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Background and Aims Acute kidney Injury (AKI) is a serious medical condition estimated to affect more than 10 million people around the world annually, resulting in a 1.7- to 6.9-fold increased risk of hospital mortality. Out of 1.7 million deaths per year caused by AKI globally, around 1.4 million occur in low- and middle-income countries, sepsis being the leading cause. AKI occurs in 40–50% of patients with sepsis and increases the mortality six- to eight-fold. By comparing the prevalence of potential risk factors in populations of patients who had developed AKI with control groups with no AKI, several risk assessment tools have been proposed and generated for specific clinical settings such as intensive care units, cardiac surgery, general surgery, those undergoing radiological investigations involving intravenous contrast and those presenting to the emergency department. The AKI Risk Assessment (ARA F4) model incorporated newer biomarkers of kidney injury (TIMP-2, IGFBP7) along with clinical parameters to detect patients at risk for AKI as fast as possible and to prevent further damage. However, they are yet to be available freely in our country. To the best of our knowledge, no risk assessment tool in the setting of tropical fever associated AKI has been proposed till date. The aim of this study is to provide a practical model to identify patients at high risk for tropical fever associated AKI in a resource limited setting in the absence of newer biomarkers. Method Ours is a retrospective, single center study. Patients who had an increase in serum creatinine (S.Cr) ≥0.3 mg/dL within 48 hours; or an increase in S.Cr to ≥1.5 times baseline, which is known or presumed to have occurred within the prior 7 days or a urine volume of &amp;lt;0.5 mL/kg/h for 6 hours were included. We recruited 342 consecutive admissions with tropical fever associated AKI and evaluated them based on clinical and biochemical profiles. Results We analyzed data of 342 patients. Our population of patients had representation from all age groups, 72% were between 21 to 60 years, 20.4% were &amp;gt;60years and 34.7% were females. There was a clear relationship between age and the number of AKI risk factors. Baseline serum creatinine was available for 117 patients, the average S.cr was 0.9591mg/dL and the average rise in S.cr was 1.22mg/dL. Leptospirosis (11.98%), dengue (84.79%), malaria (2.63%) and complicated malaria (0.29%) were the etiologies for AKI. 19,21 and 2 patients with leptospirosis had &amp;lt;=5, 6 to 10 and &amp;gt;10 risk factors respectively. 258,32 and 0 patients with dengue had &amp;lt;=5, 6 to 10 and &amp;gt;10 risk factors respectively. 8,1 and 0 patients with malaria had &amp;lt;=5, 6 to 10 and &amp;gt;10 risk factors respectively. One patient with complicated malaria had &amp;lt;=5 risk factors. 15/42 with leptospirosis, 2/290 with dengue, none with malaria and 1/1 with complicated malaria required renal replacement therapy. Five patients expired, out of which three were on renal replacement therapy. 3/286 with total risk score &amp;lt;5, 14/53 with total risk score between 6-10 and one out of two with total risk score &amp;gt;10 required renal replacement therapy. Conclusion Tropical fever associated AKI is a major public health burden in southern India. Our aim was to propose a risk stratification model to assess severity of tropical fever associated AKI and dialysis requirement in a resource limited setting. In our study, the number of risk factors, incidence of AKI and dialysis requirement were more in people with leptospirosis. We also observed that as the risk scores went up, the need for hemodialysis increased irrespective of the etiology. In the absence of availability of newer biomarkers this risk prediction score is quite useful. Ours is the first risk assessment tool in tropical fever associated AKI in resource limited setting. We are planning on a prospective evaluation of the same in the near future to validate our Tropical fever associated Acute Kidney Injury Risk assessment (TAKIR) tool. Figure In-lined.

P0608TROPICAL FEVER ASSOCIATED ACUTE KIDNEY INJURY - RISK PREDICTION MODEL IN A RESOURCE LIMITED SETTING IN SOUTH INDIA