2 4 81.1 5 76.1 6 74.5 7 71.7 8 63 9 51 44 11 27.3 12 33 LOW MED HIGH Discrimination PIII Derivation Set Stratified by Risk Score Risk Categories Integer Score Amputation- Free Survival HR p-value Low 3 85.9 1. (ref) Medium 4-7 73. 2.11 (1.54-2.89) <.1 High 8 44.6 5.5 (3.73-8.) <.1 PREVENT III DERIVATION SET N=953 9 8 7 6 5 PIII RISK SCORE for CRITICAL LIMB ISCHEMIA POINTS DIALYSIS 4 TISSUE LOSS 3 AGE 75 2 HCT % 2 CAD 1 9 8 7 6 5 4
Internal Validation 8 7 6 5 PREVENT III DERIVATION SET N=953 9 PREVENT III VALIDATION SET N=451 9 8 7 6 5 88% 64% <4 Points 4-8 Points >8 Points External Validation 1 PREVENT III DERIVATION SET N=953 9 8 7 6 5 9 8 7 6 5 BWH/USF/FSU DATASET N=716 7% 48% External Validation 2 PREVENT III DERIVATION SET N=953 9 8 7 6 5 9 8 7 6 5 VSGNNE DATASET N=1166 74% 56% <4 Points 4-8 Points >8 Points Characteristics DEMOGRAPHICS Age 75 African American MEDICATIONS Statin Beta-blocker RISK FACTORS Previous ipsilateral bypass Smoking (ever) Hypertension High cholesterol Ankle brachial index <.3 * Weight >75 kg SURGICAL CHARACTERISTICS Proximal anastomosis site CFA Distal anastomosis site Popliteal Single segment GSV conduit PIII Derivation Set n=953 (%) 7 (32.2) 173 (18.2) 431 (45.2) 554 (58.1) 138 (14.5) 79 (74.6) 774 (81.2) 445 (46.7) 457 (73.2) 52 (53.5) 464 (48.7) 3 (34.5) 781 (82.) VSGNNE Validation Set n=1166 (%) 443 (38.) 8 (.7) 386 (66.3) 494 (84.7) 124 (.6) 923 (79.4) 22 (87.7) 632 (54.3) 182 (24.1) 4 (37.7) 78 (6.7) 483 (41.2) 993 (85.3) p-value.6 <.1 <.1 <.1.7.9 <.1.5 <.1 <.1 <.1.1.42 5
Results-Validation Results-Validation Amputation-Free Survival AFS at One Year by Risk Category 9 85.9 87.7 86.3 86.4 8 73 63.7 7.1 74.1 7 6 56.1 5 44.6 45. 47.8 Low ( 3) Medium (4-7) High ( 8) PIII Derivation Set (n=953) Risk category (integer PIII Validation score) Set (n=451) Retrospective Validation Set (n=716) VSGNNE VALIDATION SET (n=1166) JVS, November, Conclusions The PIII Risk Score is easily used at initial presentation using five simple dichotomous variables: Dialysis-Dependency Tissue Loss on Presentation Hematocrit % Age 75 History of Advanced CAD Conclusions The PIII Risk Score is GENERALIZABLE Dialysis-Dependency Tissue Loss on Presentation Hematocrit % Age 75 History of Advanced CAD 6
The PIII risk score is a useful clinical tool for treatment decision planning Does it allow us to answer the question: Who is Likely to Benefit from Revascularization and Who is Not? PIII RISK SCORE for CRITICAL LIMB ISCHEMIA POINTS DIALYSIS 4 TISSUE LOSS 3 AGE 75 2 HCT % 2 CAD 1 9 8 7 6 5 VSGNE LEB Risk Prediction Models Amputation or graft occlusion at 1 year * Death at 1 year Ambulation status at 1 year Clinical failure, despite graft patency, at 1 year *Goodney et al, Annals of Vasc Surg,. Goodney et al, JVS, 9. Goodney et al, JVS,. Simons et al, JVS,. 7
Patients with no risk factors had amputation rates <1%; patients with >3 risk factors had nearly % chance of suffering amputation. Patients with no risk factors had 1-year death rates <5%; patients with >3 risk factors had 28% chance of dying by 1 year. *Goodney et al, Annals of Vasc Surg,. Goodney et al, JVS,. Likelihood of nonambulatory status at 1 year was <5% in patients with no risk factors and nearly 5% in patients with >3. After lower extremity bypass for CLI, % of patients with a patent graft did not achieve clinical improvement at 1 year. Goodney et al, JVS, 9. Simons et al, JVS,. 8
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Risk Assessment in the CLI Patient: Who is Likely to Benefit from Revascularization and Who is Not? We lack validated instruments to accurately answer this question We can predict some specific outcomes at specific time points with relatively reliable accuracy (i.e. <5% likelihood that patient is alive with an intact limb) The best we can do is try to use available data to help inform patient and physician decision-making
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