# state_sleep_2022_1012

December 12, 2022ID9273

To CiteDCA Citation Guide

- 00:00Sleep centers and just a few announcements
- 00:05before we introduce today's speaker.
- 00:08So first, please take a moment
- 00:10that you are muted and if you
- 00:12wanted to receive CME credit,
- 00:14please see the chat room for instructions.
- 00:17If you're not registered yet,
- 00:18you'll have to do that
- 00:20before you receive credit.
- 00:22And then usually the recording of
- 00:24this session is available online
- 00:26within a couple of weeks and the
- 00:28link will be provided in the chat.
- 00:30And if you have questions,
- 00:32please make use of the chat room.
- 00:35And throughout the hour.
- 00:37And we will get to them at
- 00:39the end of the talk.
- 00:40And so I'm going to hand it
- 00:43over to Doctor Javaheri,
- 00:45who will introduce today's speaker.
- 00:48Welcome, Sir.
- 00:49Well,
- 00:50thank you so much.
- 00:51It is my honor to introduce
- 00:54Doctor Ali Azar Barzin.
- 00:57He's an assistant professor in the
- 00:58Division of Sleep and circadian rhythm
- 01:00disorders at Harvard Medical School,
- 01:02and he's director of the Sleep apnea.
- 01:05Health Outcomes Research Group
- 01:06at Brigham Women's Hospital.
- 01:08He's written multiple algorithms to help
- 01:11improve characterization and diagnosis
- 01:13of obstructive sleep apnea and to
- 01:15help identify patients at heightened
- 01:17risk of morbidity from sleep apnea.
- 01:20He's really paved the way for precision
- 01:23medicine and sleep apnea treatment.
- 01:25He has many publications and and grants
- 01:29including two R1 and R2154 original peer
- 01:32reviewed papers and high impact journals.
- 01:34So.
- 01:35It's really a treat to have
- 01:37him join us today.
- 01:39And without further ado,
- 01:40I'll hand it over to you, Ali.
- 01:43OK. Thank you so good for inviting me
- 01:46to share my research and thanks for
- 01:49thanks everyone for attending my talk so.
- 01:54Can you see my slides and hear my voice?
- 01:58Yes, but you, yeah, and it's in presentation.
- 02:02OK, great. So the title of my talk
- 02:06is understanding sleep apnea beyond
- 02:09the apnea hypopnea index or HIV.
- 02:13So this slide shows my disclosure.
- 02:16I just give you a few seconds to.
- 02:19Taking note of the numbers if you want.
- 02:22And then I'll continue.
- 02:28OK, great. So I'll add the the this
- 02:31slide is actually the outline of my talk.
- 02:34I'll talk about the background.
- 02:37And the rationale for?
- 02:39Developing new metrics,
- 02:41you know, in sleep apnea.
- 02:43And then I'll review the hypoxic burden
- 02:46and and and talk about its determinants.
- 02:50Then I'll talk to you.
- 02:51I'll talk about the heart rate
- 02:53response to respiratory events and
- 02:55it's importance and if I have time.
- 02:58At the end of my talk,
- 02:59I'll talk about the EEG arousals and
- 03:02their relevance for risk prediction.
- 03:07So this, I'm sure many of you know, you know,
- 03:11obstructive sleep apnea better than I do,
- 03:13but I just quickly go over.
- 03:16The different signals that
- 03:18we collect during PSG.
- 03:20So this shows a 5 minutes PSG tracing.
- 03:25Of obstructive events for a
- 03:28patient that have service apnea.
- 03:30And as you see with the absence of air flow.
- 03:36There is an out of phase
- 03:39movement of thorax and abdomen.
- 03:41And the reduction in oxygen saturation?
- 03:45The end of each event is accompanied
- 03:48by an arousal from from sleep which.
- 03:53Then recovers the SP O2 back to normal.
- 03:58Levels and.
- 04:00The transitioning back to sleep
- 04:03is associated with collapse
- 04:05of upper airway and recurrent
- 04:08obstructive apneas during the night.
- 04:13OK. And and we use a metric called
- 04:15apnea hypopnea index which is
- 04:17the number of apneas or complete
- 04:19collapse of the airway and hypopneas.
- 04:22Of the events with partial obstruction
- 04:24in the airway per hour of sleep.
- 04:28As you know, sleep apnea is associated with
- 04:32many comorbidities and and health outcomes,
- 04:35including excessive daytime sleepiness,
- 04:37reduce quality of life,
- 04:39impair workflow performance,
- 04:42increase car accident risk and
- 04:46several cardiometabolic outcomes.
- 04:48And for example, in hypertension,
- 04:51if you define OC as an HIV
- 04:53AIDS in 5 minutes per hour,
- 04:55the prevalence of OSA in
- 04:57individuals with hypertension.
- 04:58About 82% and it's about 30% if you
- 05:02use HIV AIDS and 15 events per hour.
- 05:05And similar associations with other.
- 05:09Cardiovascular diseases.
- 05:14However. Despite that,
- 05:16observational studies of CPAP
- 05:18showed that CPAP is beneficial.
- 05:21There have been several recent randomized
- 05:24control trial that have not been able.
- 05:27To detect a benefit of
- 05:29CPAP including save cuts.
- 05:31And an Isaac study from Spain.
- 05:35So in addition to steep adherence
- 05:39and other problems with the
- 05:42randomized control trial of of CPAP.
- 05:46An important reason for for now
- 05:48finding in in these R cities,
- 05:51we believe is inadequate patient selection
- 05:53by by indices like apnea and Putnam index.
- 05:57And the reason for that is HIV is a
- 06:01simplified metric is a frequency counter.
- 06:04And doesn't capture the magnitude
- 06:07of physiological changes that
- 06:09occur during sleep.
- 06:10And and for any given HIV,
- 06:13there are radiation in in
- 06:16event characteristics.
- 06:17There are differences in the air
- 06:19flow reduction in the number
- 06:21of apneas versus hypopneas.
- 06:23There's desaturations severity.
- 06:25We're missing the depths and duration
- 06:28of Desaturation and we also are
- 06:31not measuring the cardiovascular
- 06:32and EG acute cardiovascular and EEG
- 06:35responses to respiratory events
- 06:37including changes in heart rate,
- 06:39blood pressure or or egg characteristics.
- 06:43How about other commonly used
- 06:45metrics of our system variety?
- 06:47They unfortunately they
- 06:49share similar limitations.
- 06:50For example oxygen desaturation index.
- 06:53Again it's.
- 06:55It's a frequency counter,
- 06:57doesn't have the depth or duration
- 06:59information. Minimum saturation.
