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Interaction between the Kansas City Cardiomyopathy Questionnaire and the Pocock's clinical score in predicting heart
Kiswendsida Sawadogo1, Jérôme Ambroise2, Steven Vercauteren3
1The Pôle de recherche Epidémiologie et Biostatistique, Institut de Recherche Expérimentale et Clinique (IREC-EPID), Université catholique de Louvain, Clos Chapelle-aux-Champs 30, Box B1.30.13, 1200, Brussels, Belgium. kiswendsida.sawadogo@uclouvain.be.
Insights
High Pocock
Area of Science:
- Cardiology
- Clinical Medicine
- Health Outcomes Research
Background:
- Heart failure (HF) management requires integrating multiple health metrics.
- The Kansas City Cardiomyopathy Questionnaire (KCCQ) assesses patient-reported HF symptoms and function.
- Pocock's clinical score is a traditional risk stratification tool in HF.
Purpose of the Study:
- To evaluate the relationship between the KCCQ overall summary score and Pocock's clinical score.
- To determine the predictive value of these scores for adverse outcomes in heart failure patients.
Main Methods:
- A prospective registry of 143 heart failure outpatients was analyzed.
- The primary endpoint was death or hospitalization within a 6-month follow-up period.
- Multivariate logistic regression modeled the KCCQ score, Pocock's score, and their interaction.
Main Results:
- KCCQ and Pocock's scores were inversely correlated (r = -0.24, p = 0.026).
- A high Pocock's score (>50%) was associated with a high event rate (77.8%), irrespective of KCCQ score.
- The KCCQ score helped identify risk among patients with lower Pocock's scores.
Conclusions:
- High Pocock's clinical scores indicate elevated risk for death or hospitalization in HF patients.
- The KCCQ score is valuable for risk stratification in patients with lower Pocock's clinical scores.
- Combining KCCQ and Pocock's scores may refine HF risk assessment.
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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