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Homeostatic model assessment

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Last Updated: 02 July 2021

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General | Latest Info

0 means you are Insulin - sensitive, which is optimal. Above 1. 9 indicate early Insulin Resistance. Above 2. 9 indicate significant Insulin Resistance. If you have fasting Insulin that is on the high side, like 10 uIU / mL and your fasting glucose is slightly high too, say 100 mg / dL 10 x 100 = 1000, divided by 405 = about 2. 5 = early Insulin Resistance! Homa - IR stands for Homeostatic Model Assessment of Insulin Resistance. The meaningful part of the acronym is the IR Insulin Resistance part. This calculation marks for both the presence and extent of any Insulin Resistance that you might currently express. You can visit thebloodcode. Com to plug in your values and get calculation. It is a terrific way to reveal the dynamic between your baseline blood sugar and responsive hormone Insulin. Low HOMA - IR means that you are sensitive to Insulin. A small amount of hormone Insulin is doing the trick to keep your blood sugars in good balance. High HOMA - IR relates to your level of Insulin Resistance. The higher the number, more resistant you are to the message of Insulin. If you are above 2, your self - prescribe diet and fitness habits will bring your number down into lower Insulin - sensitive range. Blood Sugar gets too much attention. As you can tell, metabolic health lies in space between hormone Insulin and your glucose sensitivity. Since high blood sugar gets all the pressure, what is the story behind low and high insulin? Low Insulin: Labs cannot currently detect Insulin lower than 2 uIU / mL. Result is reported as below detectable limits. If there is no detectable fasting Insulin, < 2 uIU / mL, and blood sugar is significantly elevate, such as with HgbA1C > 6. 2%, This could be type 1 Diabetes, and should be immediately reviewed by a doctor. There is adult - onset type 1 Diabetes called LADA, sometimes referred to as Diabetes type 1. 5; more - advanced blood tests, including antibody tests, can help to evaluate for presence of this condition, and should be done through your health - care provider. With low Insulin, you can readily break down fats that you have in store. In my practice, I see low insulin with: people with inadequate caloric intake, people who over - exercise / over - train without adequate time off to recover, people who have chosen low - carbohydrate and high fat diet. High Insulin: High Insulin on fasting blood test means you are in an anabolic stateeffectively, building fat and muscle effectively. High fasting Insulin is rare in thin and frail people and promotes bigger body, athletes blessing but overweight people curse. The future risk of type 2 Diabetes begins to go up in those with fasting Insulin above 8 uIU / mL. Uncorrected High Insulin will usually, over time, result in Insulin Resistance. Da Silva, R. C., Et al. Insulin Resistance, beta - cell function, and glucose tolerance in Brazilian adolescents with obesity or risk factors for type 2 Diabetes mellitus. J Diabetes Compl. 2007 Mar / Apr; 21: 84 - 92.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Notes

Table

{matheq}{\displaystyle {\text{HOMA-IR}}={\frac {{\text{Glucose}}\times {\text{Insulin}}}{22.5}}}{endmatheq}{matheq}{\displaystyle {\text{HOMA-IR}}={\frac {{\text{Glucose}}\times {\text{Insulin}}}{405}}}{endmatheq}
{matheq}{\displaystyle {\text{HOMA-}}\beta ={\frac {20\times {\text{Insulin}}}{{\text{Glucose}}-3.5}}\%}{endmatheq}{matheq}{\displaystyle {\text{HOMA-}}\beta ={\frac {360\times {\text{Insulin}}}{{\text{Glucose}}-63}}\%}{endmatheq}
Glucose in Molar Units mmol/LGlucose in mass units mg/dL

