Diagnosis of occupational asthma from serial measurements of forced expiratory volume in 1 s (FEV1) using the Area Between Curves (ABC) score from the Oasys plotter.

OBJECTIVES: To identify the changes in serial 2-hourly forced expiratory volume in 1 s (FEV1) measurements required to identify occupational asthma (OA) using the Oasys Area Between Curves (ABC) score. METHODS: The ABC score from 2-hourly measurements of FEV1 was compared between workers with confirmed OA and asthmatics without occupational exposure to identify the optimum separation using receiver operator characteristic (ROC) analysis. Separate analyses were made for plots using clock time and time from waking to allow for use in shift workers. Minimum record criteria were ≥6 readings per day, >4 day shifts and >4 rest days (or >9 days for controls). RESULTS: A retrospective analysis identified 22 workers with OA and 30 control asthmatics whose records reached the quality standards. Median FEV1 diurnal variation was 20.3% (IQR 16.1-32.6) for OA and 19.5% (IQR 14.5-26.1) for asthmatic controls. ROC curve analysis identified that a difference of 0.056 L/hour gave a ROC score of 0.821 for clock time and 0.768 for time from waking with a sensitivity of 73% and a specificity of 93% for the diagnosis of OA. CONCLUSIONS: The diagnosis of OA requires objective confirmation. Unsupervised serial FEV1 measurements are more difficult to obtain reliably than measurements of peak expiratory flow, which are likely to remain the standard for general use. A FEV1 ABC score >0.056 L/hour provides a valid cut-off for those who wish to use FEV1 rather than peak expiratory flow.

Identification of late asthmatic reactions following specific inhalation challenge.

Specific inhalation challenge (SIC) is the reference standard for the diagnosis of occupational asthma. Current guidelines for identifying late asthmatic reactions are not evidence based. OBJECTIVES: To identify the fall in forced expiratory volume in 1 s (FEV1) required following SIC to exceed the 95% CI for control days, factors which influence this and to show how this can be applied in routine practice using a statistical method based on the pooled SD for FEV1 from three control days. METHODS: Fifty consecutive workers being investigated for occupational asthma were asked to self-record FEV1 hourly for 2 days before admission for SIC. These 2 days were added to the in-hospital control day to calculate the pooled SD and 95% CI. RESULTS: 45/50 kept adequate measurements. The pooled 95% CI was 385 mL (SD 126), or 14.2% (SD 6.2) of the baseline FEV1, but was unrelated to the baseline FEV1 (r=0.06, p=0.68), or gender, atopy, smoking, non-specific reactivity or treatment before or during SIC. Thirteen workers had a late asthmatic reaction with ≥2 consecutive FEV1 measurements below the 95% CI for pooled control days, 4/13 had <15% and 9/13 >15% late fall from baseline. The four workers with ≥2 values below the 95% CI all had independent evidence of occupational asthma. CONCLUSION: The pooled SD method for defining late asthmatic reactions has scientific validity, accounts for interpatient spirometric variability and diurnal variation and can identify clinically relevant late asthmatic reactions from smaller exposures. For baseline FEV1 <2.5 L, a 15% fall is within the 95% CI.

Characteristics of hypersensitivity pneumonitis diagnosed by interstitial and occupational lung disease multi-disciplinary team consensus.

INTRODUCTION: The causes of hypersensitivity pneumonitis (HP) in the UK are changing as working practices evolve, and metalworking fluid (MWF) is now a frequently reported causative exposure. We aimed to review and describe all cases of HP from our UK regional service, with respect to the causative exposure and diagnostic characteristics. METHODS: In a retrospective, cross-sectional study, we collected patient data for all 206 cases of HP diagnosed within our UK-based regional NHS interstitial and occupational lung disease service, 2002-17. This included demographics, environmental and occupational exposures, clinical features, and diagnostic tests (CT imaging, bronchiolo-alveolar cell count, lung function, histology). We grouped the data by cause (occupational, non-occupational and unknown) and by presence or absence of fibrosis on CT, in order to undertake hypothesis testing. RESULTS: Cases were occupational (n = 50), non-occupational (n = 56) or cryptogenic (n = 100) in aetiology. The commonest causes were birds = 37 (18%) and MWF = 36 (17%). Other occupational causes included humidifiers and household or commercial waste, but only one case of farmers' lung. Cryptogenic cases were associated with significantly older age, female gender, lower lung function parameters, fewer alveolar lymphocyte counts >20%, and fibrosis on CT; exposure information was missing in 22-33% of cryptogenic cases. CONCLUSION: MWF is the commonest occupational cause of HP, where workers usually present with more acute/subacute features and less fibrosis on CT; refuse work is an emerging cause. Cryptogenic HP has a fibrotic phenotype, and a full occupational history should be taken, as historical workplace exposures may be relevant.

