<![CDATA[CHRISTY HEALTH INC. - Blog]]>Tue, 08 May 2018 13:38:54 -0400Weebly<![CDATA[Toward a Full View of Sepsis]]>Wed, 25 Apr 2018 18:29:51 GMThttp://christyhealth.com/blog/toward-a-full-view-of-sepsis9782425Post 2 - ​How In-home Data Collection Completes the View of a Sepsis Episode
Heads up: No clinical advice is being offered.

This is post 2 of a series specifically targeted to in-home sepsis detection.  I have a personal stake in making sure I have such a capability – my wife has survived two sepsis episodes and is at high risk of contracting sepsis in the future.  Post 1 is found here.

Sepsis is the body’s extreme response to an infection. It is life-threatening and without timely treatment can rapidly cause tissue damage, organ failure, and death.  Sepsis is a medical emergency. Time matters.” - CDC

In post 1 we showed how vital signs captured in-home can support patient and caregiver efforts to measure the signs of risk.  Vital signs are easily measured and there are many thousands of measuring devices available at reasonable price points.  Christy Health Inc. is where you can capture, manage, and analyze your vital sign data.
In this post we follow-up with data that is not easily captured, managed or analyzed but can be even more insightful than the vitals data.  We look at blood lab results.  For those with chronic conditions, labs are a recurring fact of life, and when in hospital, labs may be taken several times a day, as will be seen below.  When in-home, labs are taken periodically, as ordered by doctors, by visits to a lab, home collection and shipment to a lab, or in a doctor’s office for instance.  In our case, it’s rare to go more than 30 days between blood samples.  It’s not uncommon to have blood drawn 5 or 6 times a month.

Once again, this data is not well managed by anyone other than ourselves.  Most healthcare providers have a website for patients to look up results that organization produced.  However, Christine is currently using four lab companies depending on who ordered what test.  This means, to see the ‘whole’ picture one must aggregated the lab results of all the lab providers.  Over the last 4 years Christine has blood lab results from eleven different companies (including four hospitals).

Some Preliminaries

​In post 1 we didn’t group the data to account for where the data was captured: in-hospital or not in hospital (in-home).  We simply looked at all the data, over time, to get a picture of the whole sepsis episode.  Now we want to introduce the idea of a general proxy for the overall health condition of a person; that is, when the person is in or, not in, the hospital.  This is useful because it gives us the ability to define two states in time by means of a simple rule: in-home → more healthy, in-hospital → less healthy.  We have the timestamps for each reading so grouping in one or the other of these states without overlap is simple.  With data grouped in this way we will be able to compare the measures of the two states, make and test hypotheses.  We’ll do a little informal hypothesis testing in this post and we’ll get more formal in later posts.
As indicated above the overall number of labs and the frequency of sampling is substantially less than for vitals.  We won’t look at the reasons why this is the case, only what it means from the view of the analyst.  To introduce what we are doing and how, we start by picking the results of a single test, AST.

AST (aspartate aminotransferase) is an enzyme that is found mostly in the liver, but also in muscles. When your liver is damaged, it releases AST into your bloodstream. An AST blood test measures the amount of AST in your blood.” [1]

In addition to the result, labs provide an upper and lower range for ‘normal’ results.  Yes, there’s that word ‘normal’ again.  This normal for the population needs greater context and the context comes from the underlying conditions of the individual.  Later in the post an example will be provided.

Admission to the emergency department was approximately 7:00PM on February 12th, 2018.  The most recent blood test was midday February 7th.  As seen in Table 1, the February 7th AST reading was 16U/L.  Five days later, on the 12th, the AST reading was 58.5U/L.  The reading on the 12th came from the first blood workup after being admitted to emergency department (ED). 
As with the graphics for the vitals, the horizontal red dashed lines are the patients longer term in-home (more healthy) 90% and 10%

quantile lines and the black dashed line is the patients median reading.  The thick gray horizontal lines mark the labs high and low range markers.  As can be seen, Christine’s long term, more healthy, 90% and 10% quantiles are well within the lab ranges for the general populations ‘normal’.

