Quality of Life in Children with Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
Background: The depressive syndrome is commonly found in children suffering from chronic diseases, which is also present in patients with juvenile idiopathic arthritis (JIA).Objective: This study proposed to analyze depression's incidence in children with JIA.We also monitored the evolution of depression with the improvement of the disease under treatment. Materials and methods:We followed 145 patients suffering from JIA according to ILAR and Edmonton classification in 2001.The study was conducted over three years between 2015 and 2017.The assessment of depression was made using the Hamilton scale adapted for children by us.This scale consists of 11 fields with multiple questions, the evaluation was made by counting the score.The scale assesses overall depression intensity.It has a maximum score of 28 points, and one with eight points defines depression.Results: The results obtained using the Hamilton scale showed that, from the total of 145 patients suffering from JIA, 35 (24%) experienced mild depression, 10 (7%) moderate depression and 26 were borderline; 74 children did not experience the depressive syndrome.In the control group, depression was found in only 5% of subjects.After administering the most appropriate treatment, symptoms of depression have been improved and the depression score has decreased.Conclusions: The Hamilton questionnaire adapted for children is easy to apply and it is an important tool for assessing depression.Depression has been present in one-third of patients with JIA selected for this study.The symptoms of depression have been correlated with disease activity.Depression does not influence the disease, but the disease induces depression.
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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 | 0.001 |
| 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".