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Remote Glucose Monitoring Engagement and Glycemic Control in Type 2 Diabetes and Prediabetes: Retrospective Cohort Study.

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Τίτλος: Remote Glucose Monitoring Engagement and Glycemic Control in Type 2 Diabetes and Prediabetes: Retrospective Cohort Study.
Συγγραφείς: Huang Y; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526., Nagesh N; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526., Subramanian A; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526., Wang L; Unika Health, Sunnyvale, CA, United States., Liu Z; Unika Health, Sunnyvale, CA, United States., Sun Y; Unika Health, Sunnyvale, CA, United States., Hou W; Unika Health, Sunnyvale, CA, United States., Azimi I; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526., Rahmani AM; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.; Nhu Department of Electrical Engineering and Computer Science, The Henry Samueli School of Engineering, University of California, Irvine, Irvine, CA, United States.; Sue & Bill Gross School of Nursing, University of California, Irvine, Irvine, CA, United States., Stafford RS; Stanford University, Palo Alto, CA, United States.
Πηγή: JMIR formative research [JMIR Form Res] 2026 Sep 30; Vol. 10, pp. e95679. Date of Electronic Publication: 2026 Sep 30.
Τύπος έκδοσης: Journal Article; Research Support, Non-U.S. Gov't
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: JMIR Publications Country of Publication: Canada NLM ID: 101726394 Publication Model: Electronic Cited Medium: Internet ISSN: 2561-326X (Electronic) Linking ISSN: 2561326X NLM ISO Abbreviation: JMIR Form Res Subsets: MEDLINE
Imprint Name(s): Original Publication: Toronto, ON, Canada : JMIR Publications, [2017]-
Ιατρικοί όροι (MeSH): Diabetes Mellitus, Type 2*/blood , Diabetes Mellitus, Type 2*/therapy , Glycemic Control*/methods , Glycemic Control*/statistics & numerical data , Glycemic Control*/standards , Prediabetic State*/blood , Prediabetic State*/therapy , Blood Glucose Self-Monitoring*/methods , Blood Glucose Self-Monitoring*/statistics & numerical data , Patient Participation*/statistics & numerical data, Glycated Hemoglobin/analysis ; Blood Glucose/analysis ; Humans ; Retrospective Studies ; Female ; Male ; Middle Aged ; Aged ; Remote Patient Monitoring ; Cohort Studies ; Adult
Περίληψη: Background: Suboptimal glycemic control remains a significant public health challenge among adults with type 2 diabetes and prediabetes, with 47.4% of US adults with diagnosed diabetes having hemoglobin A1c (HbA1c) ≥7%. Remote glucose monitoring programs have shown promise for supporting self-management, but real-world evidence on the causal impact of varying patient engagement levels on glycemic outcomes remains limited.
Objective: This study aimed to estimate the causal dose-response relationship between patient engagement, operationalized as weekly glucose monitoring frequency, and glycemic control measured by HbA1c among adults enrolled in a comprehensive primary care-integrated remote monitoring program.
Methods: We conducted a retrospective cohort study of 1436 adults with type 2 diabetes or prediabetes enrolled in the Unika Health program between 2019 and 2024. The program integrated Bluetooth-connected glucose meters, a mobile app, structured lifestyle coaching, and primary care coordination across 74 physician practices. Engagement was defined as mean weekly glucose monitoring frequency during the first 6 months. The causal effect of monitoring frequency on 6-month HbA1c was estimated using marginal structural models (MSMs) with inverse probability weighting to address time-varying confounding. Covariates included age, sex, BMI, baseline HbA1c, comorbidities, medication status, and physical activity level.
Results: The cohort was predominantly older (95.4%, 1370/1436 aged ≥46 years), with 82.6% (1186/1436) having hypertension and 45.9% (659/1436) classified as obese. Overall, HbA1c decreased by a mean of 0.54 (SD 1.47; 95% CI 0.47-0.62) percentage points (P<.001) over 6 months. Cluster analysis identified 3 engagement tiers: low (n=835; mean 2.55, SD 1.35 measurements/week), medium (n=493; mean 6.19, SD 1.46 measurements/week), and high (n=108; mean 12.59, SD 3.03 measurements/week). A monotonic dose-response was observed, with mean HbA1c reductions of 0.38 (SD 1.40; 95% CI 0.29-0.48), 0.71 (SD 1.50; 95% CI 0.58-0.85), and 1.01 (SD 1.67; 95% CI 0.69-1.32) percentage points for the low, medium, and high tiers, respectively (all P<.001 by 2-tailed paired t test). In weighted MSMs, each additional weekly measurement was associated with a 0.05 (95% CI 0.03-0.07) percentage point greater HbA1c reduction (P<.001). Among patients with high baseline HbA1c (≥9%), the high-engagement group achieved a mean reduction of 3.12 (SD 1.97; 95% CI 2.29-3.94) percentage points. Findings were consistent in sensitivity analyses at 3 months (β=-0.04; P<.001) and 12 months (β=-0.03; P=.003) and across alternative weighting specifications.
