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Record W4324140135 · doi:10.1161/circ.147.suppl_1.p347

Abstract P347: Measures of Microvascular Complications Varies Across Racial/Ethnic Groups Over a Seven Year Period: Post-Hoc Analysis of Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial Data

2023· article· en· W4324140135 on OpenAlexaboutno aff
Kaustubh V. Parab, Xiaotian Gao, Neha P. Gothe, Kenneth R. Wilund, Chelsea R. Singleton

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusPost-hoc analysisEthnic groupDemographyRenal functionType 2 diabetesInternal medicineGerontologyEndocrinology

Abstract

fetched live from OpenAlex

Introduction: Type 2 diabetes (T2D) microvascular complications is a major public health issue that disproportionately affects people of color in the U.S. and Canada. There is limited understanding of racial/ethnic disparities in the longitudinal natural history of microvascular complications. We aimed to address this gap in knowledge by examining racial/ethnic differences in microvascular complication-related measures over seven years among T2D adults living in the U.S. and Canada. Hypothesis: We assessed the hypothesis that measures of microvascular complications vary by race/ethnic group over a period of seven years. Methods: From 10,251 Action to Control Cardiovascular Risk in Diabetes (ACCORD) (2003-2009) trial participants, we derived 6,683 participants having a baseline and ≥ two years of outcome recordings for our analysis (baseline mean age 62 ± 6.6 years, and 11 ± 7.4 years of diabetes diagnosis). In this longitudinal study, we used T2D microvascular measurements recorded at baseline, yearly for seven years, and during a trial exit period. Neuropathy-related measures analyzed was the Michigan Neuropathy Screening Instrument (MNSI); Nephropathy-related measures included the glomerular filtration rate (eGFR) by four-variable Modification of Diet in Renal Disease equation (ml/min/1.73 m 2 ), urine albumin (mg/dl), and urine albumin : creatinine (mg/g). We examined differences in measurement among Black (n 1 = 1,176), White (n 2 = 4,282), and Other race adults (n 3 = 1,229). We used multigroup latent growth modeling to compare models from fully constrained to unconstrained means, covariances, and residual variances models. Results: MNSI, eGFR, and urine albumin significantly differed across racial/ethnic groups (ΔX 2 MNSI (2) = 231.8, p<0.001; ΔX 2 eGFR (2) = 489.2, p<0.001; ΔX 2 urine-albumin (2) = 194.6, p<0.001). We noticed that at least one of the means and covariances differed across racial/ethnic groups. The average MNSI trajectory for Other race/ethnicity (intercept=1.88, slope=-0.08) were better than that for Black (intercept=2.07, slope=-0.09) and White adults (intercept=2.67, slope=-0.14). The average eGFR trajectories for Black (intercept=88.86, slope=-1.16) and Other race/ethnicity (intercept=85.68, slope=-1.15) were better than that for White adults (intercept=82.59, slope=-1.36). However, average urine albumin trajectories for Black adults were worst (intercept=10.77, slope=0.98) followed by Other race/ethnicity (intercept=9.36, slope=0.73) and White adults (intercept=7.65, slope=0.57). Conclusion: Trajectories of microvascular complication-related measures appear to vary by racial/ethnic group. Other race adults, with primarily consists of Hispanics, appeared to at lower risk of neuropathy for years than Black and White adults. Nephropathy outcomes could vary across racial/ethnic group depending on how nephropathy is defined.

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)0.015
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.075
GPT teacher head0.352
Teacher spread0.277 · 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 designRandomized trial
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

Citations0
Published2023
Admission routes1
Has abstractyes

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