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Predictors of sleep disordered breathing in children with Down syndrome: a systematic review and meta-analysis

Nardin Hanna, Youstina Hanna, Henrietta Blinder, Julia Bokhaut, Sherri L. Katz
European Respiratory Review 2022 31: 220026; DOI: 10.1183/16000617.0026-2022
Nardin Hanna
1University of Ottawa, Faculty of Medicine, Ottawa, ON, Canada
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Youstina Hanna
2Dept of Medicine, University of Toronto, Toronto, ON, Canada
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Henrietta Blinder
3Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
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Julia Bokhaut
3Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
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Sherri L. Katz
1University of Ottawa, Faculty of Medicine, Ottawa, ON, Canada
3Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
4Division of Respirology, Dept of Pediatrics, Children's Hospital of Eastern Ontario, Ottawa, ON, Canada
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  • For correspondence: skatz@cheo.on.ca
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    Risk-of-bias assessment (Quality in Prognosis Studies) tool.

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    Meta-analysis of association of age with obstructive sleep apnoea (OSA).

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    FIGURE 3

    Meta-analysis of association of sex with obstructive sleep apnoea (OSA).

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  • TABLE 1

    Description of studies

    First author, year [ref.]DesignSubjects nSDB definition with respect to predictorSDBIndices of SDB severityAge yearsObjective
    Anand, 2021 [16]Prospective cross-sectional53OSA: AHI ≥1 events·h−196Mean±sd AHI 8.96±1.8 events·h−1Mean (range) 5.9 (3–11.8)1) Assess the effect of quality of sleep on development and behaviour of children with trisomy 21
    2) Assess the effect of sleep apnoea on development and behaviour of children with trisomy 21
    Austeng, 2014 [17]Cross-sectional29OSA: OAI/AHI >1.5 events·h−1AHI >1.5 events·h−1 97%
    OAI >1.5 events·h−1 69%
    Mean±sd AHI 10±8.8 events·h−1Mean 81) Measure prevalence and medical follow-up of OSA in young children with Down syndrome
    2) Identify the association between OSA and age, BMI and airway surgery
    Banjar, 2013 [18]Prospective cohort23OSA: AHI >1 events·h−182.6%Mean AHI 12.3 events·h−1
    Mean OAI 4.73 events·h−1
    Not reportedIdentify sleep abnormalities in children with Down syndrome
    Basil, 2016 [19]Retrospective cohort303OSAS: AHI ≥2 events·h−174%Mild OSAS: 38.9%
    Moderate OSAS: 32.8%
    Severe OSAS: 28.2%
    Mean±sd (range) 10.6±4.06 (2–18)1) Investigate whether children with Down syndrome are at increased risk of obesity
    2) Explore OSAS, which is associated with obesity in children with Down syndrome
    Breslin, 2014 [20]Prospective cohort38OSAS: AHI >1.5 events·h−161%Mean±sd AHI 5.79±9.86 events·h−1Mean±sd (range) 9.6±.8 (7–12)1) Investigate the association between OSAS and cognition in children with Down syndrome