- 07:03It's just oversimplifies the dynamic
- 07:06of breathing and the saturation to just
- 07:09one number number for 8 hours of recording.
- 07:12Arousal index again is is a
- 07:16frequency counter doesn't consider
- 07:19the intensity of arousals.
- 07:21And one of the the better metrics is T-90,
- 07:25which is basically percent time below 90%.
- 07:29However it's based on arbitrary
- 07:32threshold of 90%.
- 07:34And it's not specific to OSA completely,
- 07:39it depends on baseline SPO 2 and.
- 07:44And and if there are other
- 07:48comorbidities that will affect the
- 07:50the value of T-90 so it may not
- 07:53respond to CPAP treatment.
- 07:56So it's the the problem with T-90 is
- 07:58that it's not specific to sleep apnea.
- 08:03OK, so due to all these limitations
- 08:07of commonly used metrics,
- 08:10we need to better quantify
- 08:12event characteristics.
- 08:14What do you see on the right side?
- 08:17Is the uh. So we we have time zero.
- 08:21Is the end of events and we
- 08:25just overlay all the events.
- 08:27These these Gray lines as you see here
- 08:31and and we took an ensemble average
- 08:34which is the red line in the top.
- 08:37Top row you see ventilation leader per
- 08:40minute and then you have the SP O2 signal.
- 08:43In the 2nd row you have heart
- 08:46rates and systolic blood pressure.
- 08:48In this this panel I'll I'll
- 08:50talk about how this ensemble
- 08:52averaging works in the next slide,
- 08:55but as you see here,
- 08:56there are.
- 08:57A large variation in the events
- 09:00characteristics and both within and
- 09:03between subjects and with with apnea
- 09:05hypopnea index and other metrics we were
- 09:09missing all this important information.
- 09:13Information like events related events into
- 09:16deficit which we call it when something
- 09:19better than event related hypoxemia,
- 09:22hypoxic burden.
- 09:24And eventually the changes in heart rate,
- 09:26blood pressure which can be used
- 09:29to quantify autonomic arousals and
- 09:32event related changes in each G like
- 09:35metrics like arousal intensity.
- 09:38So we are missing all this
- 09:40information from PSG.
- 09:42So I'll be talking about hypoxic
- 09:45burden in this next section.
- 09:47So this this graph we have air flow.
- 09:53Here on the top and then
- 09:56we have tidal volume.
- 09:58We have SP,
- 09:59O2 signals and in EKG at the bottom here,
- 10:03so I'm just going through the algorithm
- 10:06and how we developed algorithm.
- 10:09And the marking on the top the the red.
- 10:14Rectangles. They're hypopneas.
- 10:18That were manually scored
- 10:21for this period of the PSG.
- 10:25So one way to measure the burden
- 10:27of OC is to just measure the area
- 10:29under the desaturation curve.
- 10:31As you see here.
- 10:35But sometimes it's difficult to really
- 10:36find the start and end of this situation.
- 10:39So we because of that we
- 10:41designed a a search window.
- 10:44And we defined a local 200 second
- 10:47window surrounding the end of the
- 10:50respiratory events as you see here.
- 10:52And so and and why we choose 102nd?
- 10:56Because usually it's 100 seconds
- 10:59longer than the longest events and and
- 11:02and that's why we use for a second.
- 11:04So you have this for this event you have
- 11:07this 202nd and then you go to the next event.
- 11:11And you do the same and you keep
- 11:14going until you cover all the
- 11:17events during the sleep.
- 11:19At the end,
- 11:21so we all the events were aligned based
- 11:24on the end of each event which is times 0.
- 11:28So we just put everything on
- 11:30top of each other.
- 11:32And did an ensemble averaging to
- 11:36get an idea of average behavior
- 11:40or average desaturation curve.
- 11:43For for each subject,
- 11:44so it's a subject specific search
- 11:46window that we used to calculate
- 11:49the hypothesis period.
- 11:50So once we have the search window,
- 11:53we go to each respective events
- 11:54and we have this time information
- 11:56from the search window.
- 11:58And then we calculate the area under
- 12:01the curve for each each event and then
- 12:05the hypoxic burden will be the total
- 12:08area divided by total sleep time.
- 12:11So there have been some
- 12:13similar metrics in the past.
- 12:15However, there are some key differences.
- 12:18For example, some of them were they
- 12:20were based on the desaturation.
- 12:23Ohh 24% and that this session
- 12:26desaturation were not linked to
- 12:29respiratory events and there were.
- 12:32They require visual detection
- 12:34of of incomplete recovery, so.
- 12:37So we tried to to resolve all
- 12:40all all these issues with with
- 12:43the development of 556.
- 12:45So this graph that you see here.
- 12:48On the X axis we have apnea hypopnea index
- 12:51and on the Y axis we have hypoxic burden.
- 12:54As you see there is substantial
- 12:57variability for any given HIV.
- 12:59For example,
- 13:00HIV of 30 hypoxia and go from
- 13:0550 to 150% minute per hour.
- 13:08So and hypoxic pattern of 50%
- 13:11minute per hour means.
- 13:13A 10 minute per hour of 5% desaturation.
- 13:17That's how we can interpret the values of.
- 13:22And here I'm showing the the
- 13:26ensemble average desaturation curve.
- 13:30For six different subjects,
- 13:32so you you see the HIV values.
- 13:36On the top and then hypoxic and
- 13:39values have just below below
- 13:41the HIV and you see the spike.
- 13:44The severity of desaturation.
- 13:46All these subjects have similar ages.
- 13:50Well,
- 13:50there's different patterns of the saturation,
- 13:53so it's it's important to.
- 13:58To try to better vectorize the
- 14:01their sporting events and and get
- 14:04the Disat area of of of the events
- 14:07and and measure the hypoxic event.
- 14:10Uh.
- 14:11Because it's it's better,
- 14:13it's a better metrics of of our
- 14:16system ability than just counting
- 14:17the number of events so.
- 14:21In this figure,
- 14:22I'm showing the T-90 on the X
- 14:25axis and hypoxic on the Y axis.
- 14:28So there are some subjects here.
- 14:33Uh,
- 14:34with a high T-90 but a low
- 14:38value of hypoxic period,
- 14:40these are these are the subsequent
- 14:43sustained hypoxemia as opposed to
- 14:46a related intermittent hypoxemia.
- 14:48And and the interesting part is
- 14:51that T-90 when T-90 is close to 0.
- 14:55There is a wide variation
- 14:56in the hypoxic burden.
- 14:58So for many,
- 14:59many subjects,
- 15:00the T-90 really doesn't capture
- 15:03the the intermittent hypoxia that
- 15:05we were captured with hypoxia.
