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Symptom burden and quality of life in patients with malignant fungating wounds

2011· article· en· W1605899333 on OpenAlexaboutno aff
Shun‐Tsung Lo, Mark Hayter, Wen‐Yu Hu, Chiao‐Yun Tai, Mei‐Yu Hsu, Yufen Li

Bibliographic record

VenueJournal of Advanced Nursing · 2011
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsnot available
FundersTzu Chi College of Technology
KeywordsMedicineQuality of life (healthcare)Palliative careOutpatient clinicPhysical therapyInternal medicineNursing

Abstract

fetched live from OpenAlex

AIM: This study describes the relationship between symptoms and quality of life in patients with malignant fungating wounds. BACKGROUND: Malignant fungating wounds are complex wounds that can bleed, become malodorous due to infection and are painful causing physical and psychological distress. However, there is a lack of literature on the impact that such wounds can have on quality of life. METHODS: This was a descriptive, cross-sectional multi-centre study of patients with malignant fungating wounds. Participants were recruited from the palliative care, hospice, outpatient clinic and oncology units of three medical centres in Taiwan. Data were collected from February 2008 to August 2009. A structured questionnaire obtained socio-demographic information, medical details, wound assessment information and the Taiwanese version of the McGill quality of life questionnaire was administered by interview. RESULTS: McGill quality of life scores indicated that the participants had the lowest quality of life. The participant's age, dressing change frequency, pain, wound dressing comfort, wound symptom, bleeding and malodour had statistically significant negative correlations with quality of life. Multiple regression analysis showed that age, malodour, pain issues and psychological issues explained 87% of the total variance in quality of life. CONCLUSION: This study contributes to our understanding of the impact of malignant fungating wounds and how correct assessment and management is necessary to improve quality of life. Educational intervention research is needed for patients and caregivers in countries where this has not yet been performed. Further research should also identify whether nursing competence has a direct impact on quality of life.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.061
GPT teacher head0.384
Teacher spread0.323 · 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

Citations102
Published2011
Admission routes1
Has abstractyes

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