Abstract
Objective
Obstructive sleep apnea (OSA) is reported in 70% of adolescents who present for bariatric surgery. The Pediatric Sleep Questionnaire (PSQ) was developed to identify children at risk for OSA, but is not validated in adolescents with obesity. The aims of this study:1)to assess validity of the PSQ to detect OSA, and 2)determine the correlation between anthropometric and polysomnography measurements.
Methods
Cross-sectional assessment of Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) participants at high-risk for OSA. Participants completed an overnight polysomnography and caregivers completed the PSQ.
Results
Forty-five participants (84% female, 78% Caucasian, mean age=16.7±1.5 years) were evaluated. Mean BMI was 51.3±7.7kg/m2 and mean obstructive apnea-hypopnea index (oAHI) was 6.1±5.9 events/hour. For diagnosis of OSA (oAHI≥5), the total PSQ score sensitivity, specificity, and positive predictive value (PPV) were 86%, 38%, and 55%, respectively. For snoring >50% of the time, PPV was 84%, sensitivity was 64%, and specificity was 43%. Sagittal abdominal diameter correlated with oAHI and oxygen saturation nadir (rho=0.34, P=0.027), whereas BMI, neck, and waist circumference correlated with neither.
Conclusion
The PSQ demonstrated low specificity and PPV and the question regarding snoring >50% of the time did not effectively identify OSA. Sagittal abdominal diameter correlated with oAHI and oxygen saturation nadir.
Keywords: Obesity, Obstructive sleep apnea, Adolescents, Bariatric surgery
INTRODUCTION
Obstructive sleep apnea (OSA) is a sleep-related breathing disorder characterized by prolonged or intermittent partial or complete upper airway obstruction that disrupts both normal ventilation during sleep and sleep patterns.1 This disorder reportedly affects 1.2% to 5.7%1 of children in the US, and weight gain has been associated with an increasing OSA prevalence as well as increased OSA severity.2 This trend is a growing concern, with obesity estimated to affect 20.5% of American adolescents (2014).3 In a review of sleep disordered breathing (SDB) in children and adolescents with severe obesity, Verhulst et al. described six studies that reported OSA rates ranging from 13% to 59%.4 The likelihood of OSA among adolescents with severe obesity (ie, body mass index (BMI) ≥ 120% of the 95th percentile or BMI ≥ 40kg/m2) is of even more concern when considering recent data demonstrating a prevalence of >70% in a cohort of adults who presented for evaluation prior to undergoing bariatric surgery.5
Overnight, in-laboratory polysomnography (PSG) is currently considered the gold standard for diagnosing pediatric OSA.1 However, in light of the time, effort, and expense of PSG testing, a number of questionnaires have been developed to identify patients at high risk for OSA. Two examples are the Pediatric Sleep Questionnaire (PSQ) and the Berlin Questionnaire (BQ), which were developed for children and adults, respectively.6,7 The PSQ has been shown to be a reliable instrument for the identification of OSA in children from 2 to 18 years of age; it has a sensitivity of 81% to 85% and a specificity of 87%.6 The BQ has a sensitivity of 86% and a specificity of 77% in identifying adults with a respiratory disturbance index ≥ 5.7
Neither of these questionnaires has been validated in children or adults with severe obesity. Given the reliability and convenience of sleep questionnaires for the identification of OSA and the high likelihood of OSA in adolescents with severe obesity, our aim was to assess the validity of the PSQ and the BQ in the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) Study (NCT00474318) cohort. We hypothesized that both of these questionnaires would be sensitive tools to predict OSA in adolescents with severe obesity presenting for bariatric surgery.