    2) Investigate the effect of OSAS on sleep physiology in children with Down syndrome
    Brooks, 2015 [21]Prospective cohort25OSA: AHI ≥5 events·h−140%Mean±sd AHI 13.42±15.89 events·h−1Mean±sd (range) 10.14±3.39 (7.2–18.7)1) Investigate the effect of sleep and SDB on neuropsychological functioning of children with Down syndrome
    2) Determine whether treatment of SDB improves cognitive functioning
    Chamseddin, 2019 [22]Qualitative study with retrospective data collection106OSA: AHI ≥1 events·h−190%Mean±sd AHI 16.7±6.25 events·h−1Mean±sd 7.3±41) To evaluate demographic, clinical and polysomnographic features of children with Down syndrome with clinical suspicion of OSA
    2) Identify factors that predict OSA in children with Down syndrome
    Durhan, 2019 [23]Cross-sectional18OSA: AHI ≥1 events·h−161.1%Mean AHI 3.23 events·h−1Median (IQR) 6.6 (4.4–10.5)Determine the effect of OSA on periodontal and dental health in children with Down syndrome
    Dyken, 2003 [9]Prospective cohort19Sleep apnoea: apnoea index >1 event·h−1 and SaO2 low point <92% (with baseline SaO2 >92%)79%Median (IQR) AHI 6.0 (3–8) events·h−1
    Median (IQR) apnoea index 3.0 (2–5) events·h−1
    Mean±sd 9.1±4.71) Investigate OSA in young Down syndrome patients using PSG
    2) Identify the effects of therapy on OSA in young Down syndrome patients
    Elsharkawi, 2017 [24]Cross-sectional101OSA: AHI ≥1 events·h−142.6%Mild OSA: 28%
    Moderate OSA: 2%
    Severe OSA: 13%
    Mean±sd 9.1±4.01) Compare urinary biomarkers of children with Down syndrome to neurotypically healthy controls
    2) Determine whether urinary biomarkers could predict a diagnosis of OSA
    Friedman, 2018 [25]Cross-sectional113OSA: AHI ≥2 events·h−1Not reportedMean AHI 13.76 events·h−1Mean 5.891) Assess parents' accuracy in reporting their children's breathing patterns
    2) Assess risk factors associated with abnormal sleep study
    Jayaratne, 2017 [26]Qualitative study with prospective data collection63OSA: AHI >1 events·h−144.2%Not reportedMean±sd (range) 7.49±4.86 (3.1–24.4)1) Characterise the facial morphology of children with Down syndrome
    2) Compare facial anthropometric characteristics of Down syndrome patients with published norms
    3) Compare facial anthropometric characteristics of Down syndrome patients with and without OSA to predict OSA status in patients with Down syndrome
    Lee, 2020 [27]Cross-sectional30OSA: AHI ≥1 events·h−180%Median (IQR) AHI 5.2 (1.7–15.7) events·h−1Median (IQR) 11.3 (9.4–15.6)1) Measure the prevalence of OSA in children with Down syndrome
    2) Identify the role of OSA and sleep structure in affecting cognitive performance
    Maris, 2016 [28]Cross-sectional54OSA: AHIEmbedded Image2 events·h−157.1%Median (IQR) AHI 7.25 (5.7–9.8) events·h−1Median (range) 7.5 (4–18)1) Identify prevalence of sleep problems in children with Down syndrome as measured by Children's Sleep Habits Questionnaires
    2) Compare prevalence of sleep problems in children with Down syndrome and controls
    3) Investigate association between sleep problems and OSA
