# Evaluating the added-value of video recording in respiratory polygraphy for the diagnosis of obstructive sleep apnea in children

Yacine Touil, Cyril Schweitzer, Cyril Schweitzer, Emeline Renard, Manon

Maréchal, Sofia da Mota, Patricia Franco, Laurianne Coutier, Iulia Ioan

<figure><img src="image_1.png" /></figure>

► To cite this version:

Yacine Touil, Cyril Schweitzer, Cyril Schweitzer, Emeline Renard, Manon Maréchal, et al. Evaluating the added-value of video recording in respiratory polygraphy for the diagnosis of obstructive sleep apnea in children. Sleep Medicine, 2025, 125, pp.177 - 184. 10.1016/j.sleep.2024.11.040. hal-05261532

HAL Id: hal-05261532

https://hal.univ-lorraine.fr/hal-05261532v1

Submitted on 15 Sep 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>
<figure><img src="image_3.png" /></figure>

# Evaluating the added-value of video recording in respiratory polygraphy for the diagnosis of obstructive sleep apnea in children

Yacine Touil<sup>a</sup>, Cyril Schweitzer<sup>a,b,c</sup>, Emeline Renard<sup>c</sup>, Manon Maréchal<sup>b</sup>, Sofia Da Mota<sup>b</sup>, Patricia Franco<sup>d,e</sup>, Laurianne Coutier<sup>e,f,g</sup>, Iulia Ioan<sup>a,b,*</sup>,<sup>1</sup>

## ARTICLE INFO

### Keywords:

Obstructive sleep apnea

Polysomnography

Polygraphy

Sleep

Children

Simplified methods

## ABSTRACT

Polysomnography (PSG) is the gold standard for diagnosing obstructive sleep apnea (OSA) in children but not always available. Abbreviated exams exist, such as respiratory polygraphy (RP), but are less accurate for OSA diagnosis. Video recording (video-RP) may provide a more precise estimation of the total sleep time (TST) compared to RP alone. The aim of this study was to evaluate the diagnostic power of video-RP compared to RP and PSG.

Overall, 68 PSG from 68 children (median [1st; 3rd quartile] age of 9 [7; 12]years) were included. After the interpretation of the initial PSG, the analysis was deleted, and the recording was analyzed by taking into account only the respiratory signals and video recording (video-RP). Finally, a third interpretation, after deleting the previous, was performed by considering only the respiratory signals (RP).

The median [1st; 3rd percentile] obstructive apnea-hypopnea index (OAHI) was underestimated in video-RP (4.1 [2.7; 6.5]/h) as well as RP (4.0 [2.7; 6.2]/h) compared to PSG (4.8 [2.9; 6.7]/h, *p* = 0.02 and *p* = 0.01, respectively). Bland-Altman analysis confirmed the underestimation of OAHI by video-RP and RP compared to PSG, the magnitude of the difference being −0.69 ± 2.16 and −0.78 ± 2.12, respectively. OSA severity grading was different when scored by video-RP and RP compared to PSG in 14 (21 %) children.

Video-RP underestimated the OAHI compared to PSG, similar to RP. Adding the video recording did not improve the diagnostic power of RP for the diagnosis of OSA. The use of video-RP at home should be investigated in future studies.

## 1. Introduction

The gold standard for diagnosing obstructive sleep apnea (OSA) in children is polysomnography (PSG) performed in a sleep lab with sleep nurse or sleep technologist attendance and video recording [1,2]. PSG involves many electrodes installed on a child's body to score sleep stages, microarousals and arousals, and respiratory events. PSG also assesses OSA severity according to the magnitude of the obstructive apnea-hypopnea index (OAHI). However, pediatric sleep centers are scarce and there is often a lack of staff leading to important delays. Moreover, PSG is time-consuming in terms of installation and scoring.

Abbreviated exams such as respiratory polygraphy (RP) or oximetry are therefore preferred in children as it is easier for the child to cope with the installation of the device and to maintain it throughout the night [3, 4].

RP consists only of the respiratory sensors and does not require the installation of the neurophysiological electrodes, i.e. electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) electrodes. The drawback of using RP for the diagnosis of OSA is that it underestimates the number of hypopneas as it does not account for hypopneas associated with microarousals detected only by EEG and it overestimates the total sleep time (TST) as it will consider periods when

<footnote><sup>a</sup> DevAH, Faculté de Médecine, Université de Lorraine, France</footnote>

<footnote><sup>b</sup> Service d'Explorations Fonctionnelles Pédiatriques, Hôpital d'Enfants, Centre Hospitalier Universitaire de Nancy, France</footnote>

<footnote><sup>c</sup> Service de Médecine Infantile, Centre Hospitalier Universitaire de Nancy, France</footnote>

<footnote><sup>d</sup> Service Epilepsie, Sommeil, Explorations Fonctionnelles Neurologiques Pédiatriques, Hôpital Femme Mère Enfant, Hospices Civils de Lyon, Bron, France</footnote>

<footnote><sup>e</sup> CNRL, Université de Lyon 1, U1028, France</footnote>

<footnote><sup>f</sup> Service de Pneumologie Infantile, Allergologie et Centre de Référence en Mucoviscidose, Hôpital Femme Mère Enfant, Hospices Civils de Lyon, Bron, France</footnote>

<footnote>* Corresponding author. Service d'Explorations Fonctionnelles Pédiatriques, Hôpital d'Enfants, Centre Hospitalier Universitaire de Nancy, France.
E-mail address: ic.ioan@chru-nancy.fr (I. Ioan).</footnote>

<footnote n="1">¹ the two last authors have equally contributed.</footnote>
the child is calm as sleep time [4–8]. Using a video recording might
compensate for this last disadvantage as watching the video may enable
to more accurately estimate the child’s wakefulness and sleep periods
[9]. Moreover, video-RP is less time consuming in terms of installation
and interpretation compared to PSG. Technological advancement now
allows to couple video recording with RP or even with oximetry. Most
previous studies compared RP versus PSG [4–8] but none, to our
knowledge, have compared video-RP versus PSG for the diagnosis of
OSA in children, except one [10] but that did not take into account the
current recommendations for OSA diagnosis [2,11]. Furthermore,
video-RP might be performed in home environment to facilitate the
interpretation of a simple RP.