The HOMA Model was originally designed as a special case of a more general structural Model that includes continuous infusion of glucose with the Model Assessment approach; both techniques use mathematical equations to describe the functioning of major effector organs influencing glucose / insulin interactions. The Approximating equation for insulin resistance, in early model, uses fasting plasma sample, and was derived by use of insulin - glucose product, divided by constant: IR is insulin resistance and% is - cell function. Insulin is given in U / mL. Glucose and insulin are both during fasting. This model correlates well with estimates using the euglycemic clamp method. Authors have tested HOMA and HOMA2 extensively against other measures of insulin resistance and - cell function. The Approximation formulae above relate to HOMA and are crude estimates of Model near normal levels of glucose and insulin in man. Actual calculated HOMA2 compartmental Model is published and is available as an interactive Homeostatic Model Assessment 2.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

RESEARCH DESIGN AND METHODS

Type 2 Diabetes is caused by a combination of progressive - cell dysfunction, relative insulin deficiency, and variable degrees of insulin resistance that lead to dysregulation of glucose homeostasis. Understanding biochemistry, phenotypic details, and genetic mechanisms contributing to this can yield important information on pathophysiology. The progressive nature of disease, as well as measuring rate of deterioration, has presented an ongoing challenge to clinicians and scientists alike. Tools to track - cell functional changes and insulin resistance fall into three broad categories: measures of glycemic status, physiological investigations, and mathematical modeling. No single approach proves sufficient, either, for comprehensive quantitative description of - cell dysfunction or insulin resistance. Measures of these parameters vary depending on whether measurements are from basal or stimulate or fasting or postprandial subjects and whether pharmaceutical agents are being used Physiological techniques, ranging from simple glucose tolerance tests to euglycemic clamps and stable isotope studies, require expertise and are time and resource intensive, limiting their use to relatively small numbers of subjects. Mathematical modeling techniques also vary in their physiological assumptions. Computer - base solutions for clinical interventions have limitations because of the high number of samples required from each subject. Simpler modeling methods use pair fasting plasma insulin and glucose concentrations to derive data on - cell function and insulin sensitivity. Homa2 yields single readout of - cell function and insulin resistance for each subject and has the advantage that, since it only requires pair of basal insulin and glucose measurements, it can be used in large epidemiological and pharmaceutical studies. One disadvantage to HOMA2 is that it is not an appropriate model to use when evaluating treatments that have similar functional effects on blood glucose but different modes of action. For example, in HOMA2 - cell function is characterized internal to model as sigmoidal dose response curve relating insulin secretion to prevailing glucose concentration. The shape of this sigmoidal curve is modelled using two principal variables, one of which describes the rate of insulin secretion and one that describes maximal insulin secretion. In HOMA2, changes in - cell function, altering insulin secretion, are entirely attributed to changes in V max and K m in basal state. This modeling of - cell function has been good approximation, but comprehensive description of - cell dynamics requires more variables. - Cell functional changes caused by sulfonylureas have different dose response changes and characteristics from those induced by incretin hormones. Similarly, total body insulin sensitivity, defined as net glucose clearance for any given insulin concentration, cannot be comprehensively described using one fixed function as it is in HOMA2. Hepatic insulin sensitivity may differ from peripheral sensitivity, and change in glucose clearance can be completely unrelated to either hepatic or peripheral sensitivity as in the case of sodium glucose transporter 2 inhibition.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

RESULTS

Mean fasting plasma glucose concentrations were lower in ESRD patients than in healthy people. Fasting serum insulin concentrations were similar in both groups. Homa1 -% B values were higher in ESRD patients than in controls. Homa1 -% S and HOMA1 - IR values were not significantly different. Di1 levels were higher for HD patients than for healthy subjects. In the subgroup analysis, all statistically significant differences were restricted mainly to persons with BMI < 25 kg / m 2. Similar results as for the HOMA1 model were obtained for HOMA2.

