Comparing the glycaemic outcomes between real‐time continuous glucose monitoring ( rt‐CGM ) and intermittently scanned continuous glucose monitoring ( isCGM ) among adults and children with type 1 diabetes: A systematic review and meta‐analysis of randomized controlled trials
Open accessAbstract
Aim: To conduct a systematic review and meta‐analysis of randomized controlled trials (RCTs) comparing the effectiveness of real‐time continuous glucose monitoring (rtCGM) versus intermittently scanned continuous glucose monitoring (isCGM) on key glycaemic metrics (co‐primary outcomes HbA1c and time‐in‐range [TIR] 70–180 mg/dL, 3.9–10.0 mmol/L) among people with type 1 diabetes (T1D). Methods: Medline, PubMed, Scopus, Web of Science and Cochrane Central Register of clinical trials were searched. Inclusion criteria were RCTs; T1D populations of any age and insulin regimen; comparing any type of rtCGM with isCGM (only the first generation had been compared to date); and reporting the glycaemic outcomes. Glycaemic outcomes were extracted post‐intervention and expressed as mean differences and 95% CIs between the two comparators. Results were pooled using a random‐effect meta‐analysis. The risk of bias was assessed using the Cochrane RoB2 tool. The quality of evidence was assessed by the GRADE approach. Results: Five RCTs met the inclusion criteria (4 parallel and 1 crossover design; 4 with CGM use <8 weeks), involving 446 participants (354 adults; 92 children and adolescents). Overall, meta‐analysis showed rtCGM compared to isCGM improved absolute TIR by +7.0% (95% CI: 5.8%–8.3%, I 2 = 0%, p < 0.01) accompanied by a favorable effect on time‐below‐range <70 mg/dL (3.9 mmol/L) – 1.7% (95%CI: −3.0% to −0.4%; p = 0.03). No differences were seen regarding HbA1c. Conclusions: This meta‐analysis highlights that for people with T1D, rtCGM confers benefits over isCGM primarily related to increased TIR, with improvements in hypo‐ and hyperglycaemia.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
RT-CGM outperforms isCGM in reducing HbA1c and minimizing hypoglycemic episodes.
“as RT‐CGM outperforms isCGM in reducing HbA1c and minimizing hypoglycemic episodes [30]”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [30]
The Results summary (section 1) reports less time below the hypoglycaemia threshold with rt-CGM than with isCGM, but no difference in HbA1c. The Primary outcomes section (3.3) confirms that the pooled HbA1c difference was not statistically significant. The hypoglycaemia measure was time below range, not a count of episodes. (LLM, conf=0.90)
Experimental — accuracy not yet measuredSome studies failed to justify sample size calculations, undermining result credibility.
“Some studies failed to justify sample size calculations, further undermining result credibility [30, 31].”
From Effectiveness of Wearable Devices for Diabetes Management: An Overview of Systematic Reviews and Meta‐Analyses (2026) · cites this paper as [30]
The Discussion (page unavailable) says the small sample size of the available evidence may prevent reliable conclusions for some comparisons. It does not say that any included studies failed to justify their sample size calculations; searches for that point found no supporting passage. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The PRISMA 2020 statement: An updated guideline for reporting systematic reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · BMJ · doi:10.1136/bmj.n71 · Cited by 108,283 · see citing works
RoB 2: a revised tool for assessing risk of bias in randomised trials
Sterne, J. A. C., Savović, J., Page, M. J., Elbers, R. G., Blencowe, N. S., Boutron, I., Cates, C. J., Cheng, H.-Y., Corbett, M. S., Eldridge, S. M., et al. (2019) · BMJ · doi:10.1136/bmj.l4898 · Cited by 33,583 · see citing works
Interrater reliability: The kappa statistic
McHugh, M. L. (2012) · Biochemia Medica · doi:10.11613/bm.2012.031 · Cited by 19,877 · see citing works
Battelino, T., Danne, T., Bergenstal, R. M., Amiel, S. A., Beck, R., Biester, T., Bosi, E., Buckingham, B. A., Cefalu, W. T., Close, K. L., et al. (2019) · Diabetes Care · doi:10.2337/dci19-0028 · Cited by 4,032 · cited 1× · see citing works
“21 12 Of note, no significant differences in HbA1c were seen, although certainty of this evidence was low.”
