Does looped nasogastric tube feeding improve nutritional delivery for patients with dysphagia after acute stroke? A randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: nasogastric tube (NGT) feeding is commonly used after stroke, but its effectiveness is limited by frequent dislodgement. OBJECTIVE: the objective of the study was to evaluate looped NGT feeding in acute stroke patients with dysphagia. METHODS: this was a randomised controlled trial of 104 patients with acute stroke fed by NGT in three UK stroke units. NGT was secured using either a nasal loop (n = 51) or a conventional adhesive dressing (n = 53). The main outcome measure was the proportion of prescribed feed and fluids delivered via NGT in 2 weeks post-randomisation. Secondary outcomes were frequency of NGT insertions, treatment failure, tolerability, adverse events and costs at 2 weeks; mortality; length of hospital stay; residential status; and Barthel Index at 3 months. RESULTS: participants assigned to looped NGT feeding received a mean 17% (95% confidence interval 5-28%) more volume of feed and fluids, required fewer NGTs (median 1 vs 4), and had fewer electrolyte abnormalities than controls. There was more minor nasal trauma in the loop group. There were no differences in outcomes at 3 months. Looped NGT feeding cost 88 pounds sterling more per patient over 2 weeks than controls. CONCLUSION: looped NGT feeding improves delivery of feed and fluids and reduces NGT reinsertion with little additional cost.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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".