Value of the TTM risk score for early prognostication of comatose patients after out-of-hospital cardiac arrest in a Swiss university hospital.

Kägi, Emmanuel; Weck, Anja; Iten, Manuela; Levis, Anja; Haenggi, Matthias (2020). Value of the TTM risk score for early prognostication of comatose patients after out-of-hospital cardiac arrest in a Swiss university hospital. Swiss medical weekly, 150(w20344), w20344. EMH Media 10.4414/smw.2020.20344

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Comatose patients admitted to the intensive care unit (ICU) after out-of-hospital cardiac arrest frequently die after withdrawal of life support. Guidelines recommend scheduling prognostication no sooner than 96 hours after cardiac arrest, and strict withdrawal criteria leave many patients waiting for improvement for days without ever reaching a favourable outcome. In clinical practice, physicians are frequently confronted with vague living wills expressed by next of kin or an imprecise advance care directive soon after cardiac arrest. Often a decision to admit a patient to an ICU or limiting ICU treatment in terms of time or intensity is made early, based on the patient’s preferences. The Target Temperature Management (TTM) risk score is an imperfect measure that predicts outcome early, at the time of ICU admission. It was developed on a data set of 939 patients included in the TTM Trial, a study in which unconscious patients after cardiac arrest were randomised into two temperature management arms. Patient selection in that trial might impede generalisability. We aimed to validate the TTM risk score with 100 consecutive patients treated in our ICU. Although we had different survival rates, reflecting a different patient population, we were able to confirm the score’s albeit imperfect ability to predict outcome early after cardiac arrest. The suggested cut-off values of 10 and 16 can be used as a basis for discussion with the family; in particular, a risk score value below 10 predicts a favourable outcome and might guide early discussion. As in the original study, the outcome of an individual patient cannot be predicted. (ClinicalTrials.gov Identifier: NCT02722460).

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