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\begin{document}

\title{Predictors of Longitudinal Outcomes for Children Using Long-term
Non-invasive Ventilation}



\author[1]{Prabhjot Bedi}%
\author[1]{Kristie DeHaan}%
\author[1]{Joanna MacLean}%
\author[1]{Maria Castro Codesal}%
\affil[1]{University of Alberta}%


\vspace{-1em}



  
  \date{May 24, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Background: Non-invasive ventilation (NIV) is a first-line therapy for
sleep-related breathing disorders and chronic respiratory insufficiency.
Evidence about predictors that may impact long-term NIV outcomes,
however, is scarce. The aim of this study is to determine demographic,
clinical, and technology-related predictors of long-term NIV outcomes.
Methods: A ten-year multi-centred retrospective review of children
started on long-term continuous or bilevel positive airway pressure
(CPAP, BPAP) in Alberta. Demographic, technology-related, and
longitudinal clinical data was collected. Long-term outcomes examined
included ongoing NIV use, discontinuation due to improvement in
underlying condition, switch to invasive mechanical ventilation (IMV) or
death, patient/family therapy declination, transfer of services, and
hospital admissions. Results: 622 children were included. Both younger
age and CPAP use predicted higher likelihood for NIV discontinuation due
to improvement in underlying conditions. Children with upper airway
disorders or bronchopulmonary dysplasia were less likely to require NIV
continuation while presence of central nervous system (CNS) disorders
resulted in higher likelihood of hospitalizations and switch to IMV or
death. The presence of obesity/metabolic syndrome and early
NIV-associated complications predicted higher risk for NIV declination.
Children with more co-morbidities or use of additional therapies
required more hospitalizations and the latter also predicted higher risk
to be switched to IMV or death. Conclusions: Demographic, clinical data,
and NIV type impact long-term NIV outcomes and need to be considered
during the initial discussions about therapy expectations with families.
Knowledge of factors that may impact long-term NIV outcomes might help
to better monitor at-risk patients and minimize adverse outcomes.%
\end{abstract}%



\sloppy


\textbf{INTRODUCTION}

Long-term non-invasive ventilation (NIV) has become a modality of choice
for treating chronic sleep and respiratory disorders in children with
conditions leading to upper airway obstruction, abnormal drive to
breath, muscle weakness or abnormal lung gas
exchange\textsuperscript{1}. Continuous positive airway pressure (CPAP)
and bi-level positive airway pressure (BPAP) therapies both allow
children to maintain airway patency throughout the breathing cycle, and
increase lung recruitment at the end of the
expiration\textsuperscript{2}. BPAP therapies can also increase alveolar
ventilation by supporting the inspiratory part of the breathing cycle
and setting a mandatory respiratory rate. Home NIV therapies are
indicated in patients who require breathing support intermittently, most
commonly during sleep, and allow individuals to be off the machine
during most or part of the day\textsuperscript{3,4}.

Prior studies have shown NIV to be an efficacious therapy for improving
breathing during sleep in children with a variety of underlying
conditions\textsuperscript{1,5}. NIV improves outcomes in conditions
such as obstructive sleep apnea (OSA)\textsuperscript{6} and respiratory
insufficiency/failure due to lung and neuromuscular disease in
children\textsuperscript{7-10}. However, apart from predictors for NIV
adherence\textsuperscript{11,12}, very few studies have examined how
baseline clinical characteristics and technology-related factors may
impact the benefit and success of NIV in children\textsuperscript{13}.
For example, it is known that some children using NIV will discontinue
therapy due to improvements in their underlying
condition\textsuperscript{14}; however, it is unknown what underlying
clinical and technological characteristics may impact this improvement.
Factors impacting children who are at risk for NIV failure (i.e. their
breathing is not adequately supported by NIV leading to a switch to
invasive mechanical ventilation (IMV) or because they die despite using
NIV) are also less understood\textsuperscript{15}. In addition, although
patient/family declination of NIV therapy has been described in up to
15\% of children who start NIV, the factors that may impact this
decision are not clear\textsuperscript{16}. Understanding the factors
that may contribute to these outcomes will have a direct impact on
clinical practice by discussing expectations with families prior to NIV
initiation and anticipating potential challenges that might influence
NIV use.