MATERIALS AND METHODS
Patient Population
We performed a cross-sectional assessment of patients enrolled in the Teen-LABS study who were at high risk for OSA based on results of the BQ. The Teen-LABS Study is an ancillary study to the Longitudinal Assessment of Bariatric Surgery Study (NCT00465829) aimed at evaluating adolescents (aged <19 years) who were enrolled prior to undergoing bariatric surgery at each of the 5 Teen-LABS clinical centers between February 28, 2007 and December 30, 2011. Institutional review board approval was obtained for the protocol, assent/consent forms were completed, and data and safety monitoring were carried out at each institution; there was also oversight by an independent data and safety monitoring board. Determination of comorbidities was obtained from medical records review, physical examination, and patient interviews, which were performed by a trained clinical coordinator and/or investigator who followed standard definitions which can be found in the methods supplement.8
Sleep Questionnaires
Each patient’s caregiver completed both the BQ and the PSQ. The PSQ is a 22-item questionnaire developed and validated at the University of Michigan as a research tool to identify children at risk for sleep-related breathing disorders.6 It includes items intended to measure childhood sleep-related breathing disorder with subscores for snoring, sleepiness, and behavior. The scales within the questionnaire include a 9-item breathing subscale, a 2-item sleepiness subscale, a 6-item behavior subscale, and a 5-item other subscale; the latter includes questions pertaining to weight, rate of growth since birth, nocturnal enuresis, ability to awaken in the morning, and feeling unrefreshed in the morning. Given that obesity was an inclusion criterion, the response to the PSQ question, “Is your child overweight,” was recorded as an affirmative response. This response was included in the total PSQ score for each study participant.
The BQ was developed to be used in clinical settings to identify adults at risk of OSA. It includes questions regarding risk factors for OSA, which are divided into three categories: snoring, wake-time sleepiness or fatigue, and the presence of obesity or hypertension. When two or more categories are positive, a person is considered at high risk for OSA. This questionnaire was validated in primary care settings for adults (mean age=49 years) who were at high risk for OSA and, as mentioned earlier, was reported to have a sensitivity of 86% and specificity of 77% to identify patients with a respiratory disturbance index ≥ 5 on PSG.7
Overnight Polysomnography
Prior to undergoing bariatric surgery, all patients underwent a preoperative overnight PSG in a sleep laboratory at one of the participating Teen-LABS sites. All PSGs were performed for up to 12 hours in a quiet room with an ambient temperature. Patients went to bed at the time of their preference and studies were terminated when they awoke spontaneously. The following parameters were recorded simultaneously: body position, bilateral electrooculogram (EOG), three-channel electroencephalogram (EEG), chin electromyogram (EMG), anterior tibialis EMG, tracheal microphone, electrocardiogram (EKG), pulse oximetry, thoracic and abdominal inductance plethysmography, and nasal pressure transduction. Central scoring of the de-identified PSG files was performed using standard criteria as defined by the American Academy of Sleep Medicine.9 Sleep stage and respiratory scoring were performed by two qualified scorers (a certified sleep technician and a board certified sleep specialist), each blinded to patient questionnaire scores. Scoring reliability was considered acceptable when there was 90% agreement between scorers, and reported results were recorded as an average of the findings of each qualified scorer. An obstructive apnea was defined as a cessation or decrease in airflow or a decrease in the sum channel from inductive plethysmography by more than 90% of the preceding breath. An obstructive hypopnea was defined as a decrease in airflow or a decrease in the sum channel from inductive plethysmography by more than 30% when compared to the preceding breath, which was associated with an oxygen desaturation of ≥3%, an arousal, or an awakening. All obstructive events were ≥ 2 breaths’ duration. The number of apneas (including central apneas) and hypopneas per hour was calculated and reported as the apnea-hypopnea index (AHI). The obstructive apnea-hypopnea index (oAHI) was defined as the number of obstructive apneas and hypopneas per hour.
Anthropometric Measurements Related to Waist Circumference
The anatomic locations used for the measurement of umbilical waist (midpoint waist) circumference, iliac waist circumference, and sagittal abdominal diameter are shown in Figure 1. A Gulick tape measure was used for both neck circumference and umbilical waist circumference measurement, and each was taken at least two times to ensure that the two measures were within 2 cm of each other. Measurements were recorded to the nearest 0.1 centimeter. Neck circumference measurements were taken over bare necks, with the patient standing erect with arms at their sides and their feet together. The laryngeal prominence was identified and the zero value on the tape measure was placed just below it. For the umbilical waist circumference, the patient was asked to stand erect with their feet together, their abdomen relaxed, and their arms crossed over the chest to hold onto the shoulders. Measurements were then taken around the abdomen horizontally at the midpoint between the highest point of the iliac crest and lowest part of the costal margin in the mid-axillary line. The zero value on the tape measure was placed on the right side and positioned horizontally around their waist. For iliac waist circumference, the patient remained in the same position, with the zero marking on the tape measure placed on their right iliac crest. The tape measure was then passed horizontally around the patient, and a measurement taken. In addition, a marker was used to make a small marking in the center of the abdomen where the tape passed horizontally. This mark was then used to determine sagittal abdominal diameter (SAD).
