Research Needs Assessment for Children With Obstructive Sleep Apnea Undergoing Diagnostic or Surgical Procedures:

The effect of anesthesia without opioid on perioperative opioid demand in children with severe obstructive sleep apnea (OSA) for adenotonsillectomies — single-center retrospective observational study

Background

Children with severe obstructive sleep apnea (OSA) carry a higher risk of respiratory complications after adenotonsillectomy. Their altered sensitivity to opioids may be a significant contributor to respiratory morbidity. The purpose of this study was to identify how anesthesia without opioids affects perioperative opioid demand and postoperative course.

Methods

A chart review of children with severe OSA (apnea hypoxia index; AHI ≥ 10) undergoing adenotonsillectomies was performed. Comorbidities and perioperative medications were documented. Perioperative opioid doses within 48 h of procedure were calculated as morphine equivalents (mcg/kg). Pain scores, rescue medications, and postoperative complications in PICU and non-PICU settings were also documented. Anesthesia without opioid and with opioid groups were compared.

Results

The analysis included 225 children. A significantly higher percentage of children received no postoperative opioids in the anesthesia without opioid group compared to those with opioid (46 of 88 children vs. 43 of 137; P < 0.05). The incidence of severe postoperative pain between the two groups was not different in PICU (P = 0.88) or non-PICU setting (P = 0.84). Perioperative opioid administration was significantly lower in anesthesia without opioid (median, Q1, Q3: 0.0, 0.0, 83.0) compared to with opioid (144.4, 72.5, 222.2; P < 0.01). Anesthesia without opioid was one of the independent factors to achieve perioperative opioid avoidance (<50mcg/kg).

Conclusions

Anesthesia without opioid for children with severe OSA for tonsillectomy significantly reduced perioperative demand for opioid and did not affect the occurrence of severe pain. Anesthesia without opioid is an effective strategy to minimalize opioid demand perioperatively for children with severe OSA for tonsillectomy.

PICU admission and complications following adenotonsillectomies in pediatric patients: A retrospective cohort study

BACKGROUND

Children with obstructive sleep apnea (OSA) have higher risks of post-operative respiratory complication after adenotonsillectomy. However, there is no clinical standard criteria for pediatric intensive care unit (PICU) admission following adenotonsillectomy. The purpose of this study was to identify perioperative risk factors associated with the need for PICU level care after adenotonsillectomy.

METHODS

We performed a retrospective chart review of children with severe OSA (apnea hypopnea index on polysomnography; AHI ≥10) and/or post-operative PICU admission at a tertiary academic center from May 2010 to September 2018. We collected demographics, pre-existing comorbidities, perioperative medications, and post-operative complications. We defined a primary outcome as escalation of airway management while in the PICU or PICU stay >48 h. Airway escalation included the need for an invasive airway, new CPAP application, increased CPAP setting, or increased supplemental oxygen.

RESULTS

Analysis included 278 children with severe OSA and/or PICU admission. Median age was 6.6 years old; 181 (65%) were admitted to the PICU, and 60 (21.5%) had the composite outcome of escalation of airway management or prolonged stay. In patients with an escalation of airway management, 28 needed intubation or mechanical ventilation. Multivariable logistic regression showed intraoperative respiratory complications, polysomnography (PSG) peak end-tidal CO₂ (EtCO₂) reading >60 mmHg, and the presence of neuromuscular disease as significant associated factors for escalation of airway management or prolonged PICU stay (P values < 0.01; odd ratios 3.4, 5.3, and 5.4, respectively).

CONCLUSION

For children following adenotonsillectomy, PSG EtCO₂ ≥ 60%, preexisting neuromuscular disease, and intraoperative complications (hypoxia, difficult airway, etc.) were independently associated with escalation of airway management or prolonged stay. AHI was not an independent predictor for PICU complication. We concluded factors should be considered for PICU admission in addition to AHI.