Another abbreviated exam is oximetry, which can be included in the
PSG and the RP or carried out by portable oximetry. Oximetry has
previously been used in numerous research for diagnosing OSA to pri-
oritize access to a more comprehensive sleep exams in regions with
limited access to sleep labs [3,12–14]. Several parameters can be ob-
tained from the oximetry, the most robust being the oxygen desaturation
index (ODI) ≥3 % [3,13–18]. The main drawback of oximetry is the
difficulty in estimating the TST. In exchange, parents are asked to fill a
chart with the child’s sleep onset and awakening times, but the wake-
fulness periods during the nighttime remain difficult to assess. This issue
may also be overcome by adding a video recording.

The main objective of the present study was to evaluate the added-
value of a video recording for the interpretation of RP during the diag-
nosis of OSA in children. To that end, the respiratory parameters ob-
tained by either PSG, video-RP, or RP were compared in a cohort of
children with a suspicion of OSA. OSA severity grading was also
compared between the three sleep exams as was the diagnostic power of
ODI.

## 2. Material and methods

**Population.** This is a retrospective single-center study including PSG
data obtained during routine care in children referred to the Pediatric
Lung Function Department of the University Children’s Hospital of
Nancy, France, between 2022 and 2023, for a suspicion of OSA.

The inclusion criteria were PSG performed in children aged 3–18
years with a suspicion of OSA, and interpretable PSG. The exclusion
criteria were individuals with complex genetic or neurologic disorders
that are known to induce central apnea syndrome, as well as non-
interpretable PSG. Children and their parents were informed of the
study and the pseudo-anonymized used of their data and did not oppose.
The study was approved by the ethics committee of the University
Hospital of Nancy, France (number 2023PI221) and is registered on
clinicaltrials.gov (NCT06287333).

**Nocturnal polysomnography.** Children were hospitalized one-night for PSG with video recording and monitoring by a trained pediatric nurse. The clinical assessment, including detailed medical history and physical examination, was conducted by the attending physician. The demographic and clinical characteristics retained for analysis were: age, sex, body mass index (BMI) expressed as z-score [19], and comorbidities.

The PSG device, Nox A1 (Resmed, Reykjavik, Iceland), was installed
on the child in the late afternoon and consisted of EEG leads, two EOG,
chin and leg EMG, nasal cannula, thoraco-abdominal belts, pulse ox-
imetry, electrocardiogram, microphone, and body position sensor
(Fig. 1, panel a). A video recording was systematically performed during
the PSG. The PSG device was removed in the morning. The recording
was downloaded and the sleep stages, microarousals, and respiratory
events were manually scored by a sleep expert physician (II) according
to the 2012 American Academy of Sleep Medicine (AASM) pediatric
recommendations [11,20]. The following parameters were retained for
analysis: TST, the percentage of rapid eye movement (REM) and
non-REM sleep stages during the TST, total microarousal index and
respiratory-related microarousal index (defined as the total number of

microarousals and respiratory-related microarousals, respectively,
divided by the TST), OAHI (defined as the total number of obstructive
apneas, mixed apneas, and hypopneas divided by TST), the obstructive
apnea index (OAI, defined as the total number of obstructive and mixed
apneas divided by TST), the hypopnea index (HI, defined as the total
number of hypopneas divided by TST), the central apnea index (CAI,
defined as the total number of central apneas divided by TST), the total
apnea-hypopnea index (AHI, defined as the total number of apneas and
hypopneas divided by the TST), mean and nadir pulse oxygen saturation
(SpO2), the percentage of TST spent with a SpO2 less than 90 %, ODI
(defined as the total number of desaturations ≥3 % divided by the TST),
and the cardiac frequency. OSA was defined by an OAHI >1.5/h of sleep
and was categorized as mild OSA if OAHI was >1.5 and ≤5/h, moderate
OSA if OAHI was >5 and ≤10/h, and severe OSA if OAHI was >10/h [1,
2].

**Video-respiratory polygraphy.** Several weeks after the PSG analysis,
the initial scoring was entirely deleted and the EEG, EOG, and EMG
signals removed (Fig. 1, panel b). The same (II) sleep expert physician
blindly reviewed the sleep tracings consisted only in respiratory signals
and the video recording without access to child’s name and scored the
sleep periods by watching the video recording, the actigraphy and the
belts signal and removed the periods where the child’s eyes were open or
with important movement or arousal. Another TST was obtained. The
sleep expert physician (II) then scored the respiratory events on the sleep
periods according to the 2012 AASM pediatric recommendations [11].
The following parameters were retained for analysis: TST, OAHI, OAI,
HI, CAI, AHI (expressed as the number of events divided by the TST
obtained by video-RP), mean and nadir SpO2, the percentage of TST
spent with a SpO2 less than 90 %, ODI, and the cardiac frequency.