Figure 1.
Anatomical landmarks used to take abdominal measurements
For the SAD measurement, Holstein-Kahn abdominal calipers with a 20 cm extension bar were used. The extension bar was used if it was anticipated that the SAD was greater than 25 cm. As shown in Figure 2, the patient was placed in supine position on a table and directed to raise their hips and lift their back. The lower arm of the caliper was then placed under the patient’s back at the level of the mid-abdomen marking. The upper arm was lowered until it was touching, but not compressing, the abdomen. This measurement was repeated until two values were obtained within 1.0 cm of each other.
Figure 2.
Anatomical location used to measure the sagittal abdominal diameter
BMI calculations were carried out according to the method recommended by the Centers for Disease Control.10
Statistical Analysis
Demographics and clinical characteristics of study participants were described using means with standard deviations (SDs), medians with ranges, and frequencies with percentages as appropriate. Using the PSQ cut-off of 0.33 to categorize study participants by risk of OSA (high/low), the Fisher exact test was used to test differences in categorical variables between those at high risk and those at low risk. Correlations between the outcomes, PSG parameters (eg, oAHI, oxygen saturation nadir), PSQ items (including total PSQ score), and physical exam findings were assessed using Spearman Rho coefficients. Internal consistency of the PSQ was assessed using Cronbach’s alpha; this is a statistic with a range from 0 to 1 that is used to determine whether a set of questions measures the same idea. The following are the definitions for internal consistency based on Cronbach’s alpha: .00–.69 is poor, .70–.79 is fair, .80–.89 is good, and .90–.99 is excellent.
A score of 0.33 on the total PSQ was used to clinically suggest high risk for OSA, and this value was used to calculate the sensitivity and specificity of the PSQ score to correctly identify OSA.6 A score of 0.33 was also used to determine high risk for sleepiness, hyperactivity, and snoring for the PSQ subscores. Sensitivity and specificity measures and the positive predictive value (PPV) and negative predictive value (NPV) for individual questions on the PSQ were also calculated to determine whether specific questions could be used to identify patients likely to have OSA. Ninety-five percent confidence intervals were calculated for all results.
RESULTS
Demographics and Clinical Characteristics
Forty-five (38 females) of 242 enrolled Teen-LABS participants were included in the analysis, based on BQ scores that categorized these children as high risk for OSA. The final study cohort had a mean age of 16.7 years (range 13.5–19.4, SD 1.5) and a mean BMI of 51.3 kg/m2 (range 34.0–67.1, SD 7.7). Thirty-five children (78%) identified themselves as white, 7 (16%) as black, and 3 (6.6%) as multiracial. The most common comorbidities reported were sleep apnea (62%), hypertension (42%), type 2 diabetes (11%), gastroesophageal reflux disease (9%), and asthma (4%). The mean oAHI was 6.1 events/hour (range 0.1–28.0, SD 5.9). Demographic and clinical characteristics of this cohort are summarized in Table 1.
Table 1. Cohort demographic and baseline polysomnographic characteristics by obstructive sleep apnea risk level.