- 15:10So we we have done several analysis
- 15:13to show the importance of hypoxic and
- 15:16the first was the association between
- 15:19hypoxic burden and CVD related mortality.
- 15:23We use 2. Observation observational
- 15:26cohorts Mr Oz and Stephen House Mr
- 15:31Oz older men average age of about
- 15:3376 years and they were followed for
- 15:37about 10 years and there were 440 CVD
- 15:40related deaths and the Sleep Heart
- 15:43House we have both men and women.
- 15:45And the H younger lady longer 64
- 15:49year old on average followed for
- 15:52about 11 years 313 CBT related death.
- 15:55And what we showed that so we there was
- 16:00a those are some response relationship
- 16:02with the severity of hypoxic burden and and.
- 16:07And increased risk of CVD mortality
- 16:09in these two cohorts.
- 16:14We then did some analysis with incident
- 16:17heart failure and as you see here,
- 16:19I'm comparing HIV versus hypoxic
- 16:21burden and you see a clear dose
- 16:25response relationship between if you
- 16:28use hypoxic burn compared to HIV.
- 16:31And this figure on the left,
- 16:34bottom left is is interesting.
- 16:37What we did here was a
- 16:39secondary exploratory analysis.
- 16:40We categorized individuals into
- 16:43low hypoxic burden and low HIV,
- 16:46which was our reference group.
- 16:49And then low hypoxic burn,
- 16:50higher HI, higher hypoxic burn
- 16:53and low HIV and high hypoxic IHI.
- 16:57And as you see here regardless
- 17:00of the level of HIV,
- 17:02high hypoxic burden were associated
- 17:05with increased risk was while if
- 17:09you have low hypoxylon and high,
- 17:12it's really there was no association
- 17:14with with instance or failure.
- 17:19And. So a study, a clinical cohort.
- 17:24In in that. From France,
- 17:28they actually tested hypoxic burden on.
- 17:31On our clinical cohort,
- 17:33I think it was HIV written five
- 17:35they included only and there were
- 17:38immediate follow up about 78 months.
- 17:435400 patients with OSA
- 17:46and without CD baseline.
- 17:48And they had a composite outcome
- 17:51of all cosmetology or CD.
- 17:54And they they saw a similar
- 17:57association with hypoxia and.
- 17:59And and the outcomes that
- 18:02they were investigating so.
- 18:05Oh, we did some cross-sectional
- 18:09analysis in Mesa study.
- 18:11And we looked at hypoxic burden and
- 18:15blood pressure and also hypoxic
- 18:18period and chronic kidney disease and.
- 18:22So these are the two studies
- 18:23that showed hypoxic pattern was
- 18:25associated with blood pressure,
- 18:26increased blood pressure and
- 18:27hypoxic term was.
- 18:28So it's associated with higher prevalence
- 18:31ratios of moderate to severe CKD.
- 18:37There have been other studies actually
- 18:41that looked at similar metrics.
- 18:44In the last two years and
- 18:47what they found was that.
- 18:49For example, this this metric which is
- 18:53called sleep breathing impairment index.
- 18:55Similar metric was associated with
- 18:58cardiovascular risk in male patients and.
- 19:03Also some association with daytime
- 19:06sleepiness better than HIV and
- 19:09and some neurocognitive outcomes.
- 19:11Here PVD based reaction time
- 19:14and severity of desaturation.
- 19:16So there have been some other
- 19:18studies that have been interested
- 19:21in Desaturation area under the
- 19:23curve and show some some significant
- 19:26association with these outcomes.
- 19:30OK, so now here I would like to talk
- 19:34about the terminal of hypoxic Berlin.
- 19:37So. Hypoxic burden in in sleep
- 19:42apnea is mostly related to reduced
- 19:44ventilation due to OSA. However.
- 19:49A recent research letter that
- 19:52was published in Blue Journal.
- 19:54They argued about the the
- 19:57contribution of abdominal obesity.
- 20:00To hypoxic burden.
- 20:03And and so and the lack of.
- 20:08Appropriate adjustment for abdominal
- 20:10obesity in these studies that we have done.
- 20:14So the argument was that this abdominal
- 20:17obesity leads to a reduced FRC,
- 20:21which leads to decreased baseline SP
- 20:24O2 and faster and deeper desaturation.
- 20:27Independent of ventilatory decrease,
- 20:30which is related to sleep apnea.
- 20:35So just trying to clarify more.
- 20:40Assume that we have two subjects.
- 20:43With similar OSA severity
- 20:45but different hypoxic burden.
- 20:48So what you see here is the ensemble
- 20:52average curve of. Ventilation.
- 20:57And the hi is 30 and 30 burden
- 21:00which is basically the area on the
- 21:03total area under ventilatory curve.
- 21:06During sleep per hour of sleep.
- 21:09And so this, this,
- 21:11this mentality burden leads to a
- 21:14hypothetical for this particular subject
- 21:18leads to hypoxic permanent about 83%
- 21:21minute per hour, as you see here.
- 21:23Assume that we have a.
- 21:26We have another subject
- 21:28with exactly the same age.
- 21:30The same age are the same entity Berlin,
- 21:33but with a lower hypoxic Berlin.
- 21:36So the argument that was done in.
- 21:40In in the this research letter
- 21:43was that this subject here in the
- 21:45top with higher hypoxic Berlin.
- 21:47Has a lower.
- 21:50Point volume, which results to more severe,
- 21:53deeper or faster desaturation. And.
- 21:58And and we really currently don't have.
- 22:03Unless we do some city scan of of the.
- 22:08Of the visceral fat,
- 22:10we really cannot adjust for this.
- 22:13And and and and the argument was that.
- 22:17This will affect the association
- 22:20between hypercycle and and and CBD.
- 22:24So we try to answer this question
- 22:27in this study that the manuscript
- 22:29is actually under review right now.
- 22:33So we we assess the relationship
- 22:37between hypoxic burden and ventilatory
- 22:39burden as well as available measure
- 22:42of abdominal obesity and other
- 22:44confounder in in Mesa sleep study.
- 22:46They had some astrometry parameter
- 22:49in Mesa long which we used to try to
- 22:53answer this question and we separately
- 22:57tested if ventilator burden predicted CVD.
- 23:01And we also did another analysis.
- 23:06We adjusted the association of
- 23:10HBCD for desaturation sensitivity.
- 23:13And and and so the.
- 23:17The the idea behind it,
- 23:18behind this is that,
- 23:21so this subject here in the top
- 23:24will have a higher desaturation
- 23:27or tendency to desaturate.
- 23:29So we try to to adjust for
- 23:32desaturation sensitivity which was
- 23:34which we defined as the amount of
- 23:36hypoxia that you get per ventilatory
- 23:39per reduction in ventilation.
