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Comparative analysis of multiparametric scores in heart failure: does the type of follow-up matter?

Session Poster Session 1

Speaker Joao AGOSTINHO

Event : Heart Failure 2019

  • Topic : heart failure
  • Sub-topic : Chronic Heart Failure – Epidemiology, Prognosis, Outcome
  • Session type : Poster Session

Authors : JR Agostinho (Lisbon,PT), T Rodrigues (Lisbon,PT), R Santos (Lisbon,PT), N Cunha (Lisbon,PT), J Rigueira (Lisbon,PT), A Nunes-Ferreira (Lisbon,PT), I Aguiar-Ricardo (Lisbon,PT), I Goncalves (Lisbon,PT), P Antonio (Lisbon,PT), S Pereira (Lisbon,PT), MM Pedro (Lisbon,PT), F Veiga (Lisbon,PT), N Lousada (Lisbon,PT), FJ Pinto (Lisbon,PT), D Brito (Lisbon,PT)

JR Agostinho1 , T Rodrigues1 , R Santos1 , N Cunha1 , J Rigueira1 , A Nunes-Ferreira1 , I Aguiar-Ricardo1 , I Goncalves1 , P Antonio1 , S Pereira1 , MM Pedro1 , F Veiga1 , N Lousada1 , FJ Pinto1 , D Brito1 , 1Santa Maria University Hospital/CHULN, CAML, CCUL, Lisbon School of Medicine, Universidade de Lisboa, Cardiology Department - Lisbon - Portugal ,

On behalf: RICA-HFTeam


Introduction : Multiple prediction score models have been validated to predict major adverse events in patients with heart failure (HF); however, these scores do not include variables related to the type of follow-up.
Objective : To evaluate the impact of a protocol-based follow-up program (PFP) of pts with chronic HF regarding scores accuracy for predicting 1-year hospitalizations and mortality.
Methods : Data from 2 HF populations were collected: one composed of pts included in a PFP after the index-hospitalization for HF; and a second one – the control population - composed of pts hospitalized prior to the beginning of the PFP. For each pt, the risk of hospitalization and mortality at 1-year was calculated using the COACH Risk Engine, BCN Bio-HF Calculator, MAGGIC Risk Calculator and Seattle Heart Failure Model. The accuracy of each score was established using the area below the ROC curve (AUC), calibration graphs and discordance (disc) calculation. AUC comparison was established by DeLong method.
Results : The PFP group included 56 pts, and the control group, 106 pts, with no significant differences between groups [median age: 67 vs 68.4 years; male sex: 58 vs 55%; median ejection fraction 28.2 vs 30.5%; functional class II: 60.7 vs 56.2%, I: 30.4 vs 31.9; p =NS). Hospitalization and mortality rates were significantly lower in the PFP group (21.4 vs 54.7, P <0.001, 5.4 vs 17.9, p <0.001, respectively).
Hospitalization risk calculated by COACH and BCN Bio-HF was 25.5 and 7.45% (disc: -55 and -79%, respectively) in the PFP group, and 24.5 and 11.5% (disc: 19 and -65%) in the control group. Mortality risk calculated by COACH, Bio-HF BCN, MAGGIC and Seattle was 21.5, 8.35, 11.1 and 13.7% (disc: 298, 55, 106 and 153%) in the PSP group and 20, 13.1, 11.65 and 14.5% (disc: 12, -26, -35 and -19%) in the control group.
When applied to the control group, COACH and BCN Bio-HF had, respectively, good (AUC 0.835) and reasonable (AUC: 0.712) accuracy to predict hospitalization. There was a significant reduction of COACH accuracy (AUC: 0.572; P =0.011) and a non-significant accuracy reduction of BCN Bio-HF (AUC: 0.536; P =0.1) when applied to the PFP group. All scores showed good accuracy to predict 1-year mortality (AUC: 0.863, 0.87, 0.818, 0.82, respectively) when applied to the control group.
However, when applied to the PFP group, a significant predictive accuracy reduction of COACH, BCN Bio-HF and MAGGIC (AUC: 0.366, 0.642 and 0.277, P: <0.001, 0.002 and <0.001, respectively) was observed. Seattle had no significant reduction in its acuity (AUC: 0.597; P: 0.24).
Conclusions : The accuracy of scores to predict major events in pts with HF is, globally, significantly reduced when they are applied to pts under follow-up in PFP. This may be related to the magnitude of reduction in major events rate that these programs entail. In these pts, BCN Bio-HF Calculator maintained reasonable accuracy and should be regarded as the score of choice.

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