MétaCan
Menu
Back to cohort
Record W4398234701 · doi:10.1001/jama.2024.8523

Hypertension and Kidney Function After Living Kidney Donation

2024· article· en· W4398234701 on OpenAlexafffundabout
Amit Garg, Jennifer Arnold, Meaghan S. Cuerden, Christine Dipchand, Liane S. Feldman, John S. Gill, Martin Karpinski, Scott Klarenbach, Greg Knoll, Charmaine E. Lok, Matthew C. Miller, Mauricio Monroy‐Cuadros, Christopher Nguan, G. V. Ramesh Prasad, Jessica M. Sontrop, Leroy Storsley, Neil Boudville

Bibliographic record

VenueJAMA · 2024
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsSt. Michael's HospitalUniversity of CalgaryUniversity Health NetworkOttawa HospitalMcGill UniversityUniversity of OttawaSt. Joseph’s Healthcare HamiltonUniversity of ManitobaUniversity of British ColumbiaUniversity of AlbertaLawson Health Research InstituteQueen Elizabeth II Health Sciences CentreDalhousie UniversityOntario Stroke NetworkMcMaster UniversityUniversity of TorontoWestern University
FundersCanadian Institutes of Health Research
KeywordsMedicineRenal functionCreatinineBlood pressureNephrectomyAlbuminuriaKidney diseaseDonationSurgeryUrologyInternal medicineKidney

Abstract

fetched live from OpenAlex

Importance: Recent guidelines call for better evidence on health outcomes after living kidney donation. Objective: To determine the risk of hypertension in normotensive adults who donated a kidney compared with nondonors of similar baseline health. Their rates of estimated glomerular filtration rate (eGFR) decline and risk of albuminuria were also compared. Design, Setting, and Participants: Prospective cohort study of 924 standard-criteria living kidney donors enrolled before surgery and a concurrent sample of 396 nondonors. Recruitment occurred from 2004 to 2014 from 17 transplant centers (12 in Canada and 5 in Australia); follow-up occurred until November 2021. Donors and nondonors had the same annual schedule of follow-up assessments. Inverse probability of treatment weighting on a propensity score was used to balance donors and nondonors on baseline characteristics. Exposure: Living kidney donation. Main Outcomes and Measures: Hypertension (systolic blood pressure [SBP] ≥140 mm Hg, diastolic blood pressure [DBP] ≥90 mm Hg, or antihypertensive medication), annualized change in eGFR (starting 12 months after donation/simulated donation date in nondonors), and albuminuria (albumin to creatinine ratio ≥3 mg/mmol [≥30 mg/g]). Results: Among the 924 donors, 66% were female; they had a mean age of 47 years and a mean eGFR of 100 mL/min/1.73 m2. Donors were more likely than nondonors to have a family history of kidney failure (464/922 [50%] vs 89/394 [23%], respectively). After statistical weighting, the sample of nondonors increased to 928 and baseline characteristics were similar between the 2 groups. During a median follow-up of 7.3 years (IQR, 6.0-9.0), in weighted analysis, hypertension occurred in 161 of 924 donors (17%) and 158 of 928 nondonors (17%) (weighted hazard ratio, 1.11 [95% CI, 0.75-1.66]). The longitudinal change in mean blood pressure was similar in donors and nondonors. After the initial drop in donors' eGFR after nephrectomy (mean, 32 mL/min/1.73 m2), donors had a 1.4-mL/min/1.73 m2 (95% CI, 1.2-1.5) per year lesser decline in eGFR than nondonors. However, more donors than nondonors had an eGFR between 30 and 60 mL/min/1.73 m2 at least once in follow-up (438/924 [47%] vs 49/928 [5%]). Albuminuria occurred in 132 of 905 donors (15%) and 95 of 904 nondonors (11%) (weighted hazard ratio, 1.46 [95% CI, 0.97-2.21]); the weighted between-group difference in the albumin to creatinine ratio was 1.02 (95% CI, 0.88-1.19). Conclusions and Relevance: In this cohort study of living kidney donors and nondonors with the same follow-up schedule, the risks of hypertension and albuminuria were not significantly different. After the initial drop in eGFR from nephrectomy, donors had a slower mean rate of eGFR decline than nondonors but were more likely to have an eGFR between 30 and 60 mL/min/1.73 m2 at least once in follow-up. Trial Registration: ClinicalTrials.gov Identifier: NCT00936078.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.230
Teacher spread0.220 · 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

Citations36
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueJAMASame topicOrgan Donation and TransplantationFrench-language works237,207