- 23:41So we adjusted this for desaturation
- 23:44sensitivity to see if it actually.
- 23:47Anything changes and if these
- 23:49situations sensitivity by itself is
- 23:52actually predictive of of the outcomes.
- 23:55So we did the study in Mesa sleep.
- 24:00Study about 1950 subjects so the
- 24:03definition of mentality burden
- 24:06which he defined it as event
- 24:09specific area under ventilation,
- 24:11ventilation signal so mean
- 24:13normalize and air we calculate the
- 24:16area under the mean ventilation.
- 24:19And the outcomes that were tested
- 24:22was instant cardiovascular disease,
- 24:24instant coronary heart heart
- 24:26disease and all cosmos totality.
- 24:30So this is briefly shows how
- 24:33we measure penalty Berlin.
- 24:35So if you look at the ensemble
- 24:38averaging of the ventilatory curve,
- 24:41so we can get the average event duration,
- 24:43we can get the event depth.
- 24:46And events to burden can simply
- 24:49be defined as the event rate times
- 24:52vent depths time event duration,
- 24:54which is a measure of total total
- 24:58ventilatory deficit during sleep.
- 25:01So this table shows the baseline
- 25:05characteristics of the Mesa
- 25:07sleep study that we included.
- 25:11So the average age about 67 year and.
- 25:18About 5053% of women.
- 25:23Equal distribution of different
- 25:25arrays and necessities and you see
- 25:29the PMI here. What we have here?
- 25:31Is that we have the HIV,
- 25:34the median HIV in this cohort was
- 25:37about 33 events per hour when
- 25:39switching Berlin and hypoxic Berlin.
- 25:41So in Mesa as just when I get a feel
- 25:45of how much rental through loss
- 25:47there was on average in this in
- 25:51this population cohort was about 20%
- 25:54was about 3 minutes of apnea which
- 25:57is the 100% reduction in airflow
- 26:00per hour of sleep and the hypoxic.
- 26:03But 9 minutes of 4% desaturation
- 26:05per hour of sleep.
- 26:09And this graph shows the association
- 26:11between ventilated burden and hypoxemia.
- 26:14You 17 burden on the X axis and
- 26:17hypoxic burden on the Y axis.
- 26:19They were strongly correlated
- 26:21and the R score was about 0.8.
- 26:25In this table I'm showing the
- 26:29contribution of other factors.
- 26:31So the Model 1 included mentality burden.
- 26:36BRS score of 0.8 in Model 2 we added a BMI.
- 26:42And and body surface area.
- 26:44So the R-squared increased only by 1%.
- 26:48Model 3 as you see here,
- 26:51we added wakefulness to baseline SPO
- 26:542 because there was one argument
- 26:56that baseline SP O2,
- 26:58the lower the baseline the the
- 27:01deeper the saturation and that could,
- 27:04independent of ventilatory deficit,
- 27:05affect the values of hypoxic.
- 27:08And so we added. So what about 1% additional?
- 27:14Variation explained by adding
- 27:16these two variables here.
- 27:19And and and similarly in the other models
- 27:22where we did some spirometry parameters,
- 27:25so there was no change in the R square.
- 27:29So and and what what it tells us is that the.
- 27:35Did the variation in hypoxic furnace
- 27:38mostly described by reality burn
- 27:40which is the OC related component
- 27:43that we are interested in?
- 27:45So what you see here is the hypoxic
- 27:48pattern and venture burden association
- 27:50with instant CD and all Cosmo thority.
- 27:54So you have a instant CHD and this
- 27:56is a hazard ratio for hypoxia.
- 27:59Incident, CVD and all cosmetology.
- 28:02And you see a similar association
- 28:05with Renton Superman.
- 28:07And these these these hazard ratios were
- 28:10adjusted for age 6 phase BMI hypertension
- 28:14as well as the desaturation sensitivity.
- 28:17So we also adjusted for desaturation
- 28:21sensitivity to to adjust out those
- 28:24other unseen or unobserved confounders.
- 28:28That we really cannot measure in
- 28:33this large population towards.
- 28:36So the take home message is that
- 28:39hypothesis is minimally affected by
- 28:41available measure of either positive
- 28:43and lung volume and ERV do not vary
- 28:46much in OSA population the action in
- 28:48fact we looked at the coefficient
- 28:51of variation of of these different
- 28:54factors waste circumference the
- 28:56coefficient of variation was about 14%,
- 28:59BMI 19% while for rental to burden
- 29:02is was about 100% of the coefficient
- 29:06of variation. And and the.
- 29:08Another take home message is the
- 29:10hybrid and largely captures the risk
- 29:13attributable to Ben 30 burden of OC
- 29:16rather than the tendency to desaturate.
- 29:19And we favor hypoxic burden over
- 29:22ventilated burden because ventilation
- 29:24is usually more difficult to measure.
- 29:26In a home based setting and their
- 29:29calibration issues and lack
- 29:31of standardization.
- 29:34OK. So that was related to hypoxic planets.
- 29:37Next I moved to Hartford response
- 29:39to Afghans and Hypopneas.
- 29:41So this this is slide was actually.
- 29:46From doctor summers. Paper in 1995.
- 29:51Where he described sleep apnea and
- 29:54an increase in sympathetic activity
- 29:56and and increasing blood pressure.
- 29:59As you see here with each respiratory events
- 30:03there are an increase in in heart rate.
- 30:06So we were thinking so if by
- 30:09measuring this this delta heart rate,
- 30:11increasing heart rate with each event we
- 30:14may gain additional information that and
- 30:18that may be useful for risk prediction
- 30:21or for to to identify who respond to
- 30:25CPAP treatment and who benefit from C.
- 30:28So some patients have a larger heart
- 30:31rate response to events than others.
- 30:34Here I'm showing two different subjects.
- 30:38And in the bottom figure here you see the
- 30:41increase in heart rate by this Red Arrows.
- 30:45So this subject has a minimal increase
- 30:47in heart rate with each respective event,
- 30:49despite similar oxygen desaturation amounts.
- 30:54And while this subject has a
- 30:57larger increase in in heart rate.
- 31:00So Delta Hartrick can be easily measured
- 31:02from in in lab and in home PSG's and
- 31:05currently is really under utilized.
- 31:07So and we our previous study back
- 31:11in 2013 we showed that delta heart
- 31:15rate increases with event severity.
- 31:18And and in observations without
- 31:20cortical arousal and with arousal.
- 31:22So there was a similar pattern of increase.
- 31:25Obviously if you have a razor,
- 31:27you have the biggest,
- 31:29the the largest increase.
