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Record W2624187225 · doi:10.1111/sdi.12610

The physical deterioration of dialysis patients—Ignored, ill‐reported, and ill‐treated

2017· editorial· en· W2624187225 on OpenAlexaff
Paul N. Bennett, Nicole Capdarest‐Arest, Kristen Parker

Bibliographic record

VenueSeminars in Dialysis · 2017
Typeeditorial
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsSouth Health Campus
Fundersnot available
KeywordsMedicineRehabilitationQuality of life (healthcare)Physical therapyKidney diseaseDialysisIntensive care medicineRenal functionDiseaseStroke (engine)Physical exerciseRenal replacement therapyDiabetes mellitusInternal medicineNursing

Abstract

fetched live from OpenAlex

The progressive physical deterioration of dialysis patients is apparent to all who are involved in their care. Exercise can help stem this decline, yet exercise uptake in chronic and end-stage kidney disease is low. The involvement of exercise professionals has been shown to significantly increase patients' physical function and improve their quality of life. However, exercise professionals are scarce in renal programs, far less than dietetic and social work services. A review of 10 years of renal exercise publications in the physical therapy and rehabilitation literature found that only 0.4% (7 out of a total of 1763) of all published articles were focused on people with kidney disease. This compared with stroke (44%, n=883), arthritis/bone (29%, n=458), cancer (9%, n=168), respiratory (8%, n=106), cardiac (5%, n=82), and diabetes (3%, n=45). These results reflect the low emphasis placed on renal rehabilitation by the physical therapy professions and the low renal content in physical therapy tertiary education programs. This is likely to have an impact on the level of involvement of physical therapists in renal programs leading to lower physical function and poorer quality of life for renal 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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.268
Teacher spread0.261 · 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 designNot applicable
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

Citations23
Published2017
Admission routes1
Has abstractyes

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