Occupational asthma; the limited role of air-fed respiratory protective equipment.

BACKGROUND: Evidence-based reviews have found that evidence for the efficacy of respiratory protective equipment (RPE) in the management of occupational asthma (OA) is lacking. AIMS: To quantify the effectiveness of air-fed RPE in workers with sensitizer-induced OA exposed to metal-working fluid aerosols in a car engine and transmission manufacturing facility. METHODS: All workers from an outbreak of metal-working fluid-induced OA who had continuing peak expiratory flow (PEF) evidence of sensitizer-induced OA after steam cleaning and replacement of all metal-working fluid were included. Workers kept 2-hourly PEF measurements at home and work, before and after a strictly enforced programme of RPE with air-fed respirators with charcoal filters. The area-between-curve (ABC) score from the Oasys plotter was used to assess the effectiveness of the RPE. RESULTS: Twenty workers met the inclusion criteria. Records were kept for a mean of 24.6 day shifts and rest days before and 24.7 after the institution of RPE. The ABC score improved from 26.6 (SD 16.2) to 17.7 (SD 25.4) l/min/h (P > 0.05) post-RPE; however, work-related decline was <15 l/min/h in only 12 of 20 workers, despite increased asthma treatment in 5 workers. CONCLUSIONS: Serial PEF measurements assessed with the ABC score from the Oasys system allowed quantification of the effect of RPE in sensitized workers. The RPE reduced falls in PEF associated with work exposure, but this was rarely complete. This study suggests that RPE use cannot be relied on to replace source control in workers with OA, and that monitoring post-RPE introduction is needed.

Hospital Attendances and Acute Admissions Preceding a Diagnosis of Occupational Asthma.

PURPOSE: Occupational exposures are a common cause of adult-onset asthma; rapid removal from exposure to the causative agent offers the best chance of a good outcome. Despite this, occupational asthma (OA) is widely underdiagnosed. We aimed to see whether chances of diagnosis were missed during acute hospital attendances in the period between symptom onset and the diagnosis of OA. METHODS: Patients diagnosed with OA at the regional occupational lung disease service in Birmingham between 2007 and 2018 whose home address had a Birmingham postcode were included. Emergency department (ED) attendances and acute admission data were retrieved from acute hospitals in the Birmingham conurbation for the period between symptom onset and diagnosis. RESULTS: OA was diagnosed in 406 patients, 147 having a Birmingham postcode. Thirty-four percent (50/147) had acute hospital attendances to a Birmingham conurbation hospital preceding their diagnosis of OA, including 35 (24%) with respiratory illnesses, which resulted in referral for investigation of possible OA in 2/35. The median delay between symptom onset and diagnosis of OA was 30 months (IQR = 13-60) and between first hospital attendance with respiratory illness and diagnosis 12 months (IQR = 12-48, range 3-96 months) CONCLUSIONS: The chance to reduce the delay in the diagnosis of OA was missed in 33/35 patients admitted or seen in ED with respiratory symptoms in the period between symptom onset and diagnosis of OA. The diagnosis of OA was delayed by a median of 12 months by failure to ask about employment and work relationship of symptoms.

Do laboratory challenge tests for occupational asthma represent what happens in the workplace?

Specific inhalation challenge (SIC) is the diagnostic reference standard for occupational asthma; however, a positive test cannot be considered truly significant unless it can be reproduced by usual work exposures. We have compared the timing and responses during SIC in hospital to Oasys analysis of serial peak expiratory flow (PEF) during usual work exposures.All workers with a positive SIC to occupational agents between 2006 and 2015 were asked to measure PEF every 2 h from waking to sleeping for 4 weeks during usual occupational exposures. Responses were compared between the laboratory challenge and the real-world exposures at work.All 53 workers with positive SIC were included. 49 out of 53 had records suitable for Oasys analysis, 14 required more than one attempt and all confirmed occupational work-related changes in PEF. Immediate SIC reactors and deterioration within the first 2 h of starting work were significantly correlated with early recovery, and late SIC reactors and a delayed start to workplace deterioration were significantly correlated with delayed recovery. Dual SIC reactions had features of immediate or late SIC reactions at work rather than dual reactions.The concordance of timings of reactions during SIC and at work provides further validation for the clinical significance of each test.

Fractional exhaled nitric oxide in the interpretation of specific inhalational challenge tests for occupational asthma.

