Abstract
Objectives: To evaluate the influence of the practice setting on diagnostic accuracy of fractional exhaled nitric oxide (FENO) for diagnosing asthma;and to develop prediction rules for diagnostic decision-making including clinical signs and symptoms (CSS). Setting: Patients from 10 general practices and 1 private practice of 5 pneumologists in ambulatory care. Participants: 553 patients, 57.9% female. Consecutive inclusion of diagnostic-naive patients suspected of suffering from obstructive airway disease. Exclusion criteria were respiratory tract infections within the last 6 weeks. Interventions: The index test was FENO measurement. Reference standard was the Tiffeneau ratio (forced expiratory volume in 1 s/vital capacity) or airway resistance as assessed by whole body plethysmography, with additional bronchoprovocation or bronchodilator testing. Primary and secondary outcome measures: Asthma as determined by pneumologists, who were blind to FENO measurement results. Prediction rules were derived from multiple logistic regression analysis. A freely available calculator that allows computing all combinations was developed. Results: The practice setting only had minor influence on sensitivities of FENO cut-off points. In the final model (n=472), allergic rhinitis, wheezing and previous medication were positively associated with asthma. Increasing age and recurrent respiratory tract infections were negatively associated. The area under the curve (AUC) of FENO (AUC=0.650;95% CI 0.599 to 0.701) increased significantly (p< 0.0001) when combined with CSS (AUC=0.753;95% CI 0.707 to 0.798). Presence of wheezing and allergic rhinitis allowed ruling in asthma with FENO > 30 ppb. Ruling out with FENO < 16 ppb in patients < 43 years was only possible without allergic symptoms when recurrent respiratory tract infections were present. Conclusions: FENO results should be interpreted in the context of CSS to enhance their diagnostic value in primary care. The final diagnostic model appears as a sound algorithm fitting well to the established diagnostic rules related to CSS of asthma. FENO appears more effective for ruling in asthma than for ruling it out.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Institut und Poliklinik für Arbeits-, Sozial- und Umweltmedizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-34506-5 |
ISSN: | 2044-6055 |
Sprache: | Englisch |
Dokumenten ID: | 34506 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Feb. 2017, 16:04 |
Letzte Änderungen: | 17. Jul. 2024, 11:23 |