**Respiratory polygraphy.** Several weeks after the video-RP analysis,
the video-RP scoring was entirely deleted. The video recording was also
deleted, and the same sleep expert physician (II) blindly analyzed the
sleep tracings consisting only in respiratory signals without access to
child's name and excluded the parts of the recording that included ar-
tifacts or significant movement according to actigraphy and belts signal
(Fig. 1, panel c). Another TST was estimated by also using the chart
detailing the child's sleep and wake times, both in the morning and
during the night. These times were estimated by the parents who were
previously instructed to provide them to the pediatric nurse. This
requirement was made to closely replicate home conditions. The respi-
ratory events were scored according to the 2012 AASM recommenda-
tions as for the video-RP [11]. The following parameters were retained
for analysis: TST, OAHI, OAI, HI, CAI, AHI (expressed as the number of
events divided by the TST obtained by RP), mean and nadir SpO2, the
percentage of TST spent with a SpO2 less than 90 %, ODI, and the car-
diac frequency.

**Statistical analysis.** The SAS OnDemand for Academics software was
used for statistical analysis. A descriptive analysis was first conducted on
the entire group of children. The respiratory parameters were then
compared between the three sleep studies (PSG, video-RP, and RP) using
the paired samples non-parametric Wilcoxon test. The correlation be-
tween the different parameters was evaluated using Spearman's corre-
lation. Bland and Altman analysis was used to evaluate within-subject
agreement between the respiratory parameters obtained in PSG, video-
RP, and RP. Receiver-operating characteristic (ROC) curves were per-
formed to determine the optimal threshold of ODI in both video-RP and
RP to identify an OAHI >5/h in PSG. The area under the ROC curve
(AUC) and its 95 % confidence interval, the sensitivity, the specificity,
the positive predictive value (PPV), and negative predictive value (NPV)
were reported. A *p* < 0.05 was considered statistically significant.

## 3. Results

### 3.1. Population characteristics

A total of 68 PSG from 68 children, 40 (59 %) boys and 28 (41 %)
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Screenshot of a 2-min recording of polysomnography (PSG, panel a), video-respiratory polygraphy (video-RP, panel b), and respiratory polygraphy (RP, panel c) of a 13 years old boy. PSG comprises neurophysiological signals (two electrooculograms, electroencephalogram by two frontal, two central, and two occipital leads, and two electromyograms by submental leads), as well as respiratory signals (snoring volume by microphone, nasal flow, thoraco-abdominal efforts measured by thoraco-abdominal belts, pulse oxygen saturation and cardiac frequency via pulse oximetry and electrocardiogram, and activity and body position assessed by an actimetry sensor). Video-RP comprises solely respiratory signals and video recording. RP comprises solely respiratory signals. Of note, hypopneas can be scored in PSG if they are accompanied by desaturation, microarousal, or arousal. In video-RP and RP, hypopneas can only be scored when associated with desaturation or arousal, as the scoring of microarousals requires EEG recording. The first hypopnea scored in PSG was not scored in video-RP or RP due to its association with an EEG microarousal, and not with a desaturation. The second hypopnea scored in PSG was also scored in video-RP and RP as it was associated with a desaturation.</figcaption></figure>
girls, aged 3–17 years, were analyzed. Among all children, 24 (35 %) presented with non-comorbid OSA and 44 (65 %) presented with comorbidities. The most frequent comorbidities were obesity in 18 (26 %), Prader-Willi syndrome in 4 (6 %), and asthma in 4 (6 %; Table 1).

## 3.2. Obstructive sleep apnea diagnosis by polysomnography

In the entire cohort, the median [1st; 3rd percentile] OAHI was 4.8 [2.9; 6.7]/h and AHI was 5.7 [3.8; 7.8]/h (Table 2). Among all children, 4 (6 %) had an OAHI ≤1.5/h (no OSA), 34 (50 %) had a mild OSA, 21 (31 %) a moderate OSA, and 9 (13 %) a severe OSA.

## 3.3. Comparison of respiratory parameters obtained by polysomnography, video-respiratory polygraphy, and respiratory polygraphy

The respiratory parameters were then compared between the PSG, video-RP, and RP data obtained for each participant. TST, OAI, and ODI were significantly higher in video-RP and RP than in PSG while HI, OAHI, and AHI were significantly lower. In video-RP compared to RP, TST, AHI, CAI, and ODI were significantly higher but there was no statistical difference for OAI, HI, and OAHI (Table 3). Of note, in one child, the difference in TTS between video-RP and RP was of 22 min. This was due to the child prolonged period of wakefulness during the night, which parents documented, whereas there were times when the child appeared to be asleep on the video recording. In the remaining 67 children, the differences in total sleep time between the video-RP and RP ranged from −12 min to +9 min, corresponding to −3% to +1.5 % of the total sleep time,

A positive correlation was found between OAHI by PSG and OAHI by video-RP and RP (rho = 0.86, *p* < 0.0001, for both), as well as OAHI by video-RP and OAHI by RP (rho = 0.99, *p* < 0.0001).

## 3.4. Agreement between respiratory parameters obtained by polysomnography, video-respiratory polygraphy, and respiratory polygraphy

According to the Bland-Altman analysis, OAHI was slightly underestimated in video-RP and RP compared to PSG, with a mean ± standard

