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Record W2734964899 · doi:10.1056/nejmoa1703518

ACE Inhibitors and Statins in Adolescents with Type 1 Diabetes

2017· letter· en· W2734964899 on OpenAlexafffund
M. Loredana Marcovecchio, Scott T. Chiesa, Simon Bond, Denis Daneman, Sarah Dawson, Kim C. Donaghue, Timothy W. Jones, Farid H. Mahmud, Sally M. Marshall, H. A. W. Neil, R. Neil Dalton, John Deanfield, David B. Dunger

Bibliographic record

VenueNew England Journal of Medicine · 2017
Typeletter
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsSt. Thomas HospitalSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersBreakthrough T1D CanadaNIHR Cambridge Biomedical Research CentreHospital for Sick ChildrenUniversity College LondonUniversity of CambridgeDiabetes UKNational Institute for Health and Care Research
KeywordsMicroalbuminuriaMedicineInternal medicineAlbuminuriaACE inhibitorEndocrinologyType 2 diabetesDiabetes mellitusRenal functionCreatinineStatinAngiotensin-converting enzymeContext (archaeology)Blood pressure

Abstract

fetched live from OpenAlex

BACKGROUND: Among adolescents with type 1 diabetes, rapid increases in albumin excretion during puberty precede the development of microalbuminuria and macroalbuminuria, long-term risk factors for renal and cardiovascular disease. We hypothesized that adolescents with high levels of albumin excretion might benefit from angiotensin-converting-enzyme (ACE) inhibitors and statins, drugs that have not been fully evaluated in adolescents. METHODS: We screened 4407 adolescents with type 1 diabetes between the ages of 10 and 16 years of age and identified 1287 with values in the upper third of the albumin-to-creatinine ratios; 443 were randomly assigned in a placebo-controlled trial of an ACE inhibitor and a statin with the use of a 2-by-2 factorial design minimizing differences in baseline characteristics such as age, sex, and duration of diabetes. The primary outcome for both interventions was the change in albumin excretion, assessed according to the albumin-to-creatinine ratio calculated from three early-morning urine samples obtained every 6 months over 2 to 4 years, and expressed as the area under the curve. Key secondary outcomes included the development of microalbuminuria, progression of retinopathy, changes in the glomerular filtration rate, lipid levels, and measures of cardiovascular risk (carotid intima-media thickness and levels of high-sensitivity C-reactive protein and asymmetric dimethylarginine). RESULTS: The primary outcome was not affected by ACE inhibitor therapy, statin therapy, or the combination of the two. The use of an ACE inhibitor was associated with a lower incidence of microalbuminuria than the use of placebo; in the context of negative findings for the primary outcome and statistical analysis plan, this lower incidence was not considered significant (hazard ratio, 0.57; 95% confidence interval, 0.35 to 0.94). Statin use resulted in significant reductions in total, low-density lipoprotein, and non-high-density lipoprotein cholesterol levels, in triglyceride levels, and in the ratio of apolipoprotein B to apolipoprotein A1, whereas neither drug had significant effects on carotid intima-media thickness, other cardiovascular markers, the glomerular filtration rate, or progression of retinopathy. Overall adherence to the drug regimen was 75%, and serious adverse events were similar across the groups. CONCLUSIONS: The use of an ACE inhibitor and a statin did not change the albumin-to-creatinine ratio over time. (Funded by the Juvenile Diabetes Research Foundation and others; AdDIT ClinicalTrials.gov number, NCT01581476 .).

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.293
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations110
Published2017
Admission routes2
Has abstractyes

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