BackgroundBolinder, J., Antuna, R., Geelhoed-Duijvestijn, P., Kröger, J., & Weitgasser, R. (2016) · The Lancet · doi:10.1016/s0140-6736(16)31535-5 · Cited by 893 · see citing works
7. Diabetes Technology: <i>Standards of Care in Diabetes</i> — <i>2023</i>
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Hilliard, M. E., Isaacs, D., Johnson, E. L., et al. (2023) · Diabetes Care · doi:10.2337/dc23-s007 · Cited by 301 · see citing works
Reddy, M., Jugnee, N., El Laboudi, A., Spanudakis, E., Anantharaja, S., & Oliver, N. (2018) · Diabetic Medicine · doi:10.1111/dme.13561 · Cited by 245 · see citing works
Clinical Implications of Real-time and Intermittently Scanned Continuous Glucose Monitoring
Edelman, S. V., Argento, N. B., Pettus, J., & Hirsch, I. B. (2018) · Diabetes Care · doi:10.2337/dc18-1150 · Cited by 203 · see citing works
Intermittently scanned continuous glucose monitoring for type 1 diabetes
Leelarathna, L., Evans, M. L., Neupane, S., Rayman, G., Lumley, S., Cranston, I., Narendran, P., Barnard-Kelly, K., Sutton, C. J., Elliott, R. A., et al. (2022) · New England Journal of Medicine · doi:10.1056/nejmoa2205650 · Cited by 174 · see citing works
Visser, M. M., Charleer, S., Fieuws, S., De Block, C., Hilbrands, R., Van Huffel, L., Maes, T., Vanhaverbeke, G., Dirinck, E., Myngheer, N., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)00789-3 · Cited by 165 · see citing works
Hásková, A., Radovnická, L., Petruželková, L., Parkin, C. G., Grunberger, G., Horová, E., Navrátilová, V., Kádě, O., Matoulek, M., Prázný, M., et al. (2020) · Diabetes Care · doi:10.2337/dc20-0112 · Cited by 146 · see citing works
ISPAD Clinical Practice Consensus Guidelines 2022: Diabetes technologies: Glucose monitoring
Tauschmann, M., Forlenza, G. P., Hood, K. K., Cardona‐Hernandez, R., Giani, E., Hendrieckx, C., DeSalvo, D. J., Laffel, L. M., Saboo, B., Wheeler, B. J., et al. (2022) · Pediatric Diabetes · doi:10.1111/pedi.13451 · Cited by 111 · see citing works
Self-citationElbalshy, M., Haszard, J., Smith, H., Kuroko, S., Galland, B., Oliver, N., Shah, V., de Bock, M. I., & Wheeler, B. J. (2022) · Diabetic Medicine · doi:10.1111/dme.14854 · Cited by 104 · see citing works
Self-citationReddy, M., Jugnee, N., Anantharaja, S., & Oliver, N. S. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0252 · Cited by 92 · see citing works
Castellana, M., Parisi, C., Di Molfetta, S., Di Gioia, L., Natalicchio, A., Perrini, S., Cignarelli, A., Laviola, L., & Giorgino, F. (2020) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2019-001092 · Cited by 84 · see citing works
Visser, M. M., Charleer, S., Fieuws, S., Block, C. E. M. D., Hilbrands, R., Huffel, L. V., Maes, T., Vanhaverbeke, G., Dirinck, E. L., Myngheer, N., et al. (2023) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(22)00352-7 · Cited by 53 · see citing works
Dovč, K., Lanzinger, S., Cardona‐Hernandez, R., Tauschmann, M., Marigliano, M., Cherubini, V., Preikša, R. T., Schierloh, U. H. E., Clapin, H. F., Aljaser, F., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.0077 · Cited by 49 · see citing works
Burnside, M. J., Williman, J. A., Davies, H. M., Jefferies, C., Paul, R. G., Wheeler, B. J., Wiltshire, E. J., Anderson, Y. C., & de Bock, M. I. (2022) · The Lancet Regional Health - Western Pacific · doi:10.1016/j.lanwpc.2022.100644 · Cited by 48 · see citing works
Self-citationAvari, P., Moscardó, V., Jugnee, N., Oliver, N. S., & Reddy, M. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819867688 · Cited by 29 · see citing works
