Misdiagnosis Among Frequent Exacerbators of Clinically Diagnosed Asthma and COPD in Absence of Confirmation of Airflow Obstruction

Using Machine Learning with Impulse Oscillometry Data to Develop a Predictive Model for Chronic Obstructive Pulmonary Disease and Asthma

We aimed to develop and validate a machine learning model using impulse oscillometry system (IOS) profiles for accurately classifying patients into three assessment-based categories: no airflow obstruction, asthma, and chronic obstructive pulmonary disease (COPD). Our research questions were as follows: (1) Can machine learning methods accurately classify obstructive disease states based solely on multidimensional IOS data? (2) Which IOS parameters and modeling algorithms provide the best discrimination? We used data for 480 patients (240 with COPD and 240 with asthma) and 84 healthy individuals for training. Physiological and IOS parameters were combined into six feature combinations. The classification algorithms tested were logistic regression, random forest, neural network, k-nearest neighbor, and support vector machine. The optimal feature combination for identifying individuals without pulmonary obstruction, with asthma, or with COPD included 15 IOS and physiological features. The neural network classifier achieved the highest accuracy (0.786). For discriminating between healthy and unhealthy individuals, two combinations of twenty-three features performed best in the neural network algorithm (accuracy of 0.929). When distinguishing COPD from asthma, the best combination included 15 features and the neural network algorithm achieved an accuracy of 0.854. This study provides compelling technical evidence and clinical justifications for advancing IOS data-driven models to aid in COPD and asthma management.

Chronic Obstructive Pulmonary Disease Overdiagnosis and Overtreatment: A Meta-Analysis

This meta-analysis of observational studies aimed at estimating the overall prevalence of overdiagnosis and overtreatment in subjects with a clinical diagnosis of Chronic Obstructive Pulmonary Disease (COPD). MedLine, Scopus, Embase and Cochrane databases were searched, and random-effect meta-analyses of proportions were stratified by spirometry criteria (Global Initiative for COPD (GOLD) or Lower Limit of Normal (LLN)), and setting (hospital or primary care). Forty-two studies were included. Combining the data from 39 datasets, including a total of 23,765 subjects, the pooled prevalence of COPD overdiagnosis, according to the GOLD definition, was 42.0% (95% Confidence Interval (CI): 37.3-46.8%). The pooled prevalence according to the LLN definition was 48.2% (40.6-55.9%). The overdiagnosis rate was higher in primary care than in hospital settings. Fourteen studies, including a total of 8183 individuals, were included in the meta-analysis estimating the prevalence of COPD overtreatment. The pooled rates of overtreatment according to GOLD and LLN definitions were 57.1% (40.9-72.6%) and 36.3% (17.8-57.2%), respectively. When spirometry is not used, a large proportion of patients are erroneously diagnosed with COPD. Approximately half of them are also incorrectly treated, with potential adverse effects and a massive inefficiency of resources allocation. Strategies to increase the compliance to current guidelines on COPD diagnosis are urgently needed.

Construction of a Diagnostic Algorithm for Diagnosis of Adult Asthma Using Machine Learning with Random Forest and XGBoost

An evidence-based diagnostic algorithm for adult asthma is necessary for effective treatment and management. We present a diagnostic algorithm that utilizes a random forest (RF) and an optimized eXtreme Gradient Boosting (XGBoost) classifier to diagnose adult asthma as an auxiliary tool. Data were gathered from the medical records of 566 adult outpatients who visited Kindai University Hospital with complaints of nonspecific respiratory symptoms. Specialists made a thorough diagnosis of asthma based on symptoms, physical indicators, and objective testing, including airway hyperresponsiveness. We used two decision-tree classifiers to identify the diagnostic algorithms: RF and XGBoost. Bayesian optimization was used to optimize the hyperparameters of RF and XGBoost. Accuracy and area under the curve (AUC) were used as evaluation metrics. The XGBoost classifier outperformed the RF classifier with an accuracy of 81% and an AUC of 85%. A combination of symptom-physical signs and lung function tests was successfully used to construct a diagnostic algorithm on importance features for diagnosing adult asthma. These results indicate that the proposed model can be reliably used to construct diagnostic algorithms with selected features from objective tests in different settings.

Complexity in clinical diagnoses of acute exacerbation of chronic obstructive pulmonary disease

BACKGROUND

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a clinical syndrome with various causes. It is not uncommon that COPD patients presenting with dyspnea have multiple causes for their symptoms including AECOPD, pneumonia, or congestive heart failure occurring concurrently.

