Abstract

A Severe Leptospira interrogans Serovar Copenhageni Infection Diagnosed by Next- Generation Sequencing and Treated with Corticosteroids

Introduction: Leptospirosis is a worldwide zoonotic disease, with variable severity and involvement of multiple organs. Severe leptospirosis is associated with high morbidity and mortality rates, which poses a great threat to human health. Due to the limitation of traditional clinical and laboratory diagnosis methods, pathogens for many infectious diseases, including leptospirosis, remain unknown. Recently, unbiased next generation sequencing (NGS) sheds light on the precise and rapid diagnosis of intractable infectious diseases, which is greatly beneficial to the prompt treatment and reliable prognosis.

Case presentation: A 35 year old male got a fever with rapid hepato-renal-pulmonary involvement after his travel to Hunan province, China. The manifestations initiated with a jaundice-hemorrhage clinical type, and then followed by the combination of jaundice-hemorrhage and diffuse hemorrhage (PDH) clinical types, along with liver, heart, muscle and pancreas involvement. To identify the causative agent for the disease, blood sample was collected for serologicaltests, pathogen-specific PCR detection. Meanwhile, blood and sputum samples were used to do the nextgeneration sequencing, and the Leptospira interrogans serovar Copenhageni was detected and confirmed as the pathogenic agent. Based on the precise diagnosis, our patient recovered progressively with antimicrobials and supportive care.

Conclusion: NGS played a critical role in the precise diagnosis of leptospirosis infection in this case. Corticosteroids combined with antibiotics treatments based on the diagnosis and clinical signs with suspicious pulmonary hemorrhage may decelerate the disease progression. The unbiased NGS would be further used in clinics for disease diagnosis especially for the uncertain and unknown pathogens.


Author(s):

Zeng W, Liqiang L, Yuhai B, Fang W, Jiansong T, Yuan J, Jiandong L, Jianming L, Rongrong Z, Pei N, Huijue J, Liu X, Wang H, Jinmin M, Yingxia Liu



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