    Maris, 2016 [29]Cross-sectional122OSA: AHI Embedded Image2 events·h−166.4%Median (IQR) AHI 8.2 (4.3–16.7) events·h−1Median (IQR) 5.0 (2.8–10.5)1) Measure prevalence of OSA in children with Down syndrome
    2) Identify factors that are associated with disease severity
    de Miguel-Díez, 2003 [4]Prospective cohort108OSA: AHI Embedded Image3 events·h−154.6%Mean±sd AHI 6.1±6.7 events·h−1Mean±sd (range) 7.9±4.5 (1–18)1) Measure the prevalence of SDB in children with Down syndrome
    2) Identify factors that predispose children with Down syndrome to SDB
    Naime, 2021 [30]Retrospective cohort158CSA: CAI >2 events·h−1
    OSAS: AHI >2 events·h−1
    79.1% OSAS
    12% CSA
    Median (IQR) CAI 0.20 (0.0–0.83) events·h−1
    Median (IQR) AHI 5.95 (2.40–16.52) events·h−1
    Median (IQR) 4.8 (0.04–18.3)
    Median (IQR) 4.8 (2.31–9.02)
    1) Identify clinical predictors of central breathing problems in children with Down syndrome
    2) The role of sex and OSA status on presence of central breathing problems
    Nehme, 2017 [8]Retrospective cohort119OSA: AHI >5 events·h−1
    Hypoventilation: carbon dioxide 50 mmHg for ≥25% of total sleep time
    42.9%Median (IQR) AHI 3.6 (1.6–11.2) events·h−1Median (IQR) (range) 6.6 (4.4–10.5) (0.05–16.8)Determine clinical predictors of SDB in children with Down syndrome
    Posada, 2019 [31]Qualitative study with retrospective data collection53OSA: AHI >2 events·h−150.9%Median (IQR) AHI:
    0–23 months 7.0 (1.5–20.2) events·h−1
    24–84 months 8.3 (1.9–30.0) events·h−1
    85–156 months 8.4 (2.5–19.0) events·h−1
    >156 months 13.0 (4.9–29.2) events·h−1
    Median (IQR) 3.4 (1.6–8.8)Measure the incidence of sleep-related breathing disorders in children with Down syndrome living at high altitude
    Richard, 2020 [32]Retrospective case–control study56Nocturnal hypoventilation: >25% of total sleep time spent with a PtcCO2 >50 mmHgOSA 85.7%
    Nocturnal hypoventilation 17.9%
    Median (IQR) AHI 5 (3–10.2) events·h−1
    Median (IQR) mean PtcCO2 44 (43–46.5) mmHg
    Median (IQR) 4.9 (2.0–7.8)Compare PtcCO2 and pulse oximetry (SpO2) in children with Down syndrome and in control children with clinical signs of OSA
    Rosen, 2020 [33]Qualitative study with retrospective data collection418OSA: AHI >1 events·h−142.1%Mean AHI 3.6 events·h−1
    Median AHI 0.6 events·h−1
    Mean (range) 7.27 (2–17)
    Median 6
    1) Identify the prevalence of increased periodic limb movements of sleep in children with Down syndrome
    2) Determine the correlation of periodic limb movements of sleep with OSA and levels of ferritin
    Shires, 2010 [34]Retrospective cohort52OSA: AHI >1.0 events·h−163.5%Mean AHI 18.7 events·h−1Mean±sd 9.3±4.5Identify the effect of body mass on the incidence of OSA in children with Down syndrome
    Skotko, 2017 [35]Prospective cohort102OSA: AHI >1 events·h−144.1%Not reportedMedian (range) 5.6 (3–24.4)To create a predictive model to help screen for OSA in children with Down syndrome
    Waters, 2020 [36]Qualitative study with retrospective data collection152OSA: AHI >2 events·h−185.5%Mean±sd AHI 13.1±22.4 events·h−1First PSG: mean±sd 5.0±4.3
    Last PSG: mean±sd 8.2±5.1
    Identify the spectrum of OSA in children with Down syndrome

