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. 2025 Mar 27;34(5):e70053. doi: 10.1111/jsr.70053

Improving Obstructive Sleep Apnoea Mitigates Dampened Heart Rate Responses to Respiratory Events in Children With Down Syndrome

Lisa M Walter 1,✉, Marisha Shetty 1, Ahmad Bassam 1, Margot J Davey 1,2, Gillian M Nixon 1,2, Rosemary S C Horne 1
PMCID: PMC12426726  PMID: 40150823

ABSTRACT

Children with Down syndrome (DS) have a dampened heart rate (HR) response at obstructive respiratory event termination compared with typically developing children. Whether improving obstructive sleep apnoea (OSA) severity improves the HR response to both obstructive and central events remains unknown. Twenty‐four children (3–19 years at baseline) were included. Children were grouped into improved (decrease in obstructive apnoea‐hypopnoea index to ≤ 50% of baseline; n = 12; seven treated between studies) and unimproved (n = 12; two treated between studies) 2 years following baseline study. Beat‐to‐beat HR was averaged 10 s before (pre), during, and the peak after (post) each obstructive and central event during sleep, expressed as percentage change. A total of 1018 obstructive respiratory events were analysed during total sleep; 583 events were analysed at baseline and 435 at follow‐up. A total of 330 central events were analysed during total sleep; 164 central events were at baseline and 166 were at follow‐up. In the unimproved group, the % change in HR from during the event to post‐event was smaller at follow‐up for both obstructive (mean 16.8%, 95% CI [17.4%, 20.6%] vs. 22.3% [21.1%, 26.0%] and central events: 15.8% [13.6%, 17.9%] vs. 26.1% [22.4%, 29.9%]; p < 0.05 for both). % change remained unchanged between studies in the improved group. These results suggest that the dampened HR response to respiratory events seen in children with DS worsens over time when OSA does not improve, adding weight to the need for diagnosis and management of OSA in this population.

Keywords: autonomic cardiovascular control, heart rate, obstructive sleep apnoea, paediatric

1. Introduction

Obstructive sleep apnoea (OSA) is characterised by repetitive obstructive respiratory events that are associated with hypoxia, hypercarbia and sleep fragmentation (Marcus et al. 2012). In TD adults (Hamilton et al. 2004), school‐aged (O'Driscoll et al. 2009) and preschool‐aged children (Nisbet, Yiallourou, Nixon, et al. 2013), there is a decrease in heart rate (HR) and blood pressure (BP) during each respiratory event that is followed by a surge in HR and BP at the termination of the event. The bradycardia during respiratory events is significantly more pronounced during central compared with obstructive events (Tamanyan et al. 2019). It has been postulated that the adverse long‐term effects of OSA on the cardiovascular system are a result of these repetitive swings in HR and BP, which result in microvascular dysfunction (Peppard et al. 2000), endothelial cell damage (Gozal et al. 2007), resetting of the baroreceptors (Khayat et al. 2009) and increased sympathetic activation (Montesano et al. 2010; O'Brien and Gozal 2005).

The incidence of OSA in typically developing (TD) children is 1%–6% (Marcus et al. 2012), however in some children, including those with Down syndrome (DS), the incidence of OSA is much higher, with studies reporting that 31%–97% (Horne et al. 2019) of children are affected. This can be attributed to the significant reduction in upper airway size in children with DS, due to mid‐face and mandibular hypoplasia, relatively large and medially positioned tonsils and macroglossia (Shott 2006; Subramanyam et al. 2016). In addition, children with DS are also prone to obesity and general muscle hypotonia, which contribute to upper airway collapse during sleep (Subramanyam et al. 2016; Nixon et al. 2016). Children with DS also have more frequent central apnoeas during sleep (Ferri et al. 1997; Hizal et al. 2022; Fan et al. 2017). This is hypothesised to be associated with dysfunctional central respiratory control in the brainstem (Ferri et al. 1997; Siriwardhana et al. 2021) and/or related to immature respiratory central control and hypotonia (Fan et al. 2017).

