Assessing the Utility of the Metabolic Score for Insulin Resistance (METS-IR) in Evaluating Metabolic Risk Among Individuals Undergoing Master Health Checkups in a Tertiary Care Hospital in South India: A Retrospective Cohort Study

Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based, objectively measured method. It is an easily accessible tool that can be used on a large scale to detect insulin resistance in a community....

Full description

Saved in:
Bibliographic Details
Published inCurēus (Palo Alto, CA) Vol. 16; no. 9; p. e70289
Main Authors Tazeem, Mohammed Suhail, Chandrasekaran, Nirmala Devi, Srivatsa, Niveda
Format Journal Article
LanguageEnglish
Published United States Cureus 26.09.2024
Subjects
Online AccessGet full text

Cover

Loading…
Abstract Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based, objectively measured method. It is an easily accessible tool that can be used on a large scale to detect insulin resistance in a community. Methods We conducted a retrospective cohort study to explore the utility of this score in identifying metabolic risk in those individuals attending a master health checkup in a tertiary care setting. Data were collected from 254 individuals between October and December 2023. Results According to the univariate regression analysis, METS-IR had a strong correlation in predicting cardiovascular health risks, as evidenced by its positive linear association with an increase in age (β=0.186, =0.003), weight (β=0.534, <0.001), waist circumference (β=0.405, <0.001), and body mass index (BMI; β=0.635, <0.001). This explained the value of this score in depicting adiposity and insulin resistance. Lab parameters that showed a significant association were fasting blood sugar (β=0.176, =0.005) and fasting triglycerides (β=0.175, =0.005). According to the multivariate regression analysis, METS-IR had a significant positive association with fasting blood sugar ( =0.489, <0.001) and fasting triglycerides ( =0.022, =0.003), implicating its importance in cardiovascular health. High-density lipoprotein cholesterol (HDL-c; =-0.168, =0.005) confirmed its protective role with its negative association in higher quartile groups. An increase in serum albumin levels ( =-0.168, =0.005) and raised gamma-glutamyl transpeptidase (GGT) ( =0.059, =0.022) portrays its due diligence in liver health. METS-IR had a weak association with the estimated glomerular filtration rate (eGFR) with Pearson's correlation coefficient of 0.020 ( =0.756) and Spearman's rho of 0.021 ( =0.739). However, raised serum creatinine had a significant association in higher quartile groups, with a value of 0.018. Conclusions METS-IR is useful as a screening tool for predicting cardiovascular disease. However, the complex interplay of other confounding factors in identifying renal dysfunction has yet to be explored when considering this score in our study population.
AbstractList Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based, objectively measured method. It is an easily accessible tool that can be used on a large scale to detect insulin resistance in a community. Methods We conducted a retrospective cohort study to explore the utility of this score in identifying metabolic risk in those individuals attending a master health checkup in a tertiary care setting. Data were collected from 254 individuals between October and December 2023. Results According to the univariate regression analysis, METS-IR had a strong correlation in predicting cardiovascular health risks, as evidenced by its positive linear association with an increase in age (β=0.186, =0.003), weight (β=0.534, <0.001), waist circumference (β=0.405, <0.001), and body mass index (BMI; β=0.635, <0.001). This explained the value of this score in depicting adiposity and insulin resistance. Lab parameters that showed a significant association were fasting blood sugar (β=0.176, =0.005) and fasting triglycerides (β=0.175, =0.005). According to the multivariate regression analysis, METS-IR had a significant positive association with fasting blood sugar ( =0.489, <0.001) and fasting triglycerides ( =0.022, =0.003), implicating its importance in cardiovascular health. High-density lipoprotein cholesterol (HDL-c; =-0.168, =0.005) confirmed its protective role with its negative association in higher quartile groups. An increase in serum albumin levels ( =-0.168, =0.005) and raised gamma-glutamyl transpeptidase (GGT) ( =0.059, =0.022) portrays its due diligence in liver health. METS-IR had a weak association with the estimated glomerular filtration rate (eGFR) with Pearson's correlation coefficient of 0.020 ( =0.756) and Spearman's rho of 0.021 ( =0.739). However, raised serum creatinine had a significant association in higher quartile groups, with a value of 0.018. Conclusions METS-IR is useful as a screening tool for predicting cardiovascular disease. However, the complex interplay of other confounding factors in identifying renal dysfunction has yet to be explored when considering this score in our study population.
Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based, objectively measured method. It is an easily accessible tool that can be used on a large scale to detect insulin resistance in a community. Methods We conducted a retrospective cohort study to explore the utility of this score in identifying metabolic risk in those individuals attending a master health checkup in a tertiary care setting. Data were collected from 254 individuals between October and December 2023. Results According to the univariate regression analysis, METS-IR had a strong correlation in predicting cardiovascular health risks, as evidenced by its positive linear association with an increase in age (β=0.186, p=0.003), weight (β=0.534, p<0.001), waist circumference (β=0.405, p<0.001), and body mass index (BMI; β=0.635, p<0.001). This explained the value of this score in depicting adiposity and insulin resistance. Lab parameters that showed a significant association were fasting blood sugar (β=0.176, p=0.005) and fasting triglycerides (β=0.175, p=0.005). According to the multivariate regression analysis, METS-IR had a significant positive association with fasting blood sugar (B=0.489, p<0.001) and fasting triglycerides (B=0.022, p=0.003), implicating its importance in cardiovascular health. High-density lipoprotein cholesterol (HDL-c; B=-0.168, p=0.005) confirmed its protective role with its negative association in higher quartile groups. An increase in serum albumin levels (B=-0.168, p=0.005) and raised gamma-glutamyl transpeptidase (GGT) (B=0.059, p=0.022) portrays its due diligence in liver health. METS-IR had a weak association with the estimated glomerular filtration rate (eGFR) with Pearson's correlation coefficient of 0.020 (p=0.756) and Spearman's rho of 0.021 (p=0.739). However, raised serum creatinine had a significant association in higher quartile groups, with a p-value of 0.018. Conclusions METS-IR is useful as a screening tool for predicting cardiovascular disease. However, the complex interplay of other confounding factors in identifying renal dysfunction has yet to be explored when considering this score in our study population.Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based, objectively measured method. It is an easily accessible tool that can be used on a large scale to detect insulin resistance in a community. Methods We conducted a retrospective cohort study to explore the utility of this score in identifying metabolic risk in those individuals attending a master health checkup in a tertiary care setting. Data were collected from 254 individuals between October and December 2023. Results According to the univariate regression analysis, METS-IR had a strong correlation in predicting cardiovascular health risks, as evidenced by its positive linear association with an increase in age (β=0.186, p=0.003), weight (β=0.534, p<0.001), waist circumference (β=0.405, p<0.001), and body mass index (BMI; β=0.635, p<0.001). This explained the value of this score in depicting adiposity and insulin resistance. Lab parameters that showed a significant association were fasting blood sugar (β=0.176, p=0.005) and fasting triglycerides (β=0.175, p=0.005). According to the multivariate regression analysis, METS-IR had a significant positive association with fasting blood sugar (B=0.489, p<0.001) and fasting triglycerides (B=0.022, p=0.003), implicating its importance in cardiovascular health. High-density lipoprotein cholesterol (HDL-c; B=-0.168, p=0.005) confirmed its protective role with its negative association in higher quartile groups. An increase in serum albumin levels (B=-0.168, p=0.005) and raised gamma-glutamyl transpeptidase (GGT) (B=0.059, p=0.022) portrays its due diligence in liver health. METS-IR had a weak association with the estimated glomerular filtration rate (eGFR) with Pearson's correlation coefficient of 0.020 (p=0.756) and Spearman's rho of 0.021 (p=0.739). However, raised serum creatinine had a significant association in higher quartile groups, with a p-value of 0.018. Conclusions METS-IR is useful as a screening tool for predicting cardiovascular disease. However, the complex interplay of other confounding factors in identifying renal dysfunction has yet to be explored when considering this score in our study population.
Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based, objectively measured method. It is an easily accessible tool that can be used on a large scale to detect insulin resistance in a community. Methods We conducted a retrospective cohort study to explore the utility of this score in identifying metabolic risk in those individuals attending a master health checkup in a tertiary care setting. Data were collected from 254 individuals between October and December 2023. Results According to the univariate regression analysis, METS-IR had a strong correlation in predicting cardiovascular health risks, as evidenced by its positive linear association with an increase in age (β=0.186, p =0.003), weight (β=0.534, p <0.001), waist circumference (β=0.405, p <0.001), and body mass index (BMI; β=0.635, p <0.001). This explained the value of this score in depicting adiposity and insulin resistance. Lab parameters that showed a significant association were fasting blood sugar (β=0.176, p =0.005) and fasting triglycerides (β=0.175, p =0.005). According to the multivariate regression analysis, METS-IR had a significant positive association with fasting blood sugar ( B =0.489, p <0.001) and fasting triglycerides ( B =0.022, p =0.003), implicating its importance in cardiovascular health. High-density lipoprotein cholesterol (HDL-c; B =-0.168, p =0.005) confirmed its protective role with its negative association in higher quartile groups. An increase in serum albumin levels ( B =-0.168, p =0.005) and raised gamma-glutamyl transpeptidase (GGT) ( B =0.059, p =0.022) portrays its due diligence in liver health. METS-IR had a weak association with the estimated glomerular filtration rate (eGFR) with Pearson's correlation coefficient of 0.020 ( p =0.756) and Spearman's rho of 0.021 ( p =0.739). However, raised serum creatinine had a significant association in higher quartile groups, with a p- value of 0.018. Conclusions METS-IR is useful as a screening tool for predicting cardiovascular disease. However, the complex interplay of other confounding factors in identifying renal dysfunction has yet to be explored when considering this score in our study population.
Author Chandrasekaran, Nirmala Devi
Srivatsa, Niveda
Tazeem, Mohammed Suhail
AuthorAffiliation 1 General Medicine, Sri Ramaswamy Memorial (SRM) Medical College Hospital and Research Centre, SRM Institute of Science and Technology (SRMIST), Chengalpattu, IND
2 Geriatrics, Sri Ramaswamy Memorial (SRM) Medical College Hospital and Research Centre, SRM Institute of Science and Technology (SRMIST), Chengalpattu, IND
AuthorAffiliation_xml – name: 2 Geriatrics, Sri Ramaswamy Memorial (SRM) Medical College Hospital and Research Centre, SRM Institute of Science and Technology (SRMIST), Chengalpattu, IND
– name: 1 General Medicine, Sri Ramaswamy Memorial (SRM) Medical College Hospital and Research Centre, SRM Institute of Science and Technology (SRMIST), Chengalpattu, IND
Author_xml – sequence: 1
  givenname: Mohammed Suhail
  surname: Tazeem
  fullname: Tazeem, Mohammed Suhail
  organization: General Medicine, Sri Ramaswamy Memorial (SRM) Medical College Hospital and Research Centre, SRM Institute of Science and Technology (SRMIST), Chengalpattu, IND
– sequence: 2
  givenname: Nirmala Devi
  surname: Chandrasekaran
  fullname: Chandrasekaran, Nirmala Devi
  organization: General Medicine, Sri Ramaswamy Memorial (SRM) Medical College Hospital and Research Centre, SRM Institute of Science and Technology (SRMIST), Chengalpattu, IND
– sequence: 3
  givenname: Niveda
  surname: Srivatsa
  fullname: Srivatsa, Niveda
  organization: Geriatrics, Sri Ramaswamy Memorial (SRM) Medical College Hospital and Research Centre, SRM Institute of Science and Technology (SRMIST), Chengalpattu, IND
BackLink https://www.ncbi.nlm.nih.gov/pubmed/39469359$$D View this record in MEDLINE/PubMed
BookMark eNpVkktvEzEUhUeoiJbSHWvkZZGY4sc82aBolJJIrZCSdD3y2HcS04kd_IiUX8zfqCcppaxs3_vdc4-l8z4500ZDknwk-KYs8_qrCBaCuykxreo3yQUlRZVWpMrOXt3PkyvnfmGMCS4pLvG75JzVWVGzvL5I_kycA-eUXiO_AfTg1aD8AZn--LwHzzszKIGWwlhAvbForl0YlEYLcMp5rgWg6_vpapnOF59RrE_3fAjcj4r_xhfKPaLJ1sTiXEu1VzLwwaEHLcGuzZHlzoNFM-CD36BmA-Ix7NwoyNEKrFfcHlDDo4mZcTvl-TD2liZEepTk39AkevI2dkF4tQfUmI2xHi19kIcPyds-boSr5_MyWd1OV80svfv5Y95M7lJBqrJOOyH6qmI5JVknZZbTrqaQU8mzirJcElpWZVYLXhWCFLLMSSE4ZUVeypoRkrPL5PtJdhe6LUgB2ls-tDurttF_a7hq_-9otWnXZt_GYcIoLaLC9bOCNb8DON9ulRMwDFyDCa5lhJK8ZjgjEf1yQkX8tLPQv-whuB3j0Z7i0R7jEfFPr729wH_DwJ4Av7e8qw
Cites_doi 10.1089/heq.2023.0038
10.1093/NDT/GFAE069.621
10.3389/fendo.2022.851338
10.1016/j.clinbiochem.2023.110686
10.3109/0886022X.2015.1136873
10.1053/gast.2002.35354
10.3389/fendo.2023.1224967
10.2196/49617
10.1080/00325481.2019.1595983
10.1152/ajpendo.1979.237.3.E214
10.2337/dc06-1982
10.1056/NEJM199109263251307
10.1681/ASN.2004100842
10.1373/clinchem.2006.077784
10.5527/wjn.v3.i4.210
10.1016/j.diabres.2012.12.006
10.1172/JCI29024
10.1007/s40292-022-00542-5
10.1530/EJE-17-0883
10.1016/j.clnu.2021.06.017
10.1093/ndt/gfr498
10.2174/1570161114666161007164510
10.2522/ptj.20080018
10.1590/s0066-782x2011005000089
10.1186/s13098-023-01214-7
10.1186/1471-2288-11-158
10.1136/bmjopen-2021-050907
10.1016/j.clnu.2014.04.002
ContentType Journal Article
Copyright Copyright © 2024, Tazeem et al.
