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Record W4281789167 · doi:10.2337/db22-660-p

660-P: The Effect of Real-Time Continuous Glucose Monitors on Fear of Hypoglycemia in People with Type 1 Diabetes: A Systematic Review and Meta-analysis

2022· review· en· W4281789167 on OpenAlexaboutno aff
MERYEM K. TALBO, Alexandra Katz, TRICIA PETERS, Jean‐François Yale, ZEKAI WU, ANNE-SOPHIE BRAZEAU

Bibliographic record

VenueDiabetes · 2022
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyMedicineMeta-analysisHypoglycemiaType 1 diabetesInternal medicineMean differenceType 2 diabetesDiabetes mellitusPediatricsContinuous glucose monitoringInsulinEndocrinologyConfidence interval

Abstract

fetched live from OpenAlex

Background: Real-time continuous glucose monitors (rtCGM) are associated with improved type 1 diabetes (T1D) management and quality of life but little is known on their impact on fear of hypoglycemia (FOH) . This review and meta-analysis assessed the impact of rtCGM on FOH in T1D. Methods: Studies assessing FOH in non-pregnant adults with T1D using rtCGM compared to capillary blood glucose (CBG) or intermittently scanned CGM (isCGM) were included. Results from RCTs were pooled using a random-effects model to calculate the standardized mean difference (SMD) with 95% CI. Results: We identified 14 original studies, with 2590 participants and lasting 8 to 26 weeks for RCTs and 16 to 52 weeks for observational studies. Ten RCTs were included in the meta-analysis. A clear trend was observed that rtCGM was associated with lower FOH (mean difference (MD) = -3.44, 95%CI [-4.02, -2.85]) with the effect size showing a significant moderate association between rtCGM and FOH reduction compared to controls (SMD= -0.52, 95%CI [-1.02, -0.02], I2= 92%) (Figure) . Observational studies (n= 4) showed a significant association between rtCGM use and lower FOH (MD = -4.10, 95%CI [-4.84, -3.36]) . Conclusions: Compared to both isCGM and CBG; rtCGM use shows a moderate trend for lower FOH in medium-term RCTs, which was further supported by results from longer observational studies. Disclosure M.K.Talbo: None. A.Katz: None. T.Peters: None. J.Yale: Advisory Panel; Bayer AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk Canada Inc., Sanofi, Research Support; Bayer AG, Speaker's Bureau; Abbott Diabetes, AstraZeneca, Bayer AG, Dexcom, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Canada Inc., Sanofi. Z.Wu: Other Relationship; Eli Lilly and Company. A.Brazeau: Research Support; Eli Lilly and Company, Novo Nordisk, Sanofi.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.046
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.315
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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