RT Journal Article
SR Electronic
T1 Predictors of mortality for patients with obesity-related respiratory failure treated with nocturnal non-invasive ventilation
JF European Respiratory Journal
JO Eur Respir J
FD European Respiratory Society
SP PA3064
DO 10.1183/13993003.congress-2016.PA3064
VO 48
IS suppl 60
A1 Chathika Weerasuriya
A1 Dariusz Wozniak
A1 Syed Huq
A1 Michael Davies
YR 2016
UL http://erj.ersjournals.com/content/48/suppl_60/PA3064.abstract
AB Introduction: Home non-invasive ventilation (NIV) is an established treatment for patients with obesity-related respiratory failure (ORRF). In clinical practice, cardiac and respiratory comorbidities are common. Despite increasing obesity rates, there are limited pragmatic data that describe long-term treatment outcomes in such patients.Aim: To establish factors associated with survival for patients with ORRF treated with NIV.Methods: Retrospective study of consecutive patients with hypercapnic respiratory failure started on NIV (2006-2011) via a specialised regional NIV service. Patients with ORRF (obesity as main cause of respiratory failure) were identified via database.Results: 121 patients (median age 61 years, 56% male, mean BMI 50.45 kg/m2) were included. 47% of patients were admitted electively; 53% transferred during an acute admission. Comorbidities included Obstructive lung disease (OLD) (49%), Diabetes (46%), Hypertension (53%), and significant cardiovascular problems (CVS): IHD (32%), CCF (15%), AF (14%), cerebrovascular disease (7%). CVS were more common (p=0.004), and OLD less common (p=0.02) among acute admissions. At 1 year, mean NIV use was 6.1 ± 2.4 hrs, PaCO2 5.97 ± 0.99 kPa (similar for acute vs. elective). 5 year survival was 78%. Via multivariate analysis, mortality was associated with acute presentation, reduced NIV use, and raised PaCO2. CVS comorbidities did not affect initial survival, but may have an adverse impact after 5 years.Conclusions: Elective admission, NIV compliance and control of hypercapnia are associated with improved outcomes for patients with ORRF. These data support a proactive model of care.