Evaluation of primary immunodeficiency awareness of physicians in Türkiye
Bibliographic record
Abstract
Introduction: Despite recent advances in diagnosing and treating primary immunodeficiency (PID), delay in diagnosis is still an important health problem.Aim: To evaluate the awareness of physicians in Türkiye about PID.Material and methods: Internal medicine, infectious diseases, and family physicians were included in the study.The questionnaire included questions about demographic characteristics, PID education, and knowledge.The '10 warning signs of PID' developed by the Jeffrey Modell Foundation (JMF) as warning signs of PID were also scored.The total score was calculated, and an awareness comparison was made between the three physician groups.Results: A total of 320 physicians were included in the study.The mean age of the participants was 32 years (IQR: 25-68 years).Approximately one-third of physicians stated that they had never received any training on PID, and only 20% had followed a patient diagnosed with PID.Recurrent opportunistic infections were the most common symptom of PID (77.8%).Only 6.6% of the physicians were familiar with all the warning signs of PID, and no significant difference was found between the physician groups.Conclusions: In this study, it was revealed that there is a significant lack of awareness about PID among physicians.Delay in PID diagnosis and treatment is one of the most important reasons for the deterioration of patients' quality of life.Increasing the awareness of this disease by increasing physicians' education about PID is an essential step toward early diagnosis 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".