Establishment and application of evaluation criteria on reasonable use of biapenem
Bibliographic record
Abstract
OBJECTIVE To establish and retrospectively apply the drug use evaluation criterion on biapenem so as to provide basis for the reasonable clinical use of biapenem.METHODS Referring to the expert advice and guideline of clinical application of biapenem of WHO and the developed countries such as the United States and Canada,the drug use evaluation criteria on biapenem was established,and the data form was designed to collect the information of biapenem-use and to assess the drug use in a 3A hospital.RESULTS The drug use evaluation criterion on biapenem consisted of drug indications,drug use process and the results.Through the retrospective DUE application,we found that the qualified rates of some reasonable use of biapenem in a 3A hospital including temperature monitoring in patients before and after treatment,routine blood test,medication doses and administration way,solvent selection and drip time,and drug interaction were 100.0%;there were also some unreasonable use of biapenem such as lax grasping indications and contraindications,less pathogeny detecting,unreasonable antibacterial drugs combined application,long or short course of treatment in clinic,among which the qualified rate of the medication indication was 70.0%,8.3% were medication contraindications,60.0% were performed the bacterial culture and drug susceptibility testing within 72 hours before the first application;the accordant rate of the criteria of medication course was 58.3%,the combined use of antibiotics was 40.0%.CONCLUSION The DUE criterion has very strong practicability,and some problems and insufficiencies can be found in the clinical medication of biapenem,the DUE criterion possesses great significance in promotion of reasonable use of antibiotics.
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.
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 | 0.021 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".