Abstract
Introduction/objectives
Office spirometry is used for the diagnosis of patients with asthma or chronic obstructive pulmonary disease (COPD). The study aimed to determine the outcomes of post-office spirometry of patients in primary care on their clinical diagnosis, medication treatment and referral for pulmonologist evaluation.
Methods
This retrospective study was conducted in Singapore primary care clinics over two years. Demographic, clinical and prescription data were extracted from the institution electronic medical records of Asian patients 3-month before and 6-month post-spirometry. Spirometry outcomes were: Significant Bronchodilator Responsiveness (SBR); Post Bronchodilator Obstruction (PBO); SBR and PBO; and unconfirmed diagnosis.
Results
Spirometry outcomes of 343 patients were analysed. Among 151 (44.0%) with an initial diagnosis of asthma, 19 (12.6%) had SBR, which confirmed the asthma diagnosis, 9.3% had both SBR and PBO. Among 45 (13.1%) with an initial diagnosis of COPD, 10 (22.2%) had PBO which confirmed the COPD diagnosis, and 4.4% of patients had both SBR and PBO. 85 patients (24.8%) were referred to pulmonologist for further evaluation, with the highest referral rate observed in patients with SBR + PBO (33.3%).
Conclusion
Spirometry is essential to affirm diagnosis of patients with COPD in primary care. Majority of patients with an asthma diagnosis did not demonstrate positive SBR, and further evaluations might be required. Spirometry should be scaled to ensure that patients receive the appropriate treatment.
Keywords: Spirometry, Primary care, Asthma, COPD, Bronchodilator Responsiveness (SBR) and Post Bronchodilator Obstruction (PBO)
Introduction
Asthma and chronic obstructive pulmonary disease (COPD) are prevalent chronic respiratory diseases worldwide with significant morbidity and mortality [1, 2]. Such significant health outcomes can potentially be improved with appropriate diagnoses and corresponding pharmacotherapy.
Office spirometry is recommended as part of the workup for the diagnosis of asthma or COPD, based on GINA 2025 [3] and GOLD 2025 [4] documents respectively. Without spirometry, these airway disorders can be under-, over- or misdiagnosed. Population studies indicate that the prevalence of under-diagnosed asthma reaches up to 70% [5], and over-diagnosed asthma hovers between 30 and 35% in the community. Significant discrepancy between preliminary clinical-based and spirometry defined diagnosis was also reported in a study population, of which 10–95% of individuals with COPD were misdiagnosed, and 5–60% of them were incorrectly diagnosed as COPD [6].
The dearth of office spirometry in primary care contributes to inappropriate diagnoses of airway disorders. Office spirometers are not readily available in primary care clinics in certain communities, especially in low- and middle-income countries. Other barriers include lack of expertise and experience among physicians in executing office spirometry, and they also lack training in interpreting spirometry results [7]. In the primary care setting, spirometry is general of low quality, with a Netherlands study reporting only 13% of spirometry performed in primary care met American and European societies’ criteria for spirometry [8]. This gap is aggravated by the belief among physicians that clinical diagnoses are adequate, and that spirometry is unnecessary for diagnosing chronic airway disorders [9].
The paucity of spirometry in primary care has also led to higher healthcare expenditures. An American study in New Mexico revealed that patients with COPD incurred an extra US$2500 each in medical expenses during the one year prior to definitive COPD diagnosis compared to the costs after the diagnosis [10]. The additional cost and disease burden were primarily due to their increased hospitalization rates and associated poorer health outcomes.
Confirmatory diagnosis of chronic airway disorders through office spirometry is postulated to ensure patients receive appropriate medical treatment, improve health outcomes and reduce unnecessary specialist referrals to hospitals. However, in South-east Asia, studies reporting the effects of spirometry in primary care on diagnoses of airway diseases of patients and their medical treatment are sparse.
Hence this retrospective study primarily aimed to assess the clinical diagnoses status of airway disorders before and after office spirometry in patients who were managed in a public primary care institution. The secondary aims were to determine subsequent adjustment in inhaled therapeutics and incidences of pulmonologist referrals of the study population for further management.
