Asthma Control and Its Predictive Factors in Adult Asthma Patients
Bibliographic record
Abstract
BACKGROUND: Asthma is a highly prevalent condition that remains difficult to control, as its associated factors remain poorly understood. Thus, the primary aim of the present investigation was to determine the prevalence of uncontrolled asthma in hospital units in south Jordan and to evaluate the risk factors that may contribute to uncontrolled asthma. METHODS: This was a cross-sectional study involving 93 patients aged 40.5 ± 13.6 years that met the criteria of the Global Initiative for Asthma (GINA). Relevant patient data were collected via a questionnaire and through a review of medical records. The questionnaire comprised of sections pertaining to sociodemographic and clinical characteristics, as well as pharmacological asthma treatment, asthma severity and asthma control. Asthma severity was determined in line with the GINA guidelines, whereby the patients were classified into four groups (intermittent, mild persistent, moderate persistent or severe persistent). Moreover, based on the findings yielded by the asthma control questionnaire (ACQ), patients were divided into three levels, whereby those diagnosed with partly controlled and uncontrolled asthma were combined into one group, denoted as "poorly controlled asthma", with "uncontrolled asthma" and "controlled asthma" as the remaining two groups. Atopy was defined as one or more positive reactions (A/H ratio > 1) on a skin prick test. RESULTS: Asthma control was achieved in 45.2% of the sample. Moreover, older age, severe asthma according to the GINA guidelines, longer duration of asthma, atopy, being on treatment for asthma and history of allergic rhinitis were identified as the main risk factors contributing to poorly controlled asthma. Multivariate analyses, however, revealed that only atopy to two or more allergens and having severe asthmatic attacks were statistically significantly associated with poorly controlled asthma, for which the odds ratio Mantel-Haenszel (ORMH) of 17.2 and 2.2 was obtained, respectively. CONCLUSION: Our findings indicate that severe asthma and atopy to two or more allergens are the main risk factors for uncontrolled asthma. However, further studies with larger sample sizes are needed to confirm these results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".