Preoperative Depressive Mood of Patients With Esophageal Cancer Might Delay Recovery From Operation-Related Malnutrition
Bibliographic record
Abstract
BACKGROUND: We investigated the relationship between the preoperative psychological state and the perioperative nutritional conditions of patients with esophageal cancer. METHODS: Seventy-three participants underwent operations for esophageal cancer in our hospital. Depressive state was evaluated using the Self-Rating Depression Scale (SDS). General quality of life (QOL) was assessed using the SF-8™, and the nutritional assessments were evaluated through anthropometric analysis, bioelectrical impedance analysis (BIA) and some biochemical assessments. RESULTS: In the preoperative stage, patients with higher SDS scores, representing a more depressive state, had low arm circumference, grip strength, serum albumin levels and prognostic nutritional index. Patients with higher SDS scores also had a tendency for a lower physical component summary, representing physical QOL by the Eight-Item Short Form Health Survey (SF-8™). At 3 months after surgery, patients with higher preoperative SDS scores had significantly lower body mass indexes (BMIs) and had a lower tendency of body fat masses. In the univariate and multivariate analyses on the recovery of BMI at 3 months after surgery, preoperative SDS score was the only independent risk factor (odd ratio (OR): 4.07, 95% confidence interval (CI): 1.15 - 14.35) in this study. CONCLUSION: Preoperative depressive mood, as evaluated by the SDS, was the sole relevant factor for postoperative body weight recovery of patients with esophageal cancer. Preoperative depressive mood of patients with esophageal cancer might delay recovery from operation-related malnutrition. Some measures against preoperative depressive mood might be necessary for early recovery from postoperative malnutrition in patients with esophageal cancer.
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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".