Objective. Predictive efforts using individual factors or scoring systems do not adequately identify all intact survivors, and therefore all drowning victims are aggressively resuscitated in most emergency departments. More reliable outcome prediction is needed to guide early treatment decisions.

Methods. The charts of 274 near drowning patients admitted to Loma Linda University Children's Hospital were retrospectively reviewed. Patient outcome was categorized into good (near normal function), and poor (vegetative or dead) categories. Discriminant analysis was used to identify combinations of variables most able to predict outcome and a clinical classification system was constructed. The acute care hospital costs for each group were compared.

Results. Discriminant analysis classification achieved 95% accuracy, predicting death in 6 intact survivors. No combination of variables could accurately separate all intact survivors from the vegetative and dead groups. The clinical classification method achieved 93% overall accuracy, predicting death in 5 intact survivors. Of patients predicted to have a poor outcome, 5 (6.3%) survived intact. Children may experience an unpredictable, prolonged vegetative state followed by full recovery. Vegetative patients are the most expensive to care for (consuming 53% of total costs) while intact survivors are the least expensive. The majority of costs were spent on patients with poor outcome.

Conclusions. Individual outcome cannot be reliably predicted in the emergency department; therefore, aggressive resuscitation of near drowning victims should be performed. Decisions to subsequently withdraw life support should be made based on integration of likelihood of survival, high (but not absolute) certainty, and parental/societal issues. The vegetative patients are the most expensive to care for, while intact survivors are least expensive. Reduction of expenditures on patients likely to have vegetative or dead outcome would result in substantial savings, but loss of normal survivors.

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