{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["15(4)"],"submitter":["Battaglia S"],"pubmed_abstract":["Metabolic Syndrome (MS) is characterized by a low-grade inflammatory state causing an alteration of non-invasive indexes derived from blood count, namely monocyte-to-HDL ratio (MHR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR). We analyse a population of 771 subjects (394 controls and 377 MS patients) to evaluate the best predictive index of MS. The diagnosis of MS was made according to the 2006 criteria of the International Diabetes Federation (IDF). We performed ROC curve analyses to evaluate the best predictor index of MS. MHR cut-off value was used to classify the population in two different groups and to create the outcome variable of the Recursive Partitioning and Amalgamation (RECPAM) analysis. This method is a tree-st"],"journal":["PloS one"],"pagination":["e0231927"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7188261"],"repository":["biostudies-literature"],"pubmed_title":["Gender, BMI and fasting hyperglycaemia influence Monocyte to-HDL ratio (MHR) index in metabolic subjects."],"pmcid":["PMC7188261"],"pubmed_authors":["Battaglia S","Suppressa P","Sabba C","Guglielmini G","Ruggieri R","Diella FA","Scialpi N","Cariello M","Berardi E","Colapietro F","Antonica G","Noia A","Graziano G"],"additional_accession":[]},"is_claimable":false,"name":"Gender, BMI and fasting hyperglycaemia influence Monocyte to-HDL ratio (MHR) index in metabolic subjects.","description":"Metabolic Syndrome (MS) is characterized by a low-grade inflammatory state causing an alteration of non-invasive indexes derived from blood count, namely monocyte-to-HDL ratio (MHR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR). We analyse a population of 771 subjects (394 controls and 377 MS patients) to evaluate the best predictive index of MS. The diagnosis of MS was made according to the 2006 criteria of the International Diabetes Federation (IDF). We performed ROC curve analyses to evaluate the best predictor index of MS. MHR cut-off value was used to classify the population in two different groups and to create the outcome variable of the Recursive Partitioning and Amalgamation (RECPAM) analysis. This method is a tree-st","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020","modification":"2025-04-26T14:16:40.352Z","creation":"2020-05-22T19:22:00Z"},"accession":"S-EPMC7188261","cross_references":{"pubmed":["32343751"],"doi":["10.1371/journal.pone.0231927"]}}