<table><caption>**Table 1**
Demographic and clinical characteristics of children.</caption><tr><td>n</td><td>68</td></tr><tr><td>Age</td><td>10 [7; 12]</td></tr><tr><td>Boys/girls ratio</td><td>40/28</td></tr><tr><td>BMI z-score</td><td>1.11 [0.18; 2.69]</td></tr><tr><td>Non-comorbid OSA, n (%)</td><td>24 (35 %)</td></tr><tr><td>Obesity, n (%)</td><td>18 (26 %)</td></tr><tr><td>Other comorbidities, n (%)</td><td>26 (38 %)</td></tr><tr><td>Prader-Willi syndrome</td><td>4 (6 %)</td></tr><tr><td>Growth hormone deficiency</td><td>1 (1 %)</td></tr><tr><td>Corticotrop deficiency</td><td>1 (1 %)</td></tr><tr><td>Congenital hypothyroidism</td><td>1 (1 %)</td></tr><tr><td>Asthma</td><td>4 (6 %)</td></tr><tr><td>Ventricular septal defect</td><td>1 (1 %)</td></tr><tr><td>Robin syndrome</td><td>1 (1 %)</td></tr><tr><td>Palatal malformation</td><td>1 (1 %)</td></tr><tr><td>Velopharyngeal insufficiency</td><td>1 (1 %)</td></tr><tr><td>Down syndrome</td><td>1 (1 %)</td></tr><tr><td>Chromosome 16 deletion</td><td>1 (1 %)</td></tr><tr><td>Rubinstein-Taybi syndrome</td><td>1 (1 %)</td></tr><tr><td>Sickle cell anemia</td><td>1 (1 %)</td></tr><tr><td>Chronic immune thrombocytopenic purpura</td><td>1 (1 %)</td></tr><tr><td>Epilepsy</td><td>1 (1 %)</td></tr><tr><td>Spina bifida and epilepsy</td><td>1 (1 %)</td></tr><tr><td>Hypotonia</td><td>1 (1 %)</td></tr><tr><td>Prematurity</td><td>2 (3 %)</td></tr><tr><td>Marfan syndrome</td><td>1 (1 %)</td></tr></table>

Data are expressed as median [1st; 3rd percentile] unless otherwise specified. Abbreviations: BMI = body mass index.

<table><caption>**Table 2**
Polysomnography data in the entire cohort of children.</caption><thead><tr><th></th><th>PSG</th></tr></thead><tbody><tr><td>n</td><td>68</td></tr><tr><td>Total sleep time, min</td><td>443 [384; 508]</td></tr><tr><td>Non-REM sleep stage, %</td><td>82 [79; 86]</td></tr><tr><td>REM sleep stage, %</td><td>18 [14; 21]</td></tr><tr><td>Total microarousal index</td><td>10 [7; 16]</td></tr><tr><td>Respiratory-related microarousal index</td><td>2.4 [1.3; 3.8]</td></tr><tr><td>OAI</td><td>0.6 [0.3; 1.4]</td></tr><tr><td>HI</td><td>4 [2.1; 5.6]</td></tr><tr><td>OAHI</td><td>4.8 [2.9; 6.7]</td></tr><tr><td>CAI</td><td>0.6 [0.3; 1.2]</td></tr><tr><td>AHI</td><td>5.7 [3.8; 7.8]</td></tr><tr><td>Mean SpO2, %</td><td>96 [95; 97]</td></tr><tr><td>Nadir SpO2, %</td><td>91 [89; 92]</td></tr><tr><td>Percentage of TST with SpO2 &lt; 90 %</td><td>0 [0; 0.1]</td></tr><tr><td>ODI</td><td>2.8 [1.7; 5.1]</td></tr><tr><td>Cardiac frequency, bpm</td><td>74 [67; 83]</td></tr></tbody></table>

Data are expressed as median [1st; 3rd percentile]. All indexes are expressed as events per hour of sleep. Abbreviations: REM = rapid eye movement; TST = total sleep time; OAI = obstructive apnea index; HI = hypopnea index; OAHI = obstructive apnea-hypopnea index; CAI = central apnea index; AHI = apnea-hypopnea index; SpO2 = oxygen pulse saturation; ODI = oxygen desaturation index.

<table><caption>**Table 3**
Paired comparison between the respiratory parameters obtained by polysomnography (PSG), video-respiratory polygraphy (video-RP), and respiratory polygraphy (RP).</caption><thead><tr><th></th><th>PSG</th><th>Video-RP</th><th>RP</th><th>p PSG vs video-RP</th><th>p PSG vs RP</th><th>p Video-RP vs RP</th></tr></thead><tbody><tr><td>TST, min</td><td>443 [384; 508]</td><td>471 [412; 528]</td><td>465 [401; 528]</td><td>&lt;0.0001</td><td>&lt;0.0001</td><td>0.0003</td></tr><tr><td>OAI</td><td>0.6 [0.3; 1.4]</td><td>1.2 [0.5; 2.0]</td><td>1.2 [0.5; 1.9]</td><td>&lt;0.0001</td><td>&lt;0.0001</td><td>0.364</td></tr><tr><td>HI</td><td>4.0 [2.1; 5.6]</td><td>2.8 [1.4; 4.6]</td><td>2.8 [1.3; 4.6]</td><td>&lt;0.0001</td><td>&lt;0.0001</td><td>0.08</td></tr><tr><td>OAHI</td><td>4.8 [2.9; 6.7]</td><td>4.1 [2.7; 6.5]</td><td>4.0 [2.7; 6.2]</td><td>0.02</td><td>0.01</td><td>0.110</td></tr><tr><td>CAI</td><td>0.6 [0.3; 1.2]</td><td>0.6 [0.2; 1.4]</td><td>0.6 [0.2; 1.2]</td><td>0.265</td><td>0.002</td><td>&lt;0.0001</td></tr><tr><td>AHI</td><td>5.7 [3.8; 7.8]</td><td>5.2 [3.6; 7.5]</td><td>5 [3.3; 7.3]</td><td>0.005</td><td>0.0007</td><td>0.003</td></tr><tr><td>ODI</td><td>2.8 [1.7; 5.1]</td><td>3.6 [2.0; 6.3]</td><td>3.5 [1.9; 6.3]</td><td>&lt;0.0001</td><td>&lt;0.0001</td><td>0.0002</td></tr></tbody></table>

Data are expressed as median [1st; 3rd percentile]. All indexes are expressed as events per hour of sleep. Abbreviations: TST = total sleep time; OAI = obstructive apnea index; HI = hypopnea index; OAHI = obstructive apnea-hypopnea index; CAI = central apnea index; AHI = apnea-hypopnea index; ODI = oxygen desaturation index.

deviation (SD) difference of −0.69 ± 2.16 between OAHI in video-RP and OAHI in PSG and of −0.78 ± 2.12 between OAHI in RP and OAHI in PSG (Table 4, Fig. 2).

