Predictors of hyperlactataemia among children presenting with malaria in a low transmission area in The Gambia

Abstract

BackgroundHyperlactataemia and metabolic acidosis are important risk factors for malaria death, but measuring lactate at the point of care is not financially viable in many resource-poor settings. This study aimed to identify combinations of routinely available parameters that could identify children at high risk of hyperlactataemia.MethodsUsing data from a study of Gambian children aged six months to 16 years with severe or uncomplicated malaria, logistic regression modelling with a forward stepwise model selection process was used to develop a predictive model for hyperlactataemia from routinely available demographic, clinical and laboratory parameters. Potential predictors of hyperlactataemia considered for the modelling process were patient characteristics (age, sex, prior use of anti-malarials, and weight percentile for age), respiratory symptoms (deep breathing, irregular respiration, use of accessory muscles of respiration, lung crepitations, grunting respiration, cough, and age-specific respiratory rate), other clinical parameters recorded at presentation (duration of symptoms, Blantyre coma score, number of convulsions prior to admission, axillary temperature, dehydration, severe prostration, splenomegaly) and laboratory measures from blood tests (percentage parasitaemia, white cell count, lymphocyte count, neutrophil count, monocyte count, platelet count, haemoglobin level, blood glucose level).Results495 children were included, and 68 (14%) had laboratory-confirmed hyperlactataemia (lactate > 7 mmol/L). Four features were independently associated with increased hyperlactataemia risk in a multivariable age- and sex-adjusted model: lower Blantyre score (odds ratio (OR) compared to score 5 = 2.68 (95% CI, 1.03-6.96) for score 3–4 and 6.18 (95% CI, 2.24-17.07) for score 0–2, p = 0.001), higher percentage parasitaemia (OR = 1.07 (1.03-1.11) per 0031% increase, p < 0.001), high respiratory rate for age (OR = 3.09 (1.50-6.38) per unit increase, p = 0.002), and deep breathing (OR = 2.81 (1.20-6.60), p = 0.02). Cross-validated predictions from the final model achieved area under the receiver operating characteristic curve of 0.83.ConclusionsThis study identified predictors of hyperlactataemia requiring only simple bedside clinical examination and blood film examination that can be carried out in resource-limited settings to quickly identify children at risk of dangerously raised lactate. A simple spreadsheet tool implementing the final model is supplied as supplementary material.

Identifying Prognostic Factors of Severe Metabolic Acidosis and Acute Kidney Injury in African Children with Severe Falciparum Malaria: A Secondary Analysis of A Randomised Trial

“…The clinical signs associated with metabolic acidosis are varied and there are no reliable criteria for making this diagnosis clinically. Although deep breathing is a sign of respiratory distress most commonly described in relation to metabolic acidosis, its association has been contested in several studies (2,14,17,18). Similarly, there is varied signi cance in the association of metabolic acidosis and the presence of coma or convulsions (17,19).…”

“…We included candidate predictors that were complications of malaria and those that either caused or resulted from severe metabolic acidosis or AKI. For severe metabolic acidosis, this includes contributing factors like anaemia and consequences of metabolic acidosis, like deep breathing (17,25). Similarly, for acute kidney injury, candidate predictors include causative features like black water fever and hypovolaemia (26,27).…”

Identifying prognostic factors of severe metabolic acidosis and uraemia in African children with severe falciparum malaria: a secondary analysis of a randomized trial

“…Candidate predictors that were complications of malaria and those that either caused or resulted from severe metabolic acidosis or AKI were included. For severe metabolic acidosis, this includes contributing factors like anaemia and consequences of metabolic acidosis, like deep breathing [ 17 , 26 ]. Similarly, for AKI candidate predictors include causative features like black water fever and hypovolaemia [ 27 , 28 ].…”

“…The clinical signs associated with metabolic acidosis are varied and there is need for reliable criteria to make this diagnosis clinically. Although deep breathing is a sign of respiratory distress most commonly described in relation to metabolic acidosis, its association has been contested in several studies [ 2 , 14 , 17 , 18 ]. Similarly, there is varied significance in the association of metabolic acidosis and the presence of coma or convulsions [ 17 , 19 ].…”

“…Although deep breathing is a sign of respiratory distress most commonly described in relation to metabolic acidosis, its association has been contested in several studies [ 2 , 14 , 17 , 18 ]. Similarly, there is varied significance in the association of metabolic acidosis and the presence of coma or convulsions [ 17 , 19 ]. Due to the overlapping nature of these and other clinical signs, it is challenging to identify metabolic acidosis clinically [ 20 ].…”