Key result
An elastic net model using cardiovascular biomarker profiles predicted cardiac dysfunction in obesity patients with an area under the curve of 0.87 (95% CI 0.79-0.94; p<0.001).
Case-Control (n=150)
Effect estimate: AUC 0.87 (95% CI 0.79-0.94)
p-value: p=< 0.001
Cardiovascular biomarker profiles differ significantly between obese and nonobese individuals, and a specific biomarker panel can accurately predict cardiac dysfunction in obese patients without known cardiovascular disease.
May enable early detection of cardiac dysfunction in obesity; leaves open prospective validation and outcome impact.
Aim: Current knowledge on the role of obesity in causing cardiac dysfunction is insufficient. Several biomarkers reflecting biological processes that may play a role in the occurrence of cardiac dysfunction in obesity patients are available. Purpose: To compare cardiovascular biomarker profiles between obesity patients and nonobese controls, and between obesity patients with and without cardiac dysfunction, in order to better understand the underlying pathophysiology of cardiac dysfunction in obesity patients. Materials & methods: Blood samples were obtained from 100 obesity patients (BMI ≥35 kg/m2) without known cardiovascular disease, and from 50 age- and gender-matched nonobese controls (BMI ≤30 kg/m2). The third cardiovascular panel of the Olink Multiplex platform was used for the measurement of 92 biomarkers. Results: The majority (53%) of biomarkers were elevated in obesity patients compared with nonobese controls. Only 5% of the biomarkers were elevated in obesity patients with cardiac dysfunction compared with those without. Biomarkers discriminating cardiac dysfunction from no cardiac dysfunction in obesity patients differed from those discriminating obese from nonobese patients. An elastic net model for the prediction of cardiac dysfunction in obesity patients had a high area under the receiver operating curve of 0.87 (95% CI: 0.79–0.94; p < 0.001). The sensitivity of this model was 84% and the specificity was 79%. Conclusion: A multiplex immunoassay was used for the first time in obesity patients without known cardiovascular disease. These patients have cardiovascular biomarker profiles that are clearly different from nonobese controls. Comparison of obesity patients with and without cardiac dysfunction suggested an important role for inflammation, atherosclerosis and insulin resistance in the underlying pathophysiology of cardiac dysfunction in obesity patients.
No takes yet. Share an insight, caveat, or question.
Snelder et al. (2021) conducted a case-control in Obesity and cardiac dysfunction (n=150). Obesity (BMI ≥35 kg/m2) vs. Nonobese controls (BMI ≤30 kg/m2) was evaluated on Prediction of cardiac dysfunction using an elastic net model of cardiovascular biomarkers (AUC 0.87, 95% CI 0.79-0.94, p=< 0.001). An elastic net model using cardiovascular biomarker profiles predicted cardiac dysfunction in obesity patients with an area under the curve of 0.87 (95% CI 0.79-0.94; p<0.001).
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: