Evaluation of improvement measures for premature infants with tube feeding
Bibliographic record
Abstract
Objective To explore the effects of individualized feeding, intervention training, breast feeding education and kangaroo nursing on the improvement of feeding time, transition time and average hospital stay of premature infants. Methods A total of 586 hospitalized premature infants were selected as the control group who were admitted to the department before the adoption of tube feeding and feeding improvement measures for premature infants from July 2016 to December 2016.A total of 632 hospitalized premature infants admitted to this department after the implementation of improvement measures were selected as the observation group from January 2017 to July 2017.The control group was fed with traditional tube feeding method, namely gastric tube injector injection method.However, the observation group adopted the recommendations of extremely low birth-weight infant feeding proposed by McMaster university of Canada and formulated the improved measures of tube feeding and feeding of premature infants based on the long-term clinical experience of the department.The duration of tube feeding, transition time, average length of stay and nursing satisfaction of family members were compared between the two groups. Results Tube feeding time, transition time and average length of stay in the control group were compared with the observation group, and the differences were statistically significant (P<0.05). The nursing satisfaction of the observation group was compared with that of the control group, and the difference was statistically significant (P<0.05). Conclusions The improvement measures of tube feeding and feeding of premature infants have a significant effect on improving tube feeding and feeding of premature infants, which can not only shorten the transition time and average length of hospitalization of tube feeding and feeding of premature infants, but also improve the quality of nursing and nursing satisfaction. It is worth further popularizing and applying in clinic to improve nursing satisfaction. Key words: Premature infants; Tube feeding; Improvement measures
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".