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Patient selection for cardiac surgery: Time to consider subgroups within risk categories?
A van Giessen1, G A de Wit2, H A Smit1
1Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands.
Insights
Identifying homogeneous subgroups within cardiac surgery patients refines risk stratification. This enables tailored treatment strategies beyond average risk category care, moving towards personalized medicine for better patient outcomes.
Area of Science:
- Cardiology
- Medical Statistics
- Health Services Research
Background:
- Medical guidelines often assume risk categories are homogeneous, overlooking patient variability.
- Individuals with similar predicted risks may require different treatment approaches.
- Tailoring treatment allocation necessitates identifying distinct patient subgroups.
Purpose of the Study:
- To evaluate a strategy for identifying homogeneous subgroups within risk categories.
- To empirically illustrate this strategy for high-risk cardiac surgery patients.
- To enable more precise treatment allocation based on identified subgroups.
Main Methods:
- Cluster analysis applied to a dataset of 6517 cardiac surgery patients.
- Analysis performed separately for younger (<75 years) and older (≥75 years) patient groups.
- High postoperative mortality risk defined by EuroSCORE ≥ 15%.
Main Results:
- Two distinct, robust subgroups identified in younger patients, differing in preoperative state and recent cardiac events.
- Two distinct, robust subgroups identified in older patients, differing in preoperative state and comorbidities like COPD and prior surgery.
- Validity measures confirmed the quality and robustness of identified subgroups.
Conclusions:
- A feasible method for identifying homogeneous subgroups within risk categories was demonstrated.
- Subgroup-specific treatment strategies can replace average-risk strategies, advancing individualized care.
- Focusing on specific subgroups can improve allocation discussions for cardiac surgery interventions.
Background:
Medical guidelines increasingly use risk stratification and implicitly assume that individuals classified in the same risk category form a homogeneous group, while individuals with similar, or even identical, predicted risks can still be very different. We evaluate a strategy to identify homogeneous subgroups typically comprising predicted risk categories to allow further tailoring of treatment allocation and illustrate this strategy empirically for cardiac surgery patients with high postoperative mortality risk.
Methods:
Using a dataset of cardiac surgery patients (n=6517) we applied cluster analysis to identify homogenous subgroups of patients comprising the high postoperative mortality risk group (EuroSCORE ≥ 15%). Cluster analyses were performed separately within younger (<75 years) and older (≥ 75 years) patients. Validity measures were calculated to evaluate quality and robustness of the identified subgroups.
Results:
Within younger patients two distinct and robust subgroups were identified, differing mainly in preoperative state and indication of recent myocardial infarction or unstable angina. In older patients, two distinct and robust subgroups were identified as well, differing mainly in preoperative state, presence of chronic pulmonary disease, previous cardiac surgery, neurological dysfunction disease and pulmonary hypertension.
Conclusions:
We illustrated a feasible method to identify homogeneous subgroups of individuals typically comprising risk categories. This allows a single treatment strategy--optimal only on average, across all individuals in a risk category--to be replaced by subgroup-specific treatment strategies, bringing us another step closer to individualized care. Discussions on allocation of cardiac surgery patients to different interventions may benefit from focusing on such specific subgroups.
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