There were no P values <0.05 for any of the cohort characteristics when comparing the low versus high risk groups except for the ** obstructive index (P=0.048) and the ** proportion of children with obstructive apnea hypopnea index (oAHI)≥1 event/hour.
| Pediatric Sleep Questionnaire | |||
|---|---|---|---|
|
| |||
| Total (N=45) | Low risk (N=12) | High risk (N=33) | |
| Gender, Female, n (%) | 38 (84.4) | 11 (91.7) | 27(81.8) |
| Age, mean ±SD (range) years | 16.7 ±1.5 (13.5–19.4) | 16.0 ±1.7 (13.5–19.1) | 16.9 ±1.3,(14.2–19.4) |
| Race, n (%) | |||
| White | 35 (77.8) | 9 (75.0) | 26 (78.8) |
| Black | 7(15.6) | 1 (8.3) | 6 (18.2) |
| >1 Race | 3 (6.7) | 2 (16.7) | 1 (3.0) |
| Reported comorbidities, n (%) | |||
| Hypertension | 19 (42.2) | 4 (33.3) | 15 (45.5) |
| Type 2 diabetes | 5 (11.1) | 1 (8.3) | 4 (12.1) |
| Sleep apnea | 28 (62.2) | 5 (41.7) | 23 (69.7) |
| Asthma | 2 (4.4) | 1 (8.3) | 1 (3.0) |
| GERD | 4 (8.9) | 0 (0) | 4 (12.1) |
| BMI, mean±SD, (range), kg/m2 | 51.3 ±7.7 (34.0–67.1) | 52.2 ±9.0 (40.5–67.1) | 51.0 ±7.3 (34.0–65.2) |
| oAHI, events/hour * | 6.1 ±5.9 (0.1–28.0) | 4.1 ±4.8 (0.1–13.4) | 6.8 ±6.1 (0.7–28.0) |
| oAHI≥1, n (%) ** | 38 (84.4) | 7 (58.3) | 31 (93.9) |
| oAHI≥5, n (%) | 22 (48.9) | 4 (25) | 18 (54.5) |
| ETCO2>50mmHg, % TST | 4.3 ±10.4 | 2.6 ±5.6 | 5.0 ±11.7 |
| Saturation nadir, % | 86.3 ±14.5 | 82.5 ±27.9 | 87.6 ±5.1 |
| Neck circumference (cm) | 16.9 ±1.6 | 16.9 ±1.5 | 17.0 ±1.7 |
| Umbilical waist circumference (cm) | 54.6 ±6.3 | 56.2 ±7.2 | 54.5 ±5.9 |
| Iliac waist circumference (cm) | 57.0 ±5.9 | 57.5 ±6.0 | 56.8 ±5.9 |
| Sagittal abdominal diameter (cm) | 31.1 ±2.9 | 30.7 ±3.5 | 31.2 ±2.8 |
N=number, SD=standard deviation, BP=blood pressure, oAHI= obstructive apnea-hypopnea index, ETCO2 = end-tidal carbon dioxide levels, TST=total sleep time, GERD=gastroesophageal reflux disease, Circumference and diameter (inches)
(P=0.048)
(P=0.022)
Pediatric Sleep Questionnaire
The PSQ was found to have good internal consistency (Cronbach’s alpha=0.86) for this population. There was no significant correlation between the total PSQ score and oAHI or oxygen saturation nadir. Participants who had a positive response to 3 specific questions on the PSQ were significantly more likely to have a lower saturation nadir. The first question was “Does your child wake up feeling unrefreshed in the morning?” (P=0.03), the second was “Has a teacher or other supervisor commented that your child appears sleepy during the day?” (P=0.01), and the third was “My child often is easily distracted by extraneous stimuli” (P=0.047). These correlations are shown in Table 2.
Table 2.
Correlation between the individual Pediatric Sleep Questionnaire (PSQ) items and obstructive apnea hypopnea index (oAHI) and oxygen saturation nadir
The correlations for the rest of the PSQ questions were not significant with either oAHI or saturation nadir.
| oAHI | Saturation Nadir | |||
|---|---|---|---|---|
|
| ||||
| Spearman rho | P value | Spearman rho | P value | |
|
| ||||
| PSQ Q3d: Does your child wake up feeling unrefreshed in the morning? | 0.20 | 0.26 | −0.38 | 0.029 |
| PSQ Q4: Has a teacher or other supervisor commented that your child appears sleepy during the day? | 0.16 | 0.31 | −0.40 | 0.011 |
| PSQ Q8c: My child often is easily distracted by extraneous stimuli? | 0.19 | 0.23 | −0.31 | 0.047 |
| PSQ Total (using cut-off 0.33) | 0.30 | 0.049 | −0.29 | 0.26 |
| PSQ Sleepiness Subscore | 0.21 | 0.25 | −0.44 | 0.02 |
oAHI= obstructive apnea hypopnea index, PSQ=pediatric sleep questionnaire, bold font= result is statistically significant.
