Predictors of perioperative complications in higher risk children after adenotonsillectomy for obstructive sleep apnea: a prospective study.

OBJECTIVE: Retrospective studies have limitations in predicting perioperative risk following adenotonsillectomy in children with obstructive sleep apnea syndrome (OSAS). Few prospective studies exist. We hypothesized that demographic and polysomnographic (PSG) variables would predict respiratory and general perioperative complications. STUDY DESIGN: Prospective, observational cohort study. SETTING: Pediatric tertiary center. SUBJECTS AND METHODS: Consecutive children undergoing adenotonsillectomy for OSAS within 12 months of PSG were evaluated for complications occurring within 2 weeks of surgery. RESULTS: There were 329 subjects, with 27% <3 years old, 24% obese, 16% preterm, and 29% with comorbidities. In this higher risk population, 28% had respiratory complications (major and/or minor), and 33% had nonrespiratory complications. Significant associations were found between PSG parameters and respiratory complications as follows: apnea hypopnea index (rank-biserial correlation coefficient [r] = 0.174, P = .017), SpO2 nadir (r = -0.332, P < .0005), sleep time with SpO2 <90% (r = 0.298, P < .0005), peak end-tidal CO2 (r = 0.354, P < .0005), and sleep time with end-tidal CO2 >50 mm Hg (r = 0.199, P = .006). Associations were also found between respiratory complications and age <3 years (r = -0.174, P = .003) or black race (r = 0.123, P = .039). No significant associations existed between PSG parameters and nonrespiratory complications. A model using age <3 years, SpO2 nadir, and peak CO2 predicted respiratory complications better than the American Academy of Pediatrics or American Academy of Otolaryngology-Head and Neck Surgery Foundation guidelines but was imperfect (area under the curve = 0.72). CONCLUSION: Thus, PSG predicted perioperative respiratory, but not nonrespiratory, complications in children with OSAS. Age <3 years or black race are high-risk factors. Present guidelines have limitations in determining the need for postoperative admission.

Capturing PLMS and their variability in children with sickle cell disease: does ankle activity monitoring measure up to polysomnography?

OBJECTIVES: To test agreement and define differences in periodic limb movements in sleep (PLMS) measured by polysomnography and an ankle activity monitor, and to describe PLMS variability across nights, feasibility of home monitoring, and correlates of PLMS in children with sickle cell disease (SCD). METHODS: Twenty children with SCD and restless legs syndrome (RLS) symptoms or polysomnography-documented PLMS underwent concurrent attended polysomnography and ankle activity monitoring over one to two nights and home activity monitoring for three nights. Serum iron and ferritin were measured pre- and post-polysomnography. RESULTS: Adequate sensitivity (1.00), specificity (0.69), and mean bias (5.0±7.4 PLMS/h) for identifying elevated PLMS by activity monitor were obtained when scoring the period from sleep onset to offset rather than time in bed per manufacturer recommendation, and using a cut-point of 10 PLMS/h. Compared to activity monitor, only polysomnographic PLMS demonstrated periodicity, at inter-movement intervals (IMI) 20-35 s; the activity monitor overscored PLMS at the beginning and end of sleep and at shorter IMI (5-15s; p≤0.003), suggesting misclassification of nonperiodic leg movements as PLMS by activity monitor. PLMS varied across four nights by 16.1±13.4 PLMS/h. Post-polysomnography ferritin was associated (positively) with PLMS (p=0.034); RLS symptoms were not. CONCLUSIONS: Ankle activity monitoring is a valid screening measure for PLMS in children with SCD and can readily be performed at home. Interpretation should incorporate a threshold for elevated PLMS of 10/h and scoring from sleep onset to offset, which could be identified with concurrent wrist actigraphy, to better account for true PLMS.