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Record W1960743264 · doi:10.1111/hdi.12301

Prevalence of uremic itching in patients undergoing hemodialysis

2015· article· en· W1960743264 on OpenAlexvenueno aff
Mehtap Kavurmacı

Bibliographic record

VenueHemodialysis International · 2015
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsItchingMedicineHemodialysisVisual analogue scaleEtiologySurgeryDermatologyInternal medicine

Abstract

fetched live from OpenAlex

Uremic itching is a common problem with multifactorial etiology seen in hemodialysis patients. This study was carried out to determine the factors affecting and incidence of itching in patients undergoing hemodialysis treatment. The descriptive study was carried out in 130 patients who underwent hemodialysis treatment because of end-stage renal disease in Eastern Turkey between October 2014 and December 2014. A questionnaire prepared by the researcher based on the literature and the Visual Analog Scale were used for data collection. The data were collected by the researcher through face-to-face interviews in the hemodialysis unit. The evaluation of data obtained in the research has been performed using SPSS 16.0 software using percentages, chi-square analysis, and t-test. As a result of the study, 85.4% of the patients were found to have itching, the severity of itching was 4.86 ± 3.01 according to Visual Analog Scale, and itching of the patients was found to be affected by serum phosphorus and parathyroid hormone levels. Uremic itching continues to be seen as a problem in hemodialysis 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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.021
GPT teacher head0.281
Teacher spread0.260 · 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 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

Citations15
Published2015
Admission routes1
Has abstractyes

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