A Study on Risk Factors Associated with Gestational Diabetes Mellitus.
Background/Objectives: Gestational Diabetes Mellitus (GDM) is a global health issue with immediate and long-term maternal–fetal complications. Current diagnostic approaches, such as the Oral Glucose Tolerance Test (OGTT), have limitations in accessibility, sensitivity, and timing. This study aimed t...
| Publicado en: | Diabetology Vol. 6; no. 10; pp. 119 - 154 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas review tables/charts Journal Article |
| Publicado: |
MDPI
Oct2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188993721&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188993721 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 26734540 N1A2 jtl: Diabetology issn: 26734540 maglogo: N pubinfo: dt: Oct2025 vid: 6 iid: 10 pid: 97109 pub: MDPI artinfo: ui: 188993721 188993721 188993721 10.3390/diabetology6100119 188993721 ppf: 119 ppct: 35 formats: tig: atl: A Study on Risk Factors Associated with Gestational Diabetes Mellitus. aug: au: Lorenzo, Isabel Salas Pineda-Pineda, Jair J. Parra Inza, Ernesto Sigarreta Ricardo, Saylé Torralbas Fitz, Sergio José affil: Facultad de Matemáticas, Universidad Autónoma de Guerrero (UAGro), Acapulco C.P. 39650, Guerrero, Mexico sug: subj: Diabetes Mellitus, Gestational Risk Factors Diabetes Mellitus, Gestational Prevention and Control Risk Assessment Mathematics Social Network Analysis Strategic Planning Male Female Pregnancy China Pregnancy Outcomes Pregnancy-Induced Hypertension Abortion, Spontaneous Age Factors Family Health World Health Glucose Tolerance Test Systems Analysis Vitamin D Vitamin D Deficiency Sedentary Behavior Smoking Obesity Insulin Resistance Uric Acid Analysis Blood Glucose Analysis Preprocedural Fasting Maternal Health Services Male Female ab: Background/Objectives: Gestational Diabetes Mellitus (GDM) is a global health issue with immediate and long-term maternal–fetal complications. Current diagnostic approaches, such as the Oral Glucose Tolerance Test (OGTT), have limitations in accessibility, sensitivity, and timing. This study aimed to identify key nodes and structural interactions associated with GDM using graph theory and network analysis to improve early predictive strategies. Methods: A literature review inspired by PRISMA guidelines (2004–2025) identified 44 clinically relevant factors. A directed graph was constructed using Python (version 3.10.12), and centrality metrics (closeness, betweenness, eigenvector), k-core decomposition, and a Minimum Dominating Set (MDS) were computed. The MDS, derived using an integer linear programming model, was used to determine the smallest subset of nodes with systemic dominance across the network. Results: The MDS included 20 nodes, with seven showing a high out-degree (≥4), notably Apo A1, vitamin D, vitamin D deficiency, and sedentary lifestyle. Vitamin D exhibited 15 outgoing edges, connecting directly to protective factors like HDL and inversely to risk factors such as smoking and obesity. Sedentary behavior also showed high structural influence. Closeness centrality highlighted triglycerides, insulin resistance, uric acid, fasting plasma glucose, and HDL as nodes with strong predictive potential, based on their high closeness and multiple incoming connections. Conclusions: Vitamin D and sedentary behavior emerged as structurally dominant nodes in the GDM network. Alongside metabolically relevant nodes with high closeness centrality, these findings support the utility of graph-based network analysis for early detection and targeted clinical interventions in maternal health. pubtype: Academic Journal doctype: equations & formulas review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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