Metabolic Health Index (MHI): Assessment of Comorbidity in Bariatric Patients Based on Biomarkers.
PURPOSE
The focus of bariatric surgery is reduction of weight, reflected in body mass index (BMI). However, the resolution of comorbidity is a second important outcome indicator. The degree of comorbidity is hard to quantify objectively as comorbidities develop gradually and are interdependent. Multiple scoring systems quantifying comorbidity exist but they lack continuity and objectivity. In analogy with BMI as index for weight, the Metabolic Health Index (MHI) is developed as objective quantification of metabolic health status. Laboratory data were used as comorbidities affect biomarkers. Conversely, laboratory data can be used as objectively obtained variables to describe comorbidity.


METHODS
Laboratory data were collected and crosschecked by national quality registry entries. Machine learning was applied to develop an ordinal logistic regression model, using 4 clinical and 32 laboratory input variables. The output was mathematically transformed into a continuous score for intuitive interpretation, ranging from 1 to 6 (MHI).


RESULTS
In total, 4778 data records of 1595 patients were used. The degree of comorbidity is best described by age at phlebotomy, estimated Glomerular Filtration Rate (eGFR), and concentrations of glycated hemoglobin (HbA1c), triglycerides, and potassium. The model is independent of day of sampling and type of surgery. Mean MHI was significantly different between patient subgroups with increasing number of comorbidities.


CONCLUSION
The MHI reflects severity of comorbidity, enabling objective assessment of a bariatric patient's metabolic health state, regardless day of sampling and surgery type. Next to weight-focused outcome measures like %TWL, the MHI can serve as outcome measure for metabolic health.
['van Loon|Saskia L M|SLM|0000-0001-9546-872X', 'Deneer|Ruben|R|', 'Nienhuijs|Simon W|SW|', 'Wilbik|Anna|A|', 'Kaymak|Uzay|U|', 'van Riel|Natal|N|', 'Scharnhorst|Volkher|V|', 'Boer|Arjen-Kars|AK|']
D000328:Adult D050110:Bariatric Surgery D015415:Biomarkers D015992:Body Mass Index D015897:Comorbidity D017281:Cost of Illness D003940:Diagnostic Techniques, Endocrine D005260:Female D005919:Glomerular Filtration Rate D006305:Health Status Indicators D006801:Humans D008297:Male D055442:Metabolome D008875:Middle Aged D008962:Models, Theoretical D009426:Netherlands D009767:Obesity, Morbid D017063:Outcome Assessment, Health Care D011379:Prognosis D015431:Weight Loss
Biomarkers Bariatric surgery Machine learning Outcome measure Diabetes Dyslipidemia Hypertension METABOLIC SURGERY Metabolic syndrome Value based health care