PURPOSE: Fractional exhaled nitric oxide (FENO) measurements are recommended for the assessment of eosinophilic airway inflammation in asthma. Clinically relevant increases in FENO have been reported 24 h after positive specific inhalational challenge (SIC) tests in occupational asthma. We aimed to determine whether positive SICs could be discriminated from control tests, on the basis of change in FENO. METHODS: We reviewed all positive SICs to a variety of agents performed at our institution 2008-2012 and gathered data on age, sex, asthmatic response (immediate/dual/late), smoking status, inhaled corticosteroid usage, and FENO pre- and 24-h postcontrol and positive SIC from each worker. Changes in FENO after positive SICs were compared with control SICs from each worker, by using paired Student's t tests. RESULTS: In 16 workers, negative control challenges were associated with mean changes in FENO of 9 % (95 % CI -1.14 to 19.01) or 1.1 ppb (95 % CI -3.59 to 5.84); 2 of 16 (13 %) workers tested showed increases in FENO that were clinically relevant based on recent guidelines. Subsequent positive SICs were associated with mean changes in FENO of 7 % (95 % CI −15.73 to 29.6) or 2.1 ppb (95 % CI -6.07 to 10.19), which were not significantly different to controls; only 2 of 16 (13 %) workers had FENO changes that were clinically relevant. CONCLUSIONS: FENO changes above the upper confidence limits of ≥20 % or ≥6 ppb may be considered to be outside the range of normality. However, the majority of workers who had clearly positive SICs to common low molecular weight agents also had no statistically or clinically relevant increase in FENO. Therefore, change in FENO does not predict a positive SIC in this group.

Differences in serial lung function recorded on four data-logging meters.

OBJECTIVE: Lung function measurements performed several times daily are useful for the diagnosis of occupational asthma. Patient fabrication of hand-recorded charts can limit confidence in the results; this is overcome using electronic meters that log time and measurement. We have compared individual and meter differences in FEV1 and PEF recorded by hand and from meter logs using expert subjects on four data-logging spirometers with different methods of measurement and different quality control software. METHODS: Eight workers in a respiratory physiology department were asked to record FEV1 and PEF 2-hourly from waking for 7 days using four electronic meters (Easyone, Micro DL, Vitalograph Diary card 2110 and Piko-1) in random order. Subjects hand-recorded the best FEV1 and PEF from each session, this was compared with the logged data. RESULTS: Discordant measurements from individuals were lower for FEV1 than PEF and differed from 4.4-19.1% for FEV1 (mean 9.4%, p < 0.0001) and 6-23.3% for PEF (mean 12.6, p < 0.0001). There were also significant differences between meters for both variables (p < 0.0001). The magnitude of the differences in PEF was highest for the Easyone (34l/min) and lowest for the Vitalograph Diary card 2110 (14l/min) and varied significantly between meters (mean 22l/min, p = 0.002). CONCLUSIONS: Differences between hand-recorded and logged measurements are unlikely to be due solely to patient fabrication and can be due to quality criteria or other unclear software requirements applied after the results are shown on the meter screen; they differ between meters. Whether the differences shown affect clinical outcome will require further investigation.

Chronic airflow limitation in a rural Indian population: etiology and relationship to body mass index.

PURPOSE: Respiratory conditions remain a source of morbidity globally. As such, this study aimed to explore factors associated with the development of airflow obstruction (AFO) in a rural Indian setting and, using spirometry, study whether underweight is linked to AFO. METHODS: Patients > 35 years old attending a rural clinic in West Bengal, India, took a structured questionnaire, had their body mass index (BMI) measured, and had spirometry performed by an ancillary health care worker. RESULTS: In total, 416 patients completed the study; spirometry was acceptable for analysis of forced expiratory volume in 1 second in 286 cases (69%); 16% were noted to exhibit AFO. Factors associated with AFO were: increasing age (95% confidence interval (CI) 0.004-0.011; P = 0.005), smoking history (95% CI 0.07-0.174; P = 0.006), male gender (95% CI 0.19-0.47; P = 0.012), reduced BMI (95% CI 0.19-0.65; P = 0.02), and occupation (95% CI 0.12-0.84; P = 0.08). The mean BMI in males who currently smoked (n = 60; 19.29 kg/m(2); standard deviation [SD] 3.46) was significantly lower than in male never smokers (n = 33; 21.15 kg/m(2) SD 3.38; P < 0.001). AFO was observed in 27% of subjects with a BMI <18.5 kg/m(2), falling to 13% with a BMI ≥18.5 kg/m(2) (P = 0.013). AFO was observed in 11% of housewives, 22% of farm laborers, and 31% of cotton/jute workers (P = 0.035). CONCLUSION: In a rural Indian setting, AFO was related to advancing age, current or previous smoking, male gender, reduced BMI, and occupation. The data also suggest that being under-weight is linked with AFO and that a mechanistic relationship exists between low body weight, smoking tobacco, and development of AFO.

