Bibliographic record
Abstract
背景與目的：膝關節是人體全身受力最重的關節，會因過度負重，產生退化病變。當發生退化性關節炎時，會造成關節僵硬、疼痛及變形，使病人在行走及日常生活功能。全膝關節置換術，為關鍵性的治療處置，可增加病人活動功能，提升自我照顧能力，進而改善生活品質。為提升全膝關節置換術療效，物理治療為病人術後重要的醫療照護。根據美國骨科醫學會（American Academy of Orthopaedic Surgeons）臨床照護指引，提供標準化、完整性且一致性的復健計畫。然而全膝關節置換術後，常因為術後疼痛，導致病人對於術後的意願度不高，因此無法及早接受物理治療。方法：2019年1月至11月，共124位接受全膝關節置換術病人，接受南部某準醫學中心醫院之全膝關節術後國際臨床照護計畫。為提升病人手術後的療效，鼓勵病人及早於術後進行物理治療，藉由PDCA手法，改善病人疼痛，成功提升病人於手術當日接受物理治療的意願度。病人在手術前及手術後滿三個月，接受中文版退化性膝關節炎量表Western Ontario and McMaster Universities Osteoarthritis Index（WOMAC），檢測因膝關節造成的疼痛、僵硬及身體功能。病人出院時，提供不記名滿意度問卷調查，滿意度內容包括團隊各職類，包括醫師、護理師、物理治療師、藥師、營養師、心理師、社工師、麻醉師及整體表現。結果：2019年1月至11月，病人於手術當日接受物理治療率達100%；WOMAC由術前平均值為56.04，術後3個月的平均值8.52，遠低於團隊指標預設閾值分數12。結論：藉由參與國際臨床照護計畫，提升物理治療效能與安全，建構優質全膝關節置換術後之安全醫療照護環境，確實增加病人手術當日即接受物理治療的意願度；而且全方位跨領域的照護，以病人為中心，照顧病人的需求，進而提升病人的功能性活動，獲得病人很高的滿意度。臨床意義：實證指出，術後及早復健，能有效提升全膝關節置換術後的療效，藉由有效的疼痛控制及治療前後的疼痛評估，標準化、完整性且一致性的復健計畫，建構出優質安全的醫療照護環境，讓病人在術後接受物理治療過程中，感受到安全，並提升療效。
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.018 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".