Prevention and control of venous thromboembolism after major orthopedic surgery through doctor-to-patient cultivation of musculoskeletal ability based on King’s theory of goal attainment
Bibliographic record
Abstract
OBJECTIVES: To explore the prevention and management of venous thromboembolism (VTE) following major orthopaedic surgery (MOS) by fostering doctor-to-patient cultivation of musculoskeletal ability, guided by King's theory of goal attainment. METHODS: A cohort of patients (n = 116) undergoing MOS was selected for the study, and were divided into two groups: the regular group and the observation group, with patients in the regular group experiencing routine nursing care and management and those in the observation group undergoing musculoskeletal ability cultivation based on King's theory of goal attainment. Baseline data, limb vascular ultrasonography, coagulation function, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, VTE prevention efficacy, Exercise of Self-care Ability Scale (ESCA) score, and nursing satisfaction were analysed comparatively. RESULTS: There was no significant within-group difference in baseline data (P > 0.05). Following the interventions, the observation group demonstrated statistically significant reductions in the Musculoskeletal-Integrated Imaging Score, various dimensions of WOMAC scores, and D-dimer (D-D) levels (P < 0.05) both in comparison to their levels before interventions and to those observed in the regular group (P < 0.05). Additionally, the observation group exhibited increases in prothrombin time levels and various dimensions of ESCA scores (P < 0.05) post-intervention, surpassing the pre-intervention levels and those obtained in the regular group (P < 0.05). Furthermore, the observation group exhibited a significantly lower incidence of VTE (P < 0.05) and higher nursing satisfaction (P < 0.05) compared to the regular group. CONCLUSIONS: Nursing intervention measures, utilizing doctor-to-patient cultivation of musculoskeletal ability based on King's theory of goal attainment, have demonstrated a significant clinical benefit for VTE prevention and control in post-MOS patients. This approach not only effectively prevented VTE in post MOS patients but also enhanced their satisfaction towards nursing care.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".