The mean ± SD difference for HI was −1.25 ± 2.06 between video-RP and PSG and −1.30 ± 2.01 between RP and PSG (Table 4, Fig. 3). Conversely, OAI was slightly overestimated in video-RP and RP compared to PSG, with a mean ± SD difference of 0.56 ± 0.62 between OAI in video-RP and OAI in PSG, and 0.53 ± 0.60 between OAI in RP and OAI in PSG (Table 4, Fig. 4).

The Bland-Altman analysis showed very small differences for respiratory parameters between video-RP and RP (Table 4, Figs. 2–4).
<caption>**Table 4**</caption>

Bland-Altman analysis showing the agreement between the respiratory parameters in video-respiratory polygraphy (video-RP), polysomnography (PSG), and respiratory polygraphy (RP).

<table><thead><tr><th></th><th>Video-RP vs PSG</th><th>RP vs PSG</th><th>Video-RP vs RP</th></tr></thead><tbody><tr><td>OAHI</td><td>-0.69 ± 2.16</td><td>-0.78 ± 2.12</td><td>0.09 ± 0.39</td></tr><tr><td>OAI</td><td>0.56 ± 0.62</td><td>0.53 ± 0.60</td><td>0.03 ± 0.23</td></tr><tr><td>HI</td><td>-1.25 ± 2.06</td><td>-1.31 ± 2.01</td><td>0.06 ± 0.25</td></tr></tbody></table>

Data are expressed as the mean ± standard deviation (SD) difference between the respiratory indexes. All indexes are expressed as events per hour of sleep. Abbreviations: OAI = obstructive apnea index; HI = hypopnea index; OAHI = obstructive apnea-hypopnea index.

**3.5. Diagnostic power of video-respiratory polygraphy and respiratory polygraphy to detect an OAHI >5/h in PSG**

The best threshold for OAHI in video-RP to detect an OAHI >5/h in PSG was 4.7/h, with a sensitivity of 0.90, specificity of 0.89, and AUC of 0.92 (0.85; 0.99) (*p* < 0.0001). The best threshold for OAHI in RP to detect an OAHI >5/h in PSG was 4.5/h, with a sensitivity of 0.90,

specificity of 0.87, and area under the ROC curve of 0.94 (0.88; 0.99) (*p* < 0.0001).

**3.6. OSA severity grading by polysomnography, video-respiratory polygraphy, and respiratory polygraphy**

OSA severity was the same when graded by video-RP and RP than when graded by PSG for 54 (79%) of the children but differed for 14 (21%) of them. Among the 14 children for whom OSA severity differed according to the sleep exam, 1 child with no OSA was graded as mild OSA on video-RP and RP, 2 children with mild OSA on PSG were graded as no OSA on video-RP and RP, 7 children with moderate OSA on PSG were mild on video-RP and RP, and 1 severe OSA on PSG was moderate on video-RP and RP. Contrarily, 3 children with mild OSA on PSG were moderate on video RP and RP (Fig. 5, Table 5).

**3.7. Diagnostic power of ODI by video-respiratory polygraphy and respiratory polygraphy to detect an OAHI >5/h in PSG**

The best threshold for ODI in video-RP to detect an OAHI >5/h in

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Bland-Altman analysis of obstructive apnea-hypopnea index (OAHI) in video-respiratory polygraphy (video-RP), respiratory polygraphy (RP), and polysomnography (PSG). Grey solid line: mean; dashed-dotted line: 95 % confidence interval of the mean; dotted line: 99 % confidence interval of the mean.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Bland-Altman analysis of hypopnea index (HI) in video-respiratory polygraphy (video-RP), respiratory polygraphy (RP), and polysomnography (PSG). Grey solid line: mean; dashed-dotted line: 95 % confidence interval of the mean; dotted line: 99 % confidence interval of the mean.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Bland-Altman analysis of obstructive apnea index (OAI) in video-respiratory polygraphy (video-RP), respiratory polygraphy (RP), and polysomnography (PSG). Grey solid line: mean; dashed-dotted line: 95 % confidence interval of the mean; dotted line: 99 % confidence interval of the mean.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Obstructive apnea-hypopnea index measured by polysomnography (PSG) compared to video-respiratory polygraphy (video-RP) in the 14 patients for whom OSA severity grading differed. The dotted lines represent the thresholds between severity categories.</figcaption></figure>

<caption>**Table 5**</caption>

Individual comparison of obstructive apnea-hypopnea index (OAHI) by polysomnography (PSG) vs OAHI by video-respiratory polygraphy (video-RP) in the 14 (21 %) children who changed their severity category.