In addition, DS is associated with autonomic dysfunction during both wake and sleep. When awake, adults (Fernhall et al. 2005; Fernhall and Otterstetter 2003; Figueroa et al. 2005; Agiovlasitis et al. 2010; Bunsawat et al. 2015) and children (de Carvalho et al. 2015) with DS have blunted HR responses at rest and during exercise or autonomic tasks. Compared with TD children, children with DS and OSA have worse left ventricular diastolic function that is correlated with increasing OSA severity (Konstantinopoulou et al. 2016). They also exhibit impaired autonomic control of HR as evidenced by reduced HR variability (Horne et al. 2021) and dampened HR responses to spontaneous arousals from sleep (O'Driscoll et al. 2010) and to both obstructive and central respiratory events (O'Driscoll et al. 2012; Walter et al. 2024) compared to TD children.

As in TD children, the first line of treatment for OSA in children with DS is typically adenotonsillectomy (AT). However, OSA does not resolve following treatment in a higher proportion of children with DS compared to TD children (Nation and Brigger 2017). Further surgery, such as lingual tonsillectomy and tongue reduction surgery, or nonsurgical treatments, such as continuous positive airway pressure (CPAP) and non‐invasive ventilation, are often required in children with DS (Dudoignon et al. 2017; Nehme et al. 2019). We have previously identified that improvement in OSA severity prevents the worsening of autonomic function as measured by HR variability (Walter et al. 2023); however, to date, studies have not investigated the effects of improvement in OSA severity on the HR surge at respiratory event termination in children with DS. Therefore, in this study, we aimed to compare the change in HR at the termination of both obstructive and central events, 2 years following a baseline study in children with DS whose OSA had improved compared with those children whose OSA remained unimproved. We hypothesised that similar to our HR variability findings, further dampening of the post‐respiratory event surge in HR during both obstructive and central respiratory events would be mitigated in the children whose OSA was improved compared with baseline.

2. Methods

2.1. Subjects

Ethical approval for this study was obtained from the Monash University and Monash Health Human Research Ethics Committees (12276B, 14024B and 15048A). Written consent was obtained from parents and verbal assent from children over 7 years of age.

Children with DS aged 3–19 years either referred for assessment of SDB (n = 9) or from the general population of children with DS (n = 15) via publicity by DS Victoria were recruited between May 2016 and March 2018. A previous publication which compared children recruited from the community to those referred to our sleep laboratory identified that there were no differences in OSA severity after polysomnography or quality of life, behaviour, daytime functioning, and sleep symptoms based on parental questionnaires between the children recruited from the two sources (Wijayaratne et al. 2021). Parents were asked to participate in a follow‐up study with an identical protocol to assess the effects of treatment approximately 2 years after the initial study, with children returning for testing between August 2018 and May 2021. A number of follow‐up studies had to be delayed due to the closure of the sleep laboratory for research subjects between March and December 2020 as a result of the COVID‐19 pandemic. Parents completed a medical history form including details of any treatment for OSA and a demographic questionnaire. Children with DS were well at the time of the polysomnographic (PSG) studies. Two children had undergone surgery for non‐cyanotic congenital heart disease as an infant but were considered to have no active cardiac disease at the time of the studies, six had undergone AT and two had a tonsillectomy prior to the baseline study, six were on thyroxine for hypothyroidism, and one was taking melatonin for sleep‐onset insomnia. Results of the effects of treatment on sleep quality using EEG spectral analysis (Betavani et al. 2022), and the effects of treatment and improvement in OSA severity on HR variability (Walter et al. 2023) from this cohort have been previously published.

2.2. Protocol

All children underwent overnight attended PSG using standard paediatric recording techniques (Berry et al. 2020, 2012). Prior to the PSG study, height and weight were measured, and body mass index (BMI) z‐score was calculated. Electrophysiological signals were recorded using a commercially available PSG system (E‐Series or Grael, Compumedics, Melbourne, Australia). The montage included electroencephalogram (EEG) (Cz, F3‐M2, F4‐M1, C3‐M2, C4‐M1, O1‐M2 and O2‐M1), right and left electrooculogram (EOG), submental electromyogram (EMG), left and right anterior tibialis muscle EMG and electrocardiogram (ECG). Respiratory characteristics were captured using abdominal and thoracic respiratory plethysmography (Pro‐Tech zRIP Effort Sensor, Pro‐Tech Services Inc., Mukilteo, WA), oronasal thermistor, nasal pressure, and transcutaneous carbon dioxide (TcCO2) (TCM4/40, Radiometer, Denmark, Copenhagen or Sentec, Therwil, Switzerland). Peripheral oxygen saturation (SpO2) was measured using Bitmos GmbH (Bitmos, Dusseldorf, Germany), which uses Masimo signal extraction technology for signal processing, or Masimo Radical 7 (Masimo, Irving, CA), with both devices set to a 2‐s averaging time. All signals were recorded at 512 Hz.

