ANALYSIS OF TUBERCULIN SKIN TEST IN ADULT ASTHMATIC PATIENTS USING STEROIDS AS PART OF THEIR MANAGEMENT
Bibliographic record
Abstract
BACKGROUND: Tuberculosis infection being one of the major risk factor for morbidity and mortality in developing countries according to WHO and CDC. The risk of developing TB increases significantly with the drop of immunity.Using steroid (prednisolone or its equivalent) at a dose of more than 15 mg/day more than 4 weeks is associated with significant drop in immunity, hence increasing the risks of being infected with TB to eight folds AIM OF THE STUDY: To assess the risk of developing TB infection in asthmatic patients that use steroid in their asthma treatment regime.MATERIALS & METHODS: A prospective study designed to include patients complaining from Asthma who have visited Baghdad teaching hospital in the period from (June 2016 to June 2017) that included in-patients and out-patients.A questionnaire prepared to document the related information of most concern to the researcher and for the sake of study. RESULTS: In this study, we managed to enroll 60 patients. Male to female ratio was 7:23. 80% of the study cohort lived in urban residence and 20 % in suburban neighborhood. 33.3% of the patients had diabetes as comorbidity. 21.7 % of the patients used inhaled steroid as a modality of management of asthma, while 45% used systemic steroids, and 33.3 % used combined modality. Of the study cohort, 18.3 % used steroid for no more than 4 weeks, and the rest used it for more than 4 weeks. Regarding tuberculin test results, 11.7 % test positive.A significant correlations were found between the tuberculin test and the increasing age of the patient p=0.01, and the duration of use of steroids p=0.001, also, between TST and previous history of TB p=0.04.CONCLUSION: There is no relationship between the type of steroid and the risk of getting TB infection.The risk of steroid on immune system and the raise of risk increase with increasing subject age. The extended period of exposure to steroid will definitely increase the risk of TB infection.
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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 | 0.001 | 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".