Creation of a quantitative score to predict the need for mechanical support in children awaiting heart transplant

Ryan R Davies, Shylah Haldeman, Michael A. McCulloch, Christian Pizarro

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Background Due to the availability of new devices, the use of ventricular assist devices (VADs) in children has been increasing; however, patient selection and optimal timing of device implantation in this population remains uncertain. Methods A retrospective review of the United Network for Organ Sharing dataset identified 5,200 listings without mechanical circulatory support (MCS) for isolated pediatric heart transplant, 1995 to 2012. Patients were randomly divided into a derivation and validation cohort. A multivariable logistic regression model predicting the likelihood of death or need for MCS within 60 days was built using the derivation cohort and tested in the validation cohort. A simplified score (PedsMCS score) was developed and evaluated for accuracy. Results The predictive model consisted of variables present at listing (age, albumin level, creatinine clearance, serum bilirubin, mechanical ventilation, and inotropic support). It had good predictive ability (C statistic 0.7304) within the validation cohort. The simplified PedsMCS score was also predictive (C statistic 0.7217) and there was a strong correlation between predicted and expected outcomes (r = 0.91, p < 0.0001). Patients with PedsMCS score 16 or greater had a significantly higher risk of death or MCS within 2 months (36.6%) than those with low scores (< 6) (1.5%, p < 0.0001). A single point increase in PedsMCS score was associated with a 16.7% increase in the risk of death or MCS with 2 months (p < 0.0001). Conclusions We have developed and validated a simplified score to predict the need for MCS based on risk factors present at listing. This will provide more accurate prognostication in children awaiting heart transplant, and may improve patient selection.

Original languageEnglish (US)
Pages (from-to)675-684
Number of pages10
JournalAnnals of Thoracic Surgery
Volume98
Issue number2
DOIs
StatePublished - Jan 1 2014

Fingerprint

Transplants
Patient Selection
Logistic Models
Equipment and Supplies
Heart-Assist Devices
Bilirubin
Artificial Respiration
Albumins
Creatinine
Pediatrics
Serum
Population
Datasets

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Surgery
  • Pulmonary and Respiratory Medicine

Cite this

Creation of a quantitative score to predict the need for mechanical support in children awaiting heart transplant. / Davies, Ryan R; Haldeman, Shylah; McCulloch, Michael A.; Pizarro, Christian.

In: Annals of Thoracic Surgery, Vol. 98, No. 2, 01.01.2014, p. 675-684.

Research output: Contribution to journalArticle

Davies, Ryan R ; Haldeman, Shylah ; McCulloch, Michael A. ; Pizarro, Christian. / Creation of a quantitative score to predict the need for mechanical support in children awaiting heart transplant. In: Annals of Thoracic Surgery. 2014 ; Vol. 98, No. 2. pp. 675-684.
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abstract = "Background Due to the availability of new devices, the use of ventricular assist devices (VADs) in children has been increasing; however, patient selection and optimal timing of device implantation in this population remains uncertain. Methods A retrospective review of the United Network for Organ Sharing dataset identified 5,200 listings without mechanical circulatory support (MCS) for isolated pediatric heart transplant, 1995 to 2012. Patients were randomly divided into a derivation and validation cohort. A multivariable logistic regression model predicting the likelihood of death or need for MCS within 60 days was built using the derivation cohort and tested in the validation cohort. A simplified score (PedsMCS score) was developed and evaluated for accuracy. Results The predictive model consisted of variables present at listing (age, albumin level, creatinine clearance, serum bilirubin, mechanical ventilation, and inotropic support). It had good predictive ability (C statistic 0.7304) within the validation cohort. The simplified PedsMCS score was also predictive (C statistic 0.7217) and there was a strong correlation between predicted and expected outcomes (r = 0.91, p < 0.0001). Patients with PedsMCS score 16 or greater had a significantly higher risk of death or MCS within 2 months (36.6{\%}) than those with low scores (< 6) (1.5{\%}, p < 0.0001). A single point increase in PedsMCS score was associated with a 16.7{\%} increase in the risk of death or MCS with 2 months (p < 0.0001). Conclusions We have developed and validated a simplified score to predict the need for MCS based on risk factors present at listing. This will provide more accurate prognostication in children awaiting heart transplant, and may improve patient selection.",
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N2 - Background Due to the availability of new devices, the use of ventricular assist devices (VADs) in children has been increasing; however, patient selection and optimal timing of device implantation in this population remains uncertain. Methods A retrospective review of the United Network for Organ Sharing dataset identified 5,200 listings without mechanical circulatory support (MCS) for isolated pediatric heart transplant, 1995 to 2012. Patients were randomly divided into a derivation and validation cohort. A multivariable logistic regression model predicting the likelihood of death or need for MCS within 60 days was built using the derivation cohort and tested in the validation cohort. A simplified score (PedsMCS score) was developed and evaluated for accuracy. Results The predictive model consisted of variables present at listing (age, albumin level, creatinine clearance, serum bilirubin, mechanical ventilation, and inotropic support). It had good predictive ability (C statistic 0.7304) within the validation cohort. The simplified PedsMCS score was also predictive (C statistic 0.7217) and there was a strong correlation between predicted and expected outcomes (r = 0.91, p < 0.0001). Patients with PedsMCS score 16 or greater had a significantly higher risk of death or MCS within 2 months (36.6%) than those with low scores (< 6) (1.5%, p < 0.0001). A single point increase in PedsMCS score was associated with a 16.7% increase in the risk of death or MCS with 2 months (p < 0.0001). Conclusions We have developed and validated a simplified score to predict the need for MCS based on risk factors present at listing. This will provide more accurate prognostication in children awaiting heart transplant, and may improve patient selection.

AB - Background Due to the availability of new devices, the use of ventricular assist devices (VADs) in children has been increasing; however, patient selection and optimal timing of device implantation in this population remains uncertain. Methods A retrospective review of the United Network for Organ Sharing dataset identified 5,200 listings without mechanical circulatory support (MCS) for isolated pediatric heart transplant, 1995 to 2012. Patients were randomly divided into a derivation and validation cohort. A multivariable logistic regression model predicting the likelihood of death or need for MCS within 60 days was built using the derivation cohort and tested in the validation cohort. A simplified score (PedsMCS score) was developed and evaluated for accuracy. Results The predictive model consisted of variables present at listing (age, albumin level, creatinine clearance, serum bilirubin, mechanical ventilation, and inotropic support). It had good predictive ability (C statistic 0.7304) within the validation cohort. The simplified PedsMCS score was also predictive (C statistic 0.7217) and there was a strong correlation between predicted and expected outcomes (r = 0.91, p < 0.0001). Patients with PedsMCS score 16 or greater had a significantly higher risk of death or MCS within 2 months (36.6%) than those with low scores (< 6) (1.5%, p < 0.0001). A single point increase in PedsMCS score was associated with a 16.7% increase in the risk of death or MCS with 2 months (p < 0.0001). Conclusions We have developed and validated a simplified score to predict the need for MCS based on risk factors present at listing. This will provide more accurate prognostication in children awaiting heart transplant, and may improve patient selection.

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