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01-05-2016 | Uitgave 5/2016 Open Access

Quality of Life Research 5/2016

Interaction between the Kansas City Cardiomyopathy Questionnaire and the Pocock’s clinical score in predicting heart failure outcomes

Tijdschrift:
Quality of Life Research > Uitgave 5/2016
Auteurs:
Kiswendsida Sawadogo, Jérôme Ambroise, Steven Vercauteren, Marc Castadot, Michel Vanhalewyn, Jacques Col, Annie Robert
Belangrijke opmerkingen

Electronic supplementary material

The online version of this article (doi:10.​1007/​s11136-015-1154-9) contains supplementary material, which is available to authorized users.

Abstract

Purpose

Heart failure (HF) is a complex syndrome. Its appropriate management should combine several health measurements. We assessed the relationship between the Kansas City Cardiomyopathy Questionnaire (KCCQ) and the Pocock’s clinical score.

Methods

We conducted a prospective registry of HF outpatients. The main outcome was occurrence of death or hospitalization during a 6-month follow-up. A multivariate logistic regression was performed, including the KCCQ overall summary score, the Pocock’s clinical score and their interaction in the model.

Results

From January 2008 to December 2010, 143 patients were involved. Mean age of patients was 68 years, and 74 % were men. KCCQ’s overall summary score and Pocock’s clinical score were inversely correlated (r = −0.24, p = 0.026). A total of 61 (42.7 %) events occurred. There was a high proportion of events (77.8 %) in patients with a Pocock’s clinical score >50 %, whatever the KCCQ score value. When the KCCQ score was ≤50 %, there was a low increase in risk as the Pocock’s clinical score increased (OR 2.0 [0.6; 6.6]). However, when the KCCQ score was between 50 and 75 or ≥75 %, there was a high increase in risk as the Pocock’s clinical score increased (OR 6.9 [1.2; 38.9] and OR 7.4 [0.8; 69.7], respectively).

Conclusions

Patients with a high Pocock’s clinical score are at a high risk of death or hospitalization. For patients with a low Pocock’s clinical score, the KCCQ score can identify those at risk of these events.

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