Cognitive Function Status and Clinical Effects in Fibrotic Interstitial Lung Diseases
Bibliographic record
Abstract
Introduction: There is not enough research on the effect of cognitive status on the disease in this patient group. In this study, the effect of cognitive function status and clinical parameters in cases diagnosed with interstitial lung disease was investigated. Method: Demographic data, functional evaluations and radiological findings of the cases were obtained from the hospital registry system. For the evaluation of cognitive function, it was evaluated with the Montreal Cognitive Assessment Test(MoCA). Additionally, the Hospital Anxiety Depression(HAD) test and the Short Form-36(SF-36) test were applied for quality of life assessment. Results: The mean age of 62 cases diagnosed with ILD included in the study was 63.4±10.1 (42-84) years, and 41(66.1%) were women. The cut-off score of the MoCA test for cognitive dysfunction is 21, and the mean of our cases was determined as 18.4±5.8(range 4-30). In the sub-analyses, it was determined that cognitive dysfunction were worse at older ages, and anxiety assessed by HAD was observed more in the group with impaired cognitive function. No difference was detected in comorbidities, FVC %predicted, DLCO%, 6-MWT, GAP score and quality of life tests evaluated with SF-36 between cognitive impairement and normal cognitive function groups. Discussion: In this study, which is one of the few studies investigating cognitive dysfunction in ILD cases, it was determined that cognitive function was impaired and anxiety was more common in older patients when evaluated with MGD. Cognitive dysfunction should be taken into consideration and further research should be planned as it may impair the compliance of the patients with their follow-up and treatment.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".