Using an oAHI ≥5 for the diagnosis of OSA, the sensitivity, specificity, and positive PPV of the PSQ total score were 86%, 38%, and 55%, respectively. For the PSQ question “Does your child snore >50% of the time,” using the oAHI ≥1 cut-point the PPV was 84% whereas the sensitivity and specificity were 64% and 43%, respectively. Analysis of the questionnaire subscores of sleepiness and snoring, as well as sensitivity and specificity for oAHI ≥1, are reported in Table 3.
Table 3.
Pediatric Sleep Questionnaire sensitivity and specificity for identifying obstructive sleep apnea (OSA) among adolescents identified as high risk on the Berlin Questionnaire A cut-off value of 0.33 was used for the PSQ total and subscores (sleepiness & snoring).
| Item | Cutoff | Sensitivity | Specificity | PPV | NPV |
|---|---|---|---|---|---|
| PSQ Total | AHI≥1.0 | 82 (66–92) | 71 (29–96) | 94 (80–99) | 42 (15–72) |
| PSQ Total | AHI≥5.0 | 86 (64–97) | 38 (19–59) | 55 (36–72) | 75 (43–95) |
| PSQ Sleepiness | AHI≥1.0 | 63 (42–81) | 100 (48–100) | 100 (81–100) | 33 (12–62) |
| PSQ Sleepiness | AHI≥5.0 | 54 (25–81) | 47 (24–71) | 41 (18–67) | 60 (32–84) |
| PSQ Snoring | AHI≥1.0 | 59 (39–77) | 43 (10–82) | 81 (85–95) | 20 (4–48) |
| PSQ Snoring | AHI≥5.0 | 59 (33–82) | 42 (20–67) | 48 (26–70) | 53 (27–78) |
| PSQ Does your child snore <50% of the time? | AHI≥1.0 | 64 (45–80) | 43 (10–82) | 84 (64–96) | 20 (4–48) |
| PSQ Does your child snore >50% of the time? | AHI≥5.0 | 68 (43–87) | 43 (22–66) | 52 (31–72) | 60 (32–84) |
AHI= obstructive apnea hypopnea index, PPV= Positive Predictive Value, NPV=Negative Predictive Value, PSQ=pediatric sleep questionnaire.
Berlin Questionnaire
Among patients whose BQ indicated high risk, there was no correlation between the BQ total score and oAHI or oxygen saturation nadir. In addition, in our cohort, this questionnaire was found to have only acceptable internal consistency (Cronbach’s alpha=0.66). Using a cut-off of oAHI≥5, the sensitivity, specificity, and PPV of the question “Does your child snore?” were 76%, 22%, and 47%, respectively (Table 4).
Table 4.
Berlin Sleep Questionnaire sensitivity and specificity for identifying OSA among adolescents identified as high risk on the Berlin Questionnaire.
| Item | | Cutoff | Sensitivity | Specificity | Positive Predictive Value | Negative Predictive Value |
|---|---|---|---|---|---|
| Q1 – Snore | | oAHI≥1.0 | 76 (59–88) | 14 (0–58) | 82 (66–93) | 10 (0–45) |
| Q1 – Snore | | oAHI≥5.0 | 76 (53–92) | 22 (7–44) | 47 (30–65) | 50 (19–81) |
Snore= “Does your child snore at least 3–4 times per week?”
oAHI= obstructive apnea hypopnea index, Q1=question 1
Anthropometric Findings
Sagittal abdominal diameter was correlated with the O2 saturation nadir (rho −0.34, P=0.027). It also correlated with the oAHI (rho 0.34, P=0.027) (Figure 3); this remained true even after outliers were removed (rho 0.38, P=0.012). Neither BMI, nor neck and waist circumference were significantly correlated with oAHI or saturation nadir (Table 5).
