Using spirometry to rule out restriction in patients with concomitant low forced vital capacity and obstructive pattern

Comparison of Flowmetric Plethysmography and Forced Oscillatory Mechanics to Measure Airway Hyperresponsiveness in Horses

Airway hyperresponsiveness (AHR) is linked to airway inflammation and is considered a key manifestation of mild/moderate equine asthma (EA). The study purpose was to determine whether two modalities of non-invasive lung function testing (FOM-forced oscillatory mechanics vs. FP-flowmetric plethysmography) establish the same clinical diagnosis of AHR in horses, using histamine bronchoprovocation. Nineteen horses (3-25 years, 335-650 kg) with clinical signs suggestive of mild/moderate equine asthma were enrolled. FOM and FP testing was performed in each horse on two consecutive days, using a randomized cross-over design. AHR was defined by the histamine dose needed to double FOM baseline resistance, or to achieve a 35% increase in FP delta flow. Bronchoalveolar lavage fluid (BALF) was subsequently collected and stained with modified Wright's and toluidine blue stains. Binary statistical tests (related samples T-test, Mann-Whitney U, Chi-square analyses) were performed to compare study groups, with P < 0.05 considered significant. Abnormal BALF cytology confirmed EA in 14/19 (73.7%) horses. Both FOM and FP revealed AHR in 7/14 (50%) of these EA horses. An additional 4/19 (21.1%) horses showed AHR based on FP but not FOM, including two horses with normal BALF cytology. A diagnosis of AHR was more often associated with FP than FOM (P = 0.013), although the prevalence of AHR was significantly higher in EA vs. non-EA horses, regardless of testing methodology. The phase angle between thoracic and abdominal components of breathing did not differ between test groups. In conclusion, FP diagnosed AHR more frequently than did FOM, including horses with no other diagnostic evidence of EA. Without further evaluation, these two testing modalities of AHR cannot be used interchangeably.

Non-invasive techniques to assess restrictive lung disease in workers exposed to free crystalline silica

Objectives:

To compare the reliability of spirometry and body plethysmography in detecting restrictive lung disease in clay excavation workers exposed to free crystalline silica (FCS). The exhaled breath condensate (EBC) biomarkers of oxidative stress were also assessed in order to evaluate early lung damage.

Methods:

The study involved 62 workers (58 males and 4 females) at a company that extracts and processes clay.

Results:

Body plethysmography (total lung capacity below the lower normal limit) and spirometry respectively indicated restrictive pattern prevalence rates of 22.6% and 1.6%. EBC 4-hydroxynonenale levels were not sufficiently sensitive to highlight a restrictive deficit, but did distinguish low and high rates of occupational exposure. There was no correlation between plethysmography values and the intensity or duration of exposure.

Conclusions:

Only one out of 14 cases of restrictive deficit diagnosed on the basis of body plethysmography values was also identified by means of spirometry. This finding supports the need to use body plethysmography in the health surveillance of clay workers exposed to FCS.

A new spirometry-based algorithm to predict occupational pulmonary restrictive impairment

BACKGROUND

Spirometry is often included in workplace-based respiratory surveillance programmes but its performance in the identification of restrictive lung disease is poor, especially when the prevalence of this condition is low in the tested population.

AIMS

To improve the specificity (Sp) and positive predictive value (PPV) of current spirometry-based algorithms in the diagnosis of restrictive pulmonary impairment in the workplace and to reduce the proportion of false positives findings and, as a result, unnecessary referrals for lung volume measurements.

METHODS

We re-analysed two studies of hospital patients, respectively used to derive and validate a recommended spirometry-based algorithm [forced vital capacity (FVC) < 85% predicted and forced expiratory volume in 1 s (FEV1)/FVC > 55%] for the recognition of restrictive pulmonary impairment. We used true lung restrictive cases as a reference standard in 2×2 contingency tables to estimate sensitivity (Sn), Sp and PPV and negative predictive values for each diagnostic cut-off. We simulated a working population aged <65 years and with a disease prevalence ranging 1-10% and compared our best algorithm with those previously reported using receiver operating characteristic curves.

RESULTS

There were 376 patients available from the two studies for inclusion. Our best algorithm (FVC < 70% predicted and FEV1/FVC ≥ 70%) achieved the highest Sp (96%) and PPV (67 and 15% for a disease prevalence of 10 and 1%, respectively) with the lowest proportion of false positives (4%); its high Sn (71%) predicted the highest proportion of correctly classified restrictive cases (91%).

CONCLUSIONS

Our new spirometry-based algorithm may be adopted to accurately exclude pulmonary restriction and to possibly reduce unnecessary lung volume testing in an occupational health setting.

Spirometry values for detecting a restrictive pattern in occupational health settings

BACKGROUND

Pulmonary function tests are valuable measures for diagnosis and management of respiratory diseases. In the field of occupational medicine, spirometry is commonly performed, and in a considerable number of spirometries during occupational health evaluations, restrictive pattern is observed without any respiratory symptoms and may necessitate referral of the subject for body plethysmography, which is an expensive test. In this study, we evaluated the diagnostic accuracy of spirometry for detection of restrictive lung pattern in an occupational setting.

MATERIALS AND METHODS

In a cross-sectional study from 2008 to 2012, 1224 subjects were selected and entered in the study out of 1,486 individuals referred for annual spirometry. Selected subjects underwent spirometry and body plethysmography. Subjects were divided into two groups of restrictive and non-restrictive patterns and then sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of spirometry for detection of restrictive lung pattern were calculated using total lung capacity measured by plethysmography as the gold standard. Receiver operating characteristic (ROC) curves were used as well.

RESULTS

Spirometry showed sensitivity, specificity, PPV and NPV of 97.75%, 73.04%, 73.72% and 97.67% for FVC< lower limit of normal (LLN) and 98.68%, 78.00%, 77.31% and 98.83% for FVC< LLN along with FEV1/FVC≥ LLN, respectively. According to the ROC curve, the best cut-off point for FVC for detection of restrictive lung pattern was 70%.

CONCLUSION

This study showed that spirometry is a useful method in occupational health evaluations to rule out restrictive lung patterns with acceptable accuracy; however, it is not an accurate tool for detection of restrictive lung pattern in an occupational setting. Simultaneous use of FVC and FEV1/FVC for detection of restriction increases the predictive value of spirometry.