Methods
Study design
A retrospective cohort study was conducted on patients who had undertaken office spirometry between April 2018 to February 2020 at selected SingHealth Polyclinics which provided this service, and reviewed by single consultant pulmonologist with a turnaround time of two weeks. The spirometry operator was a trained technician from the pulmonary function lab from the Singapore General Hospital, a tertiary institution. In Singapore, polyclinics serve as government-subsidised primary care facilities, with SingHealth Polyclinic operating a network of these public clinics across Eastern Singapore. Data from the institution electronic medical records, including demography, clinical diagnoses, prescriptions, spirometry readings were extracted from their electronic medical records by an independent healthcare informatics officer who was not part of the study team and handed over to a Trusted Third Party (TTP) in the institution for de-identification. The deidentified data was transferred back to the study team via secured file transfer system for analysis. Ethics approval was obtained prior to commencement of the study, with waiver of consent from participants. The data was accessed between 05/12/2020 to 30/04/2025.
Study population
Local multi-ethnic Asian patients aged 18 years and older, and those who completed both pre and post bronchodilator tests in the institution were included in the analysis. Those who had spirometry in other healthcare institutions were excluded. Three weeks post-spirometry, the patients were reviewed and managed by their respective primary physicians based on the spirometry reports generated by the consultant pulmonologist. Figure 1 below shows the CONSORT flow diagram.
Fig. 1.
CONSORT flow diagram for participants who undergone spirometry and analyzed
Spirometry instrument
Office spirometry test was performed using a portable spirometry equipment, CPFS/D USB Spirometer® from Medical Graphics Corporation (MGC) Diagnostics. This is a portable full-function spirometry with prompts to guide the operator through the entire testing process, to ensure results comply with ATS/ERS acceptability criteria. The device was selected for its simplicity in data interpretation. These tests involve a pre-bronchodilator, and a post-bronchodilator forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1/FVC measurements. Patients were required to withhold short-acting beta-agonists (SABA) for at least 6 h, long-acting beta-agonists in combination with inhaled corticosteroids (LABA/ICS) for at least 12 h, and long-acting muscarinic antagonists (LAMA) for at least 48 h prior to testing. Smokers were required to abstain from smoking for at least 8 h before the tests.
Data collection
Clinical data of the patients covering a period of 3 months before and 6 months after the office spirometry procedure was extracted from their EMR. The data included baseline demographics included age, ethnicity, gender, smoking history, and body mass index (BMI), comorbidities, initial presenting symptoms, pre-spirometry clinical diagnosis, and prescribed medications. Other data covered the spirometry measurements, post-spirometry clinical diagnosis, medications and referral to pulmonologist for further management. Steroid inhaler medications extracted from the EMR were ICS and ICS-LABA inhalers: Beclometasone Dipropionate, Budesonide Turbuhaler, Fluticasone Propionate, BUD/FOR Turbuhaler, FLU/SAL-pMDI, FLU/SAL Accuhaler. Non-steroid medications extracted included Salbutamol, Ipratropium, Tiotropium, Umeclidinium, Montelukast, Theophylline and Loratadine. Referrals encompassed those referred to Otolaryngology or Respiratory specialist outpatient clinic.
Spirometry results were categorized into four groups: (1) Normal spirometry without significant bronchodilator responsiveness (NWSBR); (2) Significant bronchodilator responsiveness (SBR) (categorized as spirometry criteria for asthma diagnosis); (3) Post bronchodilator obstruction (PBO) (categorized as spirometry criteria for COPD diagnosis); and (4) Both SBR and PBO (categorized as having both asthma and COPD). SBR was defined as post bronchodilator increase in FEV1 or FVC ≥ 12% and 200mls, and PBO was defined as post bronchodilator obstructive airflow limitation with FEV1/FVC < lower limit of normal (LLN).
Statistical analyses
Demographic characteristics of the study population were summarized. Categorical variables were presented in frequencies and percentages, while continuous variables were presented in mean (standard deviation) for normally distributed data or median (interquartile range) for skewed data distribution. McNemar’s test was used to assess changes in treatment based on pre- and post-spirometry outcomes. If a patient was using a specific medication pre-spirometry and not using it post- spirometry, the medication would be considered as discontinued. A p-value of < 0.05 was considered statistically significant. All statistical analyses were performed using R (Version 4.2.3) and the Tidyverse® package.
Results
A total of 400 patients completed the spirometry test, screened for eligibility and 57 of them were removed. The remaining 343 patients were included in the analysis. Their median age was 55 years old [IQR = 33 to 64], with most being adults (76.1%) and Chinese (68.5%). About half the patients were males (53.1%), with 33.2% overweight (23 ≤ BMI < 27.5) and 28% obese (BMI ≥ 27.5). 26 patients (7.6%) were known smokers. The demographic characteristics of the study population are summarized in Table 1.
