MétaCan
Menu
Back to cohort
Record W4400880591 · doi:10.1016/j.xkme.2024.100872

Pretransplant Cognitive Function and Kidney Transplant Outcomes: A Prospective Cohort Study

2024· article· en· W4400880591 on OpenAlexaboutno aff
Aditi Gupta, Michael Grasing, Kate Young, Robert N. Montgomery, Daniel J. Murillo, Diane M. Cibrik

Bibliographic record

VenueKidney Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsnot available
FundersNational Institute on AgingNational Institutes of Health
KeywordsKidney transplantMedicineProspective cohort studyCognitionKidney transplantationCohortInternal medicineKidneyPsychiatry

Abstract

fetched live from OpenAlex

Background & Hypothesis Cognitive impairment is common in patients being evaluated for a kidney transplant (KT). The association between pretransplant cognitive function and posttransplant outcomes is unclear. Study Design We performed a prospective cohort study to assess the association between pretransplant cognitive function and clinically relevant posttransplant outcomes. Setting and Population In this single center study, participants from the transplant clinic were evaluated during their pretransplant clinic visits and followed prospectively. Outcomes Our primary outcome measure was allograft function. Secondary outcomes were length of hospitalization for KT, hospital readmission within 30 and 90 days, graft loss, graft rejection within 90 days and 1 year, and mortality. Analytic Approach We measured cognitive function with the Montreal Cognitive Assessment (MoCA) test. We assessed the association of pretransplant MoCA score with posttransplant outcomes; we used linear mixed effects models to assess the association with the change in estimated glomerular filtration rate, Poisson regression for length of hospitalization, Cox proportional hazard model for graft loss and mortality, and a logistic regression model for readmission and rejection. Results We followed 501 participants for 2.7±1.5 years. The mean age of the patients was 53±14 years and the mean pretransplant MoCA score was 25±3. Lower pretransplant MoCA scores did not adversely affect the primary outcome of allograft function or the secondary outcomes. Although higher MoCA scores predicted a higher decline in graft function (β =−0.28, 95% CI: −0.55 to−0.01, P =0.04), the effect was small and not clinically significant. Older age was associated with longer hospitalization, lower likelihood of rejection, and higher mortality. Deceased donor KT (vs living donor KT) was associated with longer hospitalization but better graft function. Longer time receiving dialysis before KT was associated with longer hospitalization. A history of diabetes mellitus was associated with higher mortality. Limitations Single center study limiting generalizability. Conclusions Pretransplant MoCA scores were not associated with the primary outcome of allograft function or the secondary outcomes. Plain-Language Summary Cognitive impairment (problems with memory and thinking) is common in patients with kidney disease. Cognitive impairment is associated with problems following instructions and remembering to take medications. Medical adherence is important in kidney transplant recipients, and inability to follow instructions and missed doses of immunosuppression increases the risk of rejection of the transplanted kidney. However, kidney transplantation also improves cognition. Hence, transplant centers wonder if cognitive impairment before transplant affects clinical outcomes after kidney transplant. We tried to answer this question by assessing cognitive function before transplantation and examining whether pretransplant cognitive function affects graft function, length of hospitalization, readmission after transplantation, rejection, and death. We did not find any strong link between cognitive function before transplant and these outcomes.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.307
Teacher spread0.289 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueKidney MedicineSame topicRenal Transplantation Outcomes and TreatmentsFrench-language works237,207