<table><thead><tr><th></th><th>OAHI by PSG</th><th>OAHI by video-RP</th></tr></thead><tbody><tr><td>Girl, 9y</td><td>13.1</td><td>6.8</td></tr><tr><td>Boy, 5a</td><td>7.6</td><td>3.0</td></tr><tr><td>Boy, 4y</td><td>7.4</td><td>4.7</td></tr><tr><td>Boy, 10y</td><td>6.7</td><td>4.9</td></tr><tr><td>Girl, 7y</td><td>6.4</td><td>4.0</td></tr><tr><td>Girl, 11y</td><td>5.8</td><td>4.8</td></tr><tr><td>Boy, 14y</td><td>5.3</td><td>4.7</td></tr><tr><td>Girl, 14y</td><td>5.3</td><td>2.2</td></tr><tr><td>Girl, 12y</td><td>4.2</td><td>5.7</td></tr><tr><td>Boy, 9y</td><td>4.0</td><td>5.5</td></tr><tr><td>Girl, 9y</td><td>3.9</td><td>5.5</td></tr><tr><td>Boy, 15y</td><td>3.7</td><td>1.0</td></tr><tr><td>Girl, 16y</td><td>2.1</td><td>0.5</td></tr><tr><td>Boy, 11y</td><td>1.4</td><td>1.9</td></tr></tbody></table>

PSG was 5/h, with an AUC of 0.84 (0.74; 0.94) (*p* < 0.0001), a sensitivity of 0.70, specificity of 0.89, PPV of 0.84, and NPV of 0.79.

The best threshold for ODI in RP to detect an OAHI >5/h in PSG was also 5/h, with an AUC of 0.84 (0.75; 0.94), a sensitivity of 0.70, specificity of 0.89, PPV of 0.84, and NPV of 0.79.

## 4. Discussion

In the present study conducted in children referred for a suspicion of OSA, the diagnostic power of video-RP for OSA diagnosis in children was similar to that of RP. Similarly to RP, OAHI was underestimated when measured by video-RP compared to PSG, mainly due to an underestimation of the HI. The diagnostic power of video-RP and RP to diagnose an OAHI >5/h in PSG was excellent with high specificity and sensitivity (about 0.90 for both). OSA severity was graded correctly by video-RP and RP in about 80 % of the children. The diagnostic power of ODI to detect an OAHI >5/h in PSG was similar between video-RP and RP with good sensitivity and specificity.

Many studies investigated the diagnostic power of RP conducted in-lab [5,21] or at-home [5,21–23] in children suspected of OSA. The underestimation of OAHI in RP observed herein is consistent throughout studies, and the threshold to identify an OAHI >5/h in PSG varies whether the exam has been performed at home or in-lab under controlled conditions [5,21–24]. These previous studies also showed that TST is overestimated in RP compared to PSG, a result which is confirmed in the present cohort. A prior study compared the

sleep/wakefulness periods between video-RP and in-hospital PSG in a group of 20 children with a suspicion of OSA. The video-RP correctly classified sleep and wakefulness in about 94 % of the over 20.000 epochs analyzed with a predictive value of 0.95 for sleep and 0.89 for wakefulness [9], leading to the hypothesis that a video recording could help overcome the overestimation of TST by RP. However, this hypothesis was not validated by the present findings. Although the periods of sleep/wakefulness in video-RP were analyzed by an expert sleep physician, it is likely that some periods of wakefulness were incorrectly identified as sleep, notably when the child slept in prone position and no movement was detected on the respiratory signals, it was challenging to see the child's face or at the onset of sleep when the child had his/her eyes closed but was not sleeping. This final hypothesis is supported by the higher TST in video-RP when compared to the TST in RP likely due to the different methods to score. For the video-RP, the sleep periods were scored by watching the video recording, the actigraphy and the belts signal whereas for the RP, the sleep physician also considered the child's sleep and wake times estimated by the parents. This requirement was made to closely replicate home conditions when using video-RP, thus eliminating the necessity for parents to record the times when the child falls asleep or awakens in the morning and throughout the night. We opted not to use the sleep nurse's/technologist's notes because our objective was to replicate a real-world setting as much as possible. In a laboratory setting where a video-RP is conducted, the sleep nurse/technologist records the times the child falls asleep or awakens during the night and in the morning while observing the video in real-time. In a home setting, these times will be established by reviewing the video recording the next day. In our humble opinion, the differences in total sleep time are clinically non-relevant, mostly ranging from -3% to +1.5 % of the total sleep time, which falls within the usual variability limits of scoring and likely to be clinically irrelevant and affect the overall OAHI. Moreover, the fact that RP was also scored by the expert sleep physician has likely increased the accuracy of the analysis, and thus increased the sensitivity of the RP herein. Consequently, the respiratory parameters of interest herein, notably OAHI, OAI, and HI were not significantly different between video-RP and RP.

In the present cohort, the OAHI was underestimated in video-RP compared to PSG, mainly due to an underestimation of HI. Indeed, even though OAI differed significantly between video-RP and PSG, this difference was very low as demonstrated by the Bland-Altman analysis. One reason for this underestimation of HI might be that video-RP does not consider non-desaturating hypopneas accompanied only by microarousals. Additionally, some obstructive apneas that were classified as being during sleep in video-RP, were likely to have occurred during wakefulness, and incorrectly scored as sleep periods in video-RP. Contrary to the present study, the comparison between video-RP performed at home and in-lab PSG in a group of 21 children aged 2–12 years with adenotonsillar hypertrophy showed similar TST, AHI, and ODI ≥4 % but with only a fair to good concordance between the measurements [10].

In Europe, in-laboratory RP with video surveillance is frequently the preferred investigative method and physicians may favor this approach for children with OSA due to its cost-effectiveness and reduced installation and analysis time compared to PSG [4]. The potential therapeutic implications of utilizing video-RP in place of the gold-standard PSG implies different clinical care decisions based on the severity of OSA which is determined by the OAHI result. These disparities will not influence the therapeutic management of children with severe OSA due to the minimal difference between the two OAHI levels. In our study, one child, an 8-year-old girl with comorbidity, transitioned from severe to moderate category status. Nonetheless, the treatment decision did not alter in her situation due to her OSA symptoms and the presence of the comorbidity; thus, she was managed as a moderate-severe case in accordance with ERS guidelines [2].

