Correlation analysis between lactic, procalcitonin and disease severity in patients with imported malaria from Africa

Abstract

Objective: To explore the clinical characteristics, the correlation between lactate, procalcitonin and disease severity of imported malaria from Africa. Methods: The clinical data of 186 patients with imported malaria were collected from January 1, 2018 to April 30, 2021 in the Guangzhou Eighth People's Hospital, Guangzhou Medical University. The general conditions, clinical symptoms, laboratory tests, treatment, and prognosis of the patients were analyzed retrospectively. Receiver operating characteristic (ROC) curves were drawn to evaluate the value of relevant indicators in predicting severe malaria. Results: A total of 186 patients were divided into severe cases (n=48) and non-severe cases (n=138) in this study, of which the mean age was (38.3±10.3) years, 169(90.9%) cases were male, 17(9.1%) cases were female. The main infection species was Plasmodium falciparum, in a total of 166 cases (89.2%). The severe cases were all falciparum malarias. Compared with the non-severe group, the lactic, procalcitonin, white blood cell count and neutrophil count of the severe group were all increased, the differences were all statistically significant (all P<0.01); the percentage of monocytes, red blood cell count, hemoglobin, hematocrit and platelet count were all decreased, the difference were all statistically significant (all P<0.01). The areas under the ROC curves (AUC)(95%CI) of lactate, procalcitonin, red blood cell count, hemoglobin, hematocrit and platelet count for predicting severe malaria was 0.753(0.663-0.844), 0.755(0.670-0.841), 0.782(0.700-0.864), 0.738(0.652-0.823), 0.760(0.676-0.844), 0.778(0.699-0.857), respectively (all P<0.01). When the Youden indexes were at their maximum, the best cut-off value of lactic was 2.29 mmol/L, with sensitivity in predicting of severe malaria was 56.3%, and the specificity was 93.5%; the best cut-off value of procalcitonin was 2.12 μg/L, with sensitivity in predicting of severe malaria was 77.1%, and the specificity was 68.1%. The fatality rate of severe malaria was 4.2% (2/48). Conclusions: Anemia and thrombocytopenia are common indicators for predicting the severity of malaria. Lactic and procalcitonin also have higher predictive value for severe malaria, which could help to identify severe malaria as early as possible, improve the cure rate and reduce the risk of death.