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Record W2038310942 · doi:10.1159/000232577

Susceptibility to Insulin Resistance after Kidney Donation: A Pilot Observational Study

2009· article· en· W2038310942 on OpenAlexaff
Walid Shehab-Eldin, Sabry Shoeb, Said Sayed Ahmed Khamis, Yassien Salah, Ahmed Shoker

Bibliographic record

VenueAmerican Journal of Nephrology · 2009
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsMedicineInsulin resistanceInternal medicineEndocrinologyRenal functionProinsulinInsulinKidneyKidney disease

Abstract

fetched live from OpenAlex

BACKGROUND: In chronic kidney disease the contribution of decreased glomerular filtration rate (GFR) versus enhanced inflammation to cause insulin resistance (IR) is controversial. AIM: This pilot observational study examines, therefore, the prevalence of IR after kidney donation and factors that may determine its level. METHODS: Insulin, proinsulin, adiponectin, malondialdehyde, and hsCRP were measured by conventional techniques in 14 previous kidney donors and 25 healthy volunteers. RESULTS: Estimated GFR from Cockcroft-Gault formula of 76.42 + or - 19.39 ml/min/1.73 m(2) in the nephrectomized group was significantly lower (p < 0.01) than that in the control group of 125 + or - 32.9 ml/min/1.73 m(2). Fasting serum insulin of 16.57 + or - 16.86 mU/l and homeostasis model assessment of insulin resistance (HOMA-IR) of 4.86 + or - 5.11 in the nephrectomized group were significantly higher (p < 0.01) than the insulin level of 6.02 + or - 4.06 mU/l and HOMA-IR of 1.5 + or - 1.06 in the control group. There was no significant difference in levels in inflammatory mediators between the two groups. None of the tested inflammatory mediators correlated significantly with IR. CONCLUSION: Reduced GFR alone in previous kidney donors is associated with increased IR.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.108
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.316
Teacher spread0.285 · 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.

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

Citations17
Published2009
Admission routes1
Has abstractyes

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