MétaCan
Menu
Back to cohort
Record W2904925526 · doi:10.1111/hdi.12689

Dermatologic manifestations in end stage renal disease

2018· review· en· W2904925526 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHemodialysis International · 2018
Typereview
Languageen
FieldMedicine
TopicEosinophilic Disorders and Syndromes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEnd stage renal diseaseHemodialysisIntensive care medicineStage (stratigraphy)DiseaseDermatologyInternal medicine

Abstract

fetched live from OpenAlex

Skin manifestations are commonly seen in end stage renal disease (ESRD). Skin involvement in this population can be extensive and dramatically worsen quality of life. Close observation of the skin and nails of ESRD patients by clinicians allows for timely diagnosis and treatment, which ultimately improves quality of life and reduces mortality. In this article we focus on the cutaneous changes most commonly seen in ESRD patients. PubMed/Medline database search was done for published literature on skin manifestations in ESRD patients. All the available literature was reviewed and relevant articles were used to discuss about clinical features, pathogenesis, histology and treatment of each skin disorder in ESRD patients. Most commonly encountered skin manifestations in patients with ESRD are pruritus, xerosis, pigmentation changes, nail changes, perforating disorders, calcifying disorders, bullous dermatoses and nephrogenic systemic fibrosis. Skin manifestations in ESRD can be difficult to treat and multiple comorbidities in this patient population can exacerbate these disorders. Many of the treatment options are experimental with evidence largely derived from the case reports and small clinical trials. More large-scale trials are needed to firmly establish evidence based treatment guidelines. Prompt evaluation and management of these disorders improve morbidity and quality of life in ESRD 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.053
GPT teacher head0.358
Teacher spread0.305 · 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