Conclusions: Higher engagement with a digitally enabled, primary care-integrated remote glucose monitoring program was causally associated with significantly greater HbA1c reductions in adults with type 2 diabetes and prediabetes. These findings support scalable remote patient monitoring strategies that actively foster sustained patient engagement as an effective approach to improving glycemic control and reducing the burden of diabetes-related complications at a population level.
(© Yong Huang, Nitish Nagesh, Ajan Subramanian, Li Wang, Zhiyu Liu, Yichen Sun, Weiyi Hou, Iman Azimi, Amir M Rahmani, Randall S Stafford. Originally published in JMIR Formative Research (https://formative.jmir.org).)
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Contributed Indexing: Keywords: causal inference; digital health; glucose monitoring; glycemic control; marginal structural models; patient-centered care; prediabetic state; remote patient monitoring; type 2 diabetes mellitus
Substance Nomenclature: 0 (Glycated Hemoglobin)
0 (Blood Glucose)
Entry Date(s): Date Created: 20260930 Date Completed: 20260930 Latest Revision: 20261007
Update Code: 20261007
PubMed Central ID: PMC13626191
DOI: 10.2196/95679
PMID: 42814765
Βάση Δεδομένων: MEDLINE
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  Data: Remote Glucose Monitoring Engagement and Glycemic Control in Type 2 Diabetes and Prediabetes: Retrospective Cohort Study.
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  Data: &lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Huang+Y%22&quot;&gt;Huang Y&lt;/searchLink&gt;; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Nagesh+N%22&quot;&gt;Nagesh N&lt;/searchLink&gt;; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Subramanian+A%22&quot;&gt;Subramanian A&lt;/searchLink&gt;; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Wang+L%22&quot;&gt;Wang L&lt;/searchLink&gt;; Unika Health, Sunnyvale, CA, United States.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Liu+Z%22&quot;&gt;Liu Z&lt;/searchLink&gt;; Unika Health, Sunnyvale, CA, United States.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Sun+Y%22&quot;&gt;Sun Y&lt;/searchLink&gt;; Unika Health, Sunnyvale, CA, United States.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Hou+W%22&quot;&gt;Hou W&lt;/searchLink&gt;; Unika Health, Sunnyvale, CA, United States.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Azimi+I%22&quot;&gt;Azimi I&lt;/searchLink&gt;; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Rahmani+AM%22&quot;&gt;Rahmani AM&lt;/searchLink&gt;; Department of Computer Science, Donald Bren School of Information and Computer Sciences, University of California, Irvine, 3211 Donald Bren Hall, Irvine, CA, 92617, United States, 1 8588881526.; Nhu Department of Electrical Engineering and Computer Science, The Henry Samueli School of Engineering, University of California, Irvine, Irvine, CA, United States.; Sue &amp; Bill Gross School of Nursing, University of California, Irvine, Irvine, CA, United States.&lt;br /&gt;&lt;searchLink fieldCode=&quot;AU&quot; term=&quot;%22Stafford+RS%22&quot;&gt;Stafford RS&lt;/searchLink&gt;; Stanford University, Palo Alto, CA, United States.