- 31:31So the hypothesis was that high delta
- 31:35heart rates is associated with increased
- 31:38risk of cardiovascular disease.
- 31:40And we separately hypothesize that
- 31:44removing respiratory stimuli.
- 31:46And and those are apneas and hypopneas
- 31:49by CPAP.
- 31:50Could be beneficial in in those
- 31:52with High Delta heart rates.
- 31:55So to test the first hypothesis,
- 31:57we looked at the Mesa and
- 32:00Steve Hartman study.
- 32:01And and this here I'm showing
- 32:04this sample flow chart.
- 32:06At the end about 14 hundreds were
- 32:10analyzing Masa and about 4600
- 32:13analyzing from Cpot health study.
- 32:16So we saw a U-shaped association
- 32:19between Dalton Hartry and subclinical
- 32:22CVD measures including.
- 32:26Calcium score NT,
- 32:27probie NP and Framingham CVD risk.
- 32:31And based on this,
- 32:32we categorize the doctor heart rate in low,
- 32:35mid and high groups.
- 32:36And we looked at, we tested that.
- 32:40Categories and and sleep harthouse.
- 32:43And what we saw was that indeed
- 32:45those with low and High Delta Party,
- 32:48they were at increased risk of
- 32:51CVD and nonfatal CVD,
- 32:54CVD mortality and all 'cause mortality.
- 32:57So, so basically.
- 33:01The risk observing the low delta
- 33:03heart rate group we we thought and we
- 33:06hypothesized that was actually non OC
- 33:09specific and mainly due to heart disease,
- 33:12diabetes or autonomic dysfunction and and
- 33:14the risk observing the height of the group.
- 33:17Was mostly OSA specific because we
- 33:21saw hired hazard ratio in those with
- 33:24severe OSA whether quantified by HIV
- 33:27or hypoxic German and the risk was
- 33:31exclusively observing those with ESS
- 33:33less than 11, so non sleepy OSA.
- 33:36So the next question was.
- 33:40If with CPAP, reduce the risk in
- 33:42those with high throughput rates.
- 33:44And and to answer this questions we
- 33:47we looked at the recuts of trial.
- 33:51So request the trial was done and
- 33:53it was published actually in 2016,
- 33:56non sleepy patients with OSA
- 33:58and coronary artery disease
- 34:01randomized to CPAP or no CPAP. And.
- 34:05The HI criteria for inclusion was
- 34:08greater than 15 ESS, less than 10,
- 34:11median follow-up was about
- 34:1357 months and the outcome?
- 34:17Was a composite of first event
- 34:20of repeat vascularization,
- 34:21my MI stroke or cardiovascular mortality.
- 34:25And we asked the question is the CPAP
- 34:28benefit contingent on the heart rate
- 34:30response to events and what we saw is
- 34:33these graph here show the point estimates.
- 34:36At average delta heart rate 6 beats per
- 34:40minute and this is what's recuts trial.
- 34:44The original recursive trial showed
- 34:46was about 0.8 non significant
- 34:49and low delta heart rate.
- 34:51There was a suggestion of harm and
- 34:54so treating people with no low
- 34:57Delta Harvard seem to I was non
- 34:59significant and very wide confidence
- 35:01interval and but within those with
- 35:03high tops of heart rate,
- 35:05higher delta heart rate.
- 35:07We saw a risk reduction at
- 35:10significant risk reduction.
- 35:14Compared to other group so.
- 35:17And and the model were just for age 6,
- 35:20PMI and cardiac intervention.
- 35:25This is basically showing the same thing,
- 35:27but we have binary subgroup analysis.
- 35:30We have all participants gained similar to.
- 35:35That's a trial, so it was no effect.
- 35:38If you look at Delta heart rate
- 35:41threatens it's it's per minute you
- 35:43see that the CPAP significantly
- 35:46reduces the risk compared to this.
- 35:51So in summary, a greater Harter
- 35:53response to respiratory events is
- 35:56a risk factor that's identifiable,
- 35:58deleterious, and potentially reversible.
- 36:00And it could be used to select patients
- 36:04most likely to exhibit long term
- 36:07cardiovascular benefit from CPAP treatments.
- 36:09I think I have time.
- 36:13Do I have maybe 6-7 minutes
- 36:15to talk about this or?
- 36:20Yep. OK. Yeah, that sounds good.
- 36:23Thank you. So in and so this this work
- 36:27is currently under review and we're here
- 36:31we we're interested in the relevance of
- 36:34EEG arousal for risk stratification.
- 36:37So really the question was,
- 36:38do arousal improve prediction of OC
- 36:42related outcomes on top of desaturation?
- 36:44So over the past four decades, several
- 36:47versions of OC definition have emerged,
- 36:50which led to confusion among patient,
- 36:53clinician and payers.
- 36:54And and you were interested which
- 36:56type of hypo you know went to the
- 36:59desaturation of arousal would inform
- 37:00research stratification and the reason
- 37:02to do this study that was this ASM
- 37:05funded study that to systematically
- 37:07compare events with arousal and
- 37:09the saturation in multiple cohorts.
- 37:11So we used sleep quite health
- 37:13Mesa and slots for this study.
- 37:16So we compared events with
- 37:18minimal desaturation and arousal.
- 37:21So that's called HIV arousal only.
- 37:25And events with the saturation
- 37:27and no arousal.
- 37:28That's called H greater than 3% only.
- 37:32So these are the two.
- 37:35To specific HIV that we were interested in.
- 37:38So just quickly showed that sample
- 37:42characteristics of sleep heart
- 37:44health have shown that in the
- 37:47previous slide Mesa and Mr Oz and.
- 37:49The outcomes that we were interested in
- 37:52was so there were some cross-sectional
- 37:55outcomes including hypertension,
- 37:56diabetes and sleepiness and some
- 37:58follow up data longitudinal data
- 38:01instance CD in in these three cohorts.
- 38:04So again so this table shows
- 38:08the total number of events.
- 38:11Analyzed in these three cohorts.
- 38:17And the distribution of events with more
- 38:20than 3% desaturation only about 54%.
- 38:2543% in Mesa and in Mr Ross for the 43%.
- 38:29And but 13% of events would with
- 38:33arousal only and no desaturation here,
- 38:37but you see here.
- 38:38These are the headlines of those events.
- 38:41And the so this translate to this
- 38:44HIV values that you see here.
- 38:47So if you if you include these
- 38:50events events with arousal only.
- 38:56So prevalence of Margaret Zero
- 38:58say would be 67 percent, 70%,
- 39:01sixty 8% in this state cohorts.
- 39:04But if you exclude these events,
- 39:06you get a 10% reduction from
- 39:10supposedly across street cops.