Copyright © 2024, Tazeem et al. 2024 Tazeem et al.
Copyright_xml – notice: Copyright © 2024, Tazeem et al.
– notice: Copyright © 2024, Tazeem et al. 2024 Tazeem et al.
DBID NPM
AAYXX
CITATION
7X8
5PM
DOI 10.7759/cureus.70289
DatabaseName PubMed
CrossRef
MEDLINE - Academic
PubMed Central (Full Participant titles)
DatabaseTitle PubMed
CrossRef
MEDLINE - Academic
DatabaseTitleList PubMed
MEDLINE - Academic

Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 2168-8184
ExternalDocumentID 10_7759_cureus_70289
39469359
Genre Journal Article
GroupedDBID 3V.
53G
5VS
7X7
8FI
8FJ
ABUWG
ADBBV
ADRAZ
AFKRA
ALIPV
ALMA_UNASSIGNED_HOLDINGS
AOIJS
BCNDV
BENPR
BPHCQ
BVXVI
CCPQU
FYUFA
GROUPED_DOAJ
HMCUK
HYE
KQ8
M48
NPM
OK1
PGMZT
PIMPY
PQQKQ
PROAC
RPM
UKHRP
AAYXX
CITATION
7X8
5PM
ID FETCH-LOGICAL-c1879-bccf8835214bdd452b92e52da48235d1278749ca86c16d7516ca23657d931153
IEDL.DBID RPM
ISSN 2168-8184
IngestDate Tue Oct 29 05:20:51 EDT 2024
Thu Oct 31 17:44:18 EDT 2024
Wed Oct 02 14:35:49 EDT 2024
Sat Nov 02 12:09:22 EDT 2024
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 9
Keywords master health checkup
metabolic score for insulin resistance (mets-ir)
insulin resistance
metabolic syndrome and endocrinology
south indian
Language English
License Copyright © 2024, Tazeem et al.
This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c1879-bccf8835214bdd452b92e52da48235d1278749ca86c16d7516ca23657d931153
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
OpenAccessLink https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11513226/
PMID 39469359
PQID 3121593041
PQPubID 23479
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_11513226
proquest_miscellaneous_3121593041
crossref_primary_10_7759_cureus_70289
pubmed_primary_39469359
PublicationCentury 2000
PublicationDate 20240926
PublicationDateYYYYMMDD 2024-09-26
PublicationDate_xml – month: 9
  year: 2024
  text: 20240926
  day: 26
PublicationDecade 2020
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: Palo Alto (CA)
PublicationTitle Curēus (Palo Alto, CA)
PublicationTitleAlternate Cureus
PublicationYear 2024
Publisher Cureus
Publisher_xml – name: Cureus
References Li Y (ref21) 2015; 34
Medeiros CC (ref1) 2011; 97
Park JH (ref18) 2013; 99
Manley SE (ref15) 2007; 53
Saadeh S (ref10) 2002; 123
Moller DE (ref4) 1991; 325
Yoon J (ref19) 2023; 15
Prasad GV (ref25) 2014; 3
Chen RY (ref8) 2024; 123
Semenkovich CF (ref27) 2006; 116
Bello-Chavolla OY (ref11) 2018; 178
Veltkamp DM (ref9) 2024; 39
Qian T (ref16) 2023; 14
Cheng H (ref6) 2024; 10
Cai Q (ref20) 2016; 38
Ko J (ref22) 2021; 40
Kilpatrick ES (ref3) 2007; 30
Bailey JL (ref28) 2006; 17
Gluvic Z (ref2) 2017; 15
Borai A (ref14) 2011; 11
Turcotte LP (ref26) 2008; 88
Johns BR (ref17) 2012; 27
González-González JG (ref5) 2022; 29
Charles K (ref7) 2024; 8
Han KY (ref12) 2022; 13
Shi W (ref23) 2019; 131
DeFronzo RA (ref13) 1979; 237
Wang P (ref24) 2021; 11
References_xml – volume: 8
  year: 2024
  ident: ref7
  article-title: The 2021 chronic kidney disease epidemiology collaboration race-free estimated glomerular filtration rate equations in kidney disease: leading the way in ending disparities
  publication-title: Health Equity
  doi: 10.1089/heq.2023.0038
  contributor:
    fullname: Charles K
– volume: 39
  year: 2024
  ident: ref9
  article-title: #2514 Clinical impact of the CKD-EPI 2021 versus the CKD-EPI 2012 formula on GFR estimation and CKD prevalence: results from a Dutch routine-care cohort
  publication-title: Nephrol Dial Transplant
  doi: 10.1093/NDT/GFAE069.621
  contributor:
    fullname: Veltkamp DM
– volume: 13
