The impact of psychiatric disorders on outcomes following heart transplantation in children.
Kia QuinlanScott R AuerbachDavid W BearlDebra A DoddCary W ThurmMatt HallDickey Catherine FuchsAndrea Nicole LambertJustin A GodownPublished in: Pediatric transplantation (2020)
Psychiatric disorders are common in pediatric HTx recipients. However, the impact of psychiatric comorbidities on patient outcomes is unknown. We aimed to assess the impact of disorders of adjustment, depression, and anxiety on HTx outcomes in children; hypothesizing that the presence of psychiatric disorders during or preceding HTx would negatively impact outcomes. All pediatric HTx recipients ≥8 years of age who survived to hospital discharge were identified from a novel linkage between the PHIS and SRTR databases (2002-2016). Psychiatric disorders were identified using ICD codes during or preceding the HTx admission. Post-transplant graft survival, freedom from readmission, and freedom from rejection were analyzed using the Kaplan-Meier method. Multivariable Cox proportional hazard models were used to adjust for covariates. A total of 1192 patients were included, of which 133 (11.2%) had depression, 197 (16.5%) had anxiety, and 218 (18.3%) had adjustment disorders. The presence of depression was independently associated with higher rates of readmission (60.9% vs 54.1% at 6 months) (AHR 1.63, 95% CI 1.22-2.18, P = .001) and inferior graft survival (70.2% vs 83.4% at 5 years) (AHR 1.62, 95% CI 1.14-2.3, P = .007). Anxiety was independently associated with higher rates of readmission (60.4% vs 53.9% at 6 months) (AHR 1.46, 95% CI 1.09-1.94, P = .01). Anxiety and depression in the pretransplant period are independently associated with outcomes following HTx in children. Evaluation and management of psychiatric comorbidities represents an important component of care in this vulnerable population.
Keyphrases
- young adults
- sleep quality
- mental health
- depressive symptoms
- ejection fraction
- newly diagnosed
- emergency department
- palliative care
- type diabetes
- machine learning
- metabolic syndrome
- skeletal muscle
- physical activity
- free survival
- deep learning
- chronic kidney disease
- hiv testing
- human immunodeficiency virus
- glycemic control
- childhood cancer
- artificial intelligence
- men who have sex with men
- affordable care act