A simple score to predict severe leptospirosis
Smith, Simon, Kennedy, Brendan J., Dermedgoglou, Alexis, Poulgrain, Suzanne S., Paavola, Matthew P., Minto, Tarryn L., Luc, Michael, Liu, Yu-Hsuan, and Hanson, Josh (2019) A simple score to predict severe leptospirosis. PLoS Neglected Tropical Diseases, 13 (2). e0007205.
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Abstract
Background The case-fatality rate of severe leptospirosis can exceed 50%. While prompt supportive care can improve survival, predicting those at risk of developing severe disease is challenging, particularly in settings with limited diagnostic support.
Methodology/Principal findings We retrospectively identified all adults with laboratory-confirmed leptospirosis in Far North Queensland, Australia, between January 1998 and May 2016. Clinical, laboratory and radiological findings at presentation were correlated with the patients' subsequent clinical course. Medical records were available in 402 patients; 50 (12%) had severe disease. The presence of oliguria (urine output 500 mL/24 hours, odds ratio (OR): 16.4, 95% confidence interval (CI): 6.9-38.8, p<0.001), abnormal auscultatory findings on respiratory examination (OR 11.2 (95% CI: 4.7-26.5, p<0.001) and hypotension (systolic blood pressure 100 mmHg, OR 4.3 (95% CI 1.7-10.7, p = 0.002) at presentation independently predicted severe disease. A three-point score (the SPiRO score) was devised using these three clinical variables, with one point awarded for each. A score could be calculated in 392 (98%) patients; the likelihood of severe disease rose incrementally: 8/287 (3%), 14/70 (20%), 18/26 (69%) and 9/9 (100%) for a score of 0, 1, 2 and 3 respectively (p = 0.0001). A SPiRO score <1 had a negative predictive value for severe disease of 97% (95% CI: 95-99%).
Conclusions/Significance A simple, three-point clinical score can help clinicians rapidly identify patients at risk of developing severe leptospirosis, prompting early transfer to referral centres for advanced supportive care. This inexpensive, bedside assessment requires minimal training and may have significant utility in the resource-limited settings which bear the greatest burden of disease.
Author summary Leptospirosis, a neglected tropical disease with a global distribution, is estimated to kill 60,000 people every year. Predicting those at risk of developing severe disease is challenging, and a simple scoring system to quantify the risk of severe disease has proven elusive. Identifying the high-risk patient is important, as it might expedite the initiation of life-saving supportive care. This review of 402 adult patients with leptospirosis in tropical Australia determined that three clinical variables identified at presentation independently predicted severe disease (a subsequent requirement for Intensive Care Unit admission, intubation, vasopressor support, renal replacement therapy or the development of pulmonary haemorrhage). These three variables (abnormal auscultatory findings on respiratory examination, hypotension and oliguria) were used to generate a simple, three-point clinical score which can be determined rapidly and reliably at the bedside by health care workers with minimal training. This simple score may help the clinical management of patients with leptospirosis, particularly in lower and middle-income countries that bear the greatest burden of disease.
Item ID: | 57734 |
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Item Type: | Article (Research - C1) |
ISSN: | 1935-2735 |
Copyright Information: | © 2019 Smith et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Date Deposited: | 27 Mar 2019 07:36 |
FoR Codes: | 32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320211 Infectious diseases @ 50% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3207 Medical microbiology > 320702 Medical infection agents (incl. prions) @ 50% |
SEO Codes: | 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920120 Zoonoses @ 100% |
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