98a261732769d982f02fc76f90ea67a2 304056.pdf bce9d1927cd79fb5df724820243ece780b33c1a1 304056.pdf 5e6c8b2893a6c521e03a2e2c2625919414736de4fa53d1f47698e16217f85414 304056.pdf Title: Exploring the Effectiveness of Self-Management Interventions in Type 2 Diabetes: A Systematic Review and Network Meta-Analysis Subject: Background: Chronic diseases are a leading cause of global morbidity and mortality. In response to this challenge, self-management interventions (SMIs) have emerged as an essential tool in improving patient outcomes. However, the diverse and complex nature of SMIs pose significant challenges in measuring their effectiveness. This work aims to investigate the comparative effectiveness of SMIs on Type 2 diabetes mellitus (T2DM) outcomes. Methods: A rigorous analytical framework was employed to assess the relative effectiveness of different SMIs, encompassing both pairwise and network meta-analysis (NMA), as well as component network meta-analysis (CNMA). Various outcomes were considered, including glycated hemoglobin (HbA1c) control, body mass index (BMI) reduction and low-density lipoprotein (LDL) cholesterol. Visualization tools were also utilized to enhance the interpretation of results. Results: SMIs were found promising in improving clinical outcomes and patient-reported measures. However, considerable heterogeneity and inconsistency across studies challenged the validity of NMA results. CNMA along with various visualization tools offered insights into the contributions of individual SMI components, highlighting the complexity of these interventions. Discussion/Conclusions: SMIs represent a valuable approach to managing chronic conditions, but their effectiveness is context-dependent. Further research is needed to elucidate the contextual factors influencing SMI outcomes. This work contributes to a comprehensive understanding of SMIs’ role in T2DM management, aiming to aid decision-makers, clinicians, and patients in selecting tailored interventions. Keywords: network meta-analysis; self-management interventions; component network meta-analysis; type 2 diabetes Author: Sofia Tsokani, Georgios Seitidis, Christos Christogiannis, Katerina-Maria Kontouli, Stavros Nikolakopoulos, Stella Zevgiti, Carola Orrego, Marta Ballester, Rosa Suñol, Monique Heijmans, Rune Poortvliet, Marieke van der Gaag, Pablo Alonso-Coello, Carlos Canelo-Aybar, Jessica Beltran, Ana I. González-González, Gimon de Graaf, Areti-Angeliki Veroniki and Dimitrios Mavridis Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Fri Dec 22 05:40:43 2023 CET ModDate: Fri Dec 22 07:10:35 2023 CET Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 21 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 9723717 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- AIQCCL+VnURWPalladioL-Bold Type 1 Custom yes yes yes 10 0 XMMWRH+URWPalladioL-Bold Type 1 Custom yes yes yes 16 0 ZISVOF+URWPalladioL-Roma Type 1 Custom yes yes yes 22 0 HIXKZZ+URWPalladioL-Ital Type 1 Custom yes yes yes 27 0 XAOEUN+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 43 0 VHXXZC+EURM10 Type 1 Builtin yes yes yes 66 0 EDDCZE+URWPalladioL-BoldItal Type 1 Custom yes yes yes 77 0 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LastModified: 2025-01-08 13:10:02 CET Size: 9723717 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 1218 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Methods Destination: section.2 Children: Item: Title: Design Destination: subsection.2.1 Item: Title: Search Strategy Destination: subsection.2.2 Item: Title: Study Selection and Data Extraction Destination: subsection.2.3 Item: Title: Risk of Bias Assessment Destination: subsection.2.4 Item: Title: Statistical Analysis Destination: subsection.2.5 Children: Item: Title: Single-Effect Analysis (SEA) Destination: subsubsection.2.5.1 Item: Title: Network Meta-Analysis (NMA) Destination: subsubsection.2.5.2 Item: Title: Component Network Meta-Analysis Destination: subsubsection.2.5.3 Item: Title: Visual Inspection of NMA Results Using a Series of