RESUMO
BACKGROUND: In general practice (GP), the diagnosis of obstructive airway diseases much relies on diagnostic questions, in view of the limited availability of lung function. We systematically assessed the relative importance of such questions for diagnosing asthma and chronic obstructive pulmonary disease (COPD), either without or with information from spirometry. METHODS: We used data obtained in a pulmonary practice to ensure the validity of diagnoses and assessments. Subjects with a diagnosis of COPD (n=260), or asthma (n=433), or other respiratory diseases (n=230), and subjects without respiratory diseases (n=364, controls) were included. The diagnostic questions comprised eight items, covering smoking history, self-attributed allergic rhinitis, dyspnea, cough, phlegm and wheeze. Optionally standard parameters of the flow-volume-curve were included. Decision trees for the diagnosis of COPD and asthma were constructed, moreover a probabilistic diagnostic network based on the results of path analyses describing the relationship between variables. RESULTS: In the decision trees, age, sex, current smoking, wheezing, dyspnea upon mild exertion, self-attributed allergic rhinitis, phlegm, forced expiratory volume in one second (FEV1), and expiratory flow rates were relevant, depending on the diagnostic comparison, while cough, dyspnea upon strong exertion and ex-smoker status were not relevant. In contrast, the probabilistic network for the diagnosis of COPD and asthma versus controls incorporated all diagnostic questions, i.e., dyspnea upon mild or strong exertion, current smoking, ex-smoking, wheezing, cough and phlegm but from spirometry only FEV1. Depending on the individual pattern, the probability for COPD could raise from 25% to 81%, while the diagnostic gain for asthma was lower. CONCLUSIONS: The study developed simple diagnostic algorithms for asthma and COPD that take into account the relative importance of clinical signs and history, as well as spirometric data if available. The diagnostic accuracy was especially high for COPD. These algorithms may be helpful as a starting point in the standardisation of diagnostic strategies in GP practices. TRIAL REGISTRATION: The study is registered under DRKS00013935 at German Clinical Trials Register (DRKS, Date of registration 01/03/2018).
RESUMO
BACKGROUND: One of the known weaknesses of spirometry is its dependence on patients' cooperation, which can only partially be alleviated by educational efforts. Therefore, procedures less dependent on cooperation might be of value in clinical practice. We investigated the diagnostic accuracy of ultrasound-based capnovolumetry for the identification of airway obstruction. METHODS: Consecutive patients from a pulmonary outpatient clinic were included in the diagnostic study. As reference standard, the presence of airway obstruction was evaluated via spirometry and bodyplethysmography. Capnovolumetry was performed as index test with an ultrasound spirometer providing a surrogate measure of exhaled carbon dioxide. Receiver operating characteristic (ROC) analysis was performed using the ratio of slopes of expiratory phases 3 and 2 (s3/s2) ≥ 0.10 as primary capnovolumetric parameter for the recognition of airway obstruction. Logistic regression was performed as secondary analysis to identify further useful capnovolumetric parameters. The diagnostic potential of capnovolumetry to identify more severe degrees of airway obstruction was evaluated additionally. RESULTS: Of 1400 patients recruited, 1287 patients were included into the analysis. Airway obstruction was present in 29% of patients. The area under the ROC-curve (AUC) of s3/s2 was 0.678 (95% CI 0.645, 0.710); sensitivity of s3/s2 ≥ 0.10 was 47.7 (95% CI 42.7, 52.8)%, specificity 79.0 (95% CI 76.3, 81.6)%. When combining this parameter with three other parameters derived from regression analysis (ratio area/volume phase 3, slope phase 3, volume phase 2), an AUC of 0.772 (95% CI 0.743, 0.801) was obtained. For severe airway obstruction (FEV1 ≤ 50% predicted) sensitivity of s3/s2 ≥ 0.10 was 75.9 (95% CI 67.1, 83.0)%, specificity 75.8 (95% CI 73.3, 78.1)%; for very severe airway obstruction (FEV1 ≤ 30% predicted) sensitivity was 86.7 (95% CI 70.3, 94.7)%, specificity 72.8 (95% CI 70.3, 75.2)%. Sensitivities increased and specificities decreased considerably when the combined capnovolumetric score was used as index test. CONCLUSIONS: Capnovolumetry by way of an ultrasound spirometer had a statistically significant albeit moderate potential for the recognition of airway obstruction in a heterogeneous population of patients typically found in clinical practice. Diagnostic accuracy of the capnovolumetric device increased with the severity of airway obstruction. TRIAL REGISTRATION: The study is registered under DRKS00013935 at German Clinical Trials Register (DRKS).