2.3. Sleep and Respiratory Analysis

All PSG studies were scored manually in 30 s epochs for sleep stages (N1, N2, N3 and REM), respiratory events > 2 breaths in duration and arousals, by trained paediatric sleep scientists using Compumedics ProFusion software according to the American Academy of Sleep Medicine paediatric guidelines (Berry et al. 2020, 2012). An obstructive apnoea was defined as the cessation of airflow in association with ongoing respiratory effort; an obstructive hypopnoea was defined as a ≥ 30% decrease in nasal pressure signal amplitude, associated with increased work of breathing and an arousal or ≥ 3% decrease in oxygen saturation; a central apnoea was defined as cessation of airflow without inspiratory effort lasting either ≥ 20 s or at least the duration of two breaths and associated with an arousal or ≥ 3% oxygen desaturation; and a central hypopnoea as ≥ 30% decrease in nasal pressure signal amplitude with reduced inspiratory effort throughout the entire duration of the event and associated with desaturation or arousal (Berry et al. 2020, 2012). A mixed apnoea was defined if an event was associated with absent respiratory effort during one portion of the event and the presence of obstructed inspiratory efforts in another portion, regardless of which portion came first (Berry et al. 2020, 2012). The obstructive apnoea‐hypopnoea index (OAHI) is defined as the total number of obstructive apnoeas, mixed apnoeas and obstructive hypopnoeas per hour of total sleep time (TST) (Berry et al. 2020, 2012). Other respiratory parameters included the respiratory disturbance index (RDI), defined as the total number of respiratory events, including obstructive and central apnoeas, mixed apnoeas, obstructive and central hypopnoeas per hour of TST; the REM RDI; the arousal index (ArI), defined as the number of cortical EEG arousals per hour of TST; the central apnoea‐hypopnoea index (CnAHI), defined as the number of central apnoeas and hypopnoeas per hour of TST (Berry et al. 2020, 2012). Desaturation measures included the average SpO2 drop, defined as the average SpO2 desaturation with scored respiratory events; SpO2 nadir, the lowest oxygen saturation associated with a respiratory event; SpO2 ≥ 4% drop, defined as the number of times the SpO2 dropped by greater than or equal to 4% per hour of TST; SpO2 ≤ 90% drop, defined as the number of times the SpO2 dropped below 90% per hour of TST; and the average transcutaneous pCO2 during TST (Av TcCO2) (Berry et al. 2020, 2012). OSA severity categories were based on the OAHI. Primary snoring (PS) was defined as an OAHI ≤ 1 event/h, Mild OSA as an OAHI of > 1 to ≤ 5 events/h, Moderate OSA as an OAHI of > 5 to ≤ 10 events/h and Severe OSA as an OAHI of > 10 events/h. The children were grouped into improved and unimproved, with improvement in OSA severity being defined as a reduction in OAHI of ≥ 50% from baseline to follow‐up. The 50% improvement point was chosen as it represents a substantial improvement in OSA severity even in those with severe OSA and has been commonly used in adult studies as a metric of OSA improvement (Fox et al. 2019; Lorenzi‐Filho et al. 2017; Zaghi et al. 2016). We have previously published the effect on HR variability of a 50% improvement in OSA severity in children with DS (Walter et al. 2023). We chose not to group the children as treated and untreated due to the variability in response to treatment on OSA severity in children with DS, which may mask the effect that a significant improvement in OSA severity would have on autonomic function. Improvement rather than resolved vs. unresolved grouping was used given the high rates of non‐resolution of OSA in children with DS after treatment.

