22q11.2 Deletion Status Influences Resource Utilization in Infants Requiring Repair of Tetralogy of Fallot and Common Arterial Trunk.
Laxmi V GhimireChristie DevoeAnita J Moon-GradyPublished in: Pediatric cardiology (2020)
22q11.2 deletion syndrome leads to both cardiac and non-cardiac developmental defects. We aimed to study the impact of 22q11.2 deletion syndrome on in-hospital outcomes in children undergoing surgical repair for tetralogy of Fallot (TOF) and truncus arteriosus (TA). Using the nationally representative Kids Inpatient Database (KID), we analyzed data from in-hospital pediatric patients for the years 2003, 2006, 2009, and 2012. We compared the in-hospital outcomes between those with and those without 22q11.2 deletion syndrome. There were 6126 cases of TOF and 968 cases of TA. 22q11.2 deletion syndrome were documented in 7.2% (n = 441) of the TOF and 27.4% (n = 265) of the TA group. 22q11.2 deletion did not significantly increase the risk of mortality in either group: [OR = 1.98 (95% CI 0.99-3.94), adjusted p = 0.053] for TOF and OR = 1.07 (95% CI 0.57-1.99), adjusted p = 0.82 for TA. However, the length of hospitalization was longer in the 22q11.2 deletion group by 8.6 days (95% CI 5.2-12), adjusted p < 0.001 for TOF and by 8.15 days (95% CI 1.05-15.25), adjusted p = 0.025 for the TA group. Acute respiratory failure [10.6% vs 5.5%, p < 0.001] and acute renal failure [6.3% vs 2.6%, p < 0.001] were higher in 22q11.2 deletion cohort within the TOF group but not in the TA group. Though survival is not affected, children with 22q11.2 deletion syndrome who undergo surgical repair for TOF and TA use significantly more hospital resources-specifically longer hospital stay and higher hospitalization cost-than those without 22q11.2 deletion syndrome. Prenatal or preoperative testing for 22q11deletion is indicated to make appropriate adjustments in parental, caregiver, and administrative expectations.
Keyphrases
- mass spectrometry
- ms ms
- respiratory failure
- case report
- young adults
- adverse drug
- acute care
- pregnant women
- emergency department
- liver failure
- type diabetes
- mental health
- cardiovascular disease
- left ventricular
- machine learning
- adipose tissue
- risk factors
- palliative care
- artificial intelligence
- patients undergoing
- hepatitis b virus
- heart failure
- big data
- metabolic syndrome
- drug induced
- deep learning
- skeletal muscle
- free survival