Correlation analysis between preoperative cognitive function and negative emotion in patients with laryngocarcinoma
Bibliographic record
Abstract
Objective To explore the correlation between preoperative cognitive function and anxiety and depression in patients with laryngocarcinoma. Methods Totally 42 patients with laryngocarcinoma who were hospitalized in the Department of Otorhinolaryngology Head and Neck Surgery of 2 ClassⅢ Grade A Hospitals in Shanxi Province from September 2017 to September 2018 were selected into the observation group by convenient sampling, while 40 healthy volunteers were included in the control group. They were investigated with Self-Rating Anxiety Scale (SAS) , Self-Rating Depression Scale (SDS) and Montreal Cognitive Assessment (MOCA) . Results The preoperative SAS and SDS scores of the observation group were (41.48±5.46) and (43.69±6.16) respectively, both higher than those of the control group (t=4.189, 6.234; P<0.01) ; the preoperative MOCA score of the observation group was (22.90±4.13) , lower than that of the control group (t=2.646, P<0.01) . Correlation analysis showed that the laryngocarcinoma patients' anxiety and depression were negatively correlated with their cognitive function (r=-0.750, -0.660; P<0.01) . Conclusions Compared with the healthy volunteers, the laryngocarcinoma patients are more susceptible to anxiety, depression and cognitive disorder. The severer their anxiety and depression, the poorer their overall cognitive function was. Key words: Laryngeal neoplasms; Anxiety; Depression; Cognitive function
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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".