Table 1.
Demographics for office spirometry patients
| Patient Characteristics | Overall (%) |
|---|---|
| Total | 343 |
| Age (median inter-quartile range IQR) | 55 [33–64] |
| Age Group (Years) | |
| Adult (18–64) | 261 (76.1) |
Elderly ( 65) |
82 (23.9) |
| Gender | |
| Male | 182 (53.1) |
| Female | 161 (46.9) |
| Ethnicity | |
| Chinese | 235 (68.5) |
| Malay | 78 (22.7) |
| Indian | 21 (6.1) |
| Others | 9 (2.6) |
| BMI (kg/m2) | |
| Underweight (< 18.5) | 26 (7.6) |
| Normal (18.5 to 22.9) | 107 (31.2) |
| Overweight (23 to 27.4) | 114 (33.2) |
| Obese (≥ 30) | 96 (28.0) |
| Smoking Status | |
| Non-Smoker | 35 (10.2) |
| Smoker | 26 (7.6) |
| Unknown | 282 (82.2) |
| Comorbidities | |
| Chronic Ischemic Heart Disease | 21 (6.1) |
| Diabetes | 18 (5.2) |
| Hyperlipidaemia | 46 (13.4) |
| Hypertension | 47 (13.7) |
| Stroke | 9 (2.6) |
Concordance between pre-spirometry clinical diagnosis and spirometry outcomes
Among 151 (45.5%) patients with an initial diagnosis of asthma, 19 (12.6%) had SBR, which confirmed the asthma diagnosis. 9.3% had both SBR and PBO(SBR + PBO). Of those with unconfirmed diagnosis prior to spirometry, 8 (5.4%) had SBR. The concordance rate between pre-spirometry diagnosis and spirometry outcomes was 21.8%.
Among 45 (13.1%) patients with an initial diagnosis of COPD, 22.2% had PBO which confirmed the COPD diagnosis. 4.4% had both SBR and PBO. Of those with unconfirmed diagnosis prior to spirometry, 7 (4.8%) had PBO. The diagnostic concordance rate was 26.7%.
A substantial proportion of patients had unconfirmed diagnoses pre-spirometry (42.9%). Among these patients with unconfirmed diagnoses, the majority (82.3%) had no SRB or PBO. A smaller subset had SBR and PBO (7.5%). Confirmed diagnoses were less common, with asthma confirmed in 5.4% and COPD confirmed in 4.8% of this subgroup.
Change in medications post-spirometry and referral to specialist
Spirometry results led to substantial changes in medication management that varied according to pre-spirometry diagnosis and spirometry outcomes. Among patients with confirmed asthma who had been initially diagnosed with asthma prior to spirometry, there was an increase in ICS/ICS-LABA inhaler prescriptions from 47.4% to 57.9%. SABA prescription rates remained stable at 42.1%, and no patients were prescribed umeclidinium. For patients with confirmed COPD who had been diagnosed with asthma pre-spirometry, management intensification was more pronounced. ICS/ICS-LABA inhaler prescriptions increased from 62.5% to 87.5%, whilst SABA prescriptions rose from 50% to 62.5%. All patients with SBR + PBO received ICS or ICS-LABA inhalers post-spirometry. In contrast, patients with unconfirmed diagnoses experienced significant reductions in respiratory medication prescriptions. ICS/ICS-LABA inhaler prescriptions declined by 10%, from 30.9% to 20.9% (p < 0.05), whilst SABA prescriptions showed a more substantial reduction of 25.4%, from 54.5% to 29.1% (p < 0.001). Table 2 reports the change in treatment management.
Table 2.
