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 &gt; 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 &lt; 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.</p

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 &gt; 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 &lt; 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.</p

Visual Analysis of Biomarkers Reveals Differences in Lipid Profiles and Liver Enzymes before and after Gastric Sleeve and Bypass

Introduction: Bariatric surgery results in both intentional and unintentional metabolic changes. In a high-volume bariatric center, extensive laboratory panels are used to monitor these changes pre- and postoperatively. Consecutive measurements of relevant biochemical markers allow exploration of the health state of bariatric patients and comparison of different patient groups. Objective: The objective of this study is to compare biomarker distributions over time between 2 common bariatric procedures, i.e., sleeve gastrectomy (SG) and gastric bypass (RYGB), using visual analytics. Methods: Both pre- and postsurgical (6, 12, and 24 months) data of all patients who underwent primary bariatric surgery were collected retrospectively. The distribution and evolution of different biochemical markers were compared before and after surgery using asymmetric beanplots in order to evaluate the effect of primary SG and RYGB. A beanplot is an alternative to the boxplot that allows an easy and thorough visual comparison of univariate data. Results: In total, 1,237 patients (659 SG and 578 RYGB) were included. The sleeve and bypass groups were comparable in terms of age and the prevalence of comorbidities. The mean presurgical BMI and the percentage of males were higher in the sleeve group. The effect of surgery on lowering of glycated hemoglobin was similar for both surgery types. After RYGB surgery, the decrease in the cholesterol concentration was larger than after SG. The enzymatic activity of aspartate aminotransferase, alanine aminotransferase, and alkaline phosphate in sleeve patients was higher presurgically but lower postsurgically compared to bypass values. Conclusions: Beanplots allow intuitive visualization of population distributions. Analysis of this large population-based data set using beanplots suggests comparable efficacies of both types of surgery in reducing diabetes. RYGB surgery reduced dyslipidemia more effectively than SG. The trend toward a larger decrease in liver enzyme activities following SG is a subject for further investigation

Improved testing for vitamin B12 deficiency: correcting MMA for eGFR reduces the number of patients classified as vitamin B12 deficient

Background: Methylmalonic acid (MMA) can detect functional vitamin B12 deficiencies as it accumulates early when intracellular deficits arise. However, impaired clearance of MMA from blood due to decreased glomerular filtration rate (eGFR) also results in elevated plasma MMA concentrations. Alternative to clinical trials, a data mining approach was chosen to quantify and compensate for the effect of decreased eGFR on MMA concentration. Methods: Comprehensive data on patient’s vitamin B12, eGFR and MMA concentrations were collected (n = 2906). The relationship between vitamin B12, renal function (eGFR) and MMA was modelled using weighted multiple linear regression. The obtained model was used to estimate the influence of decreased eGFR on MMA. Clinical impact was examined by comparing the number of patients labelled vitamin B12 deficient with and without adjustment in MMA. Results: Adjusting measured MMA concentrations for eGFR in the group of patients with low-normal vitamin B12 concentrations (90–300 pmol/L) showed that the use of unadjusted MMA concentrations overestimates vitamin B12 deficiency by 40%. Conclusions: Through a data mining approach, the influence of eGFR on the relation between MMA and vitamin B12 can be quantified and used to correct the measured MMA concentration for decreased eGFR. Especially in the elderly, eGFR-based correction of MMA may prevent over-diagnosis of vitamin B12 deficiency and corresponding treatment

Left atrial reservoir strain as a predictor of cardiac outcome in patients with heart failure: the HaFaC cohort study

Background: The left atrium (LA) is a key player in the pathophysiology of systolic and diastolic heart failure (HF). Speckle tracking derived LA reservoir strain (LASr) can be used as a prognostic surrogate for elevated left ventricular filling pressure similar to NT-proBNP. The aim of the study is to investigate the correlation between LASr and NT-proBNP and its prognostic value with regards to the composite endpoint of HF hospitalization and all-cause mortality within 1 year. Methods: Outpatients, sent to the echocardiography core lab because of HF, were enrolled into this study. Patients underwent a transthoracic echocardiographic examination, commercially available software was used to measure LASr. Blood samples were collected directly after the echocardiographic examination to determine NT-proBNP. Results: We included 174 HF patients, 43% with reduced, 36% with mildly reduced, and 21% with preserved ejection fraction. The study population showed a strong inverse correlation between LASr and log-transformed NT-proBNP (r = − 0.75, p < 0.01). Compared to NT-proBNP, LASr predicts the endpoint with a comparable specificity (83% vs. 84%), however with a lower sensitivity (70% vs. 61%). Conclusion: LASr is inversely correlated with NT-proBNP and a good echocardiographic predictor for the composite endpoint of hospitalization and all-cause mortality in patients with HF. Trial registration:https://www.trialregister.nl/trial/726

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

Supplementary Material for: Visual Analysis of Biomarkers Reveals Differences in Lipid Profiles and Liver Enzymes before and after Gastric Sleeve and Bypass

Introduction: Bariatric surgery results in both intentional and unintentional metabolic changes. In a high-volume bariatric center, extensive laboratory panels are used to monitor these changes pre- and postoperatively. Consecutive measurements of relevant biochemical markers allow exploration of the health state of bariatric patients and comparison of different patient groups. Objective: The objective of this study is to compare biomarker distributions over time between 2 common bariatric procedures, i.e., sleeve gastrectomy (SG) and gastric bypass (RYGB), using visual analytics. Methods: Both pre- and postsurgical (6, 12, and 24 months) data of all patients who underwent primary bariatric surgery were collected retrospectively. The distribution and evolution of different biochemical markers were compared before and after surgery using asymmetric beanplots in order to evaluate the effect of primary SG and RYGB. A beanplot is an alternative to the boxplot that allows an easy and thorough visual comparison of univariate data. Results: In total, 1,237 patients (659 SG and 578 RYGB) were included. The sleeve and bypass groups were comparable in terms of age and the prevalence of comorbidities. The mean presurgical BMI and the percentage of males were higher in the sleeve group. The effect of surgery on lowering of glycated hemoglobin was similar for both surgery types. After RYGB surgery, the decrease in the cholesterol concentration was larger than after SG. The enzymatic activity of aspartate aminotransferase, alanine aminotransferase, and alkaline phosphate in sleeve patients was higher presurgically but lower postsurgically compared to bypass values. Conclusions: Beanplots allow intuitive visualization of population distributions. Analysis of this large population-based data set using beanplots suggests comparable efficacies of both types of surgery in reducing diabetes. RYGB surgery reduced dyslipidemia more effectively than SG. The trend toward a larger decrease in liver enzyme activities following SG is a subject for further investigation