Risk factors for the development of refeeding syndrome in adults: A systematic review
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.
Bibliographic record
Abstract
Identifying patients with a particularly high risk of refeeding syndrome (RFS) is essential for taking preventive measures. To guide the development of clinical decision-making and risk prediction models or other screening tools for RFS, increased knowledge of risk factors is needed. Therefore, we conducted a systematic review to identify risk factors for the development of RFS. PubMed, EMBASE, Cochrane Library, and Web of Science were searched from January 1990 until March 2023. Studies investigating demographic, clinical, drug use, laboratory, and/or nutrition factors for RFS were considered. The Newcastle-Ottawa Scale was used to appraise the methodological quality of included studies. Of 1589 identified records, 30 studies were included. Thirty-three factors associated with increased risk of RFS after multivariable adjustments were identified. The following factors were reported by two or more studies, with 0-1 study reporting null findings: a previous history of alcohol misuse, cancer, comorbid hypertension, high Acute Physiology and Chronic Health Evaluation II score, high Sequential Organ Failure Assessment score, low Glasgow coma scale score, the use of diuretics before refeeding, low baseline serum prealbumin level, high baseline level of creatinine, and enteral nutrition. The majority of the studies (20, 66.7%) were of high methodological quality. In conclusion, this systematic review informs on several risk factors for RFS in patients. To improve risk stratification and guide development of risk prediction models or other screening tools, further confirmation is needed because there were a small number of studies and a low number of high-quality studies on each factor.
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 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 | 0.012 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it