METHODS

To identify clinical, radiographic, and laboratory characteristics that might help distinguish AECOPD from another dominant disease in patients with a history of COPD, we conducted a retrospective cohort study of hospitalized patients with admitting diagnosis of AECOPD who were screened for a prospective randomized controlled trial from Sep 2016 to Mar 2018. Clinical characteristics, course in hospital, and final diagnosis at discharge were reviewed and adjudicated by two authors. The final diagnosis of each patient was determined based on the synthesis of all presenting signs and symptoms, imaging, and laboratory results. We adhered to AECOPD diagnosis definitions based on the GOLD guidelines. Univariate and multivariate analyses were performed to identify any associated features of AECOPD with and without other acute processes contributing to dyspnea.

RESULTS

Three hundred fifteen hospitalized patients with admitting diagnosis of AECOPD were included. Mean age was 72.5 (SD 10.6) years. Two thirds (65.4%) had spirometry defined COPD. The most common presenting symptom was dyspnea (96.5%), followed by cough (67.9%), and increased sputum (57.5%). One hundred and eighty (57.1%) had a final diagnosis of AECOPD alone whereas 87 (27.6%) had AECOPD with other conditions and 48 (15.2%) did not have AECOPD after adjudication. Increased sputum purulence (OR 3.35, 95%CI 1.68-6.69) and elevated venous pCO2 (OR 1.04, 95%CI 1.01 - 1.07) were associated with a diagnosis of AECOPD but these were not associated with AECOPD alone without concomitant conditions. Radiographic evidence of pleural effusion (OR 0.26, 95%CI 0.12 - 0.58) was negatively associated with AECOPD with or without other conditions while radiographic evidence of pulmonary edema (OR 0.31; 95%CI 0.11 - 0.91) and lobar pneumonia (OR 0.13, 95%CI 0.07 - 0.25) suggested against the diagnosis of AECOPD alone.

CONCLUSION

The study highlighted the complexity and difficulty of AECOPD diagnosis. A more specific clinical tool to diagnose AECOPD is needed.

Ever Smoking is Not Associated with Performed Spirometry while Occupational Exposure and Respiratory Symptoms are

Objective

Despite recommendations, assessment using spirometry or peak expiratory flow is insufficient in the clinical evaluation of suspected obstructive pulmonary disease. The aim was to investigate factors associated with performing spirometry or peak flow expiratory flow assessment.

Methods

Randomly selected subjects from the general population aged 50-65 completed a respiratory questionnaire with items about the history of previously performed spirometry or peak expiratory flow. The association between ever having had spirometry or peak expiratory flow performed was analyzed for smoking, age, sex, occupational exposures, dyspnea, wheeze, self-reported physician diagnosed asthma and COPD using multivariable logistic regression models. The results are presented as odds ratios (OR) with 95% confidence intervals (95% CIs).

Results

Of the 1105 participants, 43.4% (n=479) had a history of previously performed spirometry or peak expiratory flow. Occupational exposure (OR 1.72, [95% CI] 1.30-2.27), wheeze (OR 2.29, 1.41-3.70), and dyspnea (OR 1.70, 1.11-2.60) were associated with previously performed spirometry. Compared to men, women had spirometry or peak expiratory flow performed less often (OR 0.67, 0.51-0.86). Neither current smoking (OR 0.83, 0.57-1.20) or former smoking (OR 1.27, 0.96-1.67) were associated with performed spirometry or peak expiratory flow.

Conclusion

We found no relation between smoking status and a history of previously performed spirometry or peak expiratory flow in a population-based sample of middle-aged people. This is surprising regarding the strong guidelines which highlight the importance for spirometry surveillance on current smokers due to their increased risk of lung disease. Male sex, respiratory symptoms and occupational exposures to air pollution were associated with previously performed spirometry or peak expiratory flow. The association with occupational exposure may be an effect of pre-employment screening and workplace surveillance, and the findings indicate that females do not receive the same attention regarding spirometry or peak expiratory flow.

Practical approaches to the diagnosis of asthma in school-age children

INTRODUCTION

Asthma is a chronic airways disease characterized by episodes of wheeze, chest tightness, and evidence of reversible airflow obstruction. Symptoms are frequently triggered by exercise, exposure to aeroallergens, and respiratory viruses. It is the commonest non-communicable respiratory condition in children, affecting over 5.5 million children in the European Union alone. Both over- and under- diagnosis of asthma are common for several reasons.

