Prediction of imminent, severe deterioration of children with parallel circulations using real-time processing of physiologic data.

OBJECTIVES: Sudden death is common in patients with hypoplastic left heart syndrome and comparable lesions with parallel systemic and pulmonary circulation from a common ventricular chamber. It is hypothesized that unforeseen acute deterioration is preceded by subtle changes in physiologic dynamics before overt clinical extremis. Our objective was to develop a computer algorithm to automatically recognize precursors to deterioration in real-time, providing an early warning to care staff. METHODS: Continuous high-resolution physiologic recordings were obtained from 25 children with parallel systemic and pulmonary circulation who were admitted to the cardiovascular intensive care unit of Texas Children's Hospital between their early neonatal palliation and stage 2 surgical palliation. Instances of cardiorespiratory deterioration (defined as the need for cardiopulmonary resuscitation or endotracheal intubation) were found via a chart review. A classification algorithm was applied to both primary and derived parameters that were significantly associated with deterioration. The algorithm was optimized to discriminate predeterioration physiology from stable physiology. RESULTS: Twenty cardiorespiratory deterioration events were identified in 13 of the 25 infants. The resulting algorithm was both sensitive and specific for detecting impending events, 1 to 2 hours in advance of overt extremis (receiver operating characteristic area = 0.91, 95% confidence interval = 0.88-0.94). CONCLUSIONS: Automated, intelligent analysis of standard physiologic data in real-time can detect signs of clinical deterioration too subtle for the clinician to observe without the aid of a computer. This metric may serve as an early warning indicator of critical deterioration in patients with parallel systemic and pulmonary circulation.

Rare DNA copy number variants in cardiovascular malformations with extracardiac abnormalities.

Clinically significant cardiovascular malformations (CVMs) occur in 5-8 per 1000 live births. Recurrent copy number variations (CNVs) are among the known causes of syndromic CVMs, accounting for an important fraction of cases. We hypothesized that many additional rare CNVs also cause CVMs and can be detected in patients with CVMs plus extracardiac anomalies (ECAs). Through a genome-wide survey of 203 subjects with CVMs and ECAs, we identified 55 CNVs >50 kb in length that were not present in children without known cardiovascular defects (n=872). Sixteen unique CNVs overlapping these variants were found in an independent CVM plus ECA cohort (n=511), which were not observed in 2011 controls. The study identified 12/16 (75%) novel loci including non-recurrent de novo 16q24.3 loss (4/714) and de novo 2q31.3q32.1 loss encompassing PPP1R1C and PDE1A (2/714). The study also narrowed critical intervals in three well-recognized genomic disorders of CVM, such as the cat-eye syndrome region on 22q11.1, 8p23.1 loss encompassing GATA4 and SOX7 and 17p13.3-p13.2 loss. An analysis of protein-interaction databases shows that the rare inherited and de novo CNVs detected in the combined cohort are enriched for genes encoding proteins that are direct or indirect partners of proteins known to be required for normal cardiac development. Our findings implicate rare variants such as 16q24.3 loss and 2q31.3-q32.1 loss, and delineate regions within previously reported structural variants known to cause CVMs.