Change in medications for patients with pre-spirometry clinical diagnosis of Asthma
| SBR, n = 19 (%) | PBO, n = 8 (%) | SBR + PBO, n = 14 (%) | Unconfirmed, n = 110 (%) | |||||
|---|---|---|---|---|---|---|---|---|
| 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | |
| ICS or Combination Inhalers | 9 (47.4) | 11 (57.9) | 5 (62.5) | 7 (87.5) | 10 (71.4) | 14 (100) | 34 (30.9)* | 23 (20.9)* |
| Salbutamol | 8 (42.1) | 8 (42.1) | 4 (50) | 5 (62.5) | 10 (71.4) | 10 (71.4) | 60 (54.5)*** | 32 (29.1)*** |
| Ipratropium | 3 (15.8) | 0 (0) | 2 (25) | 0 (0) | 2 (14.3) | 1 (7.1) | 6 (5.5) | 4 (3.6) |
| Tiotropium | 0 (0) | 0 (0) | 0 (0) | 1 (12.5) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Montelukast | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 1 (7.1) | 1 (7.1) | 0 (0) | 0 (0) |
| Theophylline | 0 (0) | 0 (0) | 0 (0) | 1 (12.5) | 0 (0) | 0 (0) | 1 (0.9) | 0 (0) |
| Loratadine | 4 (21.1) | 4 (21.1) | 2 (25) | 1 (12.5) | 7 (50) | 5 (35.7) | 36 (32.7) | 33 (30) |
SBR Normal or abnormal spirometry with Significant Bronchodilator Responsiveness, PBO Post bronchodilator obstructive result defined as FEV1/FVC < LLN
Medications. ICS or Combination Inhalers – Inhaled Corticosteroids or ICS and Long-acting beta-agonists (ICS/ LABA) and includes Beclomethasone, Budesonide, Fluticasone, Seretide MDI, Seretide DPI, Symbicort DPI
*, ** and *** indicates p-value < 0.05, < 0.01 and < 0.001 respectively
Among those with confirmed COPD (N = 45), medication management was intensified across multiple therapeutic classes. ICS/ICS-LABA inhaler prescriptions increased from 40% to 50%, ipratropium prescriptions doubled from 20% to 40%, and umeclidinium prescriptions increased substantially from 20% to 50%. Prescriptions for SABA, loratadine, and theophylline remained stable at 50%, 20%, and 10%, respectively. Of the two patients with SBR + PBO, one received salbutamol post-spirometry. For patients with unconfirmed diagnoses, there was a notable reduction in salbutamol prescriptions from 18.8% to 6.2%. However, no statistically significant differences were observed in treatment changes for patients initially diagnosed with COPD. Table 3 summarizes the results.
Table 3.
Change in medications for patients with pre-spirometry clinical diagnosis of COPD
| SBR, n = 1 (%) | PBO, n = 10 (%) | SBR + PBO, n = 2 (%) | Unconfirmed, n = 32 (%) | |||||
|---|---|---|---|---|---|---|---|---|
| 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | |
| ICS or Combination Inhalers | 0 (0) | 0 (0) | 3 (30) | 4 (40) | 1 (50) | 0 (0) | 1 (3.1) | 1 (3.1) |
| Salbutamol | 1 (100) | 0 (0) | 5 (50) | 5 (50) | 0 (0) | 1 (50) | 6 (18.8) | 2 (6.2) |
| Ipratropium | 0 (0) | 0 (0) | 2 (20) | 4 (40) | 0 (0) | 0 (0) | 2 (6.2) | 1 (3.1) |
| Umeclidinium | 0 (0) | 0 (0) | 2 (20) | 5 (50) | 0 (0) | 0 (0) | 3 (9.4) | 1 (3.1) |
| Theophylline | 0 (0) | 0 (0) | 1 (10) | 1 (10) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Loratadine | 0 (0) | 0 (0) | 2 (20) | 2 (20) | 0 (0) | 0 (0) | 6 (18.8) | 8 (25) |
SBR Normal or abnormal spirometry with Significant Bronchodilator Responsiveness, PBO Post bronchodilator obstructive result defined as FEV1/FVC < LLN
Medications. ICS or Combination Inhalers – Inhaled Corticosteroids or ICS and Long acting beta-agonists (ICS/ LABA) and includes Beclomethasone, Budesonide, Fluticasone, Seretide MDI, Seretide DPI, Symbicort DPI
*, ** and *** indicates p-value < 0.05, < 0.01 and < 0.001 respectively
Finally, among patients who initially had unconfirmed diagnoses but presented with respiratory symptoms, spirometry results led to targeted therapeutic interventions. For those subsequently diagnosed with confirmed asthma, both ICS/ICS-LABA and SABA prescriptions doubled from 12.5% to 25%, and from 25% to 50% respectively. Similarly, patients with confirmed COPD showed substantial treatment escalation, with ICS/ICS-LABA prescriptions rising from 0% to 28.6% and SABA prescriptions increasing from 14.3% to 28.6%. Patients diagnosed with SBR + PBO received the most intensive management, with approximately half (45.5%) prescribed ICS/ICS-LABA inhalers post-spirometry and nearly three-quarters (72.7%) receiving SABA therapy. Conversely, patients whose diagnoses remained unconfirmed experienced significant treatment discontinuation. SABA prescriptions declined substantially from 18.2% to 7.4% (p < 0.01), and loratadine prescriptions also decreased from 38.8% to 26.4% (p < 0.05). The results are tabulated in Table 4.