AREAS COVERED

The diagnosis is frequently based on parental or patient reported non-specific symptoms alone. All major asthma guidelines now recommend the use of objective tests, including spirometry, bronchodilator reversibility testing, fraction of exhaled nitric oxide measurements and challenge testing to confirm the diagnosis. Recently, the European Respiratory Society published the first evidence-based international guidelines for diagnosing asthma in school-age children using objective measures. Major barriers to implementation in primary care and less well-resourced healthcare settings are access to relevant objective tests for children and quality assurance to obtain reliable results.

EXPERT OPINION

We highlight the importance of diagnosing asthma in school-age children using objective tests and outline a practical approach for the use of widely available tests. We also review challenges and barriers to implementation of objective testing in children managed outside specialist settings.

The Role of Access and Cost-Effectiveness in Managing Asthma: A Systematic Review

Background

Inconsistent and unequal access to medical care is an issue that predates the COVID19 pandemic, which only worsened the problem. Limited access to care from asthma specialists and other specialists treating comorbid diseases may adversely affect asthma.

Objective

The purpose of this review is to identify health disparities associated with access to care for asthma, and cost-effectiveness of therapies and interventions addressing this health disparity.

Methods

A narrative systematic review was undertaken using MeSH searches of English language articles published in CINAHL, Scopus, or PubMed.

Results

A total of 725 articles were identified. Barriers recognized from the literature included access to diagnostic spirometry, access to specialists, medication formulary restrictions, and issues leading to medical nonadherence. Telemedicine, school-based health care interventions, digital applications, and non–office-based digital spirometry could be used to address these gaps in access to asthma care while potentially being cost-effective.

Conclusion

With the widespread adoption of telemedicine because of the pandemic, and adoption of other mobile services, we now have potential tools that can increase access to asthma care, which can help address this health care inequity. Evidence is limited, but favorable, that some of these tools may be cost-effective.

A systematic literature review of burden of illness in adults with uncontrolled moderate/severe asthma

BACKGROUND

There are limited published data on the burden of moderate/severe uncontrolled asthma.

METHODS

We conducted a systematic literature review to better understand the impact of moderate-to-severe asthma in the US, the UK, Germany, France, Italy, Spain, Canada, Japan, and Australia in terms of prevalence, clinical measures, health-related quality of life (HRQoL) and economic burden, for patients whose asthma is uncontrolled despite inhaled corticosteroid/long-acting β₂-agonist (ICS/LABA) therapy.

RESULTS

The prevalence of uncontrolled asthma among patients with moderate/severe disease varied but was as high as 100% in some subgroups. Patients with uncontrolled asthma generally had poor lung function (mean/median pre-bronchodilator forced expiratory volume in 1 second [FEV₁]: 1.69-2.45 L; mean/median pre-bronchodilator percent predicted FEV₁: 57.2-79.7). There was also a substantial but variable exacerbation burden associated with uncontrolled asthma, with the annualised rate of exacerbations ranging from 1.30 to 7.30 when considering various patient subgroups. Furthermore, the annualised rate of severe exacerbations ranged from 1.66 to 3.60. The HRQoL burden measured using disease-specific and generic instruments consistently demonstrated substantial impairment of HRQoL for those with uncontrolled asthma; Asthma Quality of Life Questionnaire scores ranged from 3.00 to 5.20, whilst EurQol-5 Dimensions index scores ranged from 0.53 to 0.59. Direct, indirect and total costs together with consumption of other healthcare resources associated with managing uncontrolled asthma were also substantial in the population studied; no caregiver burden was identified.

CONCLUSIONS

Our findings suggest that significant unmet needs exist for patients with uncontrolled asthma despite the availability of ICS/LABA therapy. Novel treatments are needed to help reduce the burden to patients, healthcare systems and society.

Artificial Intelligence/Machine Learning in Respiratory Medicine and Potential Role in Asthma and COPD Diagnosis

Artificial intelligence (AI) and machine learning, a subset of AI, are increasingly used in medicine. AI excels at performing well-defined tasks, such as image recognition; for example, classifying skin biopsy lesions, determining diabetic retinopathy severity, and detecting brain tumors. This article provides an overview of the use of AI in medicine and particularly in respiratory medicine, where it is used to evaluate lung cancer images, diagnose fibrotic lung disease, and more recently is being developed to aid the interpretation of pulmonary function tests and the diagnosis of a range of obstructive and restrictive lung diseases. The development and validation of AI algorithms requires large volumes of well-structured data, and the algorithms must work with variable levels of data quality. It is important that clinicians understand how AI can function in the context of heterogeneous conditions such as asthma and chronic obstructive pulmonary disease where diagnostic criteria overlap, how AI use fits into everyday clinical practice, and how issues of patient safety should be addressed. AI has a clear role in providing support for doctors in the clinical workplace, but its relatively recent introduction means that confidence in its use still has to be fully established. Overall, AI is expected to play a key role in aiding clinicians in the diagnosis and management of respiratory diseases in the future, and it will be exciting to see the benefits that arise for patients and doctors from its use in everyday clinical practice.

