Construction and clinical application of extended service system of "health manager+PGR system"
Bibliographic record
Abstract
ObjectiveFrom the perspective of out⁃of⁃hospital extended service,to explore the path of "health manager + PGR system" and to discuss the implementation effect.MethodsA total of 75 patients underwent joint replacement in our hospital from October to December 2023 were selected as the control group.And 72 cases underwent joint replacement in our hospital from January to February 2024 were selected as the observation group.The control group was accepted routine "phone + WeChat" follow⁃up.And the observation group was provided extended nursing service of "health manager + PGR system".Pain Visual Analogue Scale(VAS) scores,Daily Living Ability(ADL) scores,the Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC) scores,Harris Hip Score(HHS) scores,American Shoulder and Elbow Surgeons' Form(ASES) scores,postoperative complications,patient and nurse satisfaction were compared between the two groups.ResultsOne month and three months after surgery,there were significant differences in terms of pain VAS scores,ADL scores,WOMAC scores,HHS scores,ASES scores,patient satisfaction and nurse satisfaction between the two groups(P<0.05).ConclusionsThe extension service of "health manager + PGR system" could improve patients' compliance behavior outside hospital,accelerate rapid rehabilitation process,recover joint function early,and improve their quality of life.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".