- 39:14So it's important to really look at these
- 39:16and see if there is any any additional
- 39:19information that these is provided.
- 39:21So what what you see here is the.
- 39:26Additional role of events with this
- 39:28saturation, but no other else.
- 39:31And the model were adjusted for covariates
- 39:34and HIV based on events with arousal.
- 39:37So regardless of desaturation.
- 39:39As you see here, across all all the
- 39:43outcomes you see as significant.
- 39:46Increase in in in risk.
- 39:48But if you look at the HIV arousal only.
- 39:53There's basically nothing
- 39:55so additional those events.
- 39:58If you adjust for desaturation events
- 40:00with these saturation of the also Brazil.
- 40:03So this what what this is is basically.
- 40:07Assume that you send the subject
- 40:10and you send an HD to the subject.
- 40:13And you get all the 3% events
- 40:16with more than 3%,
- 40:17so you don't measure arousals.
- 40:20And then you bring them back to the sleep
- 40:23lab and you find those additional events.
- 40:26That were associated with arousals.
- 40:29And what what we see here that
- 40:32those really don't add any info,
- 40:34don't improve the prediction of outcomes.
- 40:38As you see here,
- 40:39and in some cases they're even protected.
- 40:43So this I think we didn't adjust
- 40:46this for BMI so this this.
- 40:48This table which is BMI again you see
- 40:53similar direction and and slightly.
- 40:55A lower heat hazard or odds ratio,
- 40:59but it's similar story that we had before.
- 41:05So what we did this was an
- 41:08additional exploratory analysis.
- 41:09We looked at individuals now with
- 41:12an HI getting 15 events per hour.
- 41:18Again, based on H 3% regards of arousal.
- 41:22So exclude everyone who had
- 41:25severe OSA by desaturation.
- 41:28Audit to Studio City and again in
- 41:30this in these individual events with
- 41:33arousal put but no desaturation.
- 41:36Were not associated to it with this stuff,
- 41:38adverse outcomes. So similar,
- 41:40similar similar results that we've found.
- 41:45And and to further investigate this,
- 41:48we looked at the arousal
- 41:50intensity and arousal index.
- 41:52I think this was just be part of the study.
- 41:55You see, that's the arousal.
- 41:56Intensity tends to go down as well if
- 41:59you get more arousals per hour of sleep.
- 42:03So there is a negative association here
- 42:05and we did another analysis, we looked at.
- 42:09Change in arousal index and the
- 42:12sleep heart health and what we saw
- 42:16was that changing arousal index was.
- 42:20Predicted by baseline, Oasis, Verity what?
- 42:23What it tells us is that over time there
- 42:26is a decline in a number of arousal.
- 42:30And separately in another study
- 42:35that my poster Gonzalo Labarca did.
- 42:39We looked at a razor burn.
- 42:42Which we defined.
- 42:43It is similar to the.
- 42:45Paper published by the Australian
- 42:48group event rate times arousal duration
- 42:50and we compared it with hypoxic burden.
- 42:53So again. Compared to hypoxic burden,
- 42:56there is no significant
- 42:58sociation with arousal burden.
- 43:03So to take your message is
- 43:05while arousal may be harmful.
- 43:07Based on experimental data,
- 43:09measurements of arousal may not
- 43:11improve its positions department.
- 43:15So in summary, measuring the depth
- 43:17and duration of this saturation.
- 43:19That should provide added predictive value.
- 43:23So we can measure hypoxic from there than
- 43:26from inlab and in home sleep studies.
- 43:29We demonstrated that hypothesis paramedics
- 43:32multiple outcomes in population base
- 43:35and and French group in Congo cohorts.
- 43:39We show that hypoxic burden is strongly
- 43:42associated with entity burden.
- 43:43And is minimally affected
- 43:46by the abdominal obesity.
- 43:48And we also showed that individual without
- 43:52sleepiness the elevated heart responsiveness.
- 43:57Those will be at increased risk
- 43:59of CVD and may benefit from CPAP.
- 44:02And additional advanced with
- 44:03arousal and all the saturation to
- 44:06not improve this prediction.
- 44:08And finally,
- 44:09I'd like to thank you the amazing
- 44:12team in Boston and elsewhere for.
- 44:15Great contributions to to help with the,
- 44:19the data,
- 44:20with the analysis and and and and everything.
- 44:23And thanks everyone for.
- 44:26Listening to my talk.
- 44:28Thank you so much. That was fantastic,
- 44:31very informative and really enjoyed
- 44:34hearing that the different algorithms
- 44:36you've helped develop or developed
- 44:38yourself and how they've been
- 44:40applied to different clinical trials.
- 44:43I'm going to take questions now,
- 44:44but I'll ask if you could please
- 44:47put your question in the chat and
- 44:50let me call on you rather than
- 44:52unmuting and and so we can avoid
- 44:55the risk of missing questions or
- 44:58not giving everyone a chance. Umm.
- 45:01So does anyone have any questions?
- 45:08Doctor Thomas is asking is loop
- 45:10gain elevated in those with
- 45:12a high heart rate response?
- 45:16We looked at this, I think the
- 45:18correlation between delta heart rate
- 45:21and Lucan was about 0.2 positive.
- 45:27Yeah. So it's just like, right, ability.
- 45:31And then Doctor Winkelman says it looked
- 45:33as if low hypoxic burden and high age chi
- 45:37were protective from mortality comment.
- 45:41I participated and high.
- 45:44Low hypoxic burden, high I
- 45:45had lower risk of mortality,
- 45:47yes, it was actually, it was insulin
- 45:49heart failure that we found, yes. Yeah.
- 45:53So lower risk of incident and
- 45:55heart failure with those with
- 45:56a high and low hypoxic burden.
- 45:58Yeah, it wasn't significant.
- 46:00So yeah. The hazard ratio I think
- 46:04was 0.9 or something like that.
- 46:08And clinically that makes sense because
- 46:10with heart failure patients in particular,
- 46:12they can often have very long apneas and
- 46:15in combination with the circulatory delay
- 46:18it can be much more detrimental than
- 46:21than a patient without heart failure.
- 46:23Doctor Thomas says patients
- 46:24come with now symptoms,
- 46:26not for future prevention mostly,
- 46:28so arousals should not be ignored.
- 46:33Yes, this has been a very controversial.
- 46:37Study that we, I mean we didn't
- 46:39expect that to see this results.
- 46:42But and and I mean it may be
- 46:44in in younger individuals if.
- 46:50The beginning of the disease.
- 46:52They may be very informative, but.
- 46:55These, these are mostly older individual
- 46:58and and I think there was another there.
- 47:01There was a study that showed the
- 47:04initiation of symptoms and that
- 47:06the time between the initiation of
- 47:09symptoms and the official diagnosis
- 47:11whatever was about maybe 11 years.