Time-ordered comorbidity correlations identify patients at risk of mis- and overdiagnosis

Diagnostic errors are common and can lead to harmful treatments. We present a data-driven, generic approach for identifying patients at risk of being mis- or overdiagnosed, here exemplified by chronic obstructive pulmonary disease (COPD). It has been estimated that 5-60% of all COPD cases are misdiagnosed. High-throughput methods are therefore needed in this domain. We have used a national patient registry, which contains hospital diagnoses for 6.9 million patients across the entire Danish population for 21 years and identified statistically significant disease trajectories for COPD patients. Using 284,154 patients diagnosed with COPD, we identified frequent disease trajectories comprising time-ordered comorbidities. Interestingly, as many as 42,459 patients did not present with these time-ordered, common comorbidities. Comparison of the individual disease history for each non-follower to the COPD trajectories, demonstrated that 9597 patients were unusual. Survival analysis showed that this group died significantly earlier than COPD patients following a trajectory. Out of the 9597 patients, we identified one subgroup comprising 2185 patients at risk of misdiagnosed COPD without the typical events of COPD patients. In all, 10% of these patients were diagnosed with lung cancer, and it seems likely that they are underdiagnosed for lung cancer as their laboratory test values and survival pattern are similar to such patients. Furthermore, only 4% had a lung function test to confirm the COPD diagnosis. Another subgroup with 2368 patients were found to be at risk of "classically" overdiagnosed COPD that survive >5.5 years after the COPD diagnosis, but without the typical complications of COPD.

Acute Exacerbations of Chronic Obstructive Pulmonary Disease: A Primer for Emergency Physicians

BACKGROUND

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) impose a significant burden on patients and the emergency health care system. Patients with COPD who present to the emergency department (ED) often have comorbidities that can complicate their management.

OBJECTIVE

To discuss strategies for the management of acute exacerbations in the ED, from initial assessment through disposition, to enable effective patient care and minimize the risk of treatment failure and prevent hospital readmissions.

DISCUSSION

Establishing a correct diagnosis early on is critical; therefore, initial evaluations should be aimed at differentiating COPD exacerbations from other life-threatening conditions. Disposition decisions are based on the intensity of symptoms, presence of comorbidities, severity of the disease, and response to therapy. Patients who are appropriate for discharge from the ED should be prescribed evidence-based treatments and smoking cessation to prevent disease progression. A patient-centric discharge care plan should include medication reconciliation; bedside "teach-back," wherein patients demonstrate proper inhaler usage; and prompt follow-up.

CONCLUSIONS

An effective assessment, accurate diagnosis, and appropriate discharge plan for patients with AECOPD could improve treatment outcomes, reduce hospitalization, and decrease unplanned repeat visits to the ED.

Recent Advances in the Management of Acute Exacerbations of Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease is a chronic, irreversible obstructive lung disease that results from exposure to noxious stimuli. Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) usually result from viral or bacterial respiratory infections, but may also result from exposure to environmental pollution. AECOPD are associated with functional decline, increased risk of subsequent exacerbations, and death. Despite the poor prognosis of AECOPD, patients are empowered through self-management programs in their battle against this lethal disease. Morbidity and mortality of chronic obstructive pulmonary disease hospitalizations are reduced by implementing standardized treatment modalities outlined in this article throughout the hospitalization and beyond.

The role of objective tests to support a diagnosis of asthma in children

In many healthcare settings asthma in children is a clinical diagnosis based on parental reported symptoms. These include intermittent episodes of wheezing, breathlessness and periodic nocturnal dry cough. Increased symptoms often coincide with colds. Confirming a diagnosis of asthma in children can be difficult and recent reports highlight that misdiagnosis, including over- and under-diagnosis of asthma are common. Recent UK National Institute of Health and Care Excellence guidelines recommend diagnostic algorithms for children from five years and adults to support a clinical suspicion of asthma. Spirometry, bronchodilator reversibility and fractional exhaled nitric oxide testing are the first line tests to diagnose asthma in children. The introduction of these tests across all healthcare settings has the potential to reduce misdiagnosis, improve asthma management and reduce healthcare spending for asthma.

