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Record W4387339061 · doi:10.1186/s12891-023-06910-z

Symptom burden, fatigue, sleep quality and perceived social support in hemodialysis patients with musculoskeletal discomfort: a single center experience from Egypt

2023· article· en· W4387339061 on OpenAlexaboutno aff
Mohammed Kamal Nassar, Samar Tharwat, Sara M. Abdel-Gawad, Rabab Elrefaey, Alaa A. Elsawi, Abdelrahman Mohamed Elsayed, Eman Nagy, Shimaa Shabaka, Rasha Samir Shemies

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2023
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersMansoura UniversityScience and Technology Development Fund
KeywordsMedicinePittsburgh Sleep Quality IndexPhysical therapySocial supportMoodAnxietySleep disorderDepression (economics)Mood disordersUnivariate analysisInternal medicineMultivariate analysisSleep qualityInsomniaPsychiatryPsychology

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Musculoskeletal disorders (MSDs) are commonly encountered in hemodialysis (HD) patients. However, the causes linked to these disorders are still partially defined. The aim of this study was to determine the frequency of MSDs and their relationship to a variety of clinico-social characteristics such as sleep quality, mood disorders, fatigue, and social support, in addition to the patients' clinical and therapeutic profile. METHOD: The study included 94 patients on maintenance HD. Clinical and Sociodemographic data was gathered. To investigate the prevalence and trends of MSDs, the Nordic Musculoskeletal Questionnaire (NMQ-E) was employed. Patients completed the modified Edmonton Symptom Assessment System, Pittsburgh Sleep Quality Index (PSQI), multidimensional Fatigue Inventory (MFI-20), and Perceived Social Support from Family Scales. Univariate and multivariate regression analysis were used to assess the determinants of MSDs. RESULTS: The patients' mean age was 49.73 and 59.6% were males. Seventy-two percent of patients were afflicted by MSDs. Knee pain (48.9%), low back pain (43.6%), shoulder pain (41.6%), hip/thigh pain (35.1%), and neck pains (35.1%) were the most reported MSD domains. Pain (p = 0.001), fatigue (p = 0.01), depression (p = 0.015), and anxiety (p = 0.003) scores were substantially higher in patients with MSDs. Furthermore, patients with MSDs engaged in less physical activity (p = 0.02) and perceived less social support (p = 0.029). Patients with MSDs had lower subjective sleep quality, daytime dysfunction domains, and global PSQI scores (p = 0.02, 0.031, 0.036, respectively). Female gender (p = 0.013), fatigue (p = 0.012), depression (p = 0.014), anxiety (p = 0.004), lower activity (p = 0.029), and PSQI score (0.027), use of erythropoiesis-stimulating agents (ESAs), antihypertensive drugs, calcium and Iron supplementation were all significantly associated with MSDs. At the multivariable regression model, administration of ESAs (p = 0.017) and pain score (p = 0.040) were the only independent variables associated with the outcome. CONCLUSION: MSDs are quite common among HD patients. Female gender, pain, fatigue, depression, anxiety, reduced activity, poor sleep quality, and use of ESAs are all significantly associated with MSDs in HD patients. Patients with MSD perceived less social support compared to the other group. Patients treated with antihypertensive drugs, calcium and iron supplements were more likely to suffer MSDs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
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
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.300
Teacher spread0.278 · 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 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

Citations13
Published2023
Admission routes1
Has abstractyes

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