Predicting death made easy after cardiac admission

Predicting death made easy after cardiac admission
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Published in CMAJ, a new tool designed for patients is better at predicting death after hospital cardiac admission than current tools – could this be an accurate way of predicting death?

A new tool designed for patients with heart disease is better at predicting death after hospital admission than current tools, according to a study published in CMAJ (Canadian Medical Association Journal). Could this be the beginning of a disease-specific comorbidity index for predicting mortality in patients admitted to hospital with a cardiac condition?

Can predicting death be measured?

Dr. Marc Jolicoeur, Montreal Heart Institute, Université de Montréal, Montréal, Canada, explains: “This cardiac-specific tool, or index, to predict death outperforms current general indexes used to predict death.

“The other available tools are good for all patients, but we developed one that is better specifically for cardiac patients.”

Current indexes already exist to help predict likelihood of death and are widely used in clinical settings, although these are not disease-specific, and accuracy for patients with cardiac issues has not been widely investigated.

Focusing specifically on cardiac admission

Researchers analysed administrative data on cardiac patients admitted to the Montreal Heart Institute to create and test an index, the Cardiac-Specific Comorbidity Index, to help predict death both in-hospital and within one year in a group.

They then tested the index in a group of almost 19,000 cardiac patients in Alberta. Their cardiac-specific comorbidity index outperformed both the Charlson-Deyo comorbidity index and the Elixhauser comorbidity index.

“Estimating risk is important for patients and their families, as well as policy-makers, to help them monitor outcomes at various hospitals and guide decisions,” says Jolicoeur.

“With this tool, patients at high risk can be flagged, and appropriate care can be taken to manage their condition.”

Most importantly, this tool was derived and validated in Canada and will therefore be suitable for use by Canadian researches, administrators and decision-makers.

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