Big Data Yields Big Insights for Treatment of Central Sleep Apnea

Big Data Yields Big Insights for Treatment of Central Sleep Apnea

"This study provides the most robust view available on the prevalence of CSA in patients on PAP therapy," said Dr. Carlos Nunez, ResMed's chief medical officer. "The findings in this new research, combined with the research presented in April 2017, underscore the importance of keeping patients on therapy through regular monitoring, and rethinking the conventional wisdom on therapeutic options based on each patient's disease severity."

The new analysis defined three groups among patients with CSA – emergent, persistent and transient – based on whether the condition was present at the start of therapy or emerged during the first 12 weeks. All three groups showed a significantly higher risk of terminating their therapy than those without CSA. The risk was highest among the emergent group, whose CSA only became apparent during treatment, and were 1.7 times more likely to terminate their therapy than those without the condition.

About the StudyThe study authors included: Atul Malhotra, University of California San Diego, United States; Peter Cistulli, University of Sydney, Australia; and Jean-Louis Pépin, Grenoble Alpes University, France.

A retrospective analysis used anonymous, aggregated telemonitoring data from a U.S. positive airway pressure therapy database, (ResMed AirView™) and analyzed it for the presence or absence of CSA during CPAP therapy at baseline (week 1) and after 12 weeks.

Session data included weekly values by averaging within each week for each patient. Defined patient groups were: OSA, emergent CSA, persistent CSA and transient CSA. Groups were compared to identify risk factors for different forms of CSA, and adherence and therapy termination rates were determined.

Patients with any form of CSA during CPAP were at higher risk of terminating therapy in the first 90 days versus those who did not develop CSA (hazard ratio 1.7 for emergent CSA, 1.4 for persistent CSA and 1.3 for transient CSA; all p<0.001).

Share it:
Share it:

[Social9_Share class=”s9-widget-wrapper”]

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

You Might Be Interested In

Mind the (trust) gap: winning back confidence with data management

10 Oct, 2019

In the age of fake news, targeted data breaches and covert facial recognition trials, society is facing a crisis of …

Read more

Cloud-based predictive analytics seeing wider adoption

30 Sep, 2018

As flash arrays become more widely adopted within the enterprise, IT teams are looking for storage products that… incorporate predictive …

Read more

4 Reasons Your Machine Learning Model is Wrong (and How to Fix It)

25 Dec, 2016

This post presents some common scenarios where a seemingly good machine learning model may still be wrong, along with a …

Read more

Recent Jobs

Senior Cloud Engineer (AWS, Snowflake)

Remote (United States (Nationwide))

9 May, 2024

Read More

IT Engineer

Washington D.C., DC, USA

1 May, 2024

Read More

Data Engineer

Washington D.C., DC, USA

1 May, 2024

Read More

Applications Developer

Washington D.C., DC, USA

1 May, 2024

Read More

Do You Want to Share Your Story?

Bring your insights on Data, Visualization, Innovation or Business Agility to our community. Let them learn from your experience.

Get the 3 STEPS

To Drive Analytics Adoption
And manage change

3-steps-to-drive-analytics-adoption

Get Access to Event Discounts

Switch your 7wData account from Subscriber to Event Discount Member by clicking the button below and get access to event discounts. Learn & Grow together with us in a more profitable way!

Get Access to Event Discounts

Create a 7wData account and get access to event discounts. Learn & Grow together with us in a more profitable way!

Don't miss Out!

Stay in touch and receive in depth articles, guides, news & commentary of all things data.