Risk factors for anxiety and depression in Chinese patients undergoing surgery for endometrial cancer
Bibliographic record
Abstract
This study analyzed risk factors for anxiety and depression in 714 patients who received surgery for endometrial cancer. Our data indicate that the incidence of postoperative anxiety and depression in 714 patients with endometrial cancer was 15.55% and 32.77%, respectively. Univariate and logistic regression analysis showed postoperative pain (odds ratio (OR) = 3.166, P = 0.000) and combined liver disease (OR = 2.318, P = 0.001) were independent risk factors for postoperative anxiety. Additionally, CD4+/CD8+ (OR = 0.513, P = 0.042) and natural killer (NK) cell ratios (OR = 0.692, P = 0.021) were independent protective factors for postoperative anxiety. As for depression, low literacy (OR = 1.943, P = 0.042), postoperative pain (OR = 2.671, P = 0.001), high clinical stage (OR = 3.469, P = 0.009), and combined liver disease (OR = 4.865, P = 0.000) were independent risk factors for postoperative depression. CD4+/CD8+ (OR = 0.628, P = 0.002) and NK cell ratio (OR = 0.710, P = 0.013) were independent protective factors for postoperative depression. In conclusion, patients with endometrial cancer have a higher incidence of postoperative anxiety and depression where postoperative pain, liver disease, and decreased immune function are risk factors for both anxiety and depression in these 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 | 0.000 | 0.001 |
| 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".