With an increasing shift towards the use of home NIV therapies in
children that are time, socially, and financially demanding for families
and the health care system\textsuperscript{17}, there is a need to
understand factors that are easily identifiable in clinical practice
that might influence long-term NIV outcomes. This information will
inform clinical practice to allow for early interventions and close
monitoring of patients at risk to decline NIV or to have adverse
outcomes. The aim of this study is to examine the impact of demographic,
clinical, technology-related, and follow-up factors on long-term
outcomes in a cohort of children using long-term NIV.

\textbf{MATERIALS AND METHODS}

\emph{Study Design}

This study is a 10-year multi-centred retrospective review of all
children who initiated long-term NIV in the province of Alberta, Canada,
from January 2005 to December 2014, with patients followed until
December 2015. Data were collected from the medical charts and sleep
laboratory records of children at the Stollery Children's Hospital
(Edmonton) and the Alberta Children's Hospital (Calgary). These two NIV
programs provided care for the majority, if not all, of children using
NIV in the province and the surrounding catchment area. The study was
approved by the respective Health Research Ethics Boards at
participating institutions.

\emph{Participants}

NIV programs at the two participating hospitals were reviewed to
identify the subjects. The inclusion criteria were children 0-18 years
of age who have used NIV for a minimum of three months outside of an
acute-care setting. We define NIV as any method of breathing support
that provides positive airway pressure through an interface outside of
the airway, including CPAP, and BPAP. As the goal included capturing
information on long-term outcomes, patients who were recommended NIV but
were not able to initiate it were excluded. No restrictions in terms of
underlying conditions were applied to the inclusion criteria.

\emph{Data Collection}

Demographic, clinical, and technology-related data were collected at: 1)
the time of NIV initiation; 2) the initial follow-up visit within the
first 12 months from NIV initiation; 3) the most recent follow-up visit
after 12 months from NIV initiation (and a minimum of 3 months apart
from the initial follow-up visit). Data was stored in an electronic
REDCap database\textsuperscript{18}.

Baseline demographic data collection included age, sex, and site of NIV
initiation. Clinical data collection included specific underlying
disease conditions, co-morbidities (defined as any additional diagnosis
aside from the primary underlying diagnosis as per previous
definition)\textsuperscript{19}, additional technologies (e.g. oxygen
therapy, V-P shunt, nasogastric/gastric-tube feeding, wheelchair),
history of previous upper airway surgeries or/and additional major
surgeries (e.g. heart surgery, neurosurgery, orthognathic surgery,
spinal surgery). Technology-related data collected included NIV type
(CPAP, BPAP or auto-PAP), mask type (nasal, oro-nasal, or other (total
face mask or nasal pillow)), and trigger for NIV use (electively without
polysomnography (PSG); electively with PSG; due to acute illness;
other), date of NIV initiation and overall duration of NIV use.
Follow-up data included the total number of NIV-related complications
reported by patients/caregivers.

\emph{Outcome measures}

Long-term outcomes, tracked at the most recent follow-up visit, included
NIV continuation, reasons for NIV discontinuation (improvements in
underlying condition, switch to IMV, death, patient or family
declination, or transfer to other services including adult services,
another NIV provider, or out-of-province care), and hospital admissions
tracked through the discharge summaries. Additional detail of the study
design has been previously published\textsuperscript{16}.

\emph{Data Analysis}

Summary statistics were reported as median (IQR) or frequencies (n, \%)
as appropriate. Logistic regression was used to perform a multivariate
analyses of outcome measures and data from the multivariate analyses
were reported as odds (Exp (B)) with the 95\% confidence interval (CI).
Demographic, clinical, technology-related and follow-up variables were
initially included. Diagnostic category was included in the analysis to
account for heterogeneity of the sample. Subjects were classified into
five diagnostic categories according to their underlying condition
(upper airway; central nervous system; musculoskeletal; cardiopulmonary;
other category for those ones with characteristics of more than one
category). Individual underlying disease conditions previously shown to
influence long-term NIV outcomes\textsuperscript{15} were also included
in the initial multivariable analysis. We also included the time period
in which NIV was initiated (Epoch 1, Jan 2005-Apr 2008; Epoch 2, May
2008-Aug 2011; Epoch 3, Sept 2011-Dec 2014).

