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Record W2315754259 · doi:10.3747/pdi.2014.00346

Selecting Peritoneal Dialysis in the Older Dialysis Population

2015· review· en· W2315754259 on OpenAlexaff
Matthew J. Oliver, Robert R. Quinn

Bibliographic record

VenuePeritoneal Dialysis International · 2015
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsPeritoneal dialysisMedicineHemodialysisIntensive care medicineDialysisPopulationPalliative careInternal medicineNursing

Abstract

fetched live from OpenAlex

Selecting peritoneal dialysis (PD) in older individuals is a complex, multi-step process. At each step, older individuals may not have the opportunity to receive PD unless care is optimized. Older individuals are less likely to complete a PD assessment, because of unstable medical conditions, consideration of palliative care, or reluctance to approach frail patients once they are established on hemodialysis (HD). Older individuals are also more likely to have medical or social conditions that contraindicate PD or to have barriers to self-care PD that may not be overcome with support. Older individuals who are eligible for PD may be reluctant to choose it, leaving HD as the default modality. Finally, receipt of PD may be compromised by urgent HD or PD catheter-related complications at the time of insertion. Despite all these challenges, older patients can do very well on PD, so each step should be well understood and optimized in renal programs to maximize PD use in older patients.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.371
Teacher spread0.324 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations16
Published2015
Admission routes1
Has abstractyes

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