What we can say with high confidence is the AST measure on the 12th is not an error and didn’t jump on a single day.  But this begs the question, how did AST evolve from 16U/L on the 7th to 58.5U/L on the 12th?  We’ll come back to this question later in this post.

​Another question goes to our investigation and analysis of the first possible date of sepsis contraction.  If AST has any explanatory power to help answer this question it will be useful.  In addition, if other lab results give corroborating results, we will be able to strengthen the statistical inferences used to make our conclusions.  We will come back to this question in a later post.

​The Pictures of a Sepsis Episode

The dates of interest are:
  • February 5th, the estimated earliest possible date of infection.
  • February 7th, the last blood test before presentation to the emergency department (ED)
  • February 12th, the date presented to the (ED).
  • February 21st, the date discharged from the hospital.
We change slightly the pictures used to view the sepsis episode.  The left-most picture shows more of the pre- and post-episode results to show more context given the sparseness of the measures.  The right-most picture shows the same window of time as the vitals, from January 30th to March 15th.  The reference values table shows the results for in-home (more healthy) and in-hospital (less healthy) states of health.

​It’s easy to see the normal range of AST for Christine (10% quantile of 11U/L to 90% quantile of 26U/L) is well within the lab produce range (5U/L to 34U/L) for Christine’s more healthy state.  On the other hand, Christine’s AST range is well outside the lab produced range during the less healthy state, from February 12th to February 21st.

Following up on a question posed above, how did AST evolve from 16U/L on the 7th to 58.5U/L on the 12th?  There are many statistical technics that can be applied to this question.  We apply the straightforward method of backward shifting a moving average to estimate one potential path.  The basic steps of this method are as follows:
  • Observe the down tick in readings on February 7th from its most recent prior result,
  • Assume the upward AST process could not have started on or before the 7th, 
  • Assume the upward evolution began on the 8th, 
  • The 8th is 4 days from the next test date on the 12th so produce a 4-day moving average,
  • Shift the 4-day moving average backward 4 days. 
This produces the brown line in the right most graph which intersects with the actual result (black) line near the actual reading of 58.5U/L on February 12th.

This helps us in several ways.  First, being able to show ED and ICU staff both the results and timings of the labs and vitals data is immediately helpful for building specific patient context.  Second, it helps us estimate the evolution of infrequently tested data points when working with fast changing health episodes like sepsis.  Note, that once in-hospital lab tests were performed daily at a minimum until the patient was showing improvement and discharged.  We can go back to the total timeseries (left most graph) to see that by early March, Christine was back in to her normal range.  If you’re wondering about that bump up in later March, yes, we know what it is but don’t want to get side tracked from this set of posts about sepsis.  Stories within stories and the data shows it.

Lastly, we have an additional way of determining the first possible sepsis contraction date using blood lab results, in addition to the method using vitals readings.  These methods will be combined in a later post examining the estimation of the sepsis contraction date.

We augment the pictures for labs with more history because of the sparseness of the data relative to the vitals data.  The new picture sets were explained and used above.  We have sufficient data to produce 55 timeseries for unique lab tests over a four-year horizon aggregated from seven lab companies.  Which, is too much for this post.  We limit ourselves in two ways: the long-term time window is from July 1st, 2017 to April 19th, 2018, and to 11 lab test results.  The test results are limited to handpicked, interesting cases coming from the standard blood tests, CBC, Basic Metabolic Panel, and Differential.  In the interest of brevity, AST was already shown, and we don’t show RBC, hematocrit, MCH, MVP, glucose, potassium, chloride, carbon dioxide, anion gap, urea nitrogen, polys, eosinophils, and basophils.

For those not familiar with the test names, abrivations, or meaning, this is a good reference site https://medlineplus.gov/ , and use the search box.   We let the pictures do the talking.
​Red blood cell count and hematocrit follow the same pattern with similar range profiles as hemoglobin and are not shown.
​MCH follows the same pattern with similar range profile as MCV and is not shown.
There are a great many observations that can be made from this data, and we’ll make none of them here. 

