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= Basic data interpretation: Overview Data =
Long term trends in the efficacy data are important for many reasons. One of the most important is that we all have the occasional bad night where the AHI is much higher than normal or the leaks are awful. Occasional bad nights do not indicate that there's something wrong with the way the PAP therapy is going. (Well, a really awful night for leaks might indicate it's time to replace those nasal pillows or to check whether the mask was put together correctly.) Sleep docs tend to focus almost exclusively on the long term data---a small number of well understood summary numbers and graphs are easier to look at than a massive amount of daily data when you are meeting with large numbers of patients each month.
'''Overview data'''
The Overview data is a graphical representation of the highlights of the Detailed Daily data over a range of days (or months or years). Each of the graphs is either a bar graph or a line graph with one entry for each day's data. The following screen shot shows three of the more useful Overview data graphs from my husband's data:<br />
[[File:overview1_zps35d8e666.jpg]]
<br />
'''The AHI graph'''
The bar for each day's AHI data is split into three colors; the relative sizes of each bar tell you the relative number of events. Bars that are<br />
* mostly dark blue (like most of hubby's) indicate the user had more Hs scored than other events,
* mostly light blue indicate the user had more OAs scored than other events, and
* mostly purple indicate the user had more CAs scored than other events.<br />
Looking at the data as a whole, we see that it took hubby about three weeks to really settle into PAP and have the AHI come down to what's now his normal range. It's also interesting to note the spike in AHI on June 12. Hubby had a bike accident on that day and got scrapped up pretty good, broke his right big toe, and got a significant laceration on his right ankle as well as banged up his shoulder. So he was in pain that night. My guess is the pain is related to the higher AHI. (I've noticed this in my own data as well.)
The usage graph is not one we talk about much here, but we can see from the number at the top left of the graph that hubby is averaging 6:57 hours of mask time and that he's only had two days with really significant problems keeping the mask on. (One of those nights was when we were driving overnight across country and didn't get to our destination until around 7:00 AM and hubby went to bed after we got in; the other was another cross country drive where we got in about 3:00.)
The Session Times graph give a good over view of your sleep patterns. If you sleep well, this graph probably won't be of much interest. If you have problems with insomnia or circadian rhythm problems, looking at the patterns in this graph may go a long way towards explaining why you may not be feeling much better even with PAP: PAP fixes OSA, but it does not fix bad sleep that are caused by other things. In hubby's Session Times data, it's easy to see that hubby's wake up times are a bit more regular than his bedtimes. It's also easy to spot which nights he had trouble keeping the mask on.
Scrolling down we can see additional graphs. Three more graphs that are often useful are shown below:
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[[File:overview2_zps72255898.jpg]]
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The Leaks and Total Leaks graphs show the maximum, 95%, and median Leaks and Total Leaks for each day. The 95% (or 90%) and median Leak graphs are are more important than the maximum values. Hubby has had a few days where his 95% leak rate is pretty high, but not high enough to have had any leaks flagged as Large Leaks in his Daily Data.
The Peak AHI graph gives graphical information about the number of apneas and hypopneas recorded in any 60 minute period during the given night's data. The Maximum Peak AHI is the maximum number of events that occurred during any one hour of the given night; this is a crude measure of how bad the worst hour of the night was. The Maximum Peak AHI values are usually going to be quite a bit higher than the overall AHI for the night because for most of use, once we start PAPing we have long period with no events and hopefully many hours where the hourly AHI is at or close to 0.
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= Basic data interpretation: Statistics Data =
Long term trends in the efficacy data are important for many reasons. One of the most important is that we all have the occasional bad night where the AHI is much higher than normal or the leaks are awful. Occasional bad nights do not indicate that there's something wrong with the way the PAP therapy is going. (Well, a really awful night for leaks might indicate it's time to replace those nasal pillows or to check whether the mask was put together correctly.) Sleep docs tend to focus almost exclusively on the long term data---a small number of well understood summary numbers and graphs are easier to look at than a massive amount of daily data when you are meeting with large numbers of patients each month.
In this post, we'll focus on how Sleepy Head presents the long term summary data.
