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Record W4400595002 · doi:10.1186/s41687-024-00750-8

The association between malnutrition risk and revised Edmonton Symptom Assessment System (ESAS-r) scores in an adult outpatient oncology population: a cross-sectional study

2024· article· en· W4400595002 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Patient-Reported Outcomes · 2024
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of GuelphGrand River HospitalCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsMedicineMalnutritionQuality of life (healthcare)PopulationNauseaLogistic regressionCross-sectional studyDepression (economics)Internal medicinePhysical therapyCancerEnvironmental healthNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer-associated malnutrition is associated with worse symptom severity, functional status, quality of life, and overall survival. Malnutrition in cancer patients is often under-recognized and undertreated, emphasizing the need for standardized pathways for nutritional management in this population. The objectives of this study were to (1) investigate the relationship between malnutrition risk and self-reported symptom severity scores in an adult oncology outpatient population and (2) to identify whether a secondary screening tool for malnutrition risk (abPG-SGA) should be recommended for patients with a specific ESAS-r cut-off score or group of ESAS-r cut-off scores. METHODS: A single-institution retrospective cross-sectional study was conducted. Malnutrition risk was measured using the Abridged Patient-Generated Subjective Global Assessment (abPG-SGA). Cancer symptom severity was measured using the Revised Edmonton Symptom Assessment System (ESAS-r). In accordance with standard institutional practice, patients completed both tools at first consult at the cancer centre. Adult patients who completed the ESAS-r and abPG-SGA on the same day between February 2017 and January 2020 were included. Spearman's correlation, Mann Whitney U tests, receiver operating characteristic curves, and binary logistic regression models were used for statistical analyses. RESULTS: 2071 oncology outpatients met inclusion criteria (mean age 65.7), of which 33.6% were identified to be at risk for malnutrition. For all ESAS-r parameters (pain, tiredness, drowsiness, nausea, lack of appetite, shortness of breath, depression, anxiety, and wellbeing), patients at risk for malnutrition had significantly higher scores (P < 0.001). All ESAS-r parameters were positively correlated with abPG-SGA score (P < 0.01). The ESAS-r parameters that best predicted malnutrition risk status were total ESAS-r score, lack of appetite, tiredness, and wellbeing (area under the curve = 0.824, 0.812, 0.764, 0.761 respectively). Lack of appetite score ≥ 1 demonstrated a sensitivity of 77.4% and specificity of 77.0%. Combining lack of appetite score ≥ 1 with total ESAS score > 14 yielded a sensitivity of 87.9% and specificity of 62.8%. CONCLUSION: Malnutrition risk as measured by the abPG-SGA and symptom severity scores as measured by the ESAS-r are positively and significantly correlated. Given the widespread use of the ESAS-r in cancer care, utilizing specific ESAS-r cut-offs to trigger malnutrition screening could be a viable way to identify cancer patients at risk for malnutrition.

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)0.003
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 score0.004
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.408
Teacher spread0.373 · 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