Table 4.
Change in medications for patients with pre-spirometry clinical diagnosis of undifferentiated
| SBR, n = 8 (%) | PBO, n = 7 (%) | SBR + PBO, n = 11 (%) | Unconfirmed, n = 121 (%) | |||||
|---|---|---|---|---|---|---|---|---|
| 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | 3-months pre spirometry | 6-months post spirometry | |
| ICS or Combination Inhalers | 1 (12.5) | 2 (25) | 0 (0) | 2 (28.6) | 0 (0) | 5 (45.5) | 5 (4.1) | 3 (2.5) |
| Salbutamol | 2 (25) | 4 (50) | 1 (14.3) | 2 (28.6) | 3 (27.3) | 8 (72.7) | 22 (18.2)** | 9 (7.4)** |
| Ipratropium | 1 (12.5) | 1 (12.5) | 1 (14.3) | 2 (28.6) | 1 (9.1) | 3 (27.3) | 3 (2.5) | 1 (0.8) |
| Tiotropium | 0 (0) | 0 (0) | 0 (0) | 1 (14.3) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Umeclidinium | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 1 (9.1) | 1 (9.1) | 1 (0.8) | 0 (0) |
| Montelukast | 1 (12.5) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | 0 (0) |
| Loratadine | 2 (25) | 2 (25) | 3 (42.9) | 2 (28.6) | 4 (36.4) | 3 (27.3) | 47 (38.8)* | 32 (26.4)* |
SBR Normal or abnormal spirometry with Significant Bronchodilator Responsiveness, PBO Post bronchodilator obstructive result defined as FEV1/FVC < LLN
Medications. ICS or Combination Inhalers – Inhaled Corticosteroids or ICS and Long acting beta-agonists (ICS/ LABA) and includes Beclomethasone, Budesonide, Fluticasone, Seretide MDI, Seretide DPI, Symbicort DPI
*, ** and *** indicates p-value < 0.05, < 0.01 and < 0.001 respectively
The overall referral rate was 24.8%, with the highest referral rate observed in patients with both SBR and PBO (33.3%). Patients with spirometry-confirmed asthma alone (21.4%) or spirometry-confirmed COPD alone (20%) had lower referral rates compared to patients with unconfirmed diagnosis from spirometry (24.7%). Among the 85 referred patients, pulmonologist clinic. The remaining (21.2%) were referred to otorhinolaryngologist clinic, of which 88.9% of them had unconfirmed spirometry diagnosis. Table 5 provides a summary on the referral rate for the spirometry diagnosis within 6-months post spirometry.
Table 5.
Post-spirometry referral based on spirometry outcomes
| Overall | Not Referred | Referred | |
|---|---|---|---|
| Total | 343 | 258 (75.2) | 85 (24.8) |
| PBO (%) | 25 (7.3) | 20 (80) | 5 (20) |
| SBR (%) | 28 (8.2) | 22 (78.6) | 6 (21.4) |
| SBR + PBO (%) | 27 (7.9) | 18 (66.7) | 9 (33.3) |
| Unconfirmed (%) | 263 (76.7) | 198 (75.3) | 65 (24.7) |
Discussion
This study investigated the concordance between clinical and spirometry diagnoses of asthma and COPD. Only 12.6% who were clinically diagnosed as asthma had positive SBR, which confirmed their diagnosis of asthma. 9.3% had SBR + PBO based on spirometry results. A previous study by Heffler et al. [10] reported a higher doctor-diagnosed and spirometry concordance rate of 24.4%.
