Early identification of leptospirosis-associated pulmonary hemorrhage syndrome by use of a validated prediction model
Introduction
Leptospirosis, a spirochetal zoonosis, has been increasingly recognized as an important cause of pulmonary hemorrhage syndrome.1, 2, 3, 4 Five to fifteen percent of the clinical infections progresses to develop severe disease manifestations.1, 2, 3, 5 The Nicaragua outbreak in 1995 raised awareness of leptospirosis as the cause of severe pulmonary hemorrhage.4 Whereas case fatality is 5–15% for Weil's disease, it is more than 50% in patients who develop leptospirosis-associated pulmonary hemorrhage syndrome (LPHS).5, 6, 7, 8
Early identification and triage of patients at risk for developing LPHS is essential to reduce the high case fatality rate. LPHS patients require intensive care unit (ICU) monitoring and aggressive supportive care for concomitant acute respiratory distress syndrome (ARDS), acute kidney injury and hypotension.9, 10, 11, 12, 13, 14 Protective mechanical ventilation modalities14 and daily hemodialysis15 have been shown to provide beneficial outcomes in clinical trials which included leptospirosis patients as subjects. However, identification of patients at risk for developing LPHS is difficult10, 11, 12, 13, 14 especially during initial hospital evaluation. Therefore predictive markers (e.g. hematology-test and biochemistry-test) need to be identified such that patients at risk for developing LPHS can be effectively identified and triaged.
We herein report the findings of a study which aimed to develop and validate a predictive model which can be used to identify patients at risk for developing LPHS at the time of hospital admission.
Section snippets
Patient cohorts
A prospective cohort study was performed at Emílio Ribas Institute of Infectology, the state infectious disease hospital in Sao Paulo, Brazil. This 200-bed hospital serves as the reference center for leptospirosis in the city which has a population of 10 million inhabitants. From October 1998 through December 2006, the study team of clinicians reviewed hospital admission records to consecutively identify suspected cases of leptospirosis during the first 24 h of hospitalization. Patients were
Derivation cohort
From January 1998 through October 2004, 281 patients with suspected leptospirosis were hospitalized at the study site. Of these 27 patients were excluded because they had evidence of disease other than leptospirosis or did not have a laboratory-confirmed diagnosis of leptospirosis and 51 were excluded for being under 14 years of age. Of the 203 subjects enrolled in the prospective derivation cohort, 172, 29 and 2 had a confirmed diagnosis on the basis of MAT, IgM ELISA and culture isolation
Discussion
Leptospirosis presents a wide variety of clinical manifestations and prognoses. Leptospirosis presenting as LPHS is associated with a high mortality rate. However, the clinical course of LPHS can be improved by early diagnosis and prompt treatment.
In the present study, we developed and validated a multivariate prediction model for LPHS based on five readily available variables. Assigning patient values to each variable, the equation we developed can be used to estimate individual risk. This
Conflict of interest
The authors state that there is no conflict of interest.
Acknowledgements
We would like to thank Mr. Carlos C.F. Marotto, Ms. Kesia Santos and Ms. Adriana Sanudo for the technical assistance. This work was supported, in part, by the National Institutes of Health (grants R01 AI052473 and D43 TW00919) and the Secretary of Health, Sao Paulo State, Brazil.
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