Abstract
Aim:
Diagnosis of COPD in primary care is hindered by underuse of spirometry. Case finding using validated symptom and health status questionnaires, and simple handheld devices in high-risk populations may improve diagnosis. This study aimed to determine the best combination of measures to optimise COPD diagnosis in the primary care setting.
Methods:
We recruited 335 current or ex-smokers, including those with an established diagnosis of COPD from general practices. Participants’ FEV1 and FEV6 were measured using a handheld spirometry device (COPD-6®). Each completed the COPD assessment test (CAT), a modified Medical Research Council (mMRC) dyspnoea scale, St George’s Respiratory Questionnaire (SGRQ) and smoking history questionnaire. From these data we calculated the predictive validity for spirometry-confirmed diagnosis of COPD. Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated for each. Kappa coefficient was used to measure the agreement between the Fixed-Ratio (FR) and Lower Limit of Normal (LLN) spirometric criteria in diagnosing COPD.
Results:
FEV1/FEV6 <0.70 alone showed significant association (p<0.0001) with COPD diagnosis and good predictive accuracy (AUROC=0.725). However, no further improvement was found after combining SGRQ, CAT and mMRC with FEV1/FEV6. FEV1 /FEV6 <0.70 using the COPD-6® handheld device had moderate sensitivity (65.7%) and high PPV (90.1%), high specificity (79.3%) and NPV (44.8%). There was good agreement between FR and LLN definitions (κ=0.70).
Conclusion:
Handheld micro-spirometers can facilitate case finding of COPD in smokers and ex-smokers attending general practice. The fixed ratio criterion currently recommended by COPD-X guidelines offers the simplest method for diagnosing COPD in Australian primary care.
Diagnosis of COPD in primary care is hindered by underuse of spirometry. Case finding using validated symptom and health status questionnaires, and simple handheld devices in high-risk populations may improve diagnosis. This study aimed to determine the best combination of measures to optimise COPD diagnosis in the primary care setting.
Methods:
We recruited 335 current or ex-smokers, including those with an established diagnosis of COPD from general practices. Participants’ FEV1 and FEV6 were measured using a handheld spirometry device (COPD-6®). Each completed the COPD assessment test (CAT), a modified Medical Research Council (mMRC) dyspnoea scale, St George’s Respiratory Questionnaire (SGRQ) and smoking history questionnaire. From these data we calculated the predictive validity for spirometry-confirmed diagnosis of COPD. Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated for each. Kappa coefficient was used to measure the agreement between the Fixed-Ratio (FR) and Lower Limit of Normal (LLN) spirometric criteria in diagnosing COPD.
Results:
FEV1/FEV6 <0.70 alone showed significant association (p<0.0001) with COPD diagnosis and good predictive accuracy (AUROC=0.725). However, no further improvement was found after combining SGRQ, CAT and mMRC with FEV1/FEV6. FEV1 /FEV6 <0.70 using the COPD-6® handheld device had moderate sensitivity (65.7%) and high PPV (90.1%), high specificity (79.3%) and NPV (44.8%). There was good agreement between FR and LLN definitions (κ=0.70).
Conclusion:
Handheld micro-spirometers can facilitate case finding of COPD in smokers and ex-smokers attending general practice. The fixed ratio criterion currently recommended by COPD-X guidelines offers the simplest method for diagnosing COPD in Australian primary care.
| Original language | English |
|---|---|
| Pages (from-to) | 1543-1554 |
| Number of pages | 12 |
| Journal | International Journal of COPD |
| Volume | 18 |
| DOIs | |
| Publication status | Published - 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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