'''Organization of the Statistics Page'''
Below the SleepyHead header, the Statistics Page looks like this:
<br />
[[File:statistics_overview_zps819c6797.png]]
<br />
As you can see, the Statistics page has three major parts and two different "views". The parts are:
''The CPAP Statistics.'' This chart has two distinct '''Report Modes'''. The ''Standard'' mode, which is shown here, is the default mode and it provides summary numbers for standard CPAP data reported for time ranging from the '''Most Recent''' (latest one-night) data to the data for the last year. The ''Monthly'' report gives summary numbers for each of the last 12 calendar months of data.
''Changes to Prescription Settings''. This chart provides a list of all machine/prescription settings you have used. For a newbie, this chart should be relatively straightforward.
''Machine Information chart.'' This shows the make, model, and serial number for each PAP machine that you've used with SleepyHead, as well as the first and last dates of usage.
The idea behind the Statistics Page is to provide a quick numerical view of the most important numbers from the efficacy data. This is the data that most DMEs print out from the proprietary software if the sleep doctor or insurance company wants more than just usage data. The organization of the summary data in the proprietary software varies from brand to brand, and we won't look at how the proprietary software organizes this data.
'''A detailed look at the CPAP Statistics'''
Here is my CPAP Statistics chart:
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[[File:CPAP-statistics_zps1e21a1e7.png]]
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You will notice that the total number of days of CPAP data is listed immediately under the header '''CPAP Statistics'''. CPAP data includes data from any kind of PAP machine that you have imported into the SleepyHead profile you are using. The dates of the range of data is also listed.
It's important to note that:
* Until you have more than 7 days of data the numbers in all columns except '''Most Recent''' will be the same
* Until you have more than 30 days of data the numbers in all columns except '''Most Recent''' and '''Last Week''' will be the same
* Until you have more than 6 months of data the numbers in the '''Last 6 months''' and '''Last year''' columns will be the same.
As you accumulate more and more data, you will start to notice that the numbers in the Last 6 months and Last year do not change very much from day to day.
The data in the CPAP Statistics is gathered in sections. We'll examine each of them in turn.
<br />
'''CPAP Usage data'''
The first two lines concern usage or compliance data:
<br />
[[File:CPAP_Usage_zpsc9d98063.png]]
<br />
The numbers for '''Average hours per night''' is a simple average: Add up the usage for each night in the time period and divide by the number of days in the time period. We can see that I didn't get much sleep last night (July 4) and that I'm averaging about 6 hours of mask time (and bed time) over the last year. There's a bit of variation between the 7-day, 30-day, 6-month, and 1-year figures, but the variation is not significant.
Sleepy Head defines '''Compliance''' for a given night as "usage is at least four hours". The line for defining Compliance can be set in the Sleepy Head preferences if desired. The percentage in the '''Compliance''' column is simply the percentage of days in the time period where the usage was at least four hours. The fact that my 1-year compliance is listed as 96% means that I used my CPAP for at least 4 hours on roughly 350 or 351 days. (Both 350/365 and 351/365 round to 0.96). Of the 15 days where I was not compliant, most of them are nights where I got less than 4 hours of sleep. Notably, however, two nights were sleep tests that I did last summer.
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'''
Therapy Efficiacy data'''
The Therapy Efficiacy data are the numbers that measure the overall effectiveness of your PAP therapy. The whole point of PAPing is to get and keep the AHI below 5.0 long term while also having the leaks under control and getting enough sleep to feel well in the daytime. Here's my Therapy Efficacy data:<br />
[[File:Therapy_Efficiacy_zpse827284e.png]]
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The indices in this list are the same as those listed on the Left Side Bar in the Daily Data. Exactly which indices will be listed here depends on the machine you are using:
* PR System One users will see everything on my list.
* Resmed S9 users will see the AHI, Obstructive Apnea Index (OAI), the Hypopnea Index (HI), and Central Apnea Index (CAI).
* DeVilbass Intellipap users will see the AHI, Apnea Index (AI), NonResponding Apnea Index (NRAI), and the Hypopnea Index (HI).
* F&P Icon users will see the AHI, Apnea Index (AI), and Hypopnea Index (HI).
The long term indices are computed in the same way the nightly indices are computed: SH counts the number of events recorded during the time frame for the index and divides that by the total run time for the time frame. In other words the long term indices are long term averages.
