Asthma and asthma-like disorder, a 5-year follow-up study

Diagnosis of asthma in primary health care: a pilot study

Some patients with an asthma diagnosis have a poor controlled asthma. One explanation may be an incorrect diagnosis. Aim. The aim of the study was to diagnose and classify patients with non-infectious lower respiratory tract problems in primary health care using internationally applied diagnostic criteria and diagnostic tests. Patients and Methods. New adult patients visiting a primary health care centre due to lower airway problems were included. The diagnostic tests included FEV₁, FVC, PEF, two questionnaires, methacholine test, and skin prick test. Results. The patients (n = 43) could be divided into four groups: asthma (28%), asthma-like disorder (44%), idiopathic cough (12%), and a nonreversible bronchial obstructive group (16%). The asthma and asthma-like groups showed similar patterns of airway symptoms and trigger factors, not significantly separated by a special questionnaire. Phlegm, heavy breathing, chest pressure/pain, cough, and wheezing were the most common symptoms. Physical exercise and scents were the dominating trigger factors. Conclusions. Nonobstructive asthma-like symptoms seem to be as common as bronchial asthma in primary health care. Due to the similarities in symptoms and trigger factors the study supports the hypothesis that asthma and nonobstructive asthma-like disorders are integrated in the same “asthma syndrome,” including different mechanisms, not only bronchial obstruction.

A scoring algorithm for predicting the presence of adult asthma: a prospective derivation study

Background:

To predict the presence of asthma in adult patients with respiratory symptoms, we developed a scoring algorithm using clinical parameters.

Methods:

We prospectively analysed 566 adult outpatients who visited Kinki University Hospital for the first time with complaints of nonspecific respiratory symptoms. Asthma was comprehensively diagnosed by specialists using symptoms, signs, and objective tools including bronchodilator reversibility and/or the assessment of bronchial hyperresponsiveness (BHR). Multiple logistic regression analysis was performed to categorise patients and determine the accuracy of diagnosing asthma.

Results:

A scoring algorithm using the symptom-sign score was developed, based on diurnal variation of symptoms (1 point), recurrent episodes (2 points), medical history of allergic diseases (1 point), and wheeze sound (2 points). A score of ≥3 had 35% sensitivity and 97% specificity for discriminating between patients with and without asthma and assigned a high probability of having asthma (accuracy 90%). A score of 1 or 2 points assigned intermediate probability (accuracy 68%). After providing additional data of forced expiratory volume in 1 second/forced vital capacity (FEV₁/FVC) ratio <0.7, the post-test probability of having asthma was increased to 93%. A score of 0 points assigned low probability (accuracy 31%). After providing additional data of positive reversibility, the post-test probability of having asthma was increased to 88%.

Conclusions:

This pragmatic diagnostic algorithm is useful for predicting the presence of adult asthma and for determining the appropriate time for consultation with a pulmonologist.