دورية أكاديمية
أعرض في EDS

Risk factor analysis and nomogram for predicting poor symptom control in smoking asthmatics.

التفاصيل البيبلوغرافية
العنوان: Risk factor analysis and nomogram for predicting poor symptom control in smoking asthmatics.
المؤلفون: Ma J; Department of Respiratory and Critical Care Medicine, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, 450003, People's Republic of China.; Department of Respiratory and Critical Care Medicine, Luoyang Central Hospital Affiliated to Zhengzhou University, Luoyang, Henan Province, 471009, People's Republic of China., Chen Z; Department of Respiratory and Critical Care Medicine, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, 450003, People's Republic of China., Wu K; Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, 550004, People's Republic of China., Lei J; Department of Respiratory and Critical Care Medicine, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, 450003, People's Republic of China., Zhao L; Department of Respiratory and Critical Care Medicine, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, Henan Province, 450003, People's Republic of China. zhaolimin2002@126.com.
المصدر: BMC pulmonary medicine [BMC Pulm Med] 2024 Jun 01; Vol. 24 (1), pp. 264. Date of Electronic Publication: 2024 Jun 01.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: BioMed Central Country of Publication: England NLM ID: 100968563 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2466 (Electronic) Linking ISSN: 14712466 NLM ISO Abbreviation: BMC Pulm Med Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : BioMed Central, [2001]-
مواضيع طبية MeSH: Asthma*/drug therapy , Asthma*/physiopathology , Nomograms* , Smoking*/epidemiology , Smoking*/adverse effects, Humans ; Male ; Female ; Risk Factors ; Adult ; Middle Aged ; ROC Curve ; Logistic Models ; China/epidemiology ; Surveys and Questionnaires ; Prognosis ; Reproducibility of Results
مستخلص: Background: Smoking induces and modifies the airway immune response, accelerating the decline of asthmatics' lung function and severely affecting asthma symptoms' control level. To assess the prognosis of asthmatics who smoke and to provide reasonable recommendations for treatment, we constructed a nomogram prediction model.
Methods: General and clinical data were collected from April to September 2021 from smoking asthmatics aged ≥14 years attending the People's Hospital of Zhengzhou University. Patients were followed up regularly by telephone or outpatient visits, and their medication and follow-up visits were recorded during the 6-months follow-up visit, as well as their asthma control levels after 6 months (asthma control questionnaire-5, ACQ-5). The study employed R4.2.2 software to conduct univariate and multivariate logistic regression analyses to identify independent risk factors for 'poorly controlled asthma' (ACQ>0.75) as the outcome variable. Subsequently, a nomogram prediction model was constructed. Internal validation was used to test the reproducibility of the model. The model efficacy was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve.
Results: Invitations were sent to 231 asthmatics who smoked. A total of 202 participants responded, resulting in a final total of 190 participants included in the model development. The nomogram established five independent risk factors (P<0.05): FEV1%pred, smoking index (100), comorbidities situations, medication regimen, and good or poor medication adherence. The area under curve (AUC) of the modeling set was 0.824(95%CI 0.765-0.884), suggesting that the nomogram has a high ability to distinguish poor asthma control in smoking asthmatics after 6 months. The calibration curve showed a C-index of 0.824 for the modeling set and a C-index of 0.792 for the self-validation set formed by 1000 bootstrap sampling, which means that the prediction probability of the model was consistent with reality. Decision curve analysis (DCA) of the nomogram revealed that the net benefit was higher when the risk threshold probability for poor asthma control was 4.5 - 93.9%.
Conclusions: FEV1%pred, smoking index (100), comorbidities situations, medication regimen, and medication adherence were identified as independent risk factors for poor asthma control after 6 months in smoking asthmatics. The nomogram established based on these findings can effectively predict relevant risk and provide clinicians with a reference to identify the poorly controlled population with smoking asthma as early as possible, and to select a better therapeutic regimen. Meanwhile, it can effectively improve the medication adherence and the degree of attention to complications in smoking asthma patients.
(© 2024. The Author(s).)
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معلومات مُعتمدة: No. U2004120 National Natural Science Foundation of China; No. U2004120 National Natural Science Foundation of China; No. U2004120 National Natural Science Foundation of China; No. U2004120 National Natural Science Foundation of China; No. U2004120 National Natural Science Foundation of China; No. 222103810053 Joint Fund Project of Science and Technology Research and Development Program of Henan Province; No. 222103810053 Joint Fund Project of Science and Technology Research and Development Program of Henan Province; No. 222103810053 Joint Fund Project of Science and Technology Research and Development Program of Henan Province; No. 222103810053 Joint Fund Project of Science and Technology Research and Development Program of Henan Province; No. 222103810053 Joint Fund Project of Science and Technology Research and Development Program of Henan Province
فهرسة مساهمة: Keywords: Asthma; Control level; Nomogram; Prognosis; Smoking
تواريخ الأحداث: Date Created: 20240602 Date Completed: 20240602 Latest Revision: 20240604
رمز التحديث: 20240604
مُعرف محوري في PubMed: PMC11144325
DOI: 10.1186/s12890-024-03076-9
PMID: 38824531
قاعدة البيانات: MEDLINE
الوصف
تدمد:1471-2466
DOI:10.1186/s12890-024-03076-9