What’s Next

​Along with post 1, post 2 demonstrates the possibility of viewing episodic health events by combining in-home and in-hospital data.  We’ve shown a few lab results collected both in-home and in-hospital.  The lab work shown above was performed by four lab companies and combined into a single timeseries for each test.
The next post will combine vitals and lab data to introduce a Sepsis Risk Indication module and to show an analytical method for retrospectively estimating a date of sepsis contraction.  Being able to estimate the infection date of sepsis episodes will be an important contribution to the current state of understanding sepsis.
Subsequent posts will examine how patient introductions to ED staff can be greatly accelerated by use of the graphical history, the importance of individualizing the patients’ normal readings relative to the populations ‘normal’.
Sepsis is a complex process and we use these posts to help build awareness, support those in similar positions as my wife and I, and to offer our services as we are able.
 
References
[1] MedlinePlus https://medlineplus.gov/labtests/asttest.html
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<![CDATA[Toward a Full View of Sepsis]]>Mon, 09 Apr 2018 00:35:07 GMThttp://christyhealth.com/blog/toward-a-full-view-of-sepsisPost 1 - How In-home Data Collection Completes the View of a Sepsis Episode
Heads up: No clinical advice is being offered.
This is post 1 of a series specifically targeted to in-home sepsis detection.  I have a personal stake in making sure I have such a capability – my wife has survived two sepsis episodes and is at high risk of contracting sepsis in the future. 
Sepsis is the body’s extreme response to an infection. It is life-threatening and without timely treatment can rapidly cause tissue damage, organ failure, and death.  Sepsis is a medical emergency. Time matters.” - CDC
Even though we are sepsis experienced we are by no means sepsis experts.  We are working with a great healthcare team.  They ‘see’ what is measured and recorded by their specialist colleagues after the fact.  They don’t ‘see’ what’s measured in-home.  We believe considerable value can accrue from in-home measurements corroborate and coordinated with in-hospital measurements.  Time is valuable when detecting sepsis and in-home measurements can fill an existing information gap when information is most valuable – at the start of an episode.
The pictures that follow visually describe a sepsis episode for one person with a unique clinical history.  The data is a combination of in-home and in-hospital collected data.  The circumstances of every reading is captured in detail.  The details of the clinical history, sepsis episode and data capture will be described in subsequent posts.

The Pictures of a Sepsis Episode

The dates of interest are
  • February 5th, the estimated earliest possible date of infection.
  • February 12th, the date presented to the emergency department (ED).
  • February 21st, the date discharged from the hospital.
Starting the pictures at January 30th and ending at March 15th is for convenience, the objective being to show sufficient pre and post episode data to show the full cycle for each of the reading sets.
In each graphic, the red dashed lines are long term 90% and 10% quantiles, while the black dashed line is the long term 50% quantile (median).  A 15-day moving average is shown in each readings graphic, as well as, each data point.  The data points are collected at irregular time intervals so, longer horizontal lines are only indicative of longer periods of time between the capture of consecutive readings.
  1. Systolic and diastolic blood pressure and mean arterial pressure (MAP) were more volatile than patient’s normal during the episode but didn’t diverge out of the patient’s normal range to any important extent.
  2. Once symptoms started manifesting, pulse rose sharply, stabilized at a high rate after treatment started and gradually started to revert toward the patient’s normal.When treatment was underway the volatility of pulse decreased at the high pulse rates.
  3. Temperature was the first vital sign that varied outside the patient’s normal range.It became very volatile in ED and ICU while the patient was experiencing waves of chills and fevers for two days after treatment started reaching a high of 104.0F and lows of 96.0F.
  4. The respiration rate tracked closely with pulse, spiking just after ED admittance (no correlation implied) stabilizing at a high rate once treatment began and then slowly decreased over time.  For this patient’s age the solid black lines are ‘normal’.  The difference between normal for the general population and the patient will be examined in later posts.
  5. While not a vial sign, we track weight closely because of the patient’s end stage renal failure condition and dialyzes treatments.  Managing fluid volume is an important part of the dialysis treatment and weight is an indicator of how well fluid volume is being managed.  In the hospital, as IVs pushed fluids in, the patient’s weight rose.  This is because the kidneys failed, and urination stopped for four days.  Dialysis was provided to manage this situation.  Over the 9 days in-hospital there were 6 dialysis treatments that pulled approximately 18 liters of fluid out of her body.

