The Metabolic Health Index Identifies Patients That Will Benefit From Metabolic Surgery.

INTRODUCTION: Metabolic syndrome is a modern world's major health hazard related to comorbidities like type 2 diabetes and cardiovascular disease. Bariatric surgery is well known to lower this health risk in patients with obesity. There is a need for an objective measure to assess the intended reduction in health hazard and indirectly the eligibility for bariatric surgery. The Metabolic Health Index (MHI) quantitatively summarizes the cumulative impact of the metabolic syndrome on health status on a scale from 1 to 6. This study describes the use of the MHI as a supportive tool in the decision for and outcome assessment of bariatric surgery. METHODS: The general usability of the MHI was tested by extending its application to patient data of five other bariatric centers in the Netherlands. Retrospective laboratory and national bariatric quality registry data of 11,501 patients were collected. RESULTS: The quantification of (improvement in) metabolic health burden as measured by the MHI was independent of the dataset that was used to derive the MHI model. Patients with MHI > 2.8 prior to surgery improved significantly more in MHI 12 mo after surgery compared to patients with MHI ≤ 2.8 (1.1 compared to 0.4 MHI points, respectively; P < 0.001). CONCLUSIONS: The MHI is robust between centers and is suitable for general use in clinical decision-making. As changes in MHI over time reflect metabolic health alterations, it is suitable as an outcome measure of surgery. An MHI cut-off value of 2.8 helps to predict the likelihood of significant improvement after surgery, independent of body mass index and known metabolic comorbidities.

Assessment of Comorbidity in Bariatric Patients through a Biomarker-Based Model-A Multicenter Validation of the Metabolic Health Index.

BACKGROUND: The metabolic health index (MHI) is a biomarker-based model that objectively assesses the cumulative impact of comorbidities type 2 diabetes mellitus, hypertension and dyslipidemia on the health state of bariatric patients. The MHI was developed on a single-center cohort using a fully laboratory data-driven approach, resulting in a MHI score on a range from 1 to 6. To show universal applicability in clinical care, the MHI was validated externally and potential laboratory-related shortcomings were evaluated. METHODS: Retrospective laboratory and national bariatric quality registry data were collected from five Dutch renowned bariatric centers (n = 11 501). MHI imprecision was derived from the cumulative effect of biological and analytical variance of the individual input variables of the MHI model. The performance of the MHI (model) was assessed in terms of discrimination and calibration. RESULTS: The cumulative imprecision in MHI was 0.25 MHI points. Calibration of the MHI model diverged over the different centers but was accounted for by misregistration of comorbidity after cross-checking the data. Discriminative performance of the MHI model was consistent across the different centers. CONCLUSIONS: The MHI model can be applied in clinical practice of bariatric centers, regardless of patient mix and analytical platform. Because the MHI is based on objective parameters, it is insensitive to diverging clinical definitions of comorbidities. Therefore, the MHI can be used to objectify severity of metabolic comorbidities in bariatric patients. The MHI can support the patient-selection process for surgery and objectively assessing the effect of surgery on the metabolic health state.