Visualization Tools Destination: subsubsection.2.5.4 Item: Title: Certainty of Evidence Assessment Destination: subsection.2.6 Item: Title: Results Destination: section.3 Children: Item: Title: Interventions Destination: subsection.3.1 Item: Title: Risk of Bias of Included Studies Destination: subsection.3.2 Item: Title: Single Effect (Pairwise Meta-Analysis) Results Destination: subsection.3.3 Item: Title: Network Meta-Analysis Results Destination: subsection.3.4 Item: Title: CNMA Results Destination: subsection.3.5 Item: Title: Visual Inspection of NMA Effects Destination: subsection.3.6 Item: Title: Confidence in NMA Results Destination: subsection.3.7 Item: Title: Discussion Destination: section.4 Item: Title: Conclusions Destination: section.5 Item: Title: References Destination: appendix.A. Info: Title: Exploring the Effectiveness of Self-Management Interventions in Type 2 Diabetes: A Systematic Review and Network Meta-Analysis Author: Sofia Tsokani, Georgios Seitidis, Christos Christogiannis, Katerina-Maria Kontouli, Stavros Nikolakopoulos, Stella Zevgiti, Carola Orrego, Marta Ballester, Rosa Suñol, Monique Heijmans, Rune Poortvliet, Marieke van der Gaag, Pablo Alonso-Coello, Carlos Canelo-Aybar, Jessica Beltran, Ana I. González-González, Gimon de Graaf, Areti-Angeliki Veroniki and Dimitrios Mavridis Subject: Background: Chronic diseases are a leading cause of global morbidity and mortality. In response to this challenge, self-management interventions (SMIs) have emerged as an essential tool in improving patient outcomes. However, the diverse and complex nature of SMIs pose significant challenges in measuring their effectiveness. This work aims to investigate the comparative effectiveness of SMIs on Type 2 diabetes mellitus (T2DM) outcomes. Methods: A rigorous analytical framework was employed to assess the relative effectiveness of different SMIs, encompassing both pairwise and network meta-analysis (NMA), as well as component network meta-analysis (CNMA). Various outcomes were considered, including glycated hemoglobin (HbA1c) control, body mass index (BMI) reduction and low-density lipoprotein (LDL) cholesterol. Visualization tools were also utilized to enhance the interpretation of results. Results: SMIs were found promising in improving clinical outcomes and patient-reported measures. However, considerable heterogeneity and inconsistency across studies challenged the validity of NMA results. CNMA along with various visualization tools offered insights into the contributions of individual SMI components, highlighting the complexity of these interventions. Discussion/Conclusions: SMIs represent a valuable approach to managing chronic conditions, but their effectiveness is context-dependent. Further research is needed to elucidate the contextual factors influencing SMI outcomes. This work contributes to a comprehensive understanding of SMIs’ role in T2DM management, aiming to aid decision-makers, clinicians, and patients in selecting tailored interventions. Keywords: network meta-analysis; self-management interventions; component network meta-analysis; type 2 diabetes Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Fri Dec 22 05:40:43 CET 2023 ModDate: Fri Dec 22 07:10:35 CET 2023 ID: 0x3d69369b1ed585f1d45a42a97bab29dd, 0x3d69369b1ed585f1d45a42a97bab29dd Filters: FilterPipeline: FlateDecode Fonts: Type1: Font: BaseFont: XMMWRH+URWPalladioL-Bold FontSubset: true FirstChar: 2 LastChar: 241 FontDescriptor: FontName: XMMWRH+URWPalladioL-Bold Flags: Symbolic FontBBox: -152, -301, 1000, 935 FontFile: true EncodingDictionary: Differences: true ToUnicode: true Font: BaseFont: VHXXZC+EURM10 FontSubset: true FirstChar: 28 LastChar: 28 FontDescriptor: FontName: VHXXZC+EURM10 Flags: Symbolic FontBBox: -32, -243, 1060, 720 FontFile: true ToUnicode: true Font: BaseFont: HYYHEA+CMBSY10 FontSubset: true FirstChar: 0 LastChar: 0 FontDescriptor: FontName: HYYHEA+CMBSY10 Flags: Symbolic FontBBox: -26, -940, 1332, 825 FontFile: true 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