- 47:14So by that time the arousal may
- 47:16not be informative any anymore.
- 47:18So and in terms of risk prediction.
- 47:22So that's that.
- 47:23I need to make that clear
- 47:25so it doesn't predict.
- 47:27Addition the added risk and top of
- 47:30desaturation based on these studies.
- 47:36I'm going to go back to Doctor
- 47:37Hoffman, doctor Yaggi said.
- 47:38Do we know the relationship
- 47:40between arousal threshold and
- 47:41delta heart rate response?
- 47:45No, I haven't done that study.
- 47:48So arousal threshold and delta heart rate,
- 47:51no, I don't. I don't know.
- 47:53But yeah, we can, we can look at it.
- 47:57And then, doctor Huff. Oh, go ahead. Sorry.
- 47:59No, I was just curious why.
- 48:02Like the gag is interested in this.
- 48:05Please unmute and and let us
- 48:07know Doctor Yaggi if you can.
- 48:10OK.
- 48:13And then Doctor Hoffman, if you want to
- 48:15unmute to ask or to make your comment,
- 48:18I bring that up just because the
- 48:21work that Andre has done has
- 48:24shown that low arousal threshold,
- 48:26the patients really struggle adhering
- 48:29to CPAP therapy and we're finding that.
- 48:34The arousal threshold
- 48:35and autonomic activity might be
- 48:38related that it might be challenging
- 48:40to treat those patients with delta
- 48:42heart rate response if they if
- 48:45it's an arousal threshold issue.
- 48:48That's interesting. Sure. Yeah,
- 48:50we should look at it. We have the data.
- 48:55Doctor Hoffman wanted to point out
- 48:56that using heart rate response can be
- 48:58tricky when we don't know if the patient
- 49:01has a cardiac autonomic neuropathy,
- 49:02which is not uncommon in patients with type
- 49:052 diabetes and and as patients are aging.
- 49:11I don't know if you have a comment for that.
- 49:15I mean I don't have a comments, but I agree.
- 49:18Yes, yeah, in in some patient
- 49:20population it may be challenging
- 49:22to measure heart rate response,
- 49:24but we haven't had any issue
- 49:25in in this large cohorts,
- 49:27population based cohorts.
- 49:29In terms of measurements of delta,
- 49:31heart rates and.
- 49:34And Doctor Winkleman, do you
- 49:35wanna unmute for your question?
- 49:37It's a little bit longer if you'd like.
- 49:46Thank you. Great talk, Ollie.
- 49:49Progression of.
- 49:51A very logical approach to this.
- 49:55I think from my perspective
- 49:58the next step is looking at
- 50:01respiratory related leg movements.
- 50:04Those leg movements that occur
- 50:05at the end of respiratory events
- 50:08that have been shown when they
- 50:09are present to be associated with
- 50:12a substantially larger increase
- 50:13in heart rate than events that do
- 50:16not terminate in the leg movement.
- 50:19Do you have any plans to investigate this?
- 50:23Absolutely. I mean, we are doing that.
- 50:27That's a good time to ask this question.
- 50:31We're trying and trying to
- 50:33have some data. To analyze that data
- 50:37and hopefully, yeah, collaborates.
- 50:40Thank you. Great talk. Thank you.
- 50:44And uh, Doctor Thomas ask,
- 50:47how does one use these insights in
- 50:49the management of individual patients?
- 50:51So you've shown a group analysis with
- 50:54with large cohorts of patients and do
- 50:56you have any recommendations to us to
- 50:59tailor this clinically at this point?
- 51:01I don't, I don't. Yeah.
- 51:03That's that's too, too early.
- 51:05Probably it's too early.
- 51:06Yeah. Yeah. Yeah.
- 51:09Um. And then someone is asking arousal
- 51:12response is related to obstructive
- 51:14sleep apnea syndrome or neuropathy?
- 51:19Uh, if you want to unmute, it's CAI.
- 51:22If you want to unmute and and.
- 51:26Clarify the question would be great.
- 51:43Is that Alice Kai? I'm not sure.
- 51:48Alice, you want to unmute and.
- 51:51Alright. Yes, I just want to know
- 51:55um arouse response is result
- 51:57is related to the authors or
- 52:01maybe from the central obstacles
- 52:05central right you're passing?
- 52:09Central sleep apnea.
- 52:16Can you clarify again? Sorry,
- 52:17we had a little difficulty hearing you.
- 52:21Means uh arouse response is related
- 52:26to obstruct sleep as clear syndrome
- 52:30or symptoms sleep aspirator syndrome.
- 52:33We only looked at the obstructive sleep
- 52:37apnea. We didn't get this central.
- 52:42And their central events were very
- 52:44rare actually in these these cohorts.
- 52:50Doctor Yaggi, I'm going to ask you
- 52:51to any new again as well to share
- 52:53your comment if you don't mind.
- 52:57Yeah. One one other question.
- 52:58I'll leave this unbelievable work.
- 53:00Thank you for sharing this with us today.
- 53:03It seemed like in the analysis
- 53:05you did looking at Delta heart
- 53:07rate in the observational studies,
- 53:09I think it was sleep heart health,
- 53:11Mr Ross Mesa where it's at a low,
- 53:14medium, high heart rate cut points
- 53:16where you dichotomize this and the
- 53:19CPAP analysis for ricotta using
- 53:22different different cut points.
- 53:25And I'm just wondering.
- 53:26The reason behind that was that yeah,
- 53:29how did you come up with those cut points
- 53:31and ricotta versus versus the other
- 53:34side. So sure. Thank you for comments.
- 53:38So basically in in sleep in Mesa
- 53:41and sleep Heart health actually
- 53:43in Mesa we looked at this U-shaped
- 53:47relationship and based on that.
- 53:49We just categorize based on the
- 53:52top 25% and and lower 25% and
- 53:57the middle was the middle 50%.
- 54:00And and then we use the same
- 54:02threshold in sleep Charter.
- 54:03So we didn't change the
- 54:05threshold in sleep harthouse.
- 54:06In regards to the,
- 54:08the question was different actually
- 54:10it's because we hypothesize that
- 54:13those with higher heart rate
- 54:15response those would benefit more
- 54:17and and we test it as a linear.
- 54:21So we test it as a.
- 54:22We didn't in the main analysis we
- 54:24it was a continuous variable and
- 54:27we showed that there was that,
- 54:28I showed the point estimates and the.
- 54:31The the binary.
- 54:33Categorization that was just just to
- 54:35show that you see the same thing if
- 54:38you divide it by a nice around number,
- 54:41like 6 beats per minute.
