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Record W2143850230 · doi:10.1111/sdi.12196

Pain in Chronic Kidney Disease: A Scoping Review

2014· review· en· W2143850230 on OpenAlexaff
Sara N. Davison, Holly M. Koncicki, Frank Brennan

Bibliographic record

VenueSeminars in Dialysis · 2014
Typereview
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineKidney diseaseIntensive care medicineChronic painDiseaseAnalgesicPain managementEpidemiologyMEDLINEPhysical therapyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

There is increasing international attention in efforts to integrate palliative care principles, including pain and symptom management, into the care of patients with advanced chronic kidney disease (CKD). The purpose of this scoping review was to determine the extent, range, and nature of research activity around pain in CKD with the goal of (i) identifying gaps in current research knowledge; (ii) guiding future research; and (iii) creating a rich database of literature to serve as a foundation of more detailed reviews in areas where the data are sufficient. This review will specifically address the epidemiology of pain in CKD, analgesic use, pharmacokinetic data of analgesics, and the management of pain in CKD. It will also capture the aspects that pertain to specific pain syndromes in CKD such as peripheral neuropathy, carpal tunnel syndrome, joint pain, and autosomal dominant polycystic kidney disease.

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)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0130.014
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.401
Teacher spread0.362 · 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 designSystematic review
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

Citations167
Published2014
Admission routes1
Has abstractyes

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