Browsing by Autor "Ravindra L. Mehta"

Now showing 1 - 6 of 6

Characteristics and Outcomes of Community and Hospital Acquired AKI in Patients With COVID-19
(American Society of Nephrology, 2022) Rolando Claure‐Del Granado; Leydi M. Oliva-Cadima; Etienne Macedo; Ravindra L. Mehta
Diagnosis, diagnostic approach and challenges in pregnancy-associated AKI—the ADQI 32 consensus meeting
(Oxford University Press, 2025) Nuttha Lumlertgul; Rolando Claure‐Del Granado; Anjali Acharya; Ghada Ankawi; Swarnalata Gowrishankar; Claudio Ronco; Ravindra L. Mehta; Catherine Nelson‐Piercy; Marlies Ostermann; Catherine Nelson‐Piercy
Despite advancements in obstetric care, pregnancy-associated acute kidney injury (PrAKI) continues to be a significant public health concern, contributing to substantial maternal and fetal morbidity and mortality. The most common causes of PrAKI include preeclampsia/eclampsia, haemorrhage, and infection. Diagnosis is influenced by gestational age and individual risk factors. Alongside traditional investigations such as imaging and kidney biopsy, novel diagnostics and biomarkers may provide valuable insights for differential diagnosis. This review aims to offer an update on the diagnostic approaches and investigational tools for PrAKI, while also addressing current challenges in the diagnostic paradigm and presenting recommendations for clinical practice and future research.
Effluent volume and dialysis dose in CRRT: time for reappraisal
(Nature Portfolio, 2011) Etienne Macedo; Rolando Claure‐Del Granado; Ravindra L. Mehta
Fluid overload in the ICU: evaluation and management
(BioMed Central, 2016) Rolando Claure‐Del Granado; Ravindra L. Mehta
SAT-173 RISK FACTORS AND DEFINITION OF KIDNEY DYSFUNCTION IN THE COMMUNITY SETTING: THE ISN 0BY25 INITIATIVE
(Elsevier BV, 2019) Etienne Macedo; Suvasini Sharma; Ulla Hemmilä; Rolando Claure‐Del Granado; Emmanuel A. Burdmann; Jorge Cerdá; Michael V. Rocco; Ravindra L. Mehta
Community-acquired acute kidney injury (CA-AKI) is common, but often unrecognized in resource- constrained settings. Risk factors for CA-AKI development have not been well studied in Low and Lower-Middle Income Countries (LLMIC). A key limitation is the heterogeneity of diseases and a lack of a standardized approach to evaluating renal dysfunction. Limited lab assessments and lack of information on the prior state of kidney health contribute to this lack of recognition. In this study, we evaluated the risk factors associated with acute kidney disease (AKD) and the efficacy of point of care (POC) serum creatinine (sCr) and urine dipstick tests to identify patients with kidney dysfunction at presentation to community health centers (CHC) and emergency departments (ED), as part of the International Society of Nephrology (ISN) 0by25 Pilot Feasibility Project.
The use of a medical application improves the diagnosis of acute kidney injury: A pre-post study
(Frontiers Media, 2022) Andrea Gáspár; Maria F. Iturricha-Cáceres; Etienne Macedo; Ravindra L. Mehta; Rolando Claure‐Del Granado
The use of mobile devices by healthcare providers has transformed many aspects of clinical practice. Mobile devices and medical applications provide many benefits, perhaps most significantly increased access to point-of-care (POC) tools, which has been shown to support better clinical decision making and improved patient outcomes. In LMICs, where computer-based technology is limited, the use of mobile technology has the potential to immensely increase access to point of care tools. In this study, we conducted an interventional, pre-post study to determine whether the use of a medical application could help healthcare providers accurately recognize and diagnose AKI. After preparing 20 clinical vignettes based on AKI cases from our center Global Snapshot study report, we asked 50 last year medical students to identify the presence and stage of AKI first without and then with the use of the IRA SLANH App (IRA SLANH app, Island of the Moon<sup>®</sup> V.1, 2014; Cochabamba-Bolivia), which was designed specifically for this study. Before the IRA SLANH app was introduced, the mean number of correctly identified cases of AKI was 14.7 ± 4.7 with a minimum of 3 and a maximum of 20. The stage of AKI was correctly identified in only 6.7 ± 4.4 of the cases. After the app was introduced, the number of correctly identified and staged cases of AKI was 20. Medical applications are useful point-of-care tools in the practice of evidence-based medicine. Their use has the potential to play a very important role in early identification and classification of AKI, particularly in LMICs potentially allowing for earlier intervention with preventive and treatment strategies to reverse kidney injury and improve recovery.