Misdiagnosis of asthma and COPD and underuse of spirometry in primary care unselected patients

BACKGROUND

The diagnosis of both asthma and chronic obstructive pulmonary disease (COPD) consists of a combination of classical symptoms and signs, and the evidence of consistent lung function abnormalities. Spiromety has been reported to be underused, possibly for practical difficulties in accessing to a lung function lab. This may lead to misdiagnosis of both asthma and COPD. We aimed to evaluate the frequency of spirometry use and the concordance between doctor-diagnosed asthma and COPD and spirometric patterns, in an unselected cohort of patients sent by general practitioners to perform a spirometry.

METHODS

The first 300 patients consecutively enrolled patients performed spirometry and bronchodilator test with salbutamol 400 mcg. Demographic, clinical and lung function data have been collected.

RESULTS

128 patients (42.7%) declared a doctor-diagnosed asthma and 75 (25%) a doctor-diagnosis of COPD; the remaining subjects never had received any respiratory diagnosis. Only 112 patients with doctor-diagnosed asthma (55.2%) and 114 (56.2%) with doctor-diagnosed COPD have ever performed a spirometry in their entire life (average time since the last spirometry was about 47.0 months). Eighty-nine (69.5%) and 10 (13.3%) patients with respectively doctor-diagnosed asthma and COPD had concordant spirometric patterns with their known diseases.

DISCUSSION

we described a worrying lack of use of spirometry and a high proportion of misdiagnosis, in patients with suspect chronic airway inflammatory diseases and cared by primary care physicians. Novel strategies to overcome this situation include should be implemented to give a better care to our patients.

Ability of Exhaled Nitric Oxide to Discriminate for Airflow Obstruction Among Frequent Exacerbators of Clinically Diagnosed Asthma

OBJECTIVE

Fraction of exhaled nitric oxide (FE_NO) has been proposed as a non-invasive biomarker for allergic inflammation seen in asthma. Many asthmatics in clinical practice have never had spirometry and recent data report misdiagnoses in patients with physician diagnosed (PD) asthma. The aim of this study was to assess the ability of FE_NO to discriminate between those with and without airflow obstruction (AO) among patients with PD-asthma.

METHODS

Frequent exacerbators of PD-asthma (with 2 or more asthma exacerbations leading to emergency room visit or hospitalization within last 12 months) were enrolled. All patients underwent diagnostic evaluations including spirometry, FE_NO testing and serum immunoglobulin (IgE) and eosinophils. Serial spirometry and methacholine challenge testing (MCT) were performed as indicated. AO was defined by a decreased FEV1/FVC ratio (< 70% and/or < LLN), or a positive MCT.

RESULTS

Of the 222 patients with PD-asthma, AO was found in 136 (vs. 86 without AO). 81.6% of patients with AO and 66.2% without AO completed FE_NO testing. There was no significant difference in the mean FE_NO levels among patients with or without AO (40.8 vs. 30.4 ppb, P = 0.10). Likewise, there was no difference in the serum IgE levels and serum eosinophils.

CONCLUSIONS

Our analyses suggest that FE_NO levels do not help discriminate between those with and without AO in patients with PD-asthma. Patients who experience symptoms of asthma may have elevated FE_NO levels above the suggested cut points of 20-25 ppb. Objective confirmation of AO should be considered in all patients with PD-asthma, irrespective of FE_NO levels.

A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal samples. A machine learning-based pipeline identified an asthma classifier consisting of 90 genes interpreted via an L2-regularized logistic regression classification model. This classifier performed with strong predictive value and sensitivity across eight test sets, including (1) a test set of independent asthmatic and control subjects profiled by RNA sequencing (positive and negative predictive values of 1.00 and 0.96, respectively; AUC of 0.994), (2) two independent case-control cohorts of asthma profiled by microarray, and (3) five cohorts with other respiratory conditions (allergic rhinitis, upper respiratory infection, cystic fibrosis, smoking), where the classifier had a low to zero misclassification rate. Following validation in large, prospective cohorts, this classifier could be developed into a nasal biomarker of asthma.