As an example: My 6th month AHI = 1.79. This means that:
:(total number of OAs + Hs + CAs in the last six months)/(total run time in last 6 months) = 1.79
In other words, in the last 6 months, I've had an average of 1.79 events each hour of sleeping with the machine. Some hours I've had a lot more than that; other hours I've had no events. But the expected number of events per hour of sleep would be 1-2 events each hour.
All the other indices are computed the same way and have the same meaning.
When we look at the numbers in aggregate, we can see some interesting things about my data:
* My '''Last Week''' numbers are quite a bit better than my 6-month and 1-year numbers. That means that my OSA has been better controlled this week than it has on average for the last 6 months. I know that my AHI numbers tend to be somewhat cyclic each month, and this week has been a "good" week.
* The '''Last Month''' data is a bit better than the 6-month and 1-year data. So the last month has been a pretty good one in terms of PAP therapy. SH data cannot provide an explanation of why it's better. However I'm through my spring allergy season and the summer allergies have not been that bad this year. And that may be a partial explanation for why the 30-day numbers are a bit better than the 6-month and 1-year numbers. More than likely my 30-day AHI will go back up once Ragweed starts to pollenate in the fall.
* The '''Last 6 month''' numbers are a tiny bit better than the Last year. The difference is not statistically significant. And taken together, the 6-month and 1-year numbers say that my machine is doing its job of preventing most of my apneas and hypopneas from happening. A long term AHI < 2.0 is quite good.
'''
Leak Statistics'''
The '''Leak Statistics''' are based on the Sleepy Head '''Leak''' data. Sleepy Head uses '''Leak''' to represent the excess or ''unintentional'' leak rate. In other words, for machines that record '''Total Leak Rate''' data, it's important to understand that
:Leak Rate = Total Leak Rate - Intentional Leak Rate
SleepyHead uses a statistical analysis to estimate the intentional leak rate from the Total Leak Rate data and uses that to compute the Leak Rate. For more details about how SleepyHead handles Leak Rate and Total Leak Rate data see 8. Leaks.
My summary Leak Statistics data looks like this:<br />
[[File:Leaks-Statistics_zps82d4b2bb.png]]
<br />
NOTE: I've changed my "top percentile" calculations to the 90% instead of the 95% because Encore reports 90% figures instead of 95%. Most SH users will see 95% numbers where my data shows 90% numbers.
The ''average'' and ''90%'' leak rates must be interpreted in terms of the statistical meanings of the words average and 90% (90th percentile) of a data set. For those who do not remember any about averages or percentiles, I suggest that you read [http://adventures-in-hosehead-land.blogspot.com/2012/03/average-median-95-numbers-guide-to.html Average, Median, 95% numbers: A guide to those who don't remember their introductory stats].
We'll start with the 90% (or 95%) leak rates because they are actually easier to understand in terms of PAP therapy.
The 90% and 95% leak rates are the 90th and 95th percentiles for the entire set of leak data for the given time frame. We can informally think about the computation needed to find the '''Last Week''' 90% leak rate as follows: Loosely speaking, the PAP machine has sampled the leak rate a finite number of times in the last 7 days. So for the 7-day 90% leak rate, we can informally think of lining up all the sample leak data points for the last 7 days in increasing order. If there are 10000 sample data points on our list, we find the 90% by finding the 9000th number on the list because .90*10000 = 9000. The 95% leak rate would be the 9500th number on our list.
The 90% leak rates for 30-day, 6-month, and 1-year are found the same way: We line up all the data points for leak rate for the entire time period in increasing order. If there are n points on the entire list, we first find the integer k that is equal to or just barely bigger than 0.9*n and then we find the kth number on the list.
The meaning of the long term 90% leak rate is the same as the meaning of the daily 90% leak rate in the Detailed Daily data. The fact that my 90% 6-month leak rate equals 3.0 means that for 90% of the time my BiPAP has been on in the last 6 months, the unintentional leak rate has been AT or LESS than 3.0 L/min. We can also say that my unintenional leak rate was ABOVE 3.0 for no more than 10% of the time my machine was running in the last 6 months. Which means that long term I have no serious leak problems to worry about.
