Association between frailty and hypoproteinaemia in older patients: meta-analysis and systematic review
Bibliographic record
Abstract
OBJECTIVE: Frailty and hypoproteinaemia are common in older individuals. Although there is evidence of a correlation between frailty and hypoproteinaemia, the relationship between frailty and hypoproteinaemia in hospitalized/critically ill and older community residents has not been clarified. Therefore, the aim of our meta-analysis was to evaluate the associations between frailty and hypoproteinaemia in different types of patients. METHODS: A systematic retrieval of articles published in the PubMed, Embase, Medline, Web of Science, Cochrane, Wanfang, and CNKI databases from their establishment to April 2024 was performed to search for studies on the associations between severity of frailty or prefrailty and hypoproteinaemia in older adults. The Newcastle‒Ottawa Scale and the Agency for Healthcare Research and Quality Scale were used to assess study quality. RESULTS: Twenty-two studies were included including 90,351 frail older people were included. Meta-analysis revealed an association between frailty or prefrailty and hypoproteinaemia (OR = 2.37, 95% CI: 1.47, 3.83; OR = 1.62, 95% CI: 1.23, 2.15), there was no significant difference in the risk of hypoproteinaemia between patients with severe frailty and those with low or moderate frailty (OR = 0.62, 95% CI:0.44, 0.87). The effect of frailty on the occurrence of hypoproteinaemia was more obvious in hospitalized patients/critically ill patients than in surgical patients (OR = 3.75, 95% CI: 2.36, 5.96), followed by older community residents (OR = 2.30, 95% CI: 1.18, 4.49). CONCLUSION: Frailty is associated with hypoproteinaemia in surgical patients, hospitalized older patients and older community residents. Future studies should focus on the benefits of albumin supplementation in preventing or alleviating frailty and related outcomes in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".