Alexithymia: a relevant psychological variable in near-fatal asthma
Bibliographic record
Abstract
Alexithymia is a psychological trait characterised by difficulty in perceiving and expressing emotions and body sensations. Failure to perceive dyspnoea could lead alexithymic asthmatics to underestimate the severity of an asthma exacerbation, and thereby increase the risk of developing a fatal or near-fatal asthma (NFA) attack. The objective of the present study was to determine the prevalence of alexithymia in NFA patients and to analyse their clinical characteristics. Alexithymia was assessed using the Toronto Alexithymia Scale in this multicentric prospective observational study. From 33 Spanish hospitals, 179 NFA patients and 40 non-NFA patients, as a control group, were enrolled. There was a higher proportion of alexithymia in the NFA group than in the non-NFA group (36 versus 13%). Patients with NFA and alexithymia were older than the rest of the NFA group, and had a lower level of education, a higher level of psychiatric morbidity, a higher proportion of severe persistent asthma and a greater number of prior very severe asthma exacerbations (49 versus 27%). Alexithymia, severe persistent asthma and a low level of education were identified as independent variables related to repeated very severe asthma exacerbations. The results show that alexithymia is more frequent in near-fatal asthma patients compared to the rest of asthmatics and is associated with recurrent very severe asthma exacerbations.
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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 | 0.001 | 0.001 |
| 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".