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Record W2945618914 · doi:10.1177/2054358119850536

Serum Apolipoprotein B and A1 Concentrations Predict Late-Onset Posttransplant Diabetes Mellitus in Prevalent Adult Kidney Transplant Recipients

2019· article· en· W2945618914 on OpenAlexaffabout
Rohit Malyala, Lindita Rapi, Michelle M. Nash, G. V. Ramesh Prasad

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2019
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineInternal medicineDiabetes mellitusInsulin resistanceApolipoprotein BEndocrinologyRisk factorType 2 Diabetes MellitusKidney transplantKidney transplantationCholesterolKidney

Abstract

fetched live from OpenAlex

Background: Glucose metabolism links closely to cholesterol metabolism. Posttransplant diabetes mellitus (PTDM) adversely affects posttransplant outcomes, but its risk factors in relation to cholesterol metabolism have not been fully delineated. The apolipoprotein B/A1 (Apo B/A1) ratio, which is associated with insulin resistance, has not been evaluated in kidney transplant recipients as a risk factor for PTDM. Objective: The objective of this study was to determine whether serum apolipoprotein profiles predict late PTDM, defined as a new onset diabetes occurring greater than 3 months posttransplant. Design: Retrospective chart review of a prevalent population of kidney transplant recipients. Setting: Large transplant center in Ontario, Canada. Patients: We identified 1104 previously nondiabetic adults who received a kidney transplant between January 1, 1998, and December 1, 2015, and were followed at 1 transplant center. Measurements: Recipients provided testing for serum apolipoprotein B (Apo B) and apolipoprotein A1 (Apo A1) concentrations from 2010, either at 3 months posttransplant for new transplant recipients or the next clinic visit for prevalent recipients. Late PTDM defined using Canadian Diabetes Association criteria as occurring ≥3 months posttransplant was recorded until May 1, 2016. Methods: All analyses were conducted with R, version 3.4.0 (The R Foundation for Statistical Computing). Comparisons were made using Student t test, Fisher exact test or chi-square test, Kaplan-Meier methodology with the logrank test, or Cox proportional hazards analysis as appropriate. Covariates for the multivariate Cox proportional hazards models of PTDM as the outcome variable were selected based on significance of the univariate associations and biological plausibility. Results: There were 53 incident late PTDM cases, or 1.71 cases per 100 patient-years. Incident late PTDM differed between the highest and lowest quartiles for Apo B/A1 ratio, 2.47 per 100 patient-years vs 0.88 per 100 patient-years ( P = .005 for difference). In multiple Cox regression analysis, first measured serum Apo B/A1 concentration better predicted subsequent PTDM than low-density lipoprotein cholesterol (LDL-C; hazard ratio [HR] = 7.80 per unit increase, P = .039 vs HR = 1.05 per unit increase, P = .774). Non-high-density lipoprotein cholesterol (HDL-C) concentrations also did not predict PTDM ( P = .136). By contrast to Apo B, Apo A1 was protective against PTDM in statin users (HR = 0.17 per unit increase, P = .016). Limitations: Posttransplant diabetes mellitus cases occurring before apolipoprotein testing was implemented were not included in the analysis. Conclusions: Apolipoproteins B and A1 better predict late PTDM than conventional markers of cholesterol metabolism.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.255
Teacher spread0.244 · 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".

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Citations18
Published2019
Admission routes2
Has abstractyes

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