Predictor variables that had a p\textless{}0.20 on univariate analysis
for each outcome were tested in the respective logistic regression
models. Co-variates considered clinically relevant, such as age, sex,
diagnostic category, number of co-morbidities, number of additional
therapies, and NIV type, were forced into multivariable analyses,
regardless of their univariate significance. A stepwise purposeful
addition and removal of covariates was performed until a best-fit model
(using the Nagelkerke R-square) was produced. Analysis was performed
using IBM SPSS Statistics version 26.0 (SPSS, Inc., Chicago,
IL)\textsuperscript{20}. Summary statistics were reported as median
(IQR) or frequencies (n, \%) as appropriate. A p-value of
\textless{}0.05 on analysis was determined to be statistically
significant.

\textbf{RESULTS}

A total of 622 children were initiated on long-term NIV in the province
of Alberta over the study period. The median age for NIV initiation 7.8
(IQR 9.2) years and 61\% were males (Table 1). The most common
diagnostic category was upper airway disorders, followed by disorders of
the central nervous system (CNS; specific underlying disorders specified
in Table 2). A quarter of children were using a technology in addition
to NIV therapy (Table 1). CPAP was used by 75\% of children and the most
common mask type was a nasal mask (62\%). 73\% of children were
initiated electively after a PSG study while 18\% started NIV during a
hospital admission. Forty-six percent of children continued NIV, 39\%
discontinued, 14\% were transferred to adult services, and 1\% were lost
to follow-up. Of the children who discontinued NIV, 16\% of the total
discontinued due to improvements in the underlying conditions, 15\% of
patients/family declined continuing NIV therapy, 5\% died, and 1\%
switched to IMV. Follow up data were available for 97\% of children for
the initial follow-up visit and 61\% had sufficient data for inclusion
at the most current visit. A total of 93\% of children reported at least
one NIV-related complication during the initial follow-up visit and 90\%
in the most current follow-up visit.

\emph{Univariate analysis}

On univariate analysis, age, NIV type, and the epoch that children
started NIV had a significant impact on most of the long-term NIV
outcomes (Table 3). Other co-variates such as the overall diagnostic
category, parameters of medical complexity, and presence of NIV
complications had outcome specific significance.

\emph{Demographic predictors}

Of the 622 children using long-term NIV, 620 (99.7\%) had available
baseline and long-term follow-up data to be included in the multivariate
analysis. Age was a significant predictor of NIV outcomes. Younger kids
were more likely to discontinue NIV due to improvement in the underlying
condition, with the odds of discontinuing NIV decreasing 5.6\% for every
one-year increase in age {[}0.944 (95\% CI 0.893 to 0.999), Figure 1{]}.
The odds of switching to IMV/death, or need for hospitalization,
decreased with increasing age. As expected, older children were more
likely to transition to adult services or out-of-province care {[}1.314
(95\% CI 1.228 to 1.387){]}. Sex was not a predictor of NIV outcomes in
our cohort.

\emph{Clinical predictors}

Diagnostic categories were also significant predictors of NIV outcomes.
Overall, children with upper airway disorders were less likely to
discontinue NIV compared to the other diagnostic categories (0.581 (95\%
CI 0.348 to 0.971, Figure 1). Children with CNS disorders had 3.3 times
higher odds of being hospitalized while using NIV. Specific underlying
conditions that were predictors of different NIV outcomes included
children with bronchopulmonary dysplasia, who had higher odds of
improving their breathing status and discontinuing NIV {[}4.707 (95\% CI
1.306 to 16.962){]}, and children with obesity/metabolic syndrome who
had higher odds of declining NIV therapy {[}2.077 (95\% CI 1.110 to
3.888){]}.

Parameters of medical complexity including use of other medical
technology, number of co-morbidities, and previous surgeries were also
significant predictors of long-term NIV outcomes. Children requiring any
technology in addition to NIV use had 3.3 (95\% CI 2.051 to 5.387) times
higher odds of NIV failure (switch to IMV or death) and 2.6 (95\% CI
1.526 to 4.340) times higher odds of hospitalization for each added
technology (Figure 1). They were also less likely to decline NIV, with a
0.417 (95\% CI 0.202 to 0.859) reduction in odds ratio for each
additional technology. The presence of comorbidities increased the odds
for hospital admissions by 1.2 (95\% CI 1.022 to 1.440) times but was
not a predictor for NIV failure or any other long-term NIV outcomes.
Children who had received a previous adenotonsillectomy surgery had 3.7
times less odds of NIV failure (switching to IMV or dying) compared to
children who did not. The presence of previous major surgeries was not a
significant predictor of long-term outcomes.

