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DOI 10.4103/ijciis.ijciis_122_16

Медицинская библиотека · International journal of critical illness and injury science · 2017

Delta model for end-stage liver disease and delta clinical prognostic indicator as predictors of mortality in patients with viral acute liver failure.

Pannu Ashok Kumar, Bhalla Ashish, Rao Chelapati, Singh Charanpreet

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Аннотация

OBJECTIVE

The objective of the study is to compare the model for end-stage liver disease (MELD) with clinical prognostic indicators (CPI) specifically the change in these parameters after 48 h of admission in predicting the mortality in patients with acute liver failure (ALF) due to acute viral hepatitis.

MATERIALS AND

METHODS

An open label, investigator-initiated prospective study was conducted that included 41 patients with acute viral hepatitis with ALF. The cases were followed prospectively till death or discharge. The MELD and CPI were calculated at admission and 48 h of admission.

RESULTS

Patients having no change or worsening in CPI score, i.e., delta CPI more negative had a higher mortality over the next 48 h compared to patients having an improvement in their respective CPI score. Delta CPI predicted adverse outcome better than the presence of any three CPI on admission (P = 0.019). Patients having no change or a worsening in MELD score, i.e., delta MELD more negative, had a higher mortality in the next 48 h compared to the patients having improvement in their respective MELD score. However, MELD >33 on admission was superior to delta MELD in predicting the adverse outcome (P = 0.019).

CONCLUSION

Among the patients with ALF due to viral hepatitis, delta CPI was found to be superior to delta MELD in predicting the adverse outcome in patients with viral ALF (P < 0.0001).

Для цитирования: Pannu Ashok Kumar, Bhalla Ashish, Rao Chelapati, Singh Charanpreet. Delta model for end-stage liver disease and delta clinical prognostic indicator as predictors of mortality in patients with viral acute liver failure.. International journal of critical illness and injury science. 2017. DOI: 10.4103/ijciis.ijciis_122_16.
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