2.4. Respiratory Event Analysis

PSG data were transferred to specialised data analysis software (LabChart 7.2, ADInstruments, Sydney, Australia) for analysis. The change in HR across individual obstructive and central respiratory events was conducted according to previously published methods (O'Driscoll et al. 2009; Nisbet, Yiallourou, Nixon, et al. 2013; Walter et al. 2024). Peak detection was used to identify the peak of the ECG R wave, and beat‐by‐beat HR was calculated from consecutive R‐wave peaks of the ECG. All respiratory events > 2 respiratory cycles in duration, including apnoeas and hypopnoeas that were free of movement or technical artefact, were analysed, irrespective of length, as young children have faster respiratory rates than older children and adults, and thus events < 10 s duration were also included (Bhattacharjee and Gozal 2009). Each respiratory event was divided into an early event phase and a late event phase of equal duration, and the HR was averaged for the late event phase, allowing comparison of data between events of different durations (Figure 1). A pre‐event baseline was determined as the 10 s prior to each event, and the HR was averaged for this phase. The 15 s following the termination of each event was called the post‐event phase, and the mean of the three consecutive beats at the HR peak during this phase was obtained.

FIGURE 1.

FIGURE 1

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Abbreviated excerpt from an original polysomnographic trace. The baseline, early and late respiratory event phases and post‐event periods are delineated by solid lines. ECG = electrocardiogram; ExpCO2 = expired carbon dioxide; HR = heart rate; RIP = respiratory inductance plethysmography; SaO2 = arterial oxygen saturation.

To ensure a stable pre‐event baseline, events occurring during a cycle of repetitive apnoeas or hypopnoeas were excluded when a respiratory event occurred in the 25 s preceding an event. The percentage change in HR from pre‐event to both late event and post‐event, and from late event to post‐event was calculated. The characteristics associated with each analysed event were also recorded, including sleep state (NREM, REM), arousal or no arousal, event type (central, obstructive) and event length.

2.5. Statistical Analysis

Statistical analysis was performed using SPSS software v27 (IBM SPSS, Chicago, USA). Data were first tested for normality and equal variance. Demographic, sleep and respiratory data were compared between groups (improved vs. unimproved) and between studies (baseline vs. follow‐up) using a two‐way repeated measures ANOVA, with study as the repeated measure. The differences in the number of respiratory events during NREM and REM sleep in the unimproved and improved groups were analysed using Fisher's Exact tests. Spearman's rank correlation was used to test the association between the number of obstructive and central respiratory events with OAHI and CAHI respectively, age, BMI z‐score and event length. To account for the clustering of data within individuals and between individual variability, multilevel linear modelling was used to independently determine the fixed effects of the group (unimproved and improved) for the phases of the respiratory events (pre‐event, late event, post‐event, the % change in HR from pre‐event to late event, pre‐event to post‐event and late event to post‐event) during total sleep, NREM and REM sleep. Individual subject IDs were entered for each respiratory event. The HR data were entered as the dependent variable. Groups and phases of respiratory events were entered as factors in the model. OAHI, associated respiratory arousals, treatment status and event length were entered into the model as covariates, and confidence interval adjustment was conducted using Bonferroni tests. The decision to account for the treatment status within each group, range of OAHI, presence of an arousal and the length of each respiratory event, and include each of these factors in our statistical model, was based on previous studies showing the importance of each of these factors to HR in OSA (O'Driscoll et al. 2009; Nisbet, Yiallourou, Nixon, et al. 2013; Tamanyan et al. 2019; Jordan et al. 2011; Haba‐Rubio et al. 2005; Trinder et al. 2003; Hietakoste et al. 2020).

3. Results

Forty‐four children with DS were recruited for the baseline study, of whom 24 children agreed to return for the follow‐up study. At follow‐up, nine children received treatment: five AT, one tonsillectomy, one lingual tonsillectomy, and two CPAP. Fifteen of the 24 children with DS who returned for the follow‐up study had been recruited from the community. Eleven of those 15 had OSA at baseline, and four had PS. The remaining nine children were recruited from the children who were having an overnight PSG for assessment of suspected OSA. Eight of these nine children had OSA, and one child had PS.

The number of children in each OSA severity group at baseline and follow‐up in both groups is presented in Table S1.

Demographic, sleep and respiratory characteristics for the improved and unimproved groups are presented in Table 1. There were no significant differences between the groups at either baseline or follow‐up for age, sex, or any of the sleep variables. OAHI increased significantly from baseline to follow‐up in the unimproved group and decreased significantly in the improved group (p < 0.05 for both). Baseline OAHI was significantly higher in the improved group compared with the unimproved group (p < 0.05), and there was no difference between the groups at follow‐up. The number of times the SpO2 dropped below 90% and dropped by at least 4% were statistically higher in the improved group compared with the unimproved group (p < 0.05 for both) at baseline but not at follow‐up.

