Effect of Risk-Graded Care Based on Caprini Risk Assessment Model on Postoperative Venous Thrombosis and Health-Related Quality of Life in Elderly Patients with Malignancy
Bibliographic record
Abstract
Objective: To investigate the effect of risk-graded care based on Caprini risk assessment model on postoperative deep vein thrombosis and quality of life in elderly patients with malignant tumors. Methods: Sixty-eight elderly patients with malignant tumors treated by surgery admitted to the Department of Geriatrics of the First Affiliated Hospital of Sun Yat-sen University from April 2021 to September 2021 were selected to be included in the control group and given routine nursing interventions in the geriatrics department, using the Autar deep vein thrombosis risk scale and cluster nursing interventions; Seventy cases of elderly patients with malignant tumors treated by surgery admitted to our geriatric department from October 2021 to 2022 were included in the observation group, and the risk-grading nursing intervention based on the Caprini risk assessment model was used in the observation group on the basis of conventional nursing interventions. The number of cases of deep vein thrombosis, D-II cluster values, average hospitalization days, nursing satisfaction, and quality of life levels were compared between the two groups. Results: The number of VTE cases and the incidence of VTE in the observation group was 0.43%(3/70) lower than that in the control group (0.89%(6/68)); the average hospital stay in the observation group (13.50+7.45) was lower than that in the control group (15.16+10.60) and the D-II aggregation value in the observation group (2.90+4.32) was lower than that in the control group (4.02+3.91); with statistically significant differences (P<0.05); the satisfaction scores of communication, safety, guidance, nursing, and nursing techniques in the observation group were (41.70+4.21), (48.53+5.12), (38.47+1.90), (56.77+3.33), (47.80+1.68) points, higher than those in the control group (30.11+8.57), (41.69+7.95), (31.75+6.95), (46.87+7.31), (36.0+9.0) points, with statistically significant differences (t-values of -10.634 to -2.404, all P<0.05); the post-intervention scores of general health, physical function, physical function, somatic pain, somatic energy, social function, emotional function, mental health, and spiritual change dimensions of quality of life in the observation group were (67.00+14.95), (65.71+25.24), (63.21+21.59), (83.63+10.65), (74.43+13.45), (70.71+20.95), (67.62+26.60), (62.60+15.12) and (76.79+20.11) and scores were higher than the control group's post-intervention scores of (57.50+19.65), (40.44+27.33), (43.01+25.86), (54.57+15.42), (42.65+20.08), (56.25+26.67), (41.18+28.87), (52.35+18.86), (66.91+23.83) scores than the control group after intervention, with statistically significant differences (t-values of -26.878 to 0.989. all P<0.05). Conclusions: Risk-graded nursing intervention based on the Caprini risk assessment model can effectively reduce the incidence of postoperative VTE in elderly patients with malignancy, improve nursing satisfaction, and enhance the quality of life of patients.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".