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Record W4229844677 · doi:10.2217/ahe.10.60

Dialysis in the Elderly

2010· article· en· W4229844677 on OpenAlexaff
Ploumis Passadakis, Elias Thodis, Dimitrios G. Oreopoulos

Bibliographic record

VenueAging Health · 2010
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicinePeritoneal dialysisDialysisComorbidityHemodialysisIntensive care medicineQuality of life (healthcare)Kidney diseaseDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Although most investigators still define as ‘elderly’ those older than 65 years of age, recently, many would consider elderly to be those 75–80 years or older, mainly because those 65–75 years of age are still active, continue working and are relatively healthy. The care of the elderly who require chronic dialysis is more complex than the management of their younger counterparts owing to their frequent comorbid conditions, numerous impairments, functional limitations and lack of social support. The ideal timing of dialysis initiation in the elderly with slowly progressing chronic kidney disease has not been clearly defined because we have not defined predictors that may negatively affect their outcomes. Recent developments in the management of hypertension and other complications, and the addition of an appropriate diet, may delay progression to dialysis. In the absence of severe comorbidity, the choice of dialysis rather than conservative nondialysis therapy is associated with longer survival in elderly patients but not in those with multiple comorbidities. Quality of life and survival rates seem to be similar in elderly patients on either hemodialysis or peritoneal dialysis, although selection bias may confound these findings. Assisted peritoneal dialysis is a suitable method for frail elderly patients who choose to be dialyzed at home.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.114

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.015
GPT teacher head0.315
Teacher spread0.300 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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