Michael S Kiernan, MD, SM Assistant Professor, Tufts University Medical Director Ventricular Assist Device Program, Tufts Medical Center.

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Presentation transcript:

Michael S Kiernan, MD, SM Assistant Professor, Tufts University Medical Director Ventricular Assist Device Program, Tufts Medical Center

 I will not discuss off label use or investigational use in my presentation.  I have financial relationships to disclose.  Employee of: None  Consultant for: None  Stockholder in: None  Research support: None  Honoraria from: Thoratec Corporation

Morgan Ann Thorac Surg 2004;77:859 Delayed Planned Early Temporary Durable

Kalogeropoulos JHLT 2015;34(12):1595 Rate RHF: 15-44%

Kalogeropoulos JHLT 2015;34(12):1595

Afterload (PVR) RV Dysfunction RAP LVAD & Ventricular Inter- dependence RHF Lampert. JHLT 1025;34:1123 Goldstein. ATS 2003;75:S42

All Patients (N=11,162) Primary CF-LVAD (N=9976) Any RVAD (5.2%) (N=521) 1,186 Patients 610 pulsatile LVAD 323 pulsatile BiVAD 253TAH No RVAD (94.8%) (N=9455) Early RVAD (≤ 14 d) (3.9%) (N=386) Consort diagram of INTERMACS study cohort

TABLE 1 – Baseline Characteristics VariableAll (N=9976)Early RVAD (N=386)No Early RVAD (N=9590) p-value Demographics Age ≥ 60 years4722 (47.3%)161 (41.7%)4561(47.6%)0.02 Male7870 (78.9%)303 (78.5%)7567 (78.9%)0.84 INTERMACS Profile N=9976 N=386 N=9590< (Critical Cardiogenic)1493 (15.0%)153 (39.6%)1340 (14.0%) 2 (Progressive Decline)3805(38.1%)155 (40.2%)3650(38.1%) 3 (Stable on inotrope)2791 (28.0%)47 (12.2%)2744 (28.6%) Medical History Ischemic etiology4748 (48.0%)189 (49.7%)4559 (47.9%)0.48 Prior CABG or valve surgery2808 (28.1%)134 (34.7%)2674 (27.9%)0.003 Laboratory Variables Sodium [mmol/L] 135 ( ) 134 ( )135 ( )0.002 Creatinine [mg/dL]1.3 ( )1.4 ( )1.3 ( ) BUN [mg/dL]25 ( )29 (4-160)25 ( )<.0001 AST [u/L]30 (3-10,000)44.5 (11-10,000)29(3-6713)<.0001 Albumin [g/dL]3.4 (0-8)3.2 (0.27-6)3.4 (0-8)<.0001 Hemodynamics RAP [mmHg]12 (-3-40)16 (0- 40)12 (-3-40) <.0001 PA pulse pressure [PASP-PADP]25 (-37-74)20.5 ( )25 ( ) <.0001 RAP/PCWP0.5 ( )0.63 (0-2.77)0.5 ( )<.0001

TABLE 1 – Baseline Characteristics VariableAll (N=9976)Early RVAD (N=386)No Early RVAD (N=9590) p-value Demographics Age ≥ 60 years4722 (47.3%)161 (41.7%)4561(47.6%)0.02 Male7870 (78.9%)303 (78.5%)7567 (78.9%)0.84 INTERMACS Profile N=9976 N=386 N=9590< (Critical Cardiogenic)1493 (15.0%)153 (39.6%)1340 (14.0%) 2 (Progressive Decline)3805(38.1%)155 (40.2%)3650(38.1%) 3 (Stable on inotrope)2791 (28.0%)47 (12.2%)2744 (28.6%) Medical History Ischemic etiology4748 (48.0%)189 (49.7%)4559 (47.9%)0.48 Prior CABG or valve surgery2808 (28.1%)134 (34.7%)2674 (27.9%)0.003 Laboratory Variables Sodium [mmol/L] 135 ( ) 134 ( )135 ( )0.002 Creatinine [mg/dL]1.3 ( )1.4 ( )1.3 ( ) BUN [mg/dL]25 ( )29 (4-160)25 ( )<.0001 AST [u/L]30 (3-10,000)44.5 (11-10,000)29(3-6713)<.0001 Albumin [g/dL]3.4 (0-8)3.2 (0.27-6)3.4 (0-8)<.0001 Hemodynamics RAP [mmHg]12 (-3-40)16 (0- 40)12 (-3-40) <.0001 PA pulse pressure [PASP-PADP]25 (-37-74)20.5 ( )25 ( ) <.0001 RAP/PCWP0.5 ( )0.63 (0-2.77)0.5 ( )<.0001