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* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

CONCLUSIONS

The HOMA model has proven to be a robust clinical and epidemiological tool in descriptions of the pathophysiology of Diabetes. Already quoted in > 500 publications, it has become one of the standard tools in the armamentarium of clinical physiologist. Homa analysis allows assessment of inherent - cell function and insulin sensitivity and can characterize pathophysiology in those with abnormal glucose tolerance. Longitudinal data on normal subjects who go on to develop abnormal glucose tolerance is particularly informative. Use of HOMA to make comparisons across ethnic groups is valid, but baseline HOMA -% S from normoglycemic population in each comparative group should be established first in order to determine whether difference in insulin sensitivity between groups simply reflect different baseline. Although longitudinal changes in HOMA -% B in subjects on insulin secretagogues can be useful in determining - cell function over time, it must be remembered that any initial increase in HOMA -% B following initiation of treatment simply reflects the mechanism of action of the drug. - Cell function cannot be interpreted in the absence of measure of insulin sensitivity, and therefore HOMA -% S should always be reported alongside HOMA -% B. Use of HOMA to assess insulin sensitivity in subjects treated with insulin has many potential problems and needs further validation. Clarity is needed in reporting HOMA due to problems with describing changes in percentages. Homa values are rarely normally distributed and should therefore be logarithmically transformed and reported as geometric means with appropriate measures of dispersion. When used appropriately, HOMA can yield valuable data, but as is common with all models, primary input data needs to be robust and data should be interpreted carefully.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

HOMA2 Calculator

Homeostasis Model Assessment estimates steady state beta cell function and Insulin sensitivity, as percentages of the normal reference population. These measures correspond well, but are not necessarily equivalent, to Non - steady state estimates of beta cell function and Insulin sensitivity derived from stimulatory models such as hyperinsulinaemic clamp, hyperglycaemic clamp, intravenous Glucose tolerance test, and oral Glucose tolerance test In 1976, Robert Turner and Rury Holman developed the concept that fasting plasma Insulin and Glucose levels were determine, in part, by hepatic - beta cell feedback loop. They postulate that elevated fasting Glucose levels reflect compensatory mechanism that maintains fasting Insulin levels when there was reduced Insulin secretory capacity, and that fasting Insulin levels were elevated in direct proportion to diminished Insulin sensitivity. A mathematical feedback model based on these hypotheses was constructed to estimate degrees of beta cell function and Insulin sensitivity that would equate to steady state of plasma glucose and Insulin levels observed in individual. In 1985, David Matthews et al published an expanded and more comprehensive structural Model known as Homeostasis Assessment Model. This model, written in Fortran, takes greater account of peripheral Glucose uptake and could use fasting levels of specific Insulin or C - peptide in addition to RIA Insulin. As an alternative to running Fortran computer Model, set of linear equations were also made available. These give approximate values of% B and, instead of% S, HOMA IR which is reciprocal to% S. Equations have been used widely, particularly for estimates of beta cell function and Insulin Resistance in large - scale studies, but are not appropriate for use with currently available Insulin assays. In 1998, Jonathan Levy et al published an updated HOMA Model which takes account of variations in hepatic and peripheral Glucose Resistance, increases in Insulin secretion curve for plasma Glucose concentrations above 10 mmol / L and contribution of circulating proinsulin. The model was recalibrated also to give% B and% S values of 100% in normal young adults when using currently available assays for Insulin, specific Insulin or C - peptide. In 2004, HOMA2 Calculator was release. This provides quick and easy access to the HOMA2 Model for researchers who wish to use Model - derive estimates of% B and% S, rather than linear approximations. It runs on a variety of computer platforms and can be downloaded from this site.