    SDB: sleep disordered breathing; OSA: obstructive sleep apnoea; AHI: apnoea–hypopnoea index; OAI: obstructive apnoea index; BMI: body mass index; OSAS: OSA syndrome; IQR: interquartile range; SaO2: arterial oxygen saturation; PSG: polysomnography; CSA: central sleep apnoea; CAI: central apnoea index; PtcCO2: transcutaneous partial pressure of carbon dioxide; SpO2: oxygen saturation measured by pulse oximetry.

    • TABLE 2

      Summary of associations by study for selected predictors of sleep disordered breathing (SDB)

      AHIoAHICAINocturnal hypoventilation
      Positive associationNegative associationNo associationPositive associationNegative associationNo associationPositive associationNegative associationNo associationPositive associationNegative associationNo association
      AgeShires [34], Lee [27]de Miguel-Díez [4] (r= −0.195; OR=2.9), Skotko [35]#Nehme [8], Breslin [20], Brooks [21], Durhan [23], Chamseddin [22], Skotko [35]# (d= −0.74)Rosen [33], Nehme [8] (OR=1.14)Maris [29] (r= −0.199), Waters [36] (Chi-squared=12.87)Nehme [8], Maris [29]Naime [30]Chamseddin [22]Richard [32]
      Male sexde Miguel-Díez [4] (OR=3.32)Brooks [21]Skotko [35], Shires [34], Austeng [17], Breslin [20] (OR=0.22), Lee [27]Maris [29], Rosen [33]Naime [30]#Naime [30]#
      Body mass indexShires [34]#, Dyken [9] (r=0.62), Basil [19] (risk ratios 2.4 and 1.4), Elsharkawi [24]#Brooks [21], Lee [27], Skotko [35], Breslin [20] (d= −0.15; OR=0.73), Austeng [17], Shires [34]# (R2=0.2), Elsharkawi [24]# (r=0.21), Durhan [23], de Miguel-Díez [4] (OR=0.7), Nehme [8]Basil [19] (Spearman ρ=0.16)Maris [29], Chamseddin [22], Nehme [8] (OR=0.71)Richard [32]
      Presence of GORDNehme [8] (OR=0.70), Shires [34]Nehme [8] (OR=0.16)
      History of rhinitis/rhinorrhoea/sinusitisNehme [8] (OR=2.13), Nehme [8] (adjustedOR=2.38)Nehme [8] (adjusted4.49)Nehme [8] (OR=2.22)
      Adenotonsillar hypertrophyShires [34] (r2=0.75), de Miguel-Díez [4]# (OR=4.7)Nehme [8] (OR=1.16), de Miguel-Díez [4]# (OR=0.4)Maris [29], Nehme [8] (OR=1.26)
      Dental examinationsDurhan [23]#Skotko [35], de Miguel-Díez [4], Durhan [23]#
      Parental questionnaires of sleep behavioursBreslin [20] (d=0.56, d=0.51), Brooks [21], Nehme [8] (OR=0.79–2.38), Friedman [25]Maris [28], Nehme [8] (OR=0.63–1.75), Brooks [21]
      SnoringBanjar [18]Posada [31]
      Parental questionnaires of neuropsychological or developmental functionAnand [16] (ρ=0.42–0.83Breslin [20] (d=0.91)Lee [27], Brooks [21], Breslin [20] (t: Mann–Whitney U=0.42–1.03, d=0.16–0.36)
      Cognitive functionAnand [16]#, Breslin [20]# (t: Mann–Whitney U=55.50, d=1.06)Anand [16]# (ρ= −0.62), Breslin [20] (d=0.91), Lee [27]# (coefficientadjusted −9.773)Breslin [20]# (t: Mann–Whitney U=1.11–85.00, d= −0.54–0.58), Brooks [21], Lee [27]# (coefficientadjusted 6.515)

      Association estimates are listed where available. In cases where estimates were not available predictors were associated with SDB if the p-values did not cross the null hypothesis (p<0.05), or based on the author's reporting. AHI: apnoea–hypopnoea index; oAHI: obstructive AHI; CAI: central apnoea index; GORD: gastro-oesophageal reflux disease. #: in cases where authors are listed twice in different columns, different outcomes were assessed, details of which may be found in supplementary table A2.

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      Predictors of sleep disordered breathing in children with Down syndrome: a systematic review and meta-analysis
      Nardin Hanna, Youstina Hanna, Henrietta Blinder, Julia Bokhaut, Sherri L. Katz
      European Respiratory Review Jun 2022, 31 (164) 220026; DOI: 10.1183/16000617.0026-2022

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      Predictors of sleep disordered breathing in children with Down syndrome: a systematic review and meta-analysis
      Nardin Hanna, Youstina Hanna, Henrietta Blinder, Julia Bokhaut, Sherri L. Katz
      European Respiratory Review Jun 2022, 31 (164) 220026; DOI: 10.1183/16000617.0026-2022
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