Table 2 - Unadjusted odds ratios for outcome of EARLY RVAD VariableLevel% with Early RVAD Odds Ratio (95% CI) [vs. reference] P-valueN for Analysis Demographics Age<604.3% (225/5254)1.27 (CI: )p= >=603.4% (161/4722)ref INTERMACS Profile110% (153/1493)6.73 (CI: )p≤ % (155/3805)2.50 (CI: ) % (78/4678)ref Medical History Ischemic etiologyyes4.0% (189/4748)1.08 (CI: )p= no3.7% (191/5153) CABG/valve surgeryyes4.8% (134/2808)1.38 (CI: )p= no3.5% (252/7168)ref Biochemical markers BUN (mg/dL) % (101/3443)0.55 (CI: )p≤ % (104/3051)0.64 (CI: ) % (177/3407)ref ALT (U/L) % (94/3111)0.53 (CI: )p≤ % (101/2965)0.60 (CI: ) % (168/3038)ref Hemodynamic variables RA pressure(-) % (42/2163)0.33 (CI: )p≤ % (61/1896)0.55 (CI: ) % (115/2030)ref PA pulse pressure (mmHg)(-) % (136/2539)2.27 (CI: )p≤ % (79/2454)1.34 (CI: ) % (57/2348)ref RA/PCWP(-) % (44/1990)0.38 (CI: )p≤ % (61/2041)0.52 (CI: ) % (113/2021)ref

Table 2 - Unadjusted odds ratios for outcome of EARLY RVAD VariableLevel% with Early RVAD Odds Ratio (95% CI) [vs. reference] P-valueN for Analysis Demographics Age<604.3% (225/5254)1.27 (CI: )p= >=603.4% (161/4722)ref INTERMACS Profile110% (153/1493)6.73 (CI: )p≤ % (155/3805)2.50 (CI: ) % (78/4678)ref Medical History Ischemic etiologyyes4.0% (189/4748)1.08 (CI: )p= no3.7% (191/5153) CABG/valve surgeryyes4.8% (134/2808)1.38 (CI: )p= no3.5% (252/7168)ref Biochemical markers BUN (mg/dL) % (101/3443)0.55 (CI: )p≤ % (104/3051)0.64 (CI: ) % (177/3407)ref ALT (U/L) % (94/3111)0.53 (CI: )p≤ % (101/2965)0.60 (CI: ) % (168/3038)ref Hemodynamic variables RA pressure(-) % (42/2163)0.33 (CI: )p≤ % (61/1896)0.55 (CI: ) % (115/2030)ref PA pulse pressure (mmHg)(-) % (136/2539)2.27 (CI: )p≤ % (79/2454)1.34 (CI: ) % (57/2348)ref RA/PCWP(-) % (44/1990)0.38 (CI: )p≤ % (61/2041)0.52 (CI: ) % (113/2021)ref

Non-adjusted associations of continuous variables with outcomes: If straight line, then linear fit is ok Assumes independent variables are linearly related to log odds of the outcome

median Model building: Handling of nonlinear relationships between predictors and outcomes Dichotomization

Truncate beyond a ‘cut-point’ Model building: Handling of nonlinear relationships between predictors and outcomes

Missing Data > 50%RV failure by echo > 20%All hemodynamic variables > 20%LVEDD > 20%Some medications

Rerun with only significant variables on full dataset # included4530 RVAD157 (41%) Excluded5289 (53%) Complete Case Approach Total N9976 Obs used1048 RVAD33 Excluded89% 1 st pass at a multivariable model included all variables from Table (even those with >20% missing) Stepwise selection with a p-value of 0.10 to enter the model and p=0.05 to stay in the model

ParameterTertileOdds Ratio95% CIP-value LVEDD1.0 to to >7.2 (ref) RAP-3.0 to < to >15 (ref) RA:PCWP-0.5 to to >0.6 (ref) ECMO < Missing data is often not missing at random Final model utilized multiple imputation which allowed us to utilize observations on all available subjects Created 10 new datasets and re-estimated the effect size (ORs)

Conclusions Predicting RVAD use is complicated due to complex physiology of RHF Low prevalence of RVAD use will limits clinical utility of risk scores Many previously identified risk factors from smaller studies were confirmed as risk factors in the INTERMACS model It takes an expert to build a risk prediction model (Thank you Robin Ruthazer!) Next steps: Create an INTERMACS validation cohort Describe the late RVAD recipients (2%) Evaluate less severe RHF not resulting in RVAD