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Effects of Prior Intensive Insulin Therapy and Risk Factors on Patient-Reported Visual Function Outcomes in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Cohort

2015· article· en· W2200349968 on OpenAlexaboutno aff
Rose Gubitosi‐Klug, Wanjie Sun, Patricia A. Cleary, Barbara H. Braffett, Lloyd Paul Aiello, Arup Das, William V. Tamborlane, Ronald Klein

Bibliographic record

VenueJAMA Ophthalmology · 2015
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
FundersNational Eye InstituteInsulet CorporationNational Institute of Diabetes and Digestive and Kidney DiseasesAbbott Diabetes CareEli Lilly and CompanyUniversity of WashingtonNational Institute of Neurological Disorders and StrokeSanofi
KeywordsMedicineInterquartile rangeType 1 diabetesDiabetic retinopathyDiabetes mellitusVisual acuityCohortRetinopathyGlycemicRandomized controlled trialCohort studyPediatricsInternal medicineSurgeryEndocrinology

Abstract

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IMPORTANCE: Preservation of vision in patients with diabetes mellitus is critical. Interventions to improve glycemic control through early intensive treatment of diabetes reduce rates of severe retinopathy and preserve visual acuity. OBJECTIVE: To assess the effects of prior intensive insulin treatment and risk factors on patient-reported visual function in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) cohort. DESIGN, SETTING, AND PARTICIPANTS: Cohort study of 1184 participants with type 1 diabetes from the DCCT/EDIC study (randomized clinical trial followed by an observational follow-up study) who completed the 25-item National Eye Institute Visual Function Questionnaire (NEI-VFQ-25) during EDIC years 17 through 20 (September 1, 2009, through April 30, 2014) in 28 institutions across the United States and Canada. MAIN OUTCOMES AND MEASURES: The primary outcome was the composite NEI-VFQ-25 score. Secondary outcomes were visual acuity (measured by the Early Treatment Diabetic Retinopathy Study protocol), retinopathy level (determined by masked grading of stereoscopic color fundus photographs), and NEI-VFQ-25 subscale scores. The composite NEI-VFQ-25 scale and its subscales were scored 0 to 100, corresponding to poor to excellent function, respectively. RESULTS: The overall average NEI-VFQ-25 score for 1184 DCCT/EDIC participants (mean [SD] age, 52.3 [6.9] years; 48% female) with a 30-year duration of diabetes was high (all participants: median, 91.7; interquartile range [IQR], 89.7-96.9; intensive treatment [n = 605]: median, 94.7; IQR, 91.0-97.2; conventional treatment [n = 579]: median, 94.0; IQR, 88.4-96.1; P = .006 for intensive vs conventional). After adjustment for sex, age, hemoglobin A1c level, and retinopathy level at DCCT baseline, the former intensive treatment group had a significant, albeit modest, improvement in overall NEI-VFQ-25 score compared with the former conventional diabetes treatment group (median difference, -1.0; 95% CI, -1.7 to -0.3; P = .006). This beneficial treatment effect was fully attributed to the prior glycemic control in DCCT (explained treatment effect: 100%). Those with visual acuity worse than 20/100 reported the largest decline in visual function (median difference, -21.0; 95% CI, -40.5 to -1.6; P = .03). CONCLUSIONS AND RELEVANCE: In the DCCT/EDIC cohort, patient-reported visual function remains high in both treatment groups, comparable to previous reports of overall health-related quality of life. Intensive diabetes therapy modestly improved NEI-VFQ-25 score 30 years after the start of the DCCT, the benefit underestimated owing to more nonparticipants from the conventional treatment group. Visual acuity had the greatest effect on patient-reported visual function from among all risk factors. TRIAL REGISTRATION: clinicaltrials.gov Identifiers: NCT00360815 and NCT00360893.

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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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.361
Teacher spread0.297 · 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 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

Citations53
Published2015
Admission routes1
Has abstractyes

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