Abstract
BackgroundRisk prediction models are well established as an adjunct to perioperative decision making, but few exist for pediatric surgical outcomes. The majority of risk tools do not feature Australasian data and do not estimate mortality risk beyond 30-days. Our aim was to develop and validate a model for mortality risk prediction in children (age <18yrs) at 30-days, 90-days and 1 year following all types of surgery using a national database. Methods and resultsThe New Zealand Ministry of Health National Minimum Dataset was accessed to obtain clinical and demographic data for all children having surgery between June 1st 2011 and July 1st 2016. Three quarters of the data were used to derive 3 models to predict 30-day, 90-day and 1-year mortality risk, and the remaining data used for validation. We constructed 3 models using data from 135 217 patients, validating a total of 11 covariates for risk prediction. Included were neonate, prematurity, ASA-PS status, heart and lung disease, active malignancy, sepsis, surgical type, surgical severity score, surgical urgency, ethnicity and socioeconomic deprivation. All models showed excellent discrimination (area under the receiver operating characteristic curve (AUROC) values of 0.947, 0.933 and 0.908 respectively) and calibration statistics (calibration slopes of 0.778, 1.125, 1.153, Brier scores of 0.001, 0.002, 0.003 respectively). ConclusionCombining objective data with severity indices, NZRISK-Paed presents a risk stratification model which is intuitive and practical. Application of 30-day, 90-day and 1-year percentage mortality risk aids in longer-term planning, shared decision-making and allocation of resource to the individual and to high needs populations.Risk prediction tools add an objective measure to pre-operative assessment but few exist for pediatric surgery and none predict mortality beyond 30-days.
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