  year: 2022
  ident: ref12
  article-title: Association between METS-IR and prehypertension or hypertension among normoglycemia subjects in Japan: a retrospective study
  publication-title: Front Endocrinol (Lausanne)
  doi: 10.3389/fendo.2022.851338
  contributor:
    fullname: Han KY
– volume: 123
  year: 2024
  ident: ref8
  article-title: Evaluation of the CKD-EPI 2021 creatinine equation using laboratory data: considerations for practice changes among clinical laboratories in British Columbia, Canada
  publication-title: Clin Biochem
  doi: 10.1016/j.clinbiochem.2023.110686
  contributor:
    fullname: Chen RY
– volume: 38
  year: 2016
  ident: ref20
  article-title: Metabolic syndrome does not always play a critical role in decreased GFR
  publication-title: Ren Fail
  doi: 10.3109/0886022X.2015.1136873
  contributor:
    fullname: Cai Q
– volume: 123
  year: 2002
  ident: ref10
  article-title: The utility of radiological imaging in nonalcoholic fatty liver disease
  publication-title: Gastroenterology
  doi: 10.1053/gast.2002.35354
  contributor:
    fullname: Saadeh S
– volume: 14
  year: 2023
  ident: ref16
  article-title: Mets-IR as a predictor of cardiovascular events in the middle-aged and elderly population and mediator role of blood lipids
  publication-title: Front Endocrinol (Lausanne)
  doi: 10.3389/fendo.2023.1224967
  contributor:
    fullname: Qian T
– volume: 10
  year: 2024
  ident: ref6
  article-title: Metabolic score for insulin resistance and new-onset type 2 diabetes in a middle-aged and older adult population: nationwide prospective cohort study and implications for primary care
  publication-title: JMIR Public Health Surveill
  doi: 10.2196/49617
  contributor:
    fullname: Cheng H
– volume: 131
  year: 2019
  ident: ref23
  article-title: Estimate of reduced glomerular filtration rate by triglyceride-glucose index: insights from a general Chinese population
  publication-title: Postgrad Med
  doi: 10.1080/00325481.2019.1595983
  contributor:
    fullname: Shi W
– volume: 237
  year: 1979
  ident: ref13
  article-title: Glucose clamp technique: a method for quantifying insulin secretion and resistance
  publication-title: Am J Physiol
  doi: 10.1152/ajpendo.1979.237.3.E214
  contributor:
    fullname: DeFronzo RA
– volume: 30
  year: 2007
  ident: ref3
  article-title: Insulin resistance, the metabolic syndrome, and complication risk in type 1 diabetes: "double diabetes" in the Diabetes Control and Complications Trial
  publication-title: Diabetes Care
  doi: 10.2337/dc06-1982
  contributor:
    fullname: Kilpatrick ES
– volume: 325
  year: 1991
  ident: ref4
  article-title: Insulin resistance—mechanisms, syndromes, and implications
  publication-title: N Engl J Med
  doi: 10.1056/NEJM199109263251307
  contributor:
    fullname: Moller DE
– volume: 17
  year: 2006
  ident: ref28
  article-title: Chronic kidney disease causes defects in signaling through the insulin receptor substrate/phosphatidylinositol 3-kinase/Akt pathway: implications for muscle atrophy
  publication-title: J Am Soc Nephrol
  doi: 10.1681/ASN.2004100842
  contributor:
    fullname: Bailey JL
– volume: 53
  year: 2007
  ident: ref15
  article-title: Comparison of 11 human insulin assays: implications for clinical investigation and research
  publication-title: Clin Chem
  doi: 10.1373/clinchem.2006.077784
  contributor:
    fullname: Manley SE
– volume: 3
  year: 2014
  ident: ref25
  article-title: Metabolic syndrome and chronic kidney disease: current status and future directions
  publication-title: World J Nephrol
