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Record W7021045609

Nutrition in advanced cancer care : a clinical perspective

2023· dissertation· en· W7021045609 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Archive (Karolinska Institutet) · 2023
Typedissertation
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationTSG101DiseaseNucleofectionWeight loss
DOInot available

Abstract

fetched live from OpenAlex

Adequate nutrition is an essential part in all stages of cancer care. By optimizing the nutrition care the benefits include increased tolerance to treatment as well as decreased mortality. Understanding how aspects of nutrition care in patients diagnosed with cancer, such as appetite, protein, albumin, and C-Reactive Protein (CRP), as well as body image, are intertwined are potentially important factors in clinical practice. All studies in the thesis were performed among patients diagnosed with advanced cancer admitted to Advanced Medical Home Care in Stockholm, Sweden. \n \n \n \nIn men diagnosed with advanced cancer, who had lost weight since diagnosis, we found an inverse association between weight loss and “physical functioning”, as measured by the RAND-36 domain, β = -1.34 (95%CI: -2.44,- 0.24 (study I). In women, we found that weight loss was associated with improvement in the RAND-36 domain role “limitations due to physical health”; β = 2.02 (95%CI:0.63,3.41). Women reported a more distressed body image than men (p = 0.02), which remained significant when only women that had lost weight after diagnosis were included. Further, we found an association between weight loss in men and body image distress, β = 0.22 (95%CI:0.07,0.37). \n \n \n \nThe aim of study II was to compare how high-protein parenteral nutrition (PN) affects the liver compared to standard PN. We found no significant difference in the proportion of patients with elevated liver enzymes in the high-protein PN group; OR 0.20 (95%CI:0.02,1.86). Patients that have received high-protein PN had a significantly higher weight at follow-up when compared to patients administered a PN containing standard amount of protein (p < 0.05). \n \n \n \nIn study III we found a significant correlation in men between low appetite, measured by the Edmonton Symptom Assessment System (ESAS), and low albumin (r = 0.27, p < 0.001). In men, lower appetite was also correlated with a higher CRP (r = 0.27, p < 0.001). In regression analysis, adjusted for confounding factors, the results remained similar. In women, there was no correlation between appetite and albumin or CRP. \n \n \n \nIn a cohort analysis (study IV) moderate and poor appetite were significantly associated with a higher mortality rate when compared to participants reporting a good appetite; HR 1.44 (95%CI:1.16,1.79) and HR 1.78 (95%CI:1.39,2.29), respectively (study IV). We also found that participants with low albumin levels (< 25 g/L), and participants in the highest tertile of CRP/albumin ratio, had higher mortality rates, HR 5.35 (95%CI:3.75,7.63) and HR 2.66 (95%CI:2.12,3.35), when compared to participants with high albumin levels (>36 g/L) and participants in the lowest tertile of CRP/albumin ratio. The associations were more pronounced in men than in women.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.089
GPT teacher head0.511
Teacher spread0.422 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes1
Has abstractyes

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