TABLE 1.

Demographic, sleep and respiratory characteristics in children with Down syndrome in the unimproved and improved groups at baseline and follow‐up.

Unimproved Improved
Baseline (n = 12), 7F/5M Follow‐up (n = 12) Baseline (n = 12), 6F/6M Follow‐up (n = 12)
Age (years) 9.2 ± 4.2 11.1 ± 4.4 11.3 ± 4.5 12.8 ± 4.1
(Age range) (3.9–19.1) (4.8–21.7) (5.6–17.1) (7.1–19.0)
BMI z‐score 1.23 ± 0.90 1.50 ± 0.75 1.06 ± 0.80 1.14 ± 0.84
Total sleep time (min) 435 ± 78 422 ± 60 397 ± 71 407 ± 46
Wake after sleep onset (%) 8 ± 4 12 ± 7 18 ± 13 12 ± 7
Sleep efficiency (%) 83 ± 12 83 ± 11 75 ± 13 81 ± 7
Sleep latency (min) 40 ± 45 27 ± 27 39 ± 37 30 ± 15
N1% 6 ± 4 7 ± 5 7 ± 7 5 ± 3
N2% 48 ± 10 46 ± 7 50 ± 8 50 ± 8
N3% 32 ± 19 29 ± 6 28 ± 9 30 ± 6
NREM % 82 ± 8 82 ± 4 84 ± 6 86 ± 6
REM % 18 ± 8 18 ± 4 16 ± 6 14 ± 6
OAHI (events/h)

6.1†

[0, 22.9]

14.4

[0.3, 54.6]

 29.5*# [1.6, 154.0]

8.4

[0, 77.0]
RDI (events/h) 10.3 ± 8.9 16.8 ± 18.5 34.3 ± 45.0# 14.5 ± 26.1
CAHI (events/h) 3.1 ± 4.3 2.2 ± 1.3 4.1 ± 5.8 5.5 ± 10.6
Arousal index (events/h) 15.5 ± 6.2 15.7 ± 7.2 26.6 ± 25.4 18.5 ± 15.6
SpO2 nadir (%) 89 ± 4 85 ± 5 83 ± 9 89 ± 6
Average SpO2 drop 4.0 ± 0.9 4.5 ± 1.0 4.7 ± 1.6 4.5 ± 1.5
SpO2 < 90%/h 0.3 ± 0.6 0.8 ± 0.6 7.7 ± 22.3* 2.8 ± 8.9
SpO2 > 4% drop/h 3.5 ± 3.1† 8.4 ± 9.1 20.3 ± 36.6*# 8.6 ± 20.3
Average TcCO2 TST 45.7 6 ± 4.9 44.2 6 ± 4.6 47.9 6 ± 4.5# 41.9 6 ± 3.3
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Note: Data presented as mean ± SD, except OAHI presented as mean [min, max]. *p < 0.05 Baseline unimproved compared to baseline improved. †p < 0.05 Baseline unimproved compared with follow‐up unimproved. #p < 0.05 Baseline improved compared to follow‐up improved.

Abbreviations: CAHI = central apnoea‐hypopnoea index; N1 = NREM stage 1; N2 = NREM stage 2; N3 = NREM stage 3; NREM = non‐rapid eye movement; OAHI = obstructive apnoea‐hypopnoea index; RDI = respiratory disturbance index; REM = rapid eye movement; SpO2 = arterial oxygen saturation; TcCO2 = transcutaneous carbon dioxide; TST = total sleep time.

3.1. Number of Obstructive and Central Respiratory Events Analysed

A total of 1018 obstructive respiratory events were analysed; 583 events were analysed during total sleep at baseline and 435 at follow‐up (Table 2). There were more obstructive events analysed in the improved group (366) than in the unimproved group (322) and more events occurred during NREM (688) than during REM (333) sleep (p < 0.001). As expected, the number of obstructive events a child had was highly correlated with the OAHI (Spearman r = 0.95, p < 0.001), and moderately correlated with age (Spearman r = 0.71, p < 0.001). BMI z‐score and event length were not significantly correlated with the number of obstructive events.