Figure 3.
Correlation between sagittal abdominal diameter and the obstructive apnea hypopnea index (oAHI)
Table 5.
Correlation between physical exam findings and obstructive apnea- hypopnea index (oAHI) and oxygen saturation nadir
| oAHI | Saturation Nadir | |||
|---|---|---|---|---|
|
| ||||
| Spearman rho | P value | Spearman rho | P value | |
|
| ||||
| Neck circumference | 0.17 | 0.27 | −0.10 | 0.50 |
| Umbilical waist circumference | 0.23 | 0.13 | −0.20 | 0.21 |
| Iliac waist circumference | 0.22 | 0.14 | −0.11 | 0.49 |
| Sagittal abdominal diameter | 0.34 | 0.027 | −0.34 | 0.027 |
| Body-mass index | 0.21 | 0.17 | −0.25 | 0.11 |
oAHI= obstructive apnea hypopnea index, bold font= result is statistically significant.
DISCUSSION
Identification of OSA in adolescents with obesity is critical, as both obesity and OSA are independently associated with increased risk of high blood pressure, type 2 diabetes, and metabolic syndrome.2 To our knowledge, this is the first study to assess the validity of the PSQ to detect OSA in adolescents with severe obesity undergoing bariatric surgery. We found that although the PSQ had good internal consistency, neither the PSQ total score nor the PSQ subscores had sufficient specificity (38 to 47% with an AHI>5) to detect OSA in adolescents with severe obesity and a positive BQ screening score.
The PSQ was first validated against PSG in a population of children who were 2 to 18 years of age without a significant difference in age and gender; BMI was not recorded. Using a cut-off score of 0.33, the PSQ correctly identified OSA in 86% of patients and had high sensitivity (85%) and specificity (87%).6 As a result, it has been used clinically to screen for OSA at many institutions. In our study, when using an oAHI ≥ 5 for the diagnosis of OSA, the sensitivity (86%) was similar to the results reported in the original validation study, however the specificity (38%) was markedly lower. Analysis of our results based solely on patient and family responses regarding the likelihood of snoring for >50% of the time demonstrated both low sensitivity (64%) and specificity (43%).
The PSQ had lower sensitivity to detect OSA in our cohort than was seen in the Washtenaw County Adenotonsillectomy Cohort study, in which the PSQ was used to predict outcomes after adenotonsillectomy. In this study, which included children ages 5 to 13 years of age, 57% male, with no significant difference between controls and those undergoing adenotonsillectomy in regard to BMI, the authors correctly classified 74% of participants; the PSQ sensitivity and specificity were 78% and 72%, respectively at baseline. However, the sensitivity of the PSQ decreased to 42%, with a specificity of 90% when it was used to identify children with persistent OSA after adenotonsillectomy.11 A previous validation study of the PSQ performed in children younger than 18 years of age who were referred to the Cincinnati Children’s Hospital Medical Center pediatric sleep clinic demonstrated a sensitivity of 87% and specificity of 11% for identifying patients with an oAHI ≥ 1 event/hour. The mean age in this group was 9.7 years, and the mean BMI was 24.7, both of which were significantly lower than our study population. When using an alternate oAHI cutoff value of 0.50, the specificity improved to 39%, whereas the sensitivity decreased to 63%.12
All of the children included in the present study scored as high risk on the BQ. Unlike the original validation study for this questionnaire that used in-home monitoring, we used in-laboratory PSG for diagnosing OSA.7 We found that this questionnaire had acceptable internal consistency, and no correlation was demonstrated between the BQ total score and either the oAHI or oxygen saturation nadir. Our finding that the Berlin Questionnaire was not a good screening tool for OSA in adolescents with severe obesity may be related to the mean age of our study population (16.7 years), which was significantly younger than the population in the validation study (49.7 years). In addition, although parents completed these questionnaires (often with input from their children), they may not have had the same insight as adults completing questionnaires for themselves.
