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Record W2949457018 · doi:10.1093/ndt/gfz103.sp686

SP686Evaluation of pain in patients undergoing hemodialysis

2019· article· en· W2949457018 on OpenAlexaboutno aff
Esmira Sadikova, Sultan Özkurt, Ahmet Uğur Yalçın

Bibliographic record

VenueNephrology Dialysis Transplantation · 2019
Typearticle
Languageen
FieldMedicine
TopicNeurological and metabolic disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodialysisIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: End stage renal disease is defined as loss of renal function requiring renal replacement therapy with any form of chronic dialysis or occasionally conservative management in the elderly or those with significant comorbidities. Pain is the one of the most common symptoms experienced by patients with ESRD; it impairs their quality of life and is undertreated. METHODS: In our study, 328 patients undergoing routine hemodialysis treatment at three different outpatient hemodialysis units in Eskişehir,Turkey between October 2017 and May 2018 were evaluated. A McGill pain questionnaire was used to assess the nature, location, frequency, intensity and of pain. Leeds assessment of neuropathic symptoms and signs (LANSS) pain scale was used for the evaluation of neuropathic pain. RESULTS: The Mean age was 65 ±12.5 years. The mean time on dialysis was 7.0±6.0 years.74.4% of the patients experienced pain. Neuropathic pain was seen in 151 patients and nociceptive pain was seen in 93 patients. In non-diabetic group, neuropathic pain was seen in 47.4% of patients. There was a direct positive relationship between the presence of residual urine and quality of life. Significant negative relation was found between the presence of residual urine and neuropathic pain. There was a negative correlation between Kt/V value and pain severity. There was negative correlation in severity of pain and the level of parathormone. Negative correlation in life quality was found in all parameters of patients with pain compared to those without pain. CONCLUSIONS: This study indicate high prevalence of pain in hemodyalisis patients. Pain in this population should be considered as an important health problem, and health professionals should prioritize clinical management and research in pain management to improve the quality of life of hemodialysis patients, and care should be taken to protect residual renal function.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.030
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.243
Teacher spread0.232 · 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.

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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