\emph{Technology-related predictors}

Technology type was a strong predictor of long-term outcomes: children
using CPAP had 23 (95\% CI 3.017 to 79.482) times higher odds of
improving their underlying condition and discontinuing therapy, whereas
children on BPAP had 4.7 (95\% CI 2.481 to 8.822) times the odds of
needing ongoing NIV (Figure 1). BPAP was also a predictor of NIV
failure, with children on BPAP having 2.3 (95\% CI 1.069 to 5.063) times
the odds of switching to IMV or dying compared to children on CPAP. Mask
type and triggers for NIV therapy did not significantly impact long-term
NIV outcomes. The period children were initiated on NIV was also a
significant predictor of NIV outcomes. Children who started NIV in the
most recent epoch (2011-2014) had 3.6 (95\% CI 2.044 to 6.277) times the
odds of continuing NIV compared to those in the previous epochs. In
contrast, children starting NIV in the second epoch (2008-2011) had 2.6
(95\% CI 1.229 to 5.552) times the odds of being switched to IMV or
dying compared to the third epoch. Expectedly, children who started NIV
in the first epoch (2005 -- 2008) and the second epoch (2008 -- 2011)
were more likely to be transferred to other services (i.e. adult
services) compared to those who started NIV in the most recent epoch
{[}5.812 (95\% CI 2.799 to 12.07) and 3.491 (95\% CI 1.845 to 6.605)
respectively{]}.

\emph{Follow-up predictors}

Early and late NIV-related complications detected during the initial and
follow-up visit significantly predicted long-term outcomes. For each
additional complication reported, the odds that the patient/family would
decline NIV increased 1.3 (95\% CI 1.034 to 1.642) and 1.4 (95\% CI
1.052 to 1.854) times at the initial and most recent follow-up visit
respectively (Figure 1). In addition, as the number of complications
increased, the odds of continuing NIV decreased by 8.7\% for each added
complication in the most recent follow up visit.

\textbf{Discussion}

This multicenter study focuses on the impact of commonly available
demographic, clinical and technology-related parameters on the outcomes
of long-term NIV therapies in children. As children may improve over
time, particularly younger children, periodic evaluation of the need for
NIV is recommended. The presence of a CNS disorder implies worse
prognosis despite NIV use, with higher risk for hospitalization and
ongoing need for NIV use in the long-term while children with upper
airway abnormalities and children with bronchopulmonary dysplasia were
more likely to be able to discontinue NIV in the long-term. Higher
medical complexity, including higher number of co-morbidities and
additional technology use, predicts an increased risk for NIV failure
(switch to IMV or death), requiring a proactive approach during periodic
clinical evaluations and discussion with patients and families. The
technology type also has an impact on long-term outcomes with children
requiring BPAP generally showing more technology dependence in the
long-term and worse outcomes despite NIV. Finally, children using NIV
during the most recent period were more successful at maintaining NIV in
the long-term and prevent need for IMV or death than in previous epochs,
suggesting a positive learning curve of the medical team with improved
counselling, patient's monitoring, and treatment strategies.

As a significant number of children discontinued NIV therapies due to
improvement of their underlying condition (16\%), periodic re-evaluation
of their underlying sleep-related breathing disorder with
polysomnography should be warranted. According to our data, this is
especially relevant in younger children and children with upper airway
disorders, as they are more likely to improve and not require NIV in the
long-term. These results adds on previous data from our group showing
higher likelihood of NIV discontinuation due to improvement in
underlying condition (OR 2.04 (1.04 to 4.03)) in a study comparing NIV
outcomes in infants (\textless{}2 years of age) versus older
children\textsuperscript{13}. These data are comparable with a previous
study describing NIV (CPAP and BPAP) discontinuation rates of 27\% of
their overall cohort based on symptoms improvement and normalization of
gas exchange (oxygen and/or carbon dioxide levels)\textsuperscript{14}.
In this study, children tend to be younger (median age 1.4 years) at NIV
discontinuation and the most frequently weaned children had upper airway
anomalies (40\%), Prader Willi syndrome (10\%) and bronchopulmonary
dysplasia (7\%). Other cohorts, however, showed lower rates of NIV
discontinuation and no differences by diagnostic
category\textsuperscript{21-23}, suggesting differences in the
population of children receiving NIV at different centers. While it is
clear from the results of this study that re-evaluation of the
underlying sleep-related breathing disorder and need for NIV support is
needed in young children and children with upper airway abnormalities or
bronchopulmonary dysplasia, this study does not analyze the periodicity
of such evaluations, for which further studies might be required.