The majority of children from our study did not change their severity category when assessed by video-RP. The small proportion of children who changed their severity category, transitioned namely from
moderate to mild OSA or from mild to no OSA. This would result in reduced implications for children classified as having mild OSA by video-RP but more significant repercussions for those classified as having no OSA as they will get no follow-up care. Consequently, we suggest using additional signals, such as pulse transit time or mandibular movements sensor, to detect the autonomic microarousals and enhance the sensitivity of video-RP. Furthermore, due to the “not perfect” diagnostic value, children exhibiting clinical symptoms suggestive of OSA and classified as having no OSA or mild OSA by video-RP, should be addressed for a comprehensive PSG evaluation.

Video-recordings alone using a standardized scoring system have previously been used for screening OSA in children. These were performed for shorter durations, at home, and only when the child presented with labored breathing [25,26]. In the first study, the video recording lasted 30 min and, when compared to in-lab PSG, it showed a high sensitivity (0.94) but low specificity for the diagnosis of OSA [25]. Similarly, the second study, in which the video recording lasted 1–2 min also showed high sensitivity (1.0) but low specificity [26]. The use of additional sensors such as RP would have likely increased the specificity as observed herein. Even oximetry, which has less sensors than RP, is likely to enhance this specificity. Herein, an ODI of 5/h by video-RP showed a good AUC with a high specificity and PPV and a fair sensitivity and NPV for diagnosing moderate/severe OSA. When using an ODI of 3/h to diagnose moderate/severe OSA, as recommended in subjects needing an adenotonsillectomy [16], the sensitivity increased but the specificity decreased herein. The literature shows that the sensitivity and specificity of ODI differs according to the population studied, the ODI threshold considered, and the recording conditions, i.e. in-lab RP, RP at home, or portable oximetry. For instance, in children with Down syndrome undergoing RP at home, the specificity of ODI at threshold of >6/h was lower than herein (0.63) but the sensitivity was higher (0.92) [27]. Moreover, in a study in typically developing children measured by portable oximetry, ODI at a threshold of 8/h, both the specificity (0.84) and sensitivity (0.82) were comparable to the present findings [17]. Importantly, when comparing video-RP and RP in the present cohort, the diagnostic power of ODI was equivalent between both sleep exams.

The present study has some limitations, such as its single-center and retrospective design. The in-hospital recording conditions and the analysis by expert sleep physicians might have limited the evaluation of the added-value of video-RP compared to RP. In other situations, at home, video recording might be useful to improve the sensitivity of RP and oximetry.

## 5. Conclusion

In the present cohort of children, video recording did not improve the diagnostic power of RP for the diagnosis of OSA. OAHI was underestimated in both video-RP and RP compared to PSG, mainly due to an underestimation of HI. The sensitivity and specificity of both video-RP and RP were excellent to detect an OAHI >5/h in PSG. Further studies are needed to evaluate the diagnostic power of video-RP performed at home compared to unattended RP for OSA in children.

## Financial disclosure

The authors have indicated they have no financial relationships relevant to this article to disclose.

## CRediT authorship contribution statement

**Yacine Touil:** Writing – original draft, Validation, Software, Methodology, Investigation, Formal analysis, Data curation. **Cyril Schweitzer:** Writing – review & editing, Writing – original draft, Validation, Methodology, Conceptualization. **Emeline Renard:** Writing – original draft, Validation, Methodology, Investigation. **Manon Maréchal:** Writing – original draft, Validation, Methodology, Investigation. **Sofia

**Da Mota:** Software, Methodology, Investigation. **Patricia Franco:** Writing – review & editing, Validation, Supervision, Methodology, Conceptualization. **Laurianne Coutier:** Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Formal analysis, Conceptualization. **Iulia Ioan:** Writing – review & editing, Supervision, Software, Project administration, Methodology, Investigation, Formal analysis, Conceptualization.

## Contributors' statement page

Conception and study design: YT, CS, SDM, PF, LC, II, Patient data collection: YT, MM, ER, SDM, LC, Polysomnographic analysis: YT, MM, SDM, II, Statistical analysis: YT, MM, LC, II, Interpretation of results: YT, CS, PF, LC, II, Manuscript preparation: YT, CS, PF, LC, II, Final revision: YT, CS, ER, MM, SDM, PF, LC, II.

## Funding source

No external funding for this manuscript.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

The authors thank Véréna Landel for proofreading the manuscript, Claude Bonabel, Claire Abenzoar, Lucie Kempf, Marie-Jeanne Arnoux, Myriam Chamagne, and Aurelia Datin for their technical assistance, and also children and their parents who agreed to participate to this study.

## References

[1] Franco P, Bourdin H, Braun F, Friffod J, Pin I, Challamel M-J. Diagnostic du syndrome d'apnée obstructive du sommeil chez l'enfant (2-18 ans): place de la polysomnographie et de la polygraphie ventilatoire, vol. 14. Médecine du sommeil; 2017. p. 77-88.

[2] Kaditis AG, Alonso Alvarez ML, Boudewyns A, Alexopoulos EI, Ersu R, Joosten K, et al. Obstructive sleep disordered breathing in 2- to 18-year-old children: diagnosis and management. Eur Respir J 2016;47:69-94.

[3] Kaditis A, Kheirandish-Gozal L, Gozal D. Pediatric OSAS: oximetry can provide answers when polysomnography is not available. Sleep Med Rev 2016;27:96-105.

