105 5 DELIRIUM | PART THREE same patient is often not clear. Therefore, a prediction algorithm could be of significant clinical value to provide this information. Martinez et al [24] developed a prediction rule for patients admitted to the internal medicine ward. This prediction rule could not be applied to our medical oncology ward as the prevalence of some of the components of the prediction rule was too low (e.g. age > 85 years). We developed an alternative algorithm in which patients with high risk for delirium are rapidly identifiedbasedon anemergency admittance combinedwithmetabolic imbalances (delirium risk 1:3) (see Figure 1). These factors are usually available upon admission of a patients with cancer and therefore this algorithm can be easily implemented in daily clinical practice. We here propose that based on this algorithm patients could be selected for preventive treatment for delirium [12-16]. We do realize that our study has some limitations such as that it is a retrospective evaluation, the number of patients are rather limited to evaluate a high number (> 10) of predisposing factors for delirium, and although it concerns only patients with cancer, tumor diagnosis is heterogeneous. On the other hand, the strength of this study is that no selection has beenmade for patients with cancer acutely admitted to the hospital and that the algorithm to determine the risk at a delirium can be easily implemented in daily practice. In future studies, preventive treatment for delirium should be evaluated for its influence on the quality of life of patients, while taking in account the added risk of treatment induced toxicity of such a treatment strategy. In addition, as previously advocated by others, we also highly recommend screening of acutely admitted patients for delirium [25]. The specificity for the cut-off in our algorithm is high (85%), but the sensitivity is only 40 percent. This means that 60 percent of the delirium cases would be missed when only attention is being focused at patients in the high-risk group. Therefore, while preventive treatment of patients identified by our algorithmwith a high risk of delirium needs further evaluation, also screening for delirium symptoms in the other patients with an emergency admission should be considered. Conclusions Delirium is a serious problem for patients with cancer admitted to the hospital. Especially patients undergoing an unscheduled admittance with a metabolic imbalance have a clinically relevant high risk to develop a delirium. Preventive delirium treatment should be evaluated for this patient group. Acknowledgments This work was supported by ZonMw The Netherlands Organization for Health Research and Development (grant number 1151.0011). The funding source did not have a role in the design, analysis and interpretation of data; in the writing of the report; nor in the decision to submit the article for publication.
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