Mean Platelet Volume (MPV), Platelet Distribution Width (PDW), Platelet Count and Plateletcrit (PCT) as predictors of in-hospital paediatric mortality: a case-control Study.


Autoria(s): Zainab, Mohammedi Golwala; Hardik, Shah; Jacob., M. Puliyel; Neeraj, Gupta; V., Sreenivas
Cobertura

Origin of publication: Uganda

Data(s)

13/07/2016

Resumo

Background: Thrombocytopenia has been shown to predict mortality. We hypothesize that platelet indices may be more useful prognostic indicators. Our study subjects were children one month to 14 years old admitted to our hospital. Aim: To determine whether platelet count, plateletcrit (PCT), mean platelet volume (MPV) and platelet distribution width (PDW) and their ratios can predict mortality in hospitalised children. Methods: Children who died during hospital stay were the cases. Controls were age matched children admitted contemporaneously. The first blood sample after admission was used for analysis. Receiver operating characteristic (ROC) curve was used to identify the best threshold for measured variables and the ratios studied. Multiple regression analysis was done to identify independent predictors of mortality. Results: Forty cases and forty controls were studied. Platelet count, PCT and the ratios of MPV/Platelet count, MPV/PCT, PDW/Platelet count, PDW/PCT and MPV x PDW/Platelet count x PCT were significantly different among children who survived compared to those who died. On multiple regression analysis the ratio of MPV/PCT, PDW/Platelet count and MPV/ Platelet count were risk factors for mortality with an odds ratio of 4.31(95% CI, 1.69-10.99), 3.86 (95% CI, 1.53-9.75), 3.45 (95% CI, 1.38-8.64) respectively. In 67% of the patients who died MPV/PCT ratio was above 41.8 and PDW/Platelet count was above 3.86. In 65% of patients who died MPV/Platelet count was above 3.45. Conclusion: The MPV/PCT, PDW/Platelet count and MPV/Platelet count, in the first sample after admission in this case control study were predictors of mortality and could predict 65% to 67% of deaths accurately.

Formato

html

Identificador

http://www.bioline.org.br/abstract?id=hs16048

Idioma(s)

en

Publicador

Makerere University Medical School

Relação

http://www.bioline.org.br/hs

Direitos

Copyright 2016 - African Health Sciences

Fonte

African Health Sciences (ISSN: 1680-6905) Vol 16 Num 2

Palavras-Chave #SICK Score; PRISM; severity of illness scores PIM; in-hospital mortality; platelet indices
Tipo

CR