- 54:44And and and there is also a
- 54:45difference in the in the population.
- 54:47So in the recuts I think it was
- 54:4990% or maybe 80% had cardiac,
- 54:54cardiac problems and about
- 54:5690% were on beta blockers so.
- 54:59It would be a different population compared
- 55:01to State Park health and other records.
- 55:08Sorry, I couldn't hear the rest.
- 55:11Or Andre, feel free to unmute,
- 55:12unmute if you wanna.
- 55:14No sure. So I'll, I'll leave.
- 55:16Great, great work and like Doctor
- 55:19Wickman said are really nice and
- 55:22elegant progression of going from
- 55:23HIV to these more continuous metrics,
- 55:25which is really nice.
- 55:26And I guess I have a couple of questions.
- 55:29One question is?
- 55:30You know, I think that, Umm,
- 55:32the markers you've developed
- 55:33are very promising and I'm just
- 55:35wondering if you were to take it
- 55:37to the next level or someone else
- 55:38were to take it to the next level.
- 55:40You know what,
- 55:41I'm going to sort of piggyback
- 55:44on Clara's question.
- 55:45You know, how do we design a trial
- 55:47where we look at people most at risk
- 55:50or most likely to respond for example.
- 55:52So what delta heart rate caught up do we use?
- 55:55Do you think we need to validate
- 55:57this more in other populations
- 55:58before you have a cut off?
- 56:00How can we operationalize that to
- 56:02the point where we can perform a
- 56:04trial that's a little bit more?
- 56:06Umm.
- 56:08Successful.
- 56:11Yes, we are trying to to do that trial
- 56:14and submit the proposal and hopefully
- 56:17get that fund that's for the delta
- 56:20heart rates and we proposed that delta
- 56:23heart rate of 6 beats per minute. OK.
- 56:27Because again we're going to recruit
- 56:30from cardiology clinic most likely.
- 56:32And yes, that's I'm going to use the same,
- 56:36the same threshold that that was in bukasa.
- 56:41You know. So.
- 56:44OK. All right.
- 56:47Three of six cardiac population.
- 56:48Here we go. All right, excellent.
- 56:50And I guess the other question I had was?
- 56:54In regards to your more recent work
- 56:56where you're looking at the risk
- 56:59of adverse outcomes and different
- 57:01definitions of the HIV that we could
- 57:03extract from the routine PhD data
- 57:05without having to use signal processing.
- 57:08And so when you're looking at events that
- 57:10are associated only with arousals versus,
- 57:13those are the 3% disabled.
- 57:15So in that population,
- 57:16what was the distribution of the
- 57:19events that were associated with 3%
- 57:22dsat versus events with just the?
- 57:24There's always is arousals alone,
- 57:27minority of events or whether
- 57:28I think I showed that in
- 57:30the one of the tables,
- 57:31I think yes, about 15% or so,
- 57:37yes, only arousal notice,
- 57:40right? So in your analysis you
- 57:44essentially you add her on the
- 57:46arousal frequency really you know
- 57:49register event related arousals or
- 57:52you know hoping really arousals.
- 57:54The total amount of the exposure
- 57:56that's already there with the 3%
- 57:59exactly and that's exactly what we did, yes.
- 58:03All right. And one of the other
- 58:05things I might suggest is that,
- 58:06you know, as we look at these
- 58:08different different studies,
- 58:09one of the key pieces of information is
- 58:12that often we use composite outcomes,
- 58:14you know, CAD stroke and they actually might
- 58:17be different mechanisms for those events.
- 58:20And similarly, you know, maybe the
- 58:22arousals may be more relevant for you know,
- 58:25cognition or rather than CVD.
- 58:28And so there's some data I think
- 58:30from Stanford looking at the.
- 58:33Hypopneas with arousals only would
- 58:35be correlating this objectives.
- 58:39I mean, we looked at the ESS,
- 58:40but you're right, yes.
- 58:42So we should look at other
- 58:44outcomes that are available,
- 58:46I think, yeah. Unfortunately,
- 58:49in this course is I think ES was
- 58:52the only one we could look at.
- 58:57Our next question asks what clinical
- 58:59parameters would help delineate
- 59:01individuals more likely to have
- 59:03significant hypoxic burden when
- 59:05they're being evaluated and in.
- 59:08So. So the. In terms of the,
- 59:13so you mean people with maybe high HIV,
- 59:16high Tina, is that the question?
- 59:20Please feel free to unmute
- 59:21the individual asking this.
- 59:23I think they mean.
- 59:24I'm wondering if they mean in the clinic.
- 59:25Are there any characteristics we can
- 59:28use to to sort of identify those?
- 59:31But I could be wrong.
- 59:36That's from
- 59:39EN 12901.
- 59:42I mean if you see a lot of events.
- 59:45A lot of these saturation,
- 59:47I mean in that meeting before before
- 59:50actually the study like you in the clinic
- 59:52you evaluating a you know patient.
- 59:56You know I understand that you know all
- 59:58that is from the study but you
- 01:00:00know clinically if we evaluating
- 01:00:02patients since they are you know pack
- 01:00:05some car clinic or characteristics that
- 01:00:08you know we could. Basically,
- 01:00:11I derive from the studies
- 01:00:13that would predict that those
- 01:00:14individuals are more likely to
- 01:00:18have significant hypoxic burden.
- 01:00:20Done that that study.
- 01:00:25You showed that abdominal adiposity
- 01:00:27wasn't associated with it,
- 01:00:29but were there any other anything like?
- 01:00:32Any characteristics?
- 01:00:36To some extent. Uh.
- 01:00:39Which is related to both sleep
- 01:00:41apnea and also maybe just
- 01:00:44adding some more hypoxia.
- 01:00:46By lowering the lung volume.
- 01:00:50I think you have BMI was the only
- 01:00:52factor that remained significant after
- 01:00:54it's just include the covariance.
- 01:01:00Ali, thank you so much.
- 01:01:02What a great talk and thank you, so good
- 01:01:05for hosting a lot of outstanding data,
- 01:01:08a lot of promising directions and
- 01:01:11looking forward to hearing from you in
- 01:01:13a couple of years when you update us
- 01:01:16and tell us that you figured it out.
- 01:01:18And looking forward to our next
- 01:01:20session that we presented by our
- 01:01:22own doctor minor at Yale,
- 01:01:24we'll be talking about sleep
- 01:01:26disturbance in the elderly population,
- 01:01:28something that we see fairly commonly.
- 01:01:30And so thank you everyone for
- 01:01:31spending your time with us today
- 01:01:33and we'll see you in one month.
- 01:01:35Thank you so much for hosting.
- 01:01:37Bye, bye. Thank you. Bye.