Using PBO criteria for the diagnosis of COPD as per GOLD guidelines, COPD was confirmed in 22.2% of those who had been diagnosed based on clinical criteria. Heffler and colleagues [10] reported a lower concordance rate of 13.3% for doctor-diagnosed COPD in Italy, and accurate clinical diagnosis of COPD was also found generally low [11, 12]. Smoking prevalence is lower in Singapore (16.5%) compared with most OCED countries, such as 24.2% in Italy. Physicians in Singapore are more inclined to refer patients for spirometry assessment to determine airway obstruction based on their smoking history. They will consider therapeutics such as inhaled Long-Acting Muscarinic Antagonists (LAMA), with or without LABA for patients with moderate to severe airway obstruction, airway hypersensitivity and frequent exacerbations according to GOLD guidelines. The high discordance between clinical and spirometry-based diagnoses of prevalent chronic airway diseases showed that asthma and COPD should not be diagnosed just clinically but confirmed with an objective test. However, patients with suspected asthma with strong clinical signs should not be immediately excluded from the diagnosis based on one spirometry test. Earlier research showed spirometry at primary care had poor sensitivity for asthma (29%) despite good specificity (90%) but has much better sensitivity for COPD (92%) with moderate specificity (84%) [13]. If clinical suspicion for asthma is high, GINA guidelines recommended having a repeat test, or referral to a respiratory specialist for methacholine challenge test. Alternatively, demonstration of peak flow variability is also recommended by GINA for diagnosis of asthma [3]. Evidence has shown that spirometry measurements could be confounded by reduced bronchodilator responsiveness with ICS treatment [14], or patients were still symptomatic requiring the inhalers [15] while they await further investigation by pulmonologists.
Following spirometry testing, changes in medication prescribing patterns were observed. Patients with an initial diagnosis of asthma with SBR, PBO, or both showed an increase in prescriptions for ICS or combination inhalers. Conversely, those with unconfirmed diagnoses had a reduction in both ICS or combination inhaler and salbutamol prescriptions. As spirometry test has poor sensitivity for asthma (29%) [13], removal of the steroid inhaler prescription requires further clinical assessment.
For patients initially diagnosed with COPD or having an unconfirmed diagnosis pre-spirometry who subsequently showed no SBR or PBO on spirometry testing, a decrease in salbutamol prescriptions was observed. This demonstrates how spirometry can guide appropriate medication prescribing and reduce unnecessary prescriptions.
Primary care physicians should regularly update patients’ smoking history, occupation, and respiratory triggers to help identify those at higher COPD risk. The abnormal spirometry results could be shared with patients and used to nudge them towards smoking cessation. Yawn et al. [16] reported that giving a detailed spirometry report to smokers increased their quit rates by 1.42 times compared to control group, which was sustained at 24 months.
The overall referral rate to pulmonologists and otorhinolaryngologists was was 24.8% for this study population, which was lower than 29% in a local study by Rachel et al. [17]. With spirometry, a significant cohort of these patients were appropriately managed in primary care, averting the need for referrals to specialist care. Nonetheless, patients diagnosed with SBR + PBO had the highest referral rate at 33%, reflecting higher disease complexity which may initially require co-management with pulmonologists to stabilise their airway disease.
Limitations
Patients who underwent office spirometry might have been followed up in other healthcare setting resulting in incomplete clinical data. Details of the respiratory symptoms were not documented adequately in the EMR, which restricted a more comprehensive analysis of the data.
Conclusion
Offering office spirometry to patients with suspected asthma and COPD is key to align evidence-based management to GINA and GOLD clinical practice guidelines. Spirometry revealed discordance between clinical and spirometry-based diagnosis in patients with respiratory symptoms. These results emphasized a need for systematic approach in diagnosing asthma and COPD, integrating both clinical assessments, spirometry, and if necessary, repeating the spirometry, and further objective tests such as methacholine challenge tests. Spirometry should be scaled to ensure that patients receive the appropriate treatment. The spirometry results enabled primary care physicians to prescribe appropriate pharmacotherapy. This made possible a reduction in need for secondary referrals.
Acknowledgements
The authors would like to thank Dr Adrian Chan and Chia Jun Chun for providing the spirometry results and performing the spirometry respectively.
Authors’ contributions
All authors conceptualised the paper and were involved in writing up the manuscript. TST performed the data collection. DXN performed the data analysis. TST, MQHL and TNC interpreted the data.
Funding
None.
Data availability
Data can be available on request.
Declarations
Ethics approval and consent to participate
Ethics approval from SingHealth Centralized Institutional Review Board was obtained prior to the commencement of the study (Reference No: 2020/2415). Consent was not obtained from participants as data was obtained from medical records.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data can be available on request.