Effect of nutrition support on quality adjusted life year in elderly patients with nutritional risk
Bibliographic record
Abstract
Objective To summarize the progress of research on the influence of nutrition support on quality adjusted life year (QALY) in elderly patients with nutritional risk, and to evaluate the feasibility of QALY as an outcome indicator. Methods Literature in Chinese, English and Japanese relating tothe feasibility of QALY and cost-utility in evaluating the influence of nutrition support on the outcomes of patients with nutritional riskpublished from 1980 to 2013 were searched in Wanfang, China National Knowledge Infrastructure, PubMed, Nature databases.The methodological quality of randomized controlled trials was assessed using Jadad scale combined with Schulz allocation concealment, and the quality of cohort studies with Newcastle-Ottawa scale. Results Totally 10 articles were found, in which 8 were selected, including 6 randomized controlled trial and 2 cohort studies, covering 1 130 patients; the other 2 were excluded for not conforming to inclusion criteria.Four of the 6 randomized controlled trial indicate that QALY is higher and all-cost is lower in the treatment group compared with the control group (or cost-utility is higher in the treatment group). The 2 cohort studies indicate that total parenteral nutrition support at home could improve the QALY of malnourished patients and could save cost compared with nutrition support at hospital when necessary. Conclusions Nutrition support for patients with nutritional risk can improve prognosis, reduce cost, and increase QALY. More large-scale, high-quality randomized controlled trials are needed to evaluate the effect of nutrition support on the QALY of elderly patients with nutritional risk. Key words: Quality adjusted life year; Nutrition support; Nutritional risk
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".