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Record W2165712123 · doi:10.1093/ndt/gfr802

Acute dialysis risk in living kidney donors

2012· article· en· W2165712123 on OpenAlexafffundabout
Ngan N. Lam, Anjie Huang, Liane S. Feldman, John S. Gill, Martin Karpinski, J. Kim, Scott Klarenbach, Greg Knoll, Krista L. Lentine, Christopher Nguan, Chirag R. Parikh, G. V. Ramesh Prasad, Darin Treleaven, Ann Young, Amit X. Garg

Bibliographic record

VenueNephrology Dialysis Transplantation · 2012
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity of AlbertaUniversity of TorontoUniversity of ManitobaMcMaster UniversitySt. Paul's HospitalMcGill University Health CentreSt. Joseph’s Healthcare HamiltonUniversity of British ColumbiaMcGill UniversityInstitute for Clinical Evaluative SciencesWestern University
FundersCanadian Institutes of Health ResearchAstellas PharmaFondation pour la Recherche MédicaleOntario Ministry of Health and Long-Term CareUniversity of AlbertaAlberta InnovatesInstitute for Clinical Evaluative Sciences
KeywordsMedicineDialysisIntensive care medicineKidneyKidney diseaseHemodialysisInternal medicineUrology

Abstract

fetched live from OpenAlex

BACKGROUND: Reduced kidney function confers a higher risk of acute kidney injury at the time of an inciting event, such as sepsis. Whether the same is true in those with reduced renal mass from living kidney donation is unknown. METHODS: We conducted a population-based matched cohort study of all living kidney donors in the province of Ontario, Canada who underwent donor nephrectomy from 1992 to 2009. We manually reviewed the medical records of these living kidney donors and linked this information to provincial health care databases. Non-donors were selected from the healthiest segment of the general population. RESULTS: There were 2027 donors and 20 270 matched non-donors. The median age was 43 years (interquartile range 34-50) and individuals were followed for a median of 6.6 years (maximum 17.7 years). The primary outcome was acute dialysis during any hospital stay. Reasons for hospitalization included infectious diseases, cardiovascular diseases and hematological malignancies. Only one donor received acute dialysis in follow-up (6.5 events per 100 000 person-years), a rate which was statistically no different than 14 non-donors (9.4 events per 100 000 person-years). CONCLUSIONS: These results are reassuring for the practice of living kidney donation. Longer follow-up of this and other donor cohorts will provide more precise estimates about this risk.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.016
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.253
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 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

Citations35
Published2012
Admission routes3
Has abstractyes

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