Automated prediction of cardiorespiratory deterioration in patients with single-ventricle parallel circulation: A multicenter validation studyCentral MessagePerspective
Craig G. Rusin, PhD,
Sebastian I. Acosta, PhD,
Kennith M. Brady, MD,
Eric Vu, MD,
Carly Scahill, MD,
Brian Fonseca, MD,
Cindy Barrett, MD,
Janet Simsic, MD,
Andrew R. Yates, MD,
Brenna Klepczynski, RN, BSN,
William J. Gaynor, MD,
Daniel J. Penny, MD, PhD, MHA
Affiliations
Craig G. Rusin, PhD
Department of Pediatrics—Cardiology, Baylor College of Medicine, Texas Children's Hospital, Houston, Tex; Address for reprints: Craig G. Rusin, PhD, 1102 Bates St, Feigin Building Suite 430.03, Houston, TX 77030.
Sebastian I. Acosta, PhD
Department of Pediatrics—Cardiology, Baylor College of Medicine, Texas Children's Hospital, Houston, Tex
Kennith M. Brady, MD
Department of Anesthesiology, Northwestern University, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Ill
Eric Vu, MD
Department of Anesthesiology, Northwestern University, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Ill
Carly Scahill, MD
Department of Pediatrics—Cardiology, Children's Hospital Colorado, Aurora, Colo
Brian Fonseca, MD
Department of Pediatrics—Cardiology, Children's Hospital Colorado, Aurora, Colo
Cindy Barrett, MD
Department of Pediatrics—Cardiology, Children's Hospital Colorado, Aurora, Colo
Janet Simsic, MD
Department of Pediatrics—Cardiology, Nationwide Children's Hospital, Columbus, Ohio
Andrew R. Yates, MD
Department of Pediatrics—Cardiology, Nationwide Children's Hospital, Columbus, Ohio
Brenna Klepczynski, RN, BSN
Department of Cardiovascular Surgery, Children's Hospital of Philadelphia, Philadelphia, Pa
William J. Gaynor, MD
Department of Cardiovascular Surgery, Children's Hospital of Philadelphia, Philadelphia, Pa
Daniel J. Penny, MD, PhD, MHA
Department of Pediatrics—Cardiology, Baylor College of Medicine, Texas Children's Hospital, Houston, Tex
Objectives: Patients with single-ventricle physiology have a significant risk of cardiorespiratory deterioration between their first- and second-stage palliation surgeries. Detection of deterioration episodes may allow for early intervention and improved outcomes. Methods: A prospective study was executed at Nationwide Children's Hospital, Children's Hospital of Philadelphia, and Children's Hospital Colorado to collect physiologic data of subjects with single ventricle physiology during all hospitalizations between neonatal palliation and II surgeries using the Sickbay software platform (Medical Informatics Corp). Timing of cardiorespiratory deterioration events was captured via chart review. The predictive algorithm previously developed and validated at Texas Children's Hospital was applied to these data without retraining. Standard metrics such as receiver operating curve area, positive and negative likelihood ratio, and alert rates were calculated to establish clinical performance of the predictive algorithm. Results: Our cohort consisted of 58 subjects admitted to the cardiac intensive care unit and stepdown units of participating centers over 14 months. Approximately 28,991 hours of high-resolution physiologic waveform and vital sign data were collected using the Sickbay. A total of 30 cardiorespiratory deterioration events were observed. the risk index metric generated by our algorithm was found to be both sensitive and specific for detecting impending events one to two hours in advance of overt extremis (receiver operating curve = 0.927). Conclusions: Our algorithm can provide a 1- to 2-hour advanced warning for 53.6% of all cardiorespiratory deterioration events in children with single ventricle physiology during their initial postop course as well as interstage hospitalizations after stage I palliation with only 2.5 alarms being generated per patient per day.
