Szükséges-e a subarachnoidealis vérzésen átesett betegek pszichológiai követése?
Bibliographic record
Abstract
Introduction: After aneurysmal subarachnoid haemorrhage (SAH), even apparently fully recovered patients often report serious psychological problems (anxiety, depression, mood swings, loss of concentration, memory impairment). Objective: Our aim is to assess, in a pilot study, the effectiveness of available and commonly used psychological tests in assessing the condition of patients after SAH and to start the development of a post-SAH psychological care system. Methods: From May 2023 to January 2024, a total of 52 patients with aneurysmal subarachnoid haemorrhage who had a good outcome, i.e., were asymptomatic or mildly symptomatic but still self-sufficient (modified Rankin scale <2), were included in our study. In addition to general patient data (age, sex, education), we recorded the treatment modality and excluded patients with significant deterioration as a complication of aneurysm treatment. According to the main aim of our study, we used the following psychological tests: Montreal Cognitive Assessment (MoCa), Spielberger State/Trait Anxiety Questionnaire (STAI-S/T), Beck Depression Questionnaire (short version; BDI-R). Results: According to the above criteria, a total of 38 women and 14 men with a mean age of 53 years (SD = 7.14) were included in our study. Psychological examination revealed cognitive impairment in 1/3 of the patients, 74% with some degree of depression, 10% with high levels of depression, and 42% with above average anxiety. There is a correlation between the level of anxiety, the severity of depression and the likelihood of developing cognitive impairment. Discussion and conclusion: Our results so far suggest that even in somatically almost asymptomatic patients, moderate to severe psychological problems occur regularly after SAH, which requires psychological care. Our study has shown that the psychological tests available in Hungarian are not suitable for accurate mapping the condition of patients with SAH and then tracking changes due to the learning effect. Furthermore, it became clear that the modified Rankin scale used to classify the outcome of the disease is not sufficient information on the psychological state of the patients, as it does not differentiate well in terms of symptoms, and therefore a new, complementary SAH-specific test needs to be applied, adopted and localised, which our institution has started to do. Orv Hetil. 2024; 165(44): 1753–1759.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".