[4] Tan HL, Gozal D, Ramirez HM, Bandla HP, Kheirandish-Gozal L. Overnight polysomnography versus respiratory polygraphy in the diagnosis of pediatric obstructive sleep apnea. Sleep 2014;37:255-60.

[5] Alonso-Álvarez ML, Terán-Santos J, Ordax Carbajo E, Cordero-Guevara JA, Navazo-Eguía AI, Kheirandish-Gozal L, et al. Reliability of home respiratory polygraphy for the diagnosis of sleep apnea in children. Chest 2015;147:1020-8.

[6] Chiner E, Cánovas C, Molina V, Sancho-Chust JN, Vanes S, Pastor E, et al. Home respiratory polygraphy is useful in the diagnosis of childhood obstructive sleep apnea syndrome. J Clin Med 2020;9.

[7] Lesser DJ, Haddad GG, Bush RA, Pian MS. The utility of a portable recording device for screening of obstructive sleep apnea in obese adolescents. J Clin Sleep Med: JCSM: official publication of the American Academy of Sleep Medicine 2012;8: 271-7.

[8] Olmo Arroyo J, De Sanctis L, Sidhoum L, Amaddeo A, Griffon L, Khirani S, et al. Quality of poly(somno)graphy recordings in children. Journal of sleep research 2021;30:e13241.

[9] Morielli A, Ladan S, Ducharme FM, Brouillette RT. Can sleep and wakefulness be distinguished in children by cardiorespiratory and videotape recordings? Chest 1996;109:680-7.

[10] Jacob SV, Morielli A, Mograss MA, Ducharme FM, Schloss MD, Brouillette RT. Home testing for pediatric obstructive sleep apnea syndrome secondary to adenotonsillar hypertrophy. Pediatr Pulmonol 1995;20:241-52.

[11] Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, et al. Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events. Deliberations of the sleep apnea definitions task force of the American Academy of sleep medicine. J Clin Sleep Med: official publication of the American Academy of Sleep Medicine 2012;8:597-619.

[12] Nixon GM, Kermack AS, Davis GM, Manoukian JJ, Brown KA, Brouillette RT. Planning adenotonsillectomy in children with obstructive sleep apnea: the role of overnight oximetry. Pediatrics 2004;113:e19-25.
[13] Polytarchou A, Ohler A, Moudaki A, Koltsida G, Kanaka-Gantenbein C, Kheirandish-Gozal L, et al. Nocturnal oximetry parameters as predictors of sleep apnea severity in resource-limited settings. Journal of sleep research 2023;32: e13638.

[14] Van Eyck A, Lambrechts C, Vanheeswijck L, Van Hoorenbeeck K, Haentjens D, Boudewyns A, et al. The role of nocturnal pulse oximetry in the screening for obstructive sleep apnea in obese children and adolescents. Sleep Med 2015;16: 1409–12.

[15] Jonas C, Thavagnanam S, Blecher G, Thambipillay G, Teng AY. Comparison of nocturnal pulse oximetry with polysomnography in children with sleep disordered breathing. Sleep Breathing Schlaf Atmung 2020;24:703–7.

[16] Papadakis CE, Chaidas K, Chimona TS, Asimakopoulou P, Ladias A, Proimos EK, et al. Use of oximetry to determine need for adenotonsillectomy for sleep-disordered breathing. Pediatrics 2018;142.

[17] Selby A, Buchan E, Davies M, Hill CM, Kingshott RN, Langley RJ, et al. Role of overnight oximetry in assessing the severity of obstructive sleep apnoea in typically developing children: a multicentre study. Arch Dis Child 2024;109:308–13.

[18] Tsai CM, Kang CH, Su MC, Lin HC, Huang EY, Chen CC, et al. Usefulness of desaturation index for the assessment of obstructive sleep apnea syndrome in children. Int J Pediatr Otorhinolaryngol 2013;77:1286–90.

[19] Organization WH. News-room fact-sheets detail obesity and overweight. Online; 2020. URL: https://wwwwhoint/newsroom/fact-sheets/detail/obesity-and-overweight.

[20] Iber C. The AASM manual for the scoring of sleep and associated events: rules. Terminology and Technical Specification. 2007.

[21] Kissow Lildal T, Boudewyns A, Kamperis K, Rittig S, Bertelsen JB, Otto M, et al. Validity of in-lab and home respiratory polygraphy for detecting obstructive sleep apnea in children. Sleep Med 2023;103:195–203.

[22] Ikizoglu NB, Kiyan E, Polat B, Ay P, Karadag B, Ersu R. Are home sleep studies useful in diagnosing obstructive sleep apnea in children with down syndrome? Pediatr Pulmonol 2019;54:1541–6.

[23] Ioan I, Renard E, Da Mota S, Bonabel C, Tiotiu A, Franco P, et al. Unattended home sleep studies for the diagnosis of obstructive sleep apnea in a population of French children. Sleep Med 2023;102:117–22.

[24] Gudnadottir G, Hafsten L, Redfors S, Ellegård E, Hellgren J. Respiratory polygraphy in children with sleep-disordered breathing. Journal of sleep research 2019;28:e12856.

[25] Sivan Y, Kornecki A, Schonfeld T. Screening obstructive sleep apnoea syndrome by home videotape recording in children. Eur Respir J 1996;9:2127–31.

[26] Thomas RJ, Dalton S, Harman K, Thacker J, Horne RSC, Davey MJ, et al. Smartphone videos to predict the severity of obstructive sleep apnoea. Arch Dis Child 2022;107:148–52.

[27] Hill CM, Elphick HE, Farquhar M, Gringras P, Pickering RM, Kingshott RN, et al. Home oximetry to screen for obstructive sleep apnoea in Down syndrome. Arch Dis Child 2018;103:962–7.