Risk Factor Analysis for 30-Day Readmission Rates of Newly Tracheostomized Children

Objectives: Pediatric patients undergo tracheostomy for a variety of reasons; however, medical complexity is common among these patients. Although tracheostomy may help to facilitate discharge, these patients may be at increased risk for hospital readmission. The purpose of this study was to evaluate our institutional rate of 30-day readmission for patients discharged with new tracheostomies and to identify risk factors associated with readmission. Study Design: A retrospective cohort study was conducted for all pediatric patients ages 0-18 years with new tracheostomies at our institution over a 36-month period. Methods: A chart review was performed for all newly tracheostomizedchildren from 2013 to 2016. We investigated documented readmissions within 30 days of discharge, reasons for readmission, demographic variables including age and ethnicity, initial discharge disposition, co-morbidities, and socioeconomic status estimated by mean household income by parental zip code. Results: 45 patients were discharged during the study time period. A total of 13 (28.9%) required readmission within 30 days of discharge. Among these 13 patients, the majority (61.5%) were readmitted for lower airway concerns, many (30.8%) were admitted for reasons unrelated to tracheostomy or respiratory concerns, and only one patient (7.7%) was readmitted for a reason related to tracheostomy itself (tracheostomalbreakdown). Age, ethnicity, discharge disposition, co-morbidities, and socioeconomic status were not associated with differences in readmission rates. Patients readmitted within 30 days had a higher number of admissions within the first year. Conclusion: Pediatric patients with new tracheostomies are at high risk for readmission after discharge from initial hospitalization. The readmissions are most likely secondary to underlying medical complexity rather than issues related specifically to the tracheostomy procedure.https://jdc.jefferson.edu/patientsafetyposters/1046/thumbnail.jp

Multimodal Sleep Apnea Detection with Missing or Noisy Modalities

Polysomnography (PSG) is a type of sleep study that records multimodal physiological signals and is widely used for purposes such as sleep staging and respiratory event detection. Conventional machine learning methods assume that each sleep study is associated with a fixed set of observed modalities and that all modalities are available for each sample. However, noisy and missing modalities are a common issue in real-world clinical settings. In this study, we propose a comprehensive pipeline aiming to compensate for the missing or noisy modalities when performing sleep apnea detection. Unlike other existing studies, our proposed model works with any combination of available modalities. Our experiments show that the proposed model outperforms other state-of-the-art approaches in sleep apnea detection using various subsets of available data and different levels of noise, and maintains its high performance (AUROC>0.9) even in the presence of high levels of noise or missingness. This is especially relevant in settings where the level of noise and missingness is high (such as pediatric or outside-of-clinic scenarios)

Pediatric polysomnography-flagging etiologies and impact on the clinical timeline

Background/objectiveThere is a paucity of literature regarding “flagging” abnormal sleep studies for expedited review. This single-center retrospective analysis (n = 266) of flagged polysomnography studies from 2019 to 2022 aimed to investigate flagging and its impact on the clinical timeline.MethodsTwo hundred sixty-six flagged polysomnography studies from 2019 to 2022 were retrospectively reviewed.ResultsFlagged study etiologies included repetitive brief oxygen desaturations (46.6%), sustained desaturations (32.3%), sustained hypercapnia (5.6%), or other concerning events (15.5%). The median time between a flagged study and scoring report finalization, medical intervention, and surgical intervention were 0 (2) days, 2 (3) days, 5 (11.25) days, and 44 (73) days, respectively. Patients with apnea–hypopnea index >30 had less time between a flagged study and surgical intervention (65.3 ± 96.7 days vs. 112 ± 119 days, p = 0.044).ConclusionAs anticipated, the time to surgical intervention was longer than to medical intervention. Patients with a higher disease severity experienced quicker scoring, report finalization, and surgical intervention

0524 Polysomnographic Characteristics of Adolescent Patients with Class III Obesity and Severe OSA (AHI ≥30)

Abstract Introduction Adolescents with obesity are at increased risk for obstructive sleep apnea (OSA). Polysomnographic characteristics of pediatric patients with severe OSA (defined as AHI ≥30 events/hour) have not been frequently described. This study aims to describe clinical characteristics and polysomnographic data from a cohort of adolescents with both severe (class III, BMI ≥40 kg/m2) obesity and severe OSA. Methods This IRB-approved, retrospective review examines clinical and polysomnographic data from pediatric patients (ages 8-18) at Nemours Children’s Hospital, Wilmington, Delaware, who had initial baseline diagnostic polysomnogram performed from December 2012-September 2021. Subgroup analysis and descriptive statistics were performed in patients with severe OSA (AHI ≥30 events/hour). Results 259 (mean age 15.2 years, range 8 – 18 years, 64.4% female, 40.2% white, 46.7% black, mean BMI 50.3 kg/m2) pediatric patients with severe obesity completed initial baseline diagnostic polysomnogram in the study period. Of these patients, 41/259 (15.8%) met criteria for severe OSA (mean age mean age 15.4 years, range 12 – 18 years, 43.9% female, 46.3% white, 43.9% black, mean BMI 53.7 kg/m2). Of these studies, the mean total AHI was 65.2 (range 31.4-159.4) events/hr, obstructive apnea index (OAI) of 11.4 (range 0 – 69.4) events/hr and hypopnea index of 47.8 (range 12.9 – 108.8) events/hour. Mean SpO2 nadir was 78.9 (range 52 – 98)% with peak ETCO2 of 53.2 (range 39 – 69) mmHg. 12/41 (29.2%) of patients met polysomnographic criteria for hypoventilation (EtCO2 &amp;gt;50 mmHg for &amp;gt;25% of TST). Sleep architecture was notable for decreased mean sleep efficiency at 62.8% and elevated arousal index (mean 62.4 arousals/hour). Conclusion Adolescents with both severe OSA and obesity demonstrated a high frequency of hypopneas compared to apneic events and disrupted sleep architecture with high arousal index and decreased sleep efficiency. Interestingly, even among those with severe OSA, ventilation was acceptable in a majority of the patients. Further analysis will be completed to correlate patient clinical characteristics, including co-morbidities and lung function measurements, to help identify which patients with severe obesity are at risk for the most severe OSA. Support (If Any) None </jats:sec