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Record W1966334892 · doi:10.1097/tp.0b013e318188425b

A Prospective Observational Study of Changes in Renal Function and Cardiovascular Risk Following Living Kidney Donation

2008· article· en· W1966334892 on OpenAlexaff
G. V. Ramesh Prasad, Deborah Lipszyc, Michael Huang, Michelle M. Nash, Lindita Rapi

Bibliographic record

VenueTransplantation · 2008
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsRenal functionMedicineBlood pressureBody mass indexInternal medicineKidneyExcretionUrologyEndocrinologyAmbulatoryProspective cohort studyLipid profileNephrectomyAmbulatory blood pressureDiabetes mellitus

Abstract

fetched live from OpenAlex

The effect of unilateral nephrectomy on the cardiovascular risk profile of living kidney donors has not been prospectively studied. We performed an observational cohort study of 58 living donors to 6 months postdonation for changes in 24-hr ambulatory blood pressure profiles, renal function, urine protein excretion, body mass index, glucose tolerance, and fasting lipid profiles. The 24-hr systolic blood pressure average and night-day ratio were unchanged from pre- to postdonation (118.9+/-11 vs. 118.1+/-14 mm Hg, P=0.77; 0.87+/-0.07 vs. 0.87+/-0.09, P=0.68, respectively). Estimated glomerular filtration rate declined from 91.9+/-16 to 61.6+/-12 mL/min/1.73 m2 (P<0.0001). Protein excretion, body mass index, glucose, and lipids were unchanged. No significant differences were noted between dippers and nondippers either pre- or postdonation. In summary, living kidney donation in the short term is safe. We suggest further observation of individuals with lower glomerular filtration rate for possible increased cardiovascular risk factors in the future.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.038
GPT teacher head0.258
Teacher spread0.221 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

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