  doi: 10.5527/wjn.v3.i4.210
  contributor:
    fullname: Prasad GV
– volume: 99
  year: 2013
  ident: ref18
  article-title: Decreased estimated glomerular filtration rate is not directly related to increased insulin resistance
  publication-title: Diabetes Res Clin Pract
  doi: 10.1016/j.diabres.2012.12.006
  contributor:
    fullname: Park JH
– volume: 116
  year: 2006
  ident: ref27
  article-title: Insulin resistance and atherosclerosis
  publication-title: J Clin Invest
  doi: 10.1172/JCI29024
  contributor:
    fullname: Semenkovich CF
– volume: 29
  year: 2022
  ident: ref5
  article-title: HOMA-IR as a predictor of health outcomes in patients with metabolic risk factors: a systematic review and meta-analysis
  publication-title: High Blood Press Cardiovasc Prev
  doi: 10.1007/s40292-022-00542-5
  contributor:
    fullname: González-González JG
– volume: 178
  year: 2018
  ident: ref11
  article-title: METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes
  publication-title: Eur J Endocrinol
  doi: 10.1530/EJE-17-0883
  contributor:
    fullname: Bello-Chavolla OY
– volume: 40
  year: 2021
  ident: ref22
  article-title: Intra-pancreatic fat deposition as a modifier of the relationship between habitual dietary fat intake and insulin resistance
  publication-title: Clin Nutr
  doi: 10.1016/j.clnu.2021.06.017
  contributor:
    fullname: Ko J
– volume: 27
  year: 2012
  ident: ref17
  article-title: Metabolic syndrome, insulin resistance and kidney function in non-diabetic individuals
  publication-title: Nephrol Dial Transplant
  doi: 10.1093/ndt/gfr498
  contributor:
    fullname: Johns BR
– volume: 15
  year: 2017
  ident: ref2
  article-title: Link between metabolic syndrome and insulin resistance
  publication-title: Curr Vasc Pharmacol
  doi: 10.2174/1570161114666161007164510
  contributor:
    fullname: Gluvic Z
– volume: 88
  year: 2008
  ident: ref26
  article-title: Skeletal muscle insulin resistance: roles of fatty acid metabolism and exercise
  publication-title: Phys Ther
  doi: 10.2522/ptj.20080018
  contributor:
    fullname: Turcotte LP
– volume: 97
  year: 2011
  ident: ref1
  article-title: Insulin resistance and its association with metabolic syndrome components
  publication-title: Arq Bras Cardiol
  doi: 10.1590/s0066-782x2011005000089
  contributor:
    fullname: Medeiros CC
– volume: 15
  year: 2023
  ident: ref19
  article-title: Comparison of METS-IR and HOMA-IR for predicting new-onset CKD in middle-aged and older adults
  publication-title: Diabetol Metab Syndr
  doi: 10.1186/s13098-023-01214-7
  contributor:
    fullname: Yoon J
– volume: 11
  year: 2011
  ident: ref14
  article-title: Selection of the appropriate method for the assessment of insulin resistance
  publication-title: BMC Med Res Methodol
  doi: 10.1186/1471-2288-11-158
  contributor:
    fullname: Borai A
– volume: 11
  year: 2021
  ident: ref24
  article-title: Usefulness of metabolic score for insulin resistance index in estimating the risk of mildly reduced estimate glomerular filtration rate: a cross-sectional study of rural population in China
  publication-title: BMJ Open
  doi: 10.1136/bmjopen-2021-050907
  contributor:
    fullname: Wang P
– volume: 34
  year: 2015
  ident: ref21
  article-title: Metabolic syndrome, but not insulin resistance, is associated with an increased risk of renal function decline
  publication-title: Clin Nutr
  doi: 10.1016/j.clnu.2014.04.002
  contributor:
    fullname: Li Y
SSID ssj0001072070
Score 2.3204005
Snippet Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based,...
Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based,...
SourceID pubmedcentral
proquest
crossref
pubmed
SourceType Open Access Repository
Aggregation Database
Index Database
StartPage e70289
SubjectTerms Endocrinology/Diabetes/Metabolism
Epidemiology/Public Health
Internal Medicine
SummonAdditionalLinks – databaseName: Scholars Portal Journals: Open Access
  dbid: M48
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1db9MwFLXGkBAvaOOzG6CLBBI8pDSO48S8oKrqtCGVh66V9hY5jkOrTclIUmn9xfwN7nWSjTIeeGyc3LY5dnwc33sOY-8tD2ymdOTlUuWesEJ6MfJWDx-YOVc6yKXzjJx9l6dL8e0ivNhjvdtodwPrfy7tyE9qWV0Nb35uv-KAR_46jKJQfTabym7qYUSbZg_YQy5wjU5JfB3Rd29bRhEfOec47svYw1lKtFnw9wLszk_3SOffuZN_TEYnB-xJxyJh3MJ-yPZs8ZQ9mnX75M_Yr3YvF6clQIIHy4YyYLdQ5u7jzDYI_dXawDmJWALyVjhrc9JhbmtilNgV4ONsujj3zuafAI9PO1VwjHh3-XxdX8KY7Irw-r6wqwbnpfSjdOdqEmKAttgJJitrLjfXNQXUsKCUbl1tgWqgoDcwoTbn6-dC6i8wxt_UVGVfEgqTcoVoASVAbp-zxcl0MTn1OksHz5CtuZcak8dE-nyRZpkIeaq4DXmmRcyDMPM5Pj-EMjqWxpdZFPrSaB7IMMoUyQIFL9h-URb2FQPjuBbJ--Ewz3isjYhHihstbCqF0gP2occxuW6FOxJc8BDeSYt34vAesHc9yAmOLNou0YUtsTkg4Q0ML_wBe9mCfhspUEJSTfOAxTvd4fYEUu3ebSnWK6fejX-D3gDIo__44mP2mCOJovwULl-z_aba2DdIgpr0revfvwHbQQpI
  priority: 102
  providerName: Scholars Portal
Title Assessing the Utility of the Metabolic Score for Insulin Resistance (METS-IR) in Evaluating Metabolic Risk Among Individuals Undergoing Master Health Checkups in a Tertiary Care Hospital in South India: A Retrospective Cohort Study
URI https://www.ncbi.nlm.nih.gov/pubmed/39469359
https://www.proquest.com/docview/3121593041
https://pubmed.ncbi.nlm.nih.gov/PMC11513226
Volume 16
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3fa9swEBZtB2MvY7-X_Qg32GB7cFLLsmztLQsp7cClpCnkzciy3IS2doidh_zF-zd2J8dds73tUZZ0CO5sfbK--46xz5YHNlc68gqpCk9YIb0YcauHH8yCKx0U0tWMTM7l6ZX4OQ_nB0x2uTCOtG-y5aC8vRuUy4XjVq7uzLDjiQ0vkjGiGDpEyeEhO8QIfXBGd39WjiOOgdyy3KMoVEOzWdtNPYjoVm1___kHVP7NjXyw2Zw8Y093KBFG7WqeswNbvmCPk909-Ev2q72rxW0HEMDBVUMM1y1UhWsmtkHX3i4NXJJIJSAuhbOWcw5TWxNiRFfD12Qyu_TOpt8An092qt9o8c_06bK-gRGVI8L5XeJWDa5W0nXlxmoSWoA2mQnGC2tuNquaDGqYEWVbr7dAOU7QFSihPle3z5nU32GEa2rWVZfyCeNqgUcCIILj9hWbnUxm41NvV7LBM1S23MuMKWICdb7I8lyEPFPchjzXIuZBmPscvw9CGR1L48s8Cn1pNA9kGOWKZH-C1-yorEr7loFxWIrk-_A1znmsjYiPFTda2EwKpXvsS-fHdNUKc6R4oCF_p62_U-fvHvvUOTnFN4euQ3RpK-wOSFgDzQu_x960Tr-3FCghKWe5x-K9cLgfQKrc-z0YrE6duwvOd_8_9T17whE7ES2Fyw_sqFlv7EfEPk3Wx4CfR3326Mfk_GKKrUTEfRf-vwHzSw4Z
link.rule.ids 230,315,730,783,787,888,2228,24330,27936,27937,31732,33757,53804,53806