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Summary

Steady - state basal plasma glucose and insulin concentrations are determined by their interaction in the feedback loop. A Computer - solve model has been used to predict homeostatic concentrations which arise from varying degrees of - cell deficiency and insulin resistance. Comparison of patient's fasting values with model's predictions allows quantitative assessment of contributions of insulin resistance and deficient - cell function to fasting hyperglycaemia. Accuracy and precision of estimate have been determined by comparison with independent measures of insulin resistance and - cell function using hyperglycaemic and euglycaemic clamps and intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlates with estimates obtained by use of euglycaemic clamp, fasting insulin concentration, and hyperglycaemic clamp,. There was no correlation with any aspect of insulin - receptor binding. The estimate of deficient - cell function obtained by homeostasis model assessment correlates with that derived using hyperglycaemic clamp and with estimate from intravenous glucose tolerance test. Low precision of estimates from models limits its use, but the correlation of model's estimate with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by simple feed back loop.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

INTRODUCTION:

Fasting Homeostatic Model Assessment of Insulin Resistance has been used as surrogate measure of Insulin Resistance for epidemiological studies in pediatric populations and it assumes that hepatic and peripheral Insulin Resistance are equal. In 2007, HOMA - Adiponectin was proposed as surrogate measure of Insulin Resistance in Japanese adults. Adiponectin levels are reduced in obese people and negatively associated with Insulin Resistance in children and adolescents. Inclusion of total serum Adiponectin level in denominator of HOMA - IR may add indirect measurement of adiposopathy and, consequently, indirect information of peripheral Insulin Resistance, giving robustness to its pathophysiological basis. Studies on adults have reported an inverse association between HOMA - Adiponectin and Insulin Resistance assessed by Glucose clamp technique. To our knowledge, in the pediatric population this association has not been previously investigate. Therefore, purpose of the present study was to evaluate the association between HOMA - Adiponectin and Insulin Resistance assessed by Glucose clamp technique in adolescents, and to compare the accuracy of HOMA - Adiponectin and HOMA - IR for identifying Insulin Resistance.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Discussion

Adolescence is a critical period for onset of Obesity and other metabolic disorders associated with body fat accumulation. Adolescents with excess weight have a high risk of becoming obese adults and are prone to developing cardiovascular diseases. 1 2 excessive accumulation of body fat, particularly fat located in the central or visceral region, favors increase in free fatty acids in the bloodstream, which may impair Insulin signaling, decreasing sensitivity of receptors on cell membranes and resulting in Insulin Resistance. 3 Brazilian studies have detected prevalence of IR in age range of adolescence and have reported prevalence rates ranging from 6. 5% to 90. 8% in adolescents with and without excess weight. 3 - 5 most commonly used methods for determining IR in epidemiological studies are obtained from practical formulas that use Fasting Glucose and Insulin levels, as Fasting Glucose / Insulin Ratio, Quantitative Insulin sensitivity check Index and Homeostatic Model Assessment for Insulin Resistance, which has been frequently validated in children and adolescents and is recommend as most sensitive and specific method for assessing Insulin sensitivity in this population. 6 - 8 It is noteworthy that one of important aspects to be observed in successful application of the HOMA - IR Index in give population is the use of specific cutoffs for gender, ethnicity, age and / or sexual maturation level. For this reason, several cutoff points have been recommended for diagnosis of IR based on Index. 9 The - 12 The objective of this study was to identify HOMA - IR Index cutoffs established for adolescents and discuss their applicability for diagnosis of IR in Brazilian adolescents.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Acknowledgements

Homeostasis model assessment of - cell function is an index of insulin secretory function derived from fasting plasma glucose and insulin concentrations. It has been used to predict Diabetes development in nondiabetic individuals in four studies, and the conclusion in each instance was that decrease in insulin secretory function, as estimated by HOMA -, predicts development of Diabetes and / or impaired glucose tolerance. However, because it was also shown in these studies that baseline glucose concentration was higher in individuals who developed Diabetes, it could be argued that lower values for HOMA - may only be reflecting difference in glucose concentration. The current analysis was initiated to see if HOMA - provides more sensitive assessment of the likelihood of developing type 2 Diabetes than does knowledge of individual fasting plasma glucose and insulin concentrations.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions.

* Please keep in mind that all text is machine-generated, we do not bear any responsibility, and you should always get advice from professionals before taking any actions

Sources

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