1. Extending the use of timepoint diagnosis of occupational asthma
Cedd Burge, Vicky Moore, Charles Pantin, Alastair Robertson, Sherwood Burge
Heart of England NHS FT
Last year we presented work on timepoint diagnosis of occupational asthma from serial peak flow records. This talk is about changes we have made to the method to address some shortcomings. Firstly I will describe the original timepoint method and a novel method of analysing specific inhalation challenges on which it is based.

2. Specific Inhalation Challenge Graph
Timepoint diagnosis is based on a new method of analysis specific inhalation challenges. This graph shows the traditional method of analysis. Explain graph, everyone knows already really. Visually the difference looks greater than the 2 drops below baseline. Why is a 20% drop required, is it too high, too low and should it be the same for everybody.

3. Stenton et al propose a new method of Specific Inhalation Challenge
FEV1 readings are taken every hour (11 hours total) for 3 baseline days
A one way ANOVA is performed on the 3 baseline days to produce an estimate of the day to day variability
FEV1 readings are taken every hour after a controlled exposure
For the result to be positive a drop outside of a Bonferonni adjusted 95% confidence limit is required from the mean of the baseline days
5%-8% drop required in the three patients tested (and it worked!)
Stenton SC, Avery AJ, Walters EH, Hendrick DJ , Statistical approaches to the identification of late asthmatic reactions , Eur Respir J , 1994 ; 7 :
Talk slowly lots of info here. State matching times. Between day variability is the between sessions error variance / sd from the anova which is a measure of the pooled standard deviatoin.

4. Example Challenge Graph using the Stenton Method
Mean of 3 control days
Lower boundary
Exposed Day
Explain graph, only one or two drops are required and there are many, negative using traditional 20% method

5. Serial PEF records
PEF readings every 2 waking hours for a 4 week period.
Used to diagnose Occupational Asthma
“Health practitioners who suspect a worker of having occupational asthma should arrange for workers to perform serial peak flow measurements at least four times a day” (BOHRF Guidelines Principal Reccomendation)
1 week of 4 shown

6. Timepoint Analysis (method adapted for serial PEF records)
Colours show 2-hourly grouped readings, green = days off
All days off are used for the 2-hourly baseline and variability
All work days used for mean exposed day
Sensitivity 77%
Specificity 88%
Analyses 43% of records
Method designed to have a specificity of 95%, actually only 88% so some problems with the statistical validity / assumptions.
Specificty increased to 92% by ignoring waking drops which made us think that that waking readings could be a problem. We also only looked at patients that woke up on similar times on work days and days off to avoid problems with diurnal variation. This restriction removes about 40% of records

7. Modified Timepoint Analysis
Excluded readings within 90 minutes of waking up (lightly shaded)
Applied a different correction factor
Applied a different correction factor for comparing means from different size populations

8. “Time from Waking” instead of “Time of Day” is analysed
Readings grouped by time from waking
Corrects for Diurnal variation
Excluded readings within 90 minutes of waking up
Readings grouped by how long after waking up they were taken. Point to the and 471 all being in the same group and at the same point of the diurnal variation curve. To analyse patients who wake up at significantly different times on work days and days off.

9. Example Oasys 2-Hourly Graph
Original 95% boundary in light blue
New boundary in purple
Explain axes, midnight to midnight, PEF, grey area shows mode times of working

10. Results Version 1 Version 2 From Waking Records Sensitivity
(similar wake)
77%
73%
72%
101
Specificity
88% (92%)
93%
189
(different wake)
76%
88%
70% 83
Bad
Worse 10
Timepoint version 1 still the best method of analysis for records with similar waking times. Anecdotally version 2 overscores with differences in waking up more than the others.
Not enough records to look at specificty (only 6 analysable for v1 and from waking, 4 for v2). Anecdotally have looked at all our gs negatives with zero quality control. Specificty of 70% for v1 and from waking, v2
Time from waking does not appear to be an improvement on version 1. This implies that patients do not record their waking time accurately and / or the time of waking up. Original papers on diurnal variation suggest that wake is the major factor on diurnal variation, staying awake all night had little effect as did lying down all day. (Hetzel and clarke 1977)
Similar wake <= 2 hour difference in waking up on days at work and days off

11. Conclusions Improved theoretical validity
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Conclusions
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Improved theoretical validity
Specificity 92%, Sensitivity 77%
Able to diagnose from smaller changes in PEF thus potentially able to identify disease earlier
Applicable to FEV1 – more data required
Requires low rest day variation and similar waking times for work and days off
Valid for 43% of current records
Lower data quantity requirements than other methods
Exclude days with different waking times
We have improved the theoretical validity of the method by excluding waking readings and applying a different correction factor for comparing means from different size populations. 12

12. Oasys Program is freely avaliable from www.occupationalasthma.com
14/04/ :02:23
14/04/ :02:23
Program is freely avaliable from
Can now download values from Asma-1 and Mini Wright Digital meters
Please see Clement Clarke and Vitalograph stands for more information