INTRODUCTION: Blood lactate concentration predicts mortality in neonates, infants, children and adults, with evidence that it has better predictive power than other markers of acid-base status such as absolute base excess or pH. OBJECTIVE: To investigate whether blood lactate concentration on admission predicts mortality in paediatric intensive care and if its addition can improve the performance of the Paediatric Index of Mortality 2 (PIM2) mortality prediction score. DESIGN AND SETTING: Retrospective cohort study in one 20-bed UK paediatric intensive care unit (PICU) using data from the PICU clinical and blood gas analyser databases between 2006 and 2010. Only cases with a blood lactate concentration measured at the same time as the PIM2 variables were included. Logistic regression was used to assess if blood lactate concentration predicted mortality independently of PIM2, adjusting for potential confounders, and if it could replace absolute base excess in the PIM2 model. RESULTS: There were 155 deaths amongst 2,380 admissions (6.5 %). Admission lactate in non-survivors was higher than in survivors (mean [standard deviation, SD]) 6.6 [5.6] versus 3.0 [2.5] mmol/l, had a positive association with mortality [adjusted odds ratio (OR) for death per unit (mmol/l)] increase 1.11 [95 % confidence interval (CI) 1.06-1.16; p < 0.001] and significantly improved the model fit of PIM2 when it replaced absolute base excess (p < 0.001). CONCLUSIONS: PICU admission blood lactate concentration predicts mortality independently of PIM2. Given the limitations of this study, a prospective multi-centre evaluation is required to establish whether it should be added to the PIM2 model with or without replacement of base excess.
INTRODUCTION: Blood lactate concentration predicts mortality in neonates, infants, children and adults, with evidence that it has better predictive power than other markers of acid-base status such as absolute base excess or pH. OBJECTIVE: To investigate whether blood lactate concentration on admission predicts mortality in paediatric intensive care and if its addition can improve the performance of the Paediatric Index of Mortality 2 (PIM2) mortality prediction score. DESIGN AND SETTING: Retrospective cohort study in one 20-bed UK paediatric intensive care unit (PICU) using data from the PICU clinical and blood gas analyser databases between 2006 and 2010. Only cases with a blood lactate concentration measured at the same time as the PIM2 variables were included. Logistic regression was used to assess if blood lactate concentration predicted mortality independently of PIM2, adjusting for potential confounders, and if it could replace absolute base excess in the PIM2 model. RESULTS: There were 155 deaths amongst 2,380 admissions (6.5 %). Admission lactate in non-survivors was higher than in survivors (mean [standard deviation, SD]) 6.6 [5.6] versus 3.0 [2.5] mmol/l, had a positive association with mortality [adjusted odds ratio (OR) for death per unit (mmol/l)] increase 1.11 [95 % confidence interval (CI) 1.06-1.16; p < 0.001] and significantly improved the model fit of PIM2 when it replaced absolute base excess (p < 0.001). CONCLUSIONS: PICU admission blood lactate concentration predicts mortality independently of PIM2. Given the limitations of this study, a prospective multi-centre evaluation is required to establish whether it should be added to the PIM2 model with or without replacement of base excess.
Authors: Tim C Jansen; Jasper van Bommel; F Jeanette Schoonderbeek; Steven J Sleeswijk Visser; Johan M van der Klooster; Alex P Lima; Sten P Willemsen; Jan Bakker Journal: Am J Respir Crit Care Med Date: 2010-05-12 Impact factor: 21.405
Authors: R C Parslow; R C Tasker; E S Draper; G J Parry; S Jones; T Chater; K Thiru; P A McKinney Journal: Arch Dis Child Date: 2008-12-23 Impact factor: 3.791
Authors: Luregn J Schlapbach; Graeme MacLaren; Marino Festa; Janet Alexander; Simon Erickson; John Beca; Anthony Slater; Andreas Schibler; David Pilcher; Johnny Millar; Lahn Straney Journal: Intensive Care Med Date: 2017-02-20 Impact factor: 17.440
Authors: E Unal; A G Pirinccioglu; S Y Yanmaz; K Yılmaz; M Taşkesen; Y K Haspolat Journal: Acta Endocrinol (Buchar) Date: 2020 Jan-Mar Impact factor: 0.877
Authors: Ryan P Barbaro; Philip S Boonstra; Matthew L Paden; Lloyd A Roberts; Gail M Annich; Robert H Bartlett; Frank W Moler; Matthew M Davis Journal: Intensive Care Med Date: 2016-03-23 Impact factor: 17.440
Authors: Massimo Antonelli; Marc Bonten; Maurizio Cecconi; Jean Chastre; Giuseppe Citerio; Giorgio Conti; J R Curtis; Goran Hedenstierna; Michael Joannidis; Duncan Macrae; Salvatore M Maggiore; Jordi Mancebo; Alexandre Mebazaa; Jean-Charles Preiser; Patricia Rocco; Jean-François Timsit; Jan Wernerman; Haibo Zhang Journal: Intensive Care Med Date: 2013-01-22 Impact factor: 17.440