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Record W1969576889 · doi:10.1159/000341727

Renal Replacement Therapy in the End-Stage Renal Disease Patient with Critical Illness

2012· review· en· W1969576889 on OpenAlexaff
Stephanie Thompson, Neesh Pannu

Bibliographic record

VenueBlood Purification · 2012
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRenal replacement therapyMedicineIntensive care medicineDialysisEnd stage renal diseaseIntensive care unitComorbidityPopulationKidney diseaseEpidemiologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Dialysis patients account for 1-9% of all intensive care unit (ICU) admissions. As a result of the increasing prevalence of patients with end-stage renal disease (ESRD) and the changing demographics of this population, the number of dialysis patients requiring hospitalization and ICU support is expected to increase. Critically ill ESRD patients have more comorbidity and higher severity of illness than the general population resulting in higher ICU and in-hospital mortality rates. ESRD patients have been excluded from trials evaluating renal replacement therapy in the ICU, therefore little information is available about the optimal management of renal replacement therapy for dialysis patients in this setting. This review focuses on the epidemiology of chronic dialysis patients admitted to the ICU and discusses an approach to providing renal replacement therapy for critically ill patients with ESRD.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.321
Teacher spread0.276 · 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 designNot applicable
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

Citations8
Published2012
Admission routes1
Has abstractyes

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