The Influence of Alexithymia on Persistent Symptoms of Dyspepsia after Laparoscopic Cholecystectomy
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate whether preoperative alexithymia might play a role in the persistence of gastrointestinal symptoms after laparoscopic cholecystectomy. METHODS: A sample of 52 consecutive patients with gallstone disease and symptoms of dyspepsia were assessed with validated scales for alexithymia (20-item Toronto Alexithymia Scale), and psychological (90-item Symptom Checklist) and gastrointestinal (GI) (Gastrointestinal Symptom Rating Scale) symptoms before surgery. GI symptoms were evaluated also one year after surgery. Change from preoperative to postoperative GI symptoms and level of GI symptoms after surgery were used to form groups of improved (n = 31) and unimproved (n = 21) patients. RESULTS: Unimproved patients had significantly higher preoperative alexithymia, psychological distress, and gastrointestinal symptom scores than patients who had improved. Regression analyses showed that alexithymia predicted the persistence of gastrointestinal symptoms more strongly than did psychological distress, even after controlling for preoperative gastrointestinal symptoms. CONCLUSION: Alexithymia played a substantial and predictive role in the persistence of GI symptoms in gallstone patients after surgery. Treatment planning and outcome of gallstone disease might be improved by preoperative assessment of alexithymia.
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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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".