Alexithymia in primary ciliary dyskinesia
Bibliographic record
Abstract
Introduction: Current evidence indicates that alexithymic deficits in processing emotions may also affect physical health and that alexithymia may be associated with organic, especially chronic, disorders. Primary ciliary dyskinesia (PCD) is a rare, inherited, autosomal recessive disorder. Uncertainty about the prognosis and evolution of the disease, lack of ongoing medical care, and symptom control often negatively impact the emotional well-being of these patients. We aimed to evaluate the frequency of alexithymia in children with PCD and the possible effects of alexithymia on PCD treatment. Methods: Patients between 5 and 18 who were followed up for PCD in pediatric pulmonology were included in the study. Patients who did not want to attend the study were also excluded from the study. The patients filled out a questionnaire including the sociodemographic characteristics and the Toronto Alexithymia Scale. Results: This is an ongoing study and the data expressed here is a preliminary report. A total of 30 patients (18 girls and 12 boys) were included. The total score was 50.52±11.48. The “difficulty in recognizing emotions” sub-score of the scale was 15.56±6.38, the “difficulty in expressing emotions” sub-score of 12.73±4.54, and the “expressive thinking” sub-score of 22.21±3.45. The total score of 4 children was above 60 points and above 50 points in 9 children. Discussion: This preliminary report has found that about 30% of patients with PCD have alexithymic deficits. This high percentage was previously reported among cancer patients, post-myocardial infarcts, and skin diseases. Conclusion: Identifying and addressing alexithymia in PCD patients may improve treatment outcomes, associated comorbidities, and health-related quality of life.
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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) | 0.003 | 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".