linkProvider National Library of Medicine
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3fb9MwELbGkICXid90_DokkOAhbeM4TsJbVXVqYZlQl0l7ixzHodW2pGrSh_7F_BvcOc1Y4Y3HxPYp0p3tz_F33zH20XDP5JEKnEJGhSOMkE6IuNXBBbPgkfIKaWtGxmdyeiG-XfqXB0x2uTCWtK-zZb-8vumXy4XlVq5u9KDjiQ1-xGNEMXSIkoN77D5O2KG4c0q3_1aGAcdQbnnuQeBHA71Zm03dD-hebX8H-gdW_s2OvLPdnDxmRzucCKP2e56wA1M-ZQ_i3U34M_arva3FjQcQwsFFQxzXLVSFfYxNg869Xmo4J5lKQGQKs5Z1DnNTE2ZEZ8PneJKcO7P5F8D3k53uN1r8M3y-rK9gRAWJcHyXulWDrZb0s7J9FUktQJvOBOOF0VebVU0GFSRE2lbrLVCWE3QlSqjNVu6zJtVXGOE3NeuqS_qEcbXAQwEQxXH7nCUnk2Q8dXZFGxxNhcudTOsiJFjniizPhc-ziBuf50qE3PNzl-MKISKtQqldmQe-K7XinvSDPCLhH-8FOyyr0rxioC2aIgE_nMg5D5UW4TDiWgmTSRGpHvvU-TFdtdIcKR5pyN9p6-_U-rvHPnROTnHu0IWIKk2FzR5Ja6B54fbYy9bpt5a8SEjKWu6xcC8cbjuQLvd-C4ar1efuwvP4_4e-Zw-nSXyans7Ovr9mjzgiKSKpcPmGHTbrjXmLSKjJ3tmw_w0fxA4U
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3fb9MwELZgSBMvaPwu48chgQQPaVrHcRLeqtJqBTJNXSftLXIch1bbkqpJH_oX829w5yRjhTceE9unSHe2P8fffcfYB8M9k0UqcHIZ5Y4wQjoh4lYHF8ycR8rLpa0ZGZ_Kkwvx7dK_bFmVVUurLHS66hfXN_1itbTcyvWNdjuemHsWjxHF0CFKuussd--zBzhpB_LOSd3-XxkEHMO54boHgR-5ersx26of0N3a_i70D7T8myF5Z8uZHrFHLVaEUfNNj9k9Uzxhh3F7G_6U_WpubHHzAYRxcFETz3UHZW4fY1Ojg69XGs5JqhIQncKsYZ7D3FSEG9Hh8CmeLM6d2fwz4PtJq_2NFv8Mn6-qKxhRUSIc36VvVWArJv0sbV9FcgvQpDTBeGn01XZdkUEFCyJuq80OKNMJujIl1Gar91mT6guM8JvqTdklfsK4XOLBAIjmuHvGFtPJYnzitIUbHE3Fy51U6zwkaDcUaZYJn6cRNz7PlAi552dDjquEiLQKpR7KLPCHUivuST_IIhL_8Z6zg6IszEsG2iIqEvHDyZzxUGkRDiKulTCpFJHqsY-dH5N1I8-R4LGG_J00_k6sv3vsfefkBOcPXYqowpTY7JG8BpoXwx570Tj91pIXCUmZyz0W7oXDbQfS5t5vwZC1Gt1diL76_6Hv2OHZ12nyY3b6_Zg95AimiKfC5Wt2UG-25g2CoTp9a6P-N95CDyc
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Assessing+the+Utility+of+the+Metabolic+Score+for+Insulin+Resistance+%28METS-IR%29+in+Evaluating+Metabolic+Risk+Among+Individuals+Undergoing+Master+Health+Checkups+in+a+Tertiary+Care+Hospital+in+South+India%3A+A+Retrospective+Cohort+Study&rft.jtitle=Cur%C4%93us+%28Palo+Alto%2C+CA%29&rft.au=Tazeem%2C+Mohammed+Suhail&rft.au=Chandrasekaran%2C+Nirmala+Devi&rft.au=Srivatsa%2C+Niveda&rft.date=2024-09-26&rft.issn=2168-8184&rft.eissn=2168-8184&rft.volume=16&rft.issue=9&rft.spage=e70289&rft_id=info:doi/10.7759%2Fcureus.70289&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2168-8184&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2168-8184&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2168-8184&client=summon