The average leak rate for a given time frame is just the (weighted) average for all the leak data in that time frame. In other words to compute the 7 day average leak rate, we look at all the leak rate data for the last 7 days as one data set and find the (weighted) average for the large data set. Loosely speaking, the PAP machine has sampled the leak rate some very large, but finite number of times in the last 7 days. You add up all the "leak rate data points for the last 7 days" and divide by the total number of data points in the 7 days and you get the weighted average leak rate for the last 7 days.
The average leak rate for the last 30 days, last 6 months, and last year is computed the same way: Informally, you add up all the sample leak rate data points for the last 30 days, 6 months, or year (respectively) and divide by the total number of data points for the same period of time.
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'''GEEK ALERT''' Skip the following paragraph if your eyes are starting to glaze over because you don't like dealing with statistics.
Understanding the long term average leak rate numbers is a bit more difficult simply because average leak rates do not have a simple "time" interpretation. Technically speaking, the leak curve is a continuous graph for each night. For the 7-day average leak rate, we string all seven of the leak curves together to get one very long curve that traps a finite amount of area between it and the horizontal axes for the graph. The 7-day average value for the leak rate would be the area under the 7-day leak curve divided by the total time the machine was running for the last 7 days. In other words, the 7-day average leak rate is just the average height of the leak curve over the course of the last 7 nights. (The idea is that the area under the curve really can just be thought of as the sum of the data points and the length of time is then just the number of data points.)
'''Note:''' Because of the way weighted averages are computed, we cannot anything about how long the leak rate was AT or BELOW the 7-day, 30-day, 6-month, or 1-year average leak rates.
<br />
'''Pressure Statistics'''
The '''Pressure Statistics''' are not very interesting if you are using a fixed pressure PAP machine, your max pressure and 90% or 95% pressure levels should equal your pressure setting. Your minimum pressure level and your average pressure level will be less than your pressure setting if you use the Ramp feature. The minimum pressure level will most likely be the starting Ramp pressure.
The '''Pressure Statistics''' are more interesting if you are using an Auto PAP in Auto mode.
My summary Pressure Statistics data looks like this:<br />
[[File:pressure_zps4027bd44.png]]
<br />
Two things need to be pointed out about my Pressure data:
* Most people will have either "Pressure" data and no IPAP/EPAP data OR they'll have IPAP/EPAP data and no "Pressure" data. I'm not sure why I have both. It's probably a SleepyHead bug.
* I've changed my "top percentile" calculations to the 90% instead of the 95% because Encore reports 90% figures instead of 95%. Most SH users will see 95% numbers where my data shows 90% numbers<br />
Several things should be pointed out about pressure data:
* Users of DeVilbass Intellipap CPAP/APAPs, F&P Icon CPAP/APAPs, and PR System One CPAP/APAPs will have Pressure data.
* Bi-level users will have IPAP/EPAP data regardless of the brand of machine.
* Resmed S9 CPAP/APAP users who use EPR will have IPAP/EPAP data because these machines act very similar to bi-levels. The IPAP data is the pressure level data; the EPAP data is the pressure level - EPR setting. In other words, if the pressure is 8 and EPR = 2, the IPAP = 8 and the EPAP = 6 = 8 - 2.
* If you use a Ramp, the Ramp pressures ARE used in the statistical computations. The min pressure, min IPAP, and min EPAP pressure numbers will typically be those used at the start of your ramp.
* The meaning of 90%, 95%, and average pressure and IPAP numbers are similar to the meanings of 90%, 95%, and average leak rates.
* The minimum and maximum pressure (IPAP/EPAP) numbers are true minimums and maximums. In other words, the 6-month min pressure number is the lowest pressure that's been recorded in the last 6 months; the 1-year maximum IPAP is the highest IPAP pressure that's been recorded in the last year.
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'''Bugs in the CPAP Statistics data'''
There are some bugs in the CPAP Statistics numbers. So if a number obviously does not make sense, its best to disregard the number. Resmed S9 summary data has been particularly challenging for JediMark to work with if no detailed daily data is available for some days. The summary data stored for a day with multiple sessions is not sufficient to compute the long term percentiles and averages when only the summary data is available.
= Important preferences settings =
= Leaks =
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