TABLE 2.

Number of obstructive and central respiratory events analysed in children with Down syndrome during NREM and REM, in the unimproved and improved groups, at baseline and follow‐up.

Obstructive respiratory events
Baseline Follow‐up
Unimproved Improved Total Unimproved Improved Total
NREM
133 277 410 189 89 278
REM
93 80 173 124 33 157
Central respiratory events
Baseline Follow‐up
Unimproved Improved Total Unimproved Improved Total
NREM
46 58 104 39 84 123
REM
33 27 60 20 23 43
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Abbreviations: NREM, non‐rapid eye movement; REM, rapid eye movement.

A total of 330 central events were analysed; 164 central events were analysed during total sleep at baseline and 166 at follow‐up. There were more central events analysed in the improved (192) than in the unimproved group (138) and more events occurred during NREM (227) than during REM (103) sleep (p < 0.02). The number of central events was moderately correlated to the CAHI (Spearman r = 0.55, p = 0.011). Age, BMI z‐score, and event length were not significantly correlated with the number of central events.

In both groups, the proportion of obstructive events analysed was higher than central events: Unimproved Group, 60% ± 30% obstructive, 40% ± 30% central; Improved Group, 71% ± 23% obstructive, 29% ± 23% central.

3.2. % Change in HR During Obstructive Respiratory Events

During obstructive and central respiratory events, the HR decreases from the pre‐event phase to the late event phase and then increases post‐event.

3.2.1. % Change in HR Between Baseline and Follow‐Up Studies

In the unimproved group during total sleep (Figure 2a) and NREM (Figure 2b), the % change in HR from the late event nadir to the post‐event surge was significantly lower at follow‐up compared with baseline (p < 0.05 and p < 0.01, respectively). In contrast, in the improved group, there was no difference between baseline and follow‐up studies during total sleep (Figure 2a) and NREM (Figure 2b). There were no differences between baseline and follow‐up studies for either the improved or the unimproved group during the other phases of the respiratory event either during total sleep (Figure 2a) or NREM (Figure 2b). During REM (Figure 2c), there were no differences between the baseline and follow‐up studies for either the improved or the unimproved group.

FIGURE 2.

FIGURE 2

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% change in HR data during obstructive respiratory events at baseline and follow‐up in children with Down syndrome with obstructive sleep apnoea, whose obstructive apnoea‐hypopnoea index was unimproved or had improved by at least 50% from baseline to follow‐up, during (a) total sleep, (b) NREM sleep and (c) REM sleep. Data presented as mean ± 95% CI. *p < 0.05, **p < 0.01.

3.2.2. % Change in HR Between Improved and Unimproved Groups

In the baseline study, during total sleep (Figure 2a), the % change in HR from the pre‐event to the post‐event phase was significantly greater in the unimproved compared with the improved group (p < 0.05), and during NREM (Figure 2b) from the late event to the post‐event phase (p < 0.05). During REM (Figure 2c), there were no differences between the unimproved and improved groups for any phase of the respiratory events at the baseline study.

In the follow‐up study, there were no differences in the % change in HR between the unimproved and improved groups for any phase of the respiratory events during total sleep (Figure 2a), NREM (Figure 2b) and REM (Figure 2c).

3.3. % Change in HR During Central Respiratory Events

3.3.1. % Change in HR Between Baseline and Follow‐Up Studies

In the unimproved group during total sleep (Figure 3a) and NREM (Figure 3b), the % change in HR from the late event phase to the post‐event phase was significantly lower at follow‐up compared with baseline (p < 0.05 and p < 0.01, respectively). In contrast, in the improved group, there was no difference between baseline and follow‐up studies during total sleep (Figure 3a) and NREM (Figure 3b). There were no differences between baseline and follow‐up studies for either the improved or the unimproved group during the other phases of the respiratory event either during total sleep (Figure 3a) or NREM (Figure 3b). During REM (Figure 3c), there were no differences between the baseline and follow‐up studies for either the improved or the unimproved group.

FIGURE 3.

FIGURE 3

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% change in HR data during central respiratory events at baseline and follow‐up in children with Down syndrome with obstructive sleep apnoea, whose obstructive apnoea‐hypopnoea index was unimproved or had improved by at least 50% from baseline to follow‐up, during (a) total sleep (b) NREM sleep and (c) REM sleep. Data presented as mean ± 95% CI. *p < 0.05, **p < 0.01.