Do long periods off work in peak expiratory flow monitoring improve the sensitivity of occupational asthma diagnosis?

INTRODUCTION: Serial peak expiratory flow (PEF) monitoring is a useful confirmatory test for occupational asthma diagnosis. As weekends off work may not be long enough for PEF records to recover, this study investigated whether including longer periods off work in PEF monitoring improves the sensitivity of occupational asthma diagnosis. METHODS: Serial PEF measurements from workers with occupational asthma and from workers not at work during their PEF record, containing minimum data amounts and at least one rest period with > or = 7 consecutive days off work, were analysed. Diagnostic sensitivity and specificity of the area between the curves (ABC) score from waking time and Oasys score for occupational asthma were calculated for each record by including only consecutive rest days 1-3 in any rest period, including only consecutive rest days from day 4 onwards in any rest period or including all available data. RESULTS: Analysing all available off work data (including periods away from work of > or = 7 days) increased the mean ABC score by 17% from 35.1 to 41.0 l/min/h (meaning a larger difference between rest and work day PEF values) (p=0.331) and the Oasys score from 3.2 to 3.3 (p=0.588). It improved the sensitivity of the ABC score for an occupational asthma diagnosis from 73% to 80% while maintaining specificity at 96%. The effect on the Oasys score using discriminant analysis was small (sensitivity changed from 85% to 88%). CONCLUSIONS: Sensitivity of PEF monitoring using the ABC score for the diagnosis of occupational asthma can be improved by having a longer period off work.

Two variants of occupational asthma separable by exhaled breath nitric oxide level.

UNLABELLED: Exhaled nitric oxide (FE(NO)) has been used as a marker of asthmatic inflammation in non-occupational asthma, but some asthmatics have a normal FE(NO). In this study we investigated whether, normal FE(NO) variants have less reactivity in methacholine challenge and smaller peak expiratory flow (PEF) responses than high FE(NO) variants in a group of occupational asthmatics. METHODS: We measured FE(NO) and PD(20) in methacholine challenge in 60 workers currently exposed to occupational agents, who were referred consecutively to a specialist occupational lung disease clinic and whose serial PEF records confirmed occupational asthma. Bronchial responsiveness (PD(20) in methacholine challenge) and the degree of PEF change to occupational exposures, (measured by calculating diurnal variation and the area between curves score of the serial PEF record in Oasys), were compared between those with normal and raised FE(NO). Potential confounding factors such as smoking, atopy and inhaled corticosteroid use were adjusted for. RESULTS: There was a significant correlation between FE(NO) and bronchial hyper-responsiveness in methacholine challenge (p = 0.011), after controlling for confounders. Reactivity to methacholine was significantly lower in the normal FE(NO) group compared to the raised FE(NO) group (p = 0.035). The two FE(NO) variants did not differ significantly according to the causal agent, the magnitude of the response in PEF to the asthmagen at work, or diurnal variation. CONCLUSIONS: Occupational asthma patients present as two different variants based on FE(NO). The group with normal FE(NO) have less reactivity in methacholine challenge, while the PEF changes in relation to work are similar.

Serial lung function variability using four portable logging meters.

OBJECTIVE: Portable lung function logging meters that allow measurement of peak expiratory flow (PEF) and forced expiratory volume in 1 second (FEV(1)) are useful for the diagnosis and exclusion of asthma. The aim of this study was to investigate the within and between-session variability of PEF and FEV(1) for four logging meters and to determine the sensitivity of meters to detect FEV(1) and PEF diurnal changes. METHODS: Thirteen assessors (all hospital staff members) were asked to record 1 week of 2-hour PEF and FEV(1) measurements using four portable lung function meters. Within-session variability of PEF and FEV(1) were compared for each meter using a coefficient of variation (COV). Between-session variability was quantified using parameter estimates from a cosinor analysis which modeled diurnal change for both lung function measures and also allowed for variation between days for individual sessions. RESULTS: The mean within-session COV for FEV(1) was consistently lower than that for PEF (p < 0.001). PEF showed a higher but not significantly different (p = 0.068) sensitivity for detecting diurnal variation than FEV(1). PEF was also slightly more variable between days, but not significantly different than FEV(1) (p = 0.409). PEF and FEV(1) diurnal variability did not differ between the 4 meters (p = 0.154 and 0.882 respectively), but within-session FEV(1) COV differed between meters (p = 0.009). CONCLUSION: PEF was marginally more sensitive to within-day variability than FEV(1) but was less repeatable. Overall, differences between the 4 meters were small, suggesting that all meters are clinically useful.