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Eur J Cardiothorac Surg 1999;16:424-428
© 1999 Elsevier Science NL

A simple approach to risk stratification in adult heart transplantation

Clinical Effectiveness Unit, The Royal College of Surgeons of England, London, UK

Corresponding author. St George's Hospital, Blackshaw Road, London SW17 0QT, UK. Tel.: +44-181-725-3565; fax: +44-181-725-2049
e-mail: ajmurday{at}sghms.ac.uk

Objective: While there are numerous reports in the literature of risk factors for graft failure after heart transplantation, simple models for risk stratification are lacking. This study describes a simple method for risk stratification in adult heart transplantation that can be applied when the size of a dataset is insufficient for formal regression modelling. Methods: Multi-centre prospective cohort study. Fourteen risk factors documented in the literature as increasing post transplant graft failure were used to formulate a model. Risk factors included in the model were recipient age >50 years, pre-operative ventilatory support, pre-operative circulatory support, >1 previous sternotomy, pulmonary vascular resistance >2.5 wood units, male with body surface area >2.5 m², retransplant, ischaemic time >3.5 h, donor age >45 years, donor inotropic support >10 µg/kg per min dopamine, female donor, ratio donor/recipient body surface area <0.7, donor with diabetes and history of donor drug abuse. Four risk groups were defined depending on the number of risk factors present: Low, none; moderate, 1; high, 2 or 3; very high, 4 or more. Graft survival to 30 days was chosen as the primary outcome. The model was tested on 373 adult transplants performed in the UK between April 1995 and December 1996. Results: Twenty eight transplants were low risk, 82 moderate, 201 high and 62 very high. The 30-day survival (70% CI) for the risk groups was low, 97% (93–100), moderate 95% (92–98), high 87% (84–89) and very high 80% (75–83) (P=0.02). Conclusions: This preliminary model enables some stratification of heart transplant procedures according to donor and recipient risk profile. Further work will be directed at refining and validating the model.

Key Words: Heart transplantation • Predictive modelling • Risk factors

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