3.3.2. % Change in HR Between Improved and Unimproved Groups

There were no differences in % change in HR between the improved and unimproved groups for any phase of the respiratory events during total sleep (Figure 3a), NREM (Figure 3b) or REM (Figure 3c) at either the baseline or follow‐up studies.

3.4. Comparison of % Change in HR Between Obstructive and Central Respiratory Events

Data presented in Supporting Information S1.

3.5. The Effect of Age, Sex, BMI z ‐Score, Treatment Status and OSA Severity at Baseline on % Change in HR for Obstructive and Central Respiratory Events

Data presented in Supporting Information S1.

4. Discussion

Children with DS have a higher risk of developing OSA compared with TD children, and the treatment of their OSA is often less effective. In this study, we assessed whether an improvement in OSA severity, measured as an improvement in OAHI by at least 50% 2 years after a baseline study, would improve or normalise the surge in HR at the termination of both obstructive and central respiratory events. However, during total sleep and during NREM and REM analysed separately, there was no difference between studies in the improved group. In contrast, in the unimproved group during total sleep and NREM, the % change in HR from the late event nadir to the post‐event surge in HR was significantly smaller at follow‐up compared with the baseline study. This was apparent for both obstructive and central respiratory events, following adjustment for OAHI, respiratory event length, and whether the event was associated with respiratory arousal and treatment status. Age, sex, BMI z‐score and OSA severity had no significant impact on the % change in HR when analysed at the participant level based on the individual child's mean values for each phase of the respiratory event instead of analysing every event for every child as for the previous analysis (see Table S2). Analysing the surge in HR at respiratory event termination is a method of examining autonomic cardiovascular function during sleep. Importantly, the current study shows that improvement in OSA prevents the worsening of the autonomic control of HR and that ongoing, even mild OSA may have further detrimental effects on cardiovascular functioning over time.

Results from the current study build on our previous research, which showed that children with DS exhibited dampened HR response to obstructive respiratory events compared with TD children (Walter et al. 2024) and from the same cohort of children, that improvement in OSA severity prevents further worsening of autonomic dysfunction measures using heart rate variability (Walter et al. 2023). The post‐event surges in HR and BP that characterise OSA are attributed to an elevation in sympathetic nervous system activity during the respiratory event, a consequence of event‐related arousals and hypoxia, which oppose the normal dipping of HR and BP that typically occur during sleep (Leung 2009; Kohler and Stradling 2013). Autonomic function during sleep measured using HR variability is dampened in children with DS and OSA compared with TD children matched for OSA severity, age and sex, evidenced by reduced parasympathetic activity (Horne et al. 2021).

The fall in HR during central events was greater compared to obstructive events during NREM in both groups and at both the baseline and follow‐up studies. This is similar to the HR response found in TD children, where central events elicited a greater fall in HR during events compared with obstructive events during NREM (Tamanyan et al. 2019). However, there was a differential HR response at event termination during NREM and REM, whereby the HR response was significantly greater in central compared to obstructive events during NREM and smaller during REM. Importantly, we previously identified that children with DS had a dampened HR response to central respiratory event termination compared with TD children (Walter et al. 2024). Children with DS can have significant numbers of central apnoeas, which may be exacerbated in children with complex comorbidities and unresolved congenital heart defects. In our cohort, only two children required surgery for non‐cyanotic congenital heart disease as infants, and so the dampened HR response found in our cohort to central respiratory events may under‐represent the response in children with more complex comorbidities. More obstructive than central events were analysed in our study. In contrast, a small study of children with DS (n = 10) reported a higher number of central events (89.4%) compared with obstructive events (9.4%), with the majority of the central events occurring during NREM and a higher number of obstructive events occurring during REM (Ferri et al. 1997).

Age, sex, BMI and OSA severity have been shown to affect autonomic control in children (Nisbet, Yiallourou, Walter, et al. 2013; Horne et al. 2018). This was not evident in our study when the mean change in HR for each child was analysed rather than analysing every respiratory event from every child. However, averaging the events per child does not take into account the difference in the number of events occurring between children, so a child with only a few respiratory events has as much input into the results as does a child who has a large number of events. Therefore, any differences between groups were potentially negated. Treatment status also did not have any significant effect on the % change in HR, which was not entirely unexpected given that OSA does not resolve following treatment in a higher proportion of children with DS compared to TD children (Nation and Brigger 2017). However, the low number of participantsmay have affected the power of the multilevel linear modelling adjusting for covariates, and a real effect of those covariates on outcome may have been missed.