The presence of high medical complexity seems to influence ongoing need
for NIV as well as higher risk for NIV failure resulting in escalation
to IMV or death and higher need for hospitalization despite NIV use.
Medically complex children have been defined as those having multiple
underlying conditions, impairment of daily functioning, and/or
technology dependence\textsuperscript{24,25}. While previous research
have shown higher risk for escalation to IMV or death in children with
certain underlying conditions who are more prone to have high medical
complexity (neurologic, neuromuscular and cardiac
conditions)\textsuperscript{15}, to our knowledge, the impact of
specific parameters of medical complexity in long-term NIV outcomes have
not been studied before. Although only a small proportion of children
using NIV in our cohort required switch to IMV or died in our cohort
(1\% and 5\% respectively), in alignment with data from previous
studies\textsuperscript{15,22,23,26-29}, this study adds on critical
information about which patients are at higher risk for adverse
outcomes, allowing stakeholders to better plan for the care of children
with ongoing high medical needs after NIV initiation. Further these
results provide guidance to clinicians and families of medically complex
children regarding long-term expectations for NIV and counselling for
overall goals of care.

A frequent concern for clinicians caring for children using NIV is the
patient/family decision to discontinue NIV therapy (15\% in our cohort),
particularly in children with OSA\textsuperscript{30}. Although
patient/family-reported reasons for NIV declination were not analyzed in
this study, interesting data arose from these results. Unexpectedly, no
specific diagnostic category predicted the patient/family decision to
stop NIV therapy. The presence of OSA per se did not predict
patient/family NIV declination while children with obesity/metabolic
syndrome using NIV were more likely decline NIV. The reasons for these
findings are unclear. As highlighted in a previous qualitative study,
these children may have a different perception of their health and need
of NIV as well as psychological, social and health barriers for NIV
continuation\textsuperscript{31}. The presence of NIV-related
complications was, not surprisingly, a significant predictor for NIV
declination. This has previously been examined in studies looking at
predictors of NIV adherence\textsuperscript{32}. We, however, could not
find studies describing factors influencing the patient/family decision
to fully discontinue NIV. Knowing this information will allow clinicians
to anticipate which patients are more likely to stop NIV over time and
work with children and families to prevent dropouts. In addition, this
information highlights the need for ongoing close monitoring of children
using NIV to detect technology-related complications and implement early
interventions that mitigate such events and prevent therapy declination.

The outcomes of long-term NIV use appear more promising for children
using NIV in the most recent epoch period. While more children continue
using NIV therapy lately suggesting less patient/family NIV declination,
escalation to IMV or death has decreased compared to the previous
epochs. These findings are not surprising, as previous reports have
demonstrated similar learning curves resulting in higher long-term
adherence rates\textsuperscript{33,34}. These improvements might be due
to changes that have taken place in our pediatric NIV programs over
time, including closer monitoring of children requiring NIV therapies
and early detection of NIV-related complications, barriers to NIV
initiation, family support and counselling, and larger availability of
mask interfaces for pediatric ages and more customization options
available, although these changes have not been included in this study
analysis\textsuperscript{33,35,36}. This information is encouraging to
continue investing resources and time in the care of this group of
children.

There were some limitations to our study. There are likely to be more
co-variates that influence the outcomes we have examined; however, as
our study is a retrospective chart review, data collection was limited
to the information present in the patient's medical records. In
addition, the data reported in the second follow-up visit (i.e. number
of NIV related complications) was only available in 61\% of our cohort.
To account for this bias, we ran the statistics with and without the
second follow-up variable. Since the models did not significantly change
with the addition of this co-variate, we decided to include it into our
regression analysis.

\textbf{Conclusion}

The results of this study reflect the influence of demographic, clinical
characteristics and technology of the children receiving NIV on
long-term therapy outcomes particularly age, diagnostic category and
specific underlying conditions, added comorbidities and technologies in
use and technology type. These results are important for clinicians, as
they can use available information to discuss goals and expectations of
NIV with children and families even prior to NIV initiation and optimize
resources to ensure adequate follow up management and improve the
success children may achieve using NIV therapy.

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