Nguyen, A., & White, J. R. (2022) · Clinical Diabetes · doi:10.2337/cd22-0102 · Cited by 20 · see citing works
Préau, Y., Armand, M., Galie, S., Schaepelynck, P., & Raccah, D. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0515 · Cited by 16 · see citing works
Elbalshy, M. M., Styles, S. E., Haszard, J. J., Galland, B. C., Crocket, H. R., Jefferies, C., Wiltshire, E. J., Tomlinson, P. A., de Bock, M. I., & Wheeler, B. J. (2022) · Pediatric Diabetes · doi:10.1111/pedi.13331 · Cited by 15 · see citing works
Self-citationRadovnická, L., Hásková, A., Do, Q. D., Horová, E., Navrátilová, V., Mikeš, O., Cihlář, D., Parkin, C. G., Grunberger, G., Prázný, M., et al. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0152 · Cited by 14 · see citing works
Urakami, T., Terada, H., Yoshida, K., Kuwabara, R., Mine, Y., Aoki, M., Shoji, Y., Suzuki, J., & Morioka, I. (2022) · Journal of Diabetes Investigation · doi:10.1111/jdi.13830 · Cited by 13 · see citing works
Price, D. A., Graham, C., Parkin, C. G., & Peyser, T. A. (2015) · Journal of Diabetes Science and Technology · doi:10.1177/1932296815607863 · Cited by 9 · see citing works
Zhou, Y., Mai, X., Deng, H., Yang, D., Zheng, M., Huang, B., Xu, L., Weng, J., Xu, W., & Yan, J. (2022) · Journal of Diabetes · doi:10.1111/1753-0407.13296 · Cited by 9 · see citing works
Self-citationMessaaoui, A., Tenoutasse, S., Hajselova, L., & Crenier, L. (2022) · Diabetes Therapy · doi:10.1007/s13300-022-01297-x · Cited by 9 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- American Diabetes Association professional practice Committee.7. Diabetes technology: standards of medical Care in Diabetes-2022. Diabetes Care. 2021;45:S97-S112.
- Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. www. covid ence. org
Cited by
Sorted by citations
Conti, M., Massari, G., Meneghini, E., Pasquino, B., Agosti, B., Chinotti, F., Pintaudi, B., Girelli, A., & Bertuzzi, F. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13030642 · Cited by 21 · see citing works
Talaiti, M., Liao, X., Abulimiti, N., Zeng, M., & Wang, Y. (2026) · Journal of Diabetes Research · doi:10.1155/jdr/1464982
- Authors
- Zhou, Y., Sardana, D., Kuroko, S., Haszard, J. J., de Block, M. I., Weng, J., Jefferies, C., & Wheeler, B. J.
- Affiliations
- University of Science and Technology of China (CN)
- OU Health (US)
- University of Otago (NZ)
- Department of Paediatrics University of Otago Christchurch New Zealand
- University of Auckland (NZ)
- Health New Zealand (NZ)
- Corresponding author
- Wheeler, Benjamin John
- ORCID
- Venue
- Diabetic Medicine
- Publisher
- Wiley
- Published
- 2024-01-10
- Volume
- 41
- Issue
- 3
- Pages
- e15280-e15280
- ISSN
- 0742-3071 (ISSN-L)
- 1464-5491
- OpenAlex
- W4390696862
- Cited by
- 25
- References
- 27
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 7
- FWCI
- 1.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Diabetic Medicine (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- IUScholarWorks (Indiana University) (submittedVersion, cc-by-nc-nd)
- Funders
- University of Otago
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- type 1 diabetes, real-time continuous glucose monitoring, intermittently scanned continuous glucose monitoring, glycemic control, HbA1c, time in range, time below range, hypoglycemia, hyperglycemia, children and adolescents, adults
- MeSH terms
- Continuous Glucose Monitoring, Adolescent, Adult, Blood Glucose, Child, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans, Hypoglycemic Agents, Blood Glucose Self-Monitoring, Randomized Controlled Trials as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review