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  Data: Background: Suboptimal glycemic control remains a significant public health challenge among adults with type 2 diabetes and prediabetes, with 47.4% of US adults with diagnosed diabetes having hemoglobin A&lt;subscript&gt;1c&lt;/subscript&gt; (HbA&lt;subscript&gt;1c&lt;/subscript&gt;) ≥7%. Remote glucose monitoring programs have shown promise for supporting self-management, but real-world evidence on the causal impact of varying patient engagement levels on glycemic outcomes remains limited.&lt;br /&gt;Objective: This study aimed to estimate the causal dose-response relationship between patient engagement, operationalized as weekly glucose monitoring frequency, and glycemic control measured by HbA&lt;subscript&gt;1c&lt;/subscript&gt; among adults enrolled in a comprehensive primary care-integrated remote monitoring program.&lt;br /&gt;Methods: We conducted a retrospective cohort study of 1436 adults with type 2 diabetes or prediabetes enrolled in the Unika Health program between 2019 and 2024. The program integrated Bluetooth-connected glucose meters, a mobile app, structured lifestyle coaching, and primary care coordination across 74 physician practices. Engagement was defined as mean weekly glucose monitoring frequency during the first 6 months. The causal effect of monitoring frequency on 6-month HbA&lt;subscript&gt;1c&lt;/subscript&gt; was estimated using marginal structural models (MSMs) with inverse probability weighting to address time-varying confounding. Covariates included age, sex, BMI, baseline HbA&lt;subscript&gt;1c&lt;/subscript&gt;, comorbidities, medication status, and physical activity level.&lt;br /&gt;Results: The cohort was predominantly older (95.4%, 1370/1436 aged ≥46 years), with 82.6% (1186/1436) having hypertension and 45.9% (659/1436) classified as obese. Overall, HbA&lt;subscript&gt;1c&lt;/subscript&gt; decreased by a mean of 0.54 (SD 1.47; 95% CI 0.47-0.62) percentage points (P&amp;lt;.001) over 6 months. Cluster analysis identified 3 engagement tiers: low (n=835; mean 2.55, SD 1.35 measurements/week), medium (n=493; mean 6.19, SD 1.46 measurements/week), and high (n=108; mean 12.59, SD 3.03 measurements/week). A monotonic dose-response was observed, with mean HbA&lt;subscript&gt;1c&lt;/subscript&gt; reductions of 0.38 (SD 1.40; 95% CI 0.29-0.48), 0.71 (SD 1.50; 95% CI 0.58-0.85), and 1.01 (SD 1.67; 95% CI 0.69-1.32) percentage points for the low, medium, and high tiers, respectively (all P&amp;lt;.001 by 2-tailed paired t test). In weighted MSMs, each additional weekly measurement was associated with a 0.05 (95% CI 0.03-0.07) percentage point greater HbA&lt;subscript&gt;1c&lt;/subscript&gt; reduction (P&amp;lt;.001). Among patients with high baseline HbA&lt;subscript&gt;1c&lt;/subscript&gt; (≥9%), the high-engagement group achieved a mean reduction of 3.12 (SD 1.97; 95% CI 2.29-3.94) percentage points. Findings were consistent in sensitivity analyses at 3 months (β=-0.04; P&amp;lt;.001) and 12 months (β=-0.03; P=.003) and across alternative weighting specifications.&lt;br /&gt;Conclusions: Higher engagement with a digitally enabled, primary care-integrated remote glucose monitoring program was causally associated with significantly greater HbA&lt;subscript&gt;1c&lt;/subscript&gt; reductions in adults with type 2 diabetes and prediabetes. These findings support scalable remote patient monitoring strategies that actively foster sustained patient engagement as an effective approach to improving glycemic control and reducing the burden of diabetes-related complications at a population level.&lt;br /&gt; (&#169; Yong Huang, Nitish Nagesh, Ajan Subramanian, Li Wang, Zhiyu Liu, Yichen Sun, Weiyi Hou, Iman Azimi, Amir M Rahmani, Randall S Stafford. Originally published in JMIR Formative Research (https://formative.jmir.org).)
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  Label: References
  Group: RefInfo
  Data: J Diabetes Metab Disord. 2020 Jan 10;19(1):115-127. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2232550161%22&quot;&gt;32550161)&lt;/searchLink&gt;&lt;br /&gt;Diabetes Care. 2020 Jul;43(7):1636-1649. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2232513817%22&quot;&gt;32513817)&lt;/searchLink&gt;&lt;br /&gt;Sci Rep. 2021 Jan 13;11(1):1176. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2233441946%22&quot;&gt;33441946)&lt;/searchLink&gt;&lt;br /&gt;Diabetes Care. 2006 Aug;29(8):1757-63. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2216873776%22&quot;&gt;16873776)&lt;/searchLink&gt;&lt;br /&gt;JAMA Intern Med. 2017 Jul 1;177(7):920-929. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2228600913%22&quot;&gt;28600913)&lt;/searchLink&gt;&lt;br /&gt;Front Endocrinol (Lausanne). 2025 Nov 20;16:1695381. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2241356012%22&quot;&gt;41356012)&lt;/searchLink&gt;&lt;br /&gt;Diabetes Res Clin Pract. 2022 Jan;183:109119. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2234879977%22&quot;&gt;34879977)&lt;/searchLink&gt;&lt;br /&gt;Diabetes Care. 2026 Jan 1;49(Supplement&amp;#95;1):S1-S5. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2241358883%22&quot;&gt;41358883)&lt;/searchLink&gt;&lt;br /&gt;Epidemiology. 2000 Sep;11(5):550-60. