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Kolhe, Nitin

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Dr. Kolhe received the M.B.B.S degree (1992) from Lokmanya Tilak Medical College, Mumbai, India and the M.D (1996) and D.M (1998) degrees from the King Edward Memorial Hospital, Mumbai, India. He subsequently completed Nephrology training from Leeds and London and obtained his CCT (Certificate of Completion of Training) in internal medicine (2005) and Nephrology (2006). He worked in the Hypertension unit at St. George’s Hospital and has extensive experience in managing resistant hypertension. Since 2006, Dr. Kolhe has been a Consultant in Renal Medicine at the University Hospitals of Derby and Burton NHS Foundation Trust. He was an expert adviser on the UK NCEPOD ‘Adding Insult to Injury’ (AKI) study and was involved with the development of electronic recognition for AKI in Derby in 2010 and AKI-care bundle in 2014 He was the co-chair for the NHS England AKI Measurement work stream and is member of AKI-Clinical Study Group (CSG) and Peritoneal dialysis (CSG)
Institutional profile
Dr. Kolhe is a member of Acute Renal Injury Research in Derby (ARID) group and leading a prospective research in epidemiology of AKI studying the role of nephrology input in the outcome, especially in relation to mortality and development of chronic kidney disease over a period of ten years. Dr. Kolhe has also studied epidemiology of acute kidney injury in England of the last 15 years. Dr Kolhe is an Educational Ambassador for International Society of Nephrology and mentor for nephrology units in developing countries. Dr. Kolhe regularly teaches medical students, foundation and speciality trainees. Dr. Kolhe has also conducted teaching sessions for general practitioners. He also has taught on peritoneal dialysis access academy.

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    Clinical Characteristics and Outcomes of Drug-Induced Acute Kidney Injury Cases.
    (Elsevier, 2023-08-14) Yousif, Zaid K; Koola, Jejo D; Macedo, Etienne; Cerda, Jorge; Goldstein, Stuart L; Chakravarthi, Rajasekara; Lewington, Andrew; Selewski, David; Zappitelli, Michael; Cruz, Dinna; Tolwani, Ashita; Joy, Melanie S; Jha, Vivekanand; Ramachandran, Raja; Ostermann, Marlies; Pandya, Bhavna; Acharya, Anjali; Brophy, Patrick; Ponce, Daniela; Steinke, Julia; Bouchard, Josee; Irarrazabal, Carlos E; Irarrazabal, Romina; Boltansky, Andrés; Askenazi, David; Kolhe, Nitin; Claure-Del Granado, Rolando; Benador, Nadine; Castledine, Clare; Davenport, Andrew; Barratt, Jonathan; Bhandari, Sunil; Riley, Alyssa A; Davis, T K; Farmer, Christopher; Hogarth, Michael; Thomas, Mark; Murray, Patrick T; Robinson-Cohen, Cassianne; Nicoletti, Paola; Vaingankar, Sucheta; Mehta, Ravindra; Awdishu, Linda; Consultant Physician and Nephrologist; Thomas, Mark
    Introduction: Drug-induced acute kidney injury (DI-AKI) is a frequent adverse event. The identification of DI-AKI is challenged by competing etiologies, clinical heterogeneity among patients, and a lack of accurate diagnostic tools. Our research aims to describe the clinical characteristics and predictive variables of DI-AKI. Methods: We analyzed data from the Drug-Induced Renal Injury Consortium (DIRECT) study (NCT02159209), an international, multicenter, observational cohort study of enriched clinically adjudicated DI-AKI cases