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Record W4381571187 · doi:10.1155/2023/5106107

Control-IQ Technology Positively Impacts Patient Reported Outcome Measures and Glycemic Control in Youth with Type 1 Diabetes in a Real-World Setting

2023· article· en· W4381571187 on OpenAlexaff
Caroline Zuijdwijk, Jennilea Courtney, Nicholas Mitsakakis, Lamia Hayawi, Stephanie Sutherland, Dennis Newhook, Alexandra Ahmet, Ellen B. Goldbloom, Karine Khatchadourian, Sarah Lawrence

Bibliographic record

VenuePediatric Diabetes · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsChildren's Hospital of Eastern OntarioAgricultural Research Institute of OntarioUniversity of Ottawa
FundersTandem Diabetes CareAmerican Diabetes Association
KeywordsGlycemicMedicineType 1 diabetesPromDiabetes mellitusInsulin pumpPediatricsEndocrinology

Abstract

fetched live from OpenAlex

Objective. To determine the impact of the t:slim X2 insulin pump with Control-IQ technology on the quality of life and glycemic control in youth with type 1 diabetes (T1D) and their parents in a real-world setting. Research Design and Methods. We conducted a single-center, prospective study on pediatric patients (6–18 years old) with T1D using a Tandem t:slim X2 pump and initiating Control-IQ technology as part of routine care. Youth (≥8 years) and parents completed validated patient-reported outcome measures (PROMs) at baseline and the end of the study (16 weeks). Glycemic control measures were recorded at baseline and every 4 weeks until the end of the study. Results. Fifty-nine youth participated; the median (IQR) age was 13.8 (11.1, 15.7) years, and T1D duration was 6.3 (3.1, 8.4) years. INSPIRE scores (evaluating expectations (baseline) and impact (post) of Control-IQ technology) were favorable, unchanged at the end of the study for youth, and lower for parents ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>p</a:mi> <a:mo>=</a:mo> <a:mn>0.04</a:mn> </a:math> ). Other PROM scores improved by the end of the study with mean (95% CI) differences for youth and parents, respectively, as follows: Diabetes Impact and Device Satisfaction (DIDS) Scale Diabetes Impact −1.08 (−1.51, −0.64) ( <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>p</c:mi> <c:mo>&lt;</c:mo> <c:mn>0.001</c:mn> </c:math> ) and −1.41 (−1.96, −0.87) ( <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>p</e:mi> <e:mo>&lt;</e:mo> <e:mn>0.001</e:mn> </e:math> ); DIDS Scale Device Satisfaction +0.43 (0.11, 0.74) ( <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>p</g:mi> <g:mo>=</g:mo> <g:mn>0.01</g:mn> </g:math> ) and +0.58 (0.31, 0.85) ( <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:mi>p</i:mi> <i:mo>&lt;</i:mo> <i:mn>0.001</i:mn> </i:math> ); Hypoglycemia Fear Survey −4.41 (−7.65, −1.17) ( <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" id="M6"> <k:mi>p</k:mi> <k:mo>=</k:mo> <k:mn>0.01</k:mn> </k:math> ) and −7.64 (−11.66, −3.62) ( <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" id="M7"> <m:mi>p</m:mi> <m:mo>&lt;</m:mo> <m:mn>0.001</m:mn> </m:math> ); and WHO-5 Well-Being Index +5.10 (−1.40, 11.6) ( <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" id="M8"> <o:mi>p</o:mi> <o:mo>=</o:mo> <o:mn>0.12</o:mn> </o:math> ) and +9.60 (3.40, 15.8) ( <q:math xmlns:q="http://www.w3.org/1998/Math/MathML" id="M9"> <q:mi>p</q:mi> <q:mo>=</q:mo> <q:mn>0.003</q:mn> </q:math> ). The mean time in range increased from 52.6% at baseline to 62.6% ( <s:math xmlns:s="http://www.w3.org/1998/Math/MathML" id="M10"> <s:mi>p</s:mi> <s:mo>&lt;</s:mo> <s:mn>0.001</s:mn> </s:math> ) at 4 weeks, sustained to 16 weeks. Conclusions. Initiation of Control-IQ technology in a real-world setting significantly reduced the impact of diabetes on daily life while simultaneously improving glycemic control. Trial Registration. This trial is registered with ClinicalTrials.gov Identifier NCT04838561 (https://www.clinicaltrials.gov/ct2/show/NCT04838561?term=Control-IQ&amp;cond=Type+1+Diabetes&amp;cntry=CA&amp;draw=2&amp;rank=1).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.282
Teacher spread0.258 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2023
Admission routes1
Has abstractyes

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