Causes of misdiagnosis of chronic obstructive pulmonary disease: A systematic scoping review

BACKGROUND

Chronic obstructive pulmonary disease (COPD) has serious implications at both the individual and the societal level. It is crucial that COPD is diagnosed correctly to ensure provision of the right treatment. However, the current diagnostic procedures may lead to misdiagnosis.

AIM

The aim of this scoping review was to disseminate knowledge about potential causes of misdiagnosis of COPD.

METHODS

A systematic, comprehensive search was performed in PubMed, Embase and Cinahl.

RESULTS

A thorough review produced a sample of 73 articles. The synthesis revealed five potential causes of misdiagnosis of COPD, including: the threshold for defining COPD (n = 36), errors made in primary care (n = 15), errors linked to the spirometry test (n = 13), differential diagnoses (n = 10), and patient-related factors (n = 8).

CONCLUSIONS

The causes of misdiagnosis of COPD are attributable mainly to spirometry and to the healthcare professional performing the diagnostic assessment. With a view to limiting misdiagnosis of COPD, future research should help clarify strategies for alternative objective tests for determining if a patient has COPD and explore how to better support primary care in the diagnosing of COPD.

Addressing the misdiagnosis of asthma in adults: where does it go wrong?

INTRODUCTION

Asthma is diagnosed based on patients' respiratory symptoms of wheeze, cough, chest tightness and/or dyspnea together with physiologic evidence of variable and reversible expiratory airflow limitation. A high prevalence of overdiagnosis, underdiagnosis and misdiagnosis of adult asthma has been reported in the literature. Areas covered: Misdiagnosis of asthma in adults can occur in the community due to physicians' failure to confirm airflow limitation using spirometry, the relatively poor sensitivity of spirometry to absolutely rule in asthma, the complexity of multiple asthma phenotypes and endotypes, and the inherent day to day variability of asthma symptoms and airflow limitation. Consequences of asthma misdiagnosis to the patient and to the healthcare system include increased medication costs, increased potential side effects related to unnecessary use of medications and lost opportunities to diagnose the true cause of patients' respiratory symptoms. Expert commentary: Here we provide a review of the problem of misdiagnosis of adult asthma and suggestions for how to decrease the risk of misdiagnosis.

Action plans for COPD: strategies to manage exacerbations and improve outcomes

COPD is the third-largest killer in the world, and certainly takes a toll on the health care system. Recurrent COPD exacerbations accelerate lung-function decline, worsen mortality, and consume over US$50 billion in health care spending annually. This has led to a tide of payment reforms eliciting interest in strategies reducing preventable COPD exacerbations. In this review, we analyze and discuss the evidence for COPD action plan-based self-management strategies. Although action plans may provide stabilization of acute symptomatology, there are several limitations. These include patient-centered attributes, such as comprehension and adherence, and nonadherence of health care providers to established guidelines. While no single intervention can be expected independently to translate into improved outcomes, structured together within a comprehensive integrated disease-management program, they may provide a robust paradigm.

Office spirometry correlates with laboratory spirometry in patients with symptomatic asthma and COPD

OBJECTIVES

Spirometry remains underutilized in the evaluation of obstructive lung disease. While office spirometry (OS) has been compared to formal laboratory-based spirometry (LS) in healthy subjects, the correlation has never been formally assessed in patients with symptomatic obstructive lung disease. The aim of this study was to investigate the correlation in this population.

METHODS

We used a retrospective study design to analyze spirometry data from patients that underwent both OS and LS. Two flow sensing office (portable) spirometers were used and compared with laboratory-based (body plethymosgraph) spirometer. Accuracy and reliability were assessed using Bland Altman analysis.

RESULTS

Among 185 patients with symptomatic obstructive lung disease, 129 had undergone both OS and LS. Of these, 107 patients had both tests performed less than 90 days apart and were included in final analyses. Mean age was 54 years with mean FEV1 of 1.97 L (65% predicted). Ninety-two patients had airflow obstruction, as determined by a FEV1/FVC ratio of <70%. We found significant correlation in the values between OS and LS for both FEV1 and FVC (r = 0.937 and 0.90, respectively, P < 0.001). Eighty-seven percent of patients had a concordant spirometry in terms of airflow obstruction. Correlation was independent of the office spirometer (and hence the Flow-sensing mechanism) used.

CONCLUSIONS

In patients with known asthma and chronic obstructive pulmonary disease (COPD), OS is accurate and reliable when compared to formal laboratory-based spirometry. Routine use of OS should be encouraged to improve spirometry utilization and healthcare outcomes in patients with Asthma and COPD.