What’s Next

This introductory post demonstrates the possibility of viewing episodic health events by combining in-home and in-hospital data.  We’ve shown a few of the possible readings and data points collected both in-home and in-hospital.  Adding pre and post lab results performed outside of hospital to lab work completed in-hospital will be shown in a later post.  Additionally, later posts will examine how patient introduction to ED staff can be greatly accelerated by use of the graphical history. 
There will be a post introducing a Sepsis Risk Indication module.  That post will include a discussion about the importance of knowing what the patient’s normal readings are relative to the populations ‘normal’.  Yet another post will describe a method for retrospectively estimating the first possible infection date.  Being able to estimate the infection date will be an important contribution to the current state of understanding sepsis.
Sepsis is a complex process and we use these posts to help build awareness, support those in similar positions as my wife and I, and to offer our services as we are able.
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<![CDATA[Christy‚Äôs home hemodialysis treatment - A typical day.]]>Mon, 08 Jan 2018 18:31:23 GMThttp://christyhealth.com/blog/christys-home-hemodialysis-treatment-a-typical-dayChristy and her caregiver set up the dialysis machine as they were trained, following the manuals, and based on their experience.  While the machine is priming, Christy performs the pretreatment measurements and data collection.  These include: weight, sitting and standing blood pressure and pulse, and temperature.  There are many other data points that may need to be captured on any given treatment day depending on the specific circumstances and needs.  More on these details in a future blog post.
 
It’s agreed that 1 Liter of fluid should to be removed this treatment.  The snap and tap is performed and pretreatment is competed all the way to being ready to connect to her access.  Christy continues to use the catheter originally place in her neck and upper chest.  Christy is using a catheter for her access for a variety of reasons.  If you have a fistula or graft, the access care and management is somewhat different, but the overall hemodialysis treatment is the same.
 
Today her caregiver is not changing the catheter dressing.  This happens once a week because she uses Tegaderm CHG by 3M (Chlorhexidine Gluconate I.V. Securement Dressing – Gel pad contains 2% w/w CHG [TM]).  After gloving and masking, caregiver removes the arterial (red) toggle cap, cleans, aspirates and flushes the line noting a smooth easy pull and push of the syringe, then connects the line.  No heparin is needed as yesterday’s pod and post were clear.  The step is then repeated on the venous (blue) lines and dialysis is ready to be performed. 
 
The caregiver sets up the machine with specific starting rates and volumes learned by experience.  After checking that all lines that should be open are open and all lines that should be closed are closed; the kidney button is pressed to begin treatment.  In less than a minute readings start to indicate a normal start, and the caregiver starts documenting the blood flow rate, pressures as well as all the other treatment observation data.  We’ll discuss much more about this in a future blog post.
 
Caregiver gradually increases the blood flow rate incrementally making note of the arterial and venous pressures until the blood flow rate is running at 400 milliliters per minute.  This is the target run rate for Christy.  Every 30 minutes the caregiver takes note of blood pressure, pulse, dialysate, UF and the arterial, venous and effluent pressures. After about 2.5 hours the treatment is almost complete.
 
They prepare to return the blood and stop the dialysis machine.  The caregiver disconnects the arterial line from Christy, connecting it to the dialysis machine and presses the rinse back button.  While the blood is returning, the arterial catheter port is cleaned with an alcohol swab and is capped with an antibiotic gel cap. If you have a fistula or graft your access care is different but the result should be the same.  With the blood returned and the machine stopped, the venous line is disconnected and the port cleaned and capped. 
 
The post-treatment vitals are collected:  sitting and standing BP, weight and temperature, patient and access condition.  Caregiver notices that the pod has a slight blood film and the post is slightly streaked.  Perhaps they will need to use heparin tomorrow.  Christy now takes pictures of the end of session post and pod condition.  More on this topic in an upcoming blog post.
 
Before Christy Health, the caregiver would hand write and then make sure the treatment flowsheet report was compete, scan it, then email it to the administrating nurse.  Now a button click does it all and we’ll explain all that in a future blog post.]]>