Easily accessible, accurate, and cost-effective tools are needed to identify OSA in adolescents with severe obesity. To this end, we investigated the usefulness of anthropometric measurements to predict OSA in these teenagers with severe obesity. In adults, it is widely acknowledged that increased neck circumference, when corrected for height, correlates with increased risk for OSA.13 In a 2009 study, 700 children between the ages of 5 and 12 years were randomly sampled from a local elementary school.14 Investigators found that waist circumference, but not neck circumference, was associated with SDB.14 Katz et al. reported on 222 children between the ages of 7 and 18 years who were referred to primary care physicians for SDB; 60% were overweight or obese. They found the neck-to-waist ratio to be an independent predictor of OSA, except in children with a BMI greater than the 99th percentile.15 In our population, neither neck circumference nor waist circumference correlated with oAHI or oxygen saturation nadir; however, sagittal abdominal diameter was significantly correlated with both oAHI and the oxygen saturation nadir. These studies suggest that no single anthropometric measure has yet been identified to predict OSA in children. Our study suggests that, as seen for adults, sagittal abdominal diameter correlates with OSA risk in adolescents with obesity; however, confirmatory studies are necessary to better understand the usefulness of this measure in normal weight, overweight, and children and adolescents with obesity.16
Our study had several limitations. Because all of the participants were bariatric patients with severe obesity, our results may not be generalizable to the corresponding non-surgical population or to a less obese population. Our cohort was, however, representative of children presenting for bariatric surgery. In addition, there is always concern that surveys completed with parental input may not fully reflect the experience of the child. However observations of sleep behaviors require someone other than the patient to give feedback, and thus may be more valid than patients’ impressions of their own sleep. Moreover, while the sleep studies were carried out at multiple locations, central scoring of the de-identified PSG files was performed using standard criteria by a board-certified pediatric sleep physician. Lastly, the cohort was predominantly female, making it difficult to determine if gender influenced study parameters.
CONCLUSION
This is the first study to assess the validity of the PSQ to detect OSA in adolescents with severe obesity, and our results indicate that it is not an effective screening tool in this population. Furthermore, there was not a specific question or subscore of the PSQ that correlated with a diagnosis of OSA. Similar results were found with the Berlin Questionnaire. Further studies would be useful to assess whether the PSQ might be useful as a tool to follow these patients over time. Novel findings of this study are the correlation between sagittal abdominal diameter and oAHI as well as oxygen desaturation nadir. Further evaluation of this anthropometric measurement in a larger sample of obese and overweight adolescents with OSA is warranted.
Study Importance questions.
What is already known about the subject?
Obstructive sleep apnea (OSA) is reported in 70% of adolescents who present for bariatric surgery.
The Pediatric Sleep Questionnaire (PSQ) has been shown to be a reliable tool for the identification of OSA in children aged 2–18 years, but it has not been validated in children or adolescents with severe obesity.
What does this study add?
This is the first study to assess the validity of the PSQ to detect OSA in adolescents with severe obesity.
Although the PSQ had good internal consistency in the study population, neither the PSQ total nor the PSQ subscores had sufficient specificity or PPV to detect OSA in adolescents with severe obesity at high risk for OSA based upon symptoms.
Sagittal abdominal diameter correlated with OSA risk in adolescents with severe obesity.
Acknowledgments
Funding Source: This study was conducted as a cooperative agreement and funded by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), with a grant to Cincinnati Children’s Hospital Medical Center (Dr. Thomas Inge, PI; U01 DK072493) and UM1DK095710 (PI, Dr. Ralph Buncher, University of Cincinnati) and Supplement (American Recovery and Reinvestment Act of 2009 (ARRA). We gratefully acknowledge the significant contributions made by the Teen-LABS Consortium as well as our parent study LABS Consortium (U01 DK066557).
Footnotes
Previous Presentations: Presented as a poster at the 2015 joint meeting of the American Academy of Sleep Medicine and the Sleep Research Society.
Conflict of interest disclosure: The authors have no other financial or corporate interests to disclose associated with this work. I have no relevant financial interest to disclose. As the corresponding author, I have been involved in all aspects of this project. In addition, I have had full access to the data and take responsibility for the information presented.
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