Predicting Perioperative Respiratory Adverse Events in Children With Sleep-Disordered Breathing

BACKGROUND

No evidence currently exists to quantify the risk and incidence of perioperative respiratory adverse events (PRAEs) in children with sleep-disordered breathing (SDB) undergoing all procedures requiring general anesthesia. Our objective was to determine the incidence of PRAEs and the risk factors in children with polysomnography-confirmed SDB undergoing procedures requiring general anesthesia.

METHODS

Retrospective review of all patients with polysomnography-confirmed SDB undergoing general anesthesia from January 2009 to December 2013. Demographic and perioperative outcome variables were compared between children who experienced PRAEs and those who did not. Generalized estimating equations were used to build a predictive model of PRAEs.

RESULTS

In a cohort of 393 patients, 51 PRAEs occurred during 43 (5.6%) of 771 anesthesia encounters. Using generalized estimating equations, treatment with continuous positive airway pressure or bilevel positive airway pressure (odds ratio, 1.63; 95% confidence interval [CI], 1.05-2.54; P = .031), outpatient (odds ratio, 1.37; 95% CI, 1.03-1.91; P = .047), presence of severe obstructive sleep apnea (odds ratio, 1.63; 95% CI, 1.09-2.42; P = .016), use of preoperative oxygen (odds ratio 1.82; 95% CI, 1.11-2.97; P = .017), history of prematurity (odds ratio, 2.31; 95% CI, 1.33-4.01; P = .003), and intraoperative airway management with endotracheal intubation (odds ratio, 3.03; 95% CI, 1.79-5.14; P < .001) were associated with PRAEs.

CONCLUSIONS

We propose the risk factors identified within this cohort of SDB patients could be incorporated into a preoperative risk assessment tool that might better to identify the risk of PRAE during general anesthesia. Further investigation and validation of this model could contribute to improved preoperative risk stratification, decision-making (postoperative admission and level of monitoring), and health care resource allocation.

Predictors of postoperative respiratory complications in children undergoing adenotonsillectomy

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is commonly treated with adenotonsillectomy (AT), bringing risk of perioperative respiratory adverse events (PRAEs). We aimed to concurrently identify clinical and polysomnographic predictors of PRAEs in children undergoing AT.

METHODS

Retrospective study of children undergoing AT at a tertiary-care pediatric hospital, with prior in-hospital polysomnography, January 2010 to December 2016. PRAEs included those requiring oxygen, jaw thrust, positive airway pressure, or mechanical ventilation. Relationships of PRAEs to preoperative comorbidities or polysomnography results were examined with univariable logistic regression. Variables with P < .1 and age were included in backward stepwise multivariable logistic regression. Predictive performance (area under the curve, AUC) was validated with bootstrap resampling.

RESULTS

Analysis included 374 children, median age 6.1 years; 286 (76.5%) had ≥ 1 comorbidity. 344 (92.0%) had sleep-disordered breathing; 232 (62.0%) moderate-severe; 66 (17.6%) had ≥ 1 PRAE. PRAEs were more frequent in children with craniofacial, genetic, cardiac, airway anomaly, or neurological conditions, AHI ≥ 5 events/h and oxygen saturation nadir ≤ 80% on preoperative polysomnography. Prediction modeling identified cardiac comorbidity (odds ratio [OR] 2.09 [1.11, 3.89]), airway anomaly (OR 3.19 [1.33, 7.49]), and younger age (OR < 3 years: 4.10 (1.79, 9.26; 3 to 6 years: 2.21 [1.18, 4.15]) were associated with PRAEs (AUC 0.74; corrected AUC 0.68).

CONCLUSIONS

Prediction modeling concurrently evaluating comorbidities and polysomnography metrics identified cardiac disease, airway anomaly, and young age as independent predictors of PRAEs. These findings suggest that medical comorbidity and age are more important factors in predicting PRAEs than PSG metrics in a medically complex population.