We must acknowledge the limitations of the study. Of the 44 children in the original cohort at baseline, there were 20 children whose parents were not willing for their child to participate in the follow‐up sleep study. Overnight PSG studies in young children, especially those with an intellectual disability, are often poorly tolerated, and this is reflected in the children who refused to participate in the follow‐up study being significantly younger than the children who returned. Eight of the children had received treatment prior to the baseline study, which may have impacted the baseline data of the untreated group, as without previous treatment, they may have had more severe OSA. The study protocol originally aimed at a two‐year follow‐up period; however, because of local COVID restrictions, we were unable to maintain consistency with regard to the timing of the follow‐up studies, with the time between studies ranging from 22 to 31 months. The inclusion of a follow‐up group of TD children matched for OSA severity, age and sex at baseline would also have been advantageous and should be considered for future studies.

Although the American Academy of Pediatrics has recommended that children with DS have an overnight PSG study by the age of 4 years as significant OSA may be present in these children (Bull et al. 2011), it has been shown that 39% of children with DS do not have a PSG (Knollman et al. 2019). As many children with DS develop OSA after the age of 4 years, they should continue to be monitored beyond this age (Wijayaratne et al. 2021). Fifteen of the 24 children with DS who returned for the follow‐up study had been recruited from the community and had not been referred for a PSG by a clinician based on any suspicion of OSA. Eleven (73.3%) of those 15 had OSA at baseline and 4 (26.7%) had PS, highlighting that all children with DS should be regularly assessed with polysomnography.

5. Conclusion

This is a novel study that investigated the effect of OSA improvement on the dampened HR response to obstructive and central respiratory events in children with DS. We identified that a reduction in OSA severity by at least 50%, 2 years following the baseline study, mitigated the worsening of the dampened HR response seen in the children whose OSA had not improved. The high incidence of OSA in children with DS has a significant potential impact on long‐term health. These findings further support the importance not only of identifying and treating OSA in children with DS as early as possible but also of treatment of persisting OSA in this population. Treating OSA will contribute to improving their cardiovascular health and may also improve behavioural problems and cognitive function.

Author Contributions

Lisa M. Walter: conceptualization, methodology, formal analysis, writing – original draft. Marisha Shetty: writing – review and editing, formal analysis. Ahmad Bassam: formal analysis, writing – review and editing. Margot J. Davey: writing – review and editing, conceptualization. Gillian M. Nixon: conceptualization, funding acquisition, writing – review and editing. Rosemary S. C. Horne: conceptualization, writing – review and editing, funding acquisition.

Ethics Statement

Ethical approval for the current study was obtained from the Monash University and Monash Health Human Research Ethics Committees (12276B, 14024B and 15048A).

Consent

Written informed consent was obtained from parents and verbal assent from children over 7 years of age.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1. Supporting Information.

JSR-34-e70053-s001.docx (370.4KB, docx)

Acknowledgements

We would like to thank all the parents and their children who participated in the study and the staff of the Melbourne Children’s Sleep Centre, where the study was carried out. Open access publishing facilitated by Monash University, as part of the Wiley ‐ Monash University agreement via the Council of Australian University Librarians.

Walter, L. M. , Shetty M., Bassam A., Davey M. J., Nixon G. M., and Horne R. S. C.. 2025. “Improving Obstructive Sleep Apnoea Mitigates Dampened Heart Rate Responses to Respiratory Events in Children With Down Syndrome.” Journal of Sleep Research 34, no. 5: e70053. 10.1111/jsr.70053.

Funding: This work was supported by the Angior Family Foundation, the Jack Brockhoff Foundation and the Jérôme LeJeune Foundation.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author [RSCH] upon reasonable request and subject to approval of the Monash Health and Monash University ethics committees.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1. Supporting Information.

JSR-34-e70053-s001.docx (370.4KB, docx)

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author [RSCH] upon reasonable request and subject to approval of the Monash Health and Monash University ethics committees.

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