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2210955408%22&quot;&gt;10955408)&lt;/searchLink&gt;&lt;br /&gt;BMC Health Serv Res. 2018 Jun 26;18(1):495. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2229940936%22&quot;&gt;29940936)&lt;/searchLink&gt;&lt;br /&gt;J Diabetes Sci Technol. 2023 May;17(3):794-825. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2234957864%22&quot;&gt;34957864)&lt;/searchLink&gt;&lt;br /&gt;J Formos Med Assoc. 2024 Feb;123(2):283-292. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2237798146%22&quot;&gt;37798146)&lt;/searchLink&gt;&lt;br /&gt;Lancet Diabetes Endocrinol. 2017 Jun;5(6):423-430. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2228456416%22&quot;&gt;28456416)&lt;/searchLink&gt;&lt;br /&gt;Ann Behav Med. 2003 Aug;26(1):1-7. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2212867348%22&quot;&gt;12867348)&lt;/searchLink&gt;&lt;br /&gt;Patient Prefer Adherence. 2023 Sep 07;17:2227-2235. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2237701426%22&quot;&gt;37701426)&lt;/searchLink&gt;&lt;br /&gt;J Diabetes Sci Technol. 2014 Feb 21;8(2):378-389. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2224876591%22&quot;&gt;24876591)&lt;/searchLink&gt;&lt;br /&gt;Diabetes Metab J. 2018 Dec;42(6):480-487. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2230113142%22&quot;&gt;30113142)&lt;/searchLink&gt;&lt;br /&gt;Exp Clin Endocrinol Diabetes. 2006 Jul;114(7):384-8. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2216915542%22&quot;&gt;16915542)&lt;/searchLink&gt;&lt;br /&gt;Value Health. 2010 Dec;13(8):1038-45. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2220946182%22&quot;&gt;20946182)&lt;/searchLink&gt;&lt;br /&gt;Diabetes Res Clin Pract. 2024 Mar;209:111027. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2238000665%22&quot;&gt;38000665)&lt;/searchLink&gt;&lt;br /&gt;PLoS One. 2013 Nov 08;8(11):e79246. (PMID: &lt;searchLink fieldCode=&quot;PM&quot; term=&quot;%2224250826%22&quot;&gt;24250826)&lt;/searchLink&gt;
– Name: SubjectMinor
  Label: Contributed Indexing
  Group:
  Data: &lt;i&gt;Keywords: &lt;/i&gt;causal inference; digital health; glucose monitoring; glycemic control; marginal structural models; patient-centered care; prediabetic state; remote patient monitoring; type 2 diabetes mellitus
– Name: NumberCAS
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  Group: ID
  Data: 0 (Glycated Hemoglobin)&lt;br /&gt;0 (Blood Glucose)
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  Label: Entry Date(s)
  Group: Date
  Data: &lt;i&gt;Date Created: &lt;/i&gt;20260930 &lt;i&gt;Date Completed: &lt;/i&gt;20260930 &lt;i&gt;Latest Revision: &lt;/i&gt;20261007
– Name: DateUpdate
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  Group: Date
  Data: 20261007
– Name: PubmedCentralID
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  Data: PMC13626191
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  Label: DOI
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  Data: 10.2196/95679
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  Label: PMID
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  Data: 42814765
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=cmedm&AN=42814765
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.2196/95679
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: e95679
    Subjects:
      – SubjectFull: Glycated Hemoglobin analysis
        Type: general
      – SubjectFull: Blood Glucose analysis
        Type: general
      – SubjectFull: Humans
        Type: general
      – SubjectFull: Retrospective Studies
        Type: general
      – SubjectFull: Female
        Type: general
      – SubjectFull: Male
        Type: general
      – SubjectFull: Middle Aged
        Type: general
      – SubjectFull: Aged
        Type: general
      – SubjectFull: Remote Patient Monitoring
        Type: general
      – SubjectFull: Cohort Studies
        Type: general
      – SubjectFull: Adult
        Type: general
      – SubjectFull: Diabetes Mellitus, Type 2 blood
        Type: general
      – SubjectFull: Diabetes Mellitus, Type 2 therapy
        Type: general
      – SubjectFull: Glycemic Control methods
        Type: general
      – SubjectFull: Glycemic Control statistics & numerical data
        Type: general
      – SubjectFull: Glycemic Control standards
        Type: general
      – SubjectFull: Prediabetic State blood
        Type: general
      – SubjectFull: Prediabetic State therapy
        Type: general
      – SubjectFull: Blood Glucose Self-Monitoring methods
        Type: general
      – SubjectFull: Blood Glucose Self-Monitoring statistics & numerical data
        Type: general
      – SubjectFull: Patient Participation statistics & numerical data
        Type: general
    Titles:
      – TitleFull: Remote Glucose Monitoring Engagement and Glycemic Control in Type 2 Diabetes and Prediabetes: Retrospective Cohort Study.
        Type: main
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          Dates:
            – D: 30
              M: 09
              Text: 2026 Sep 30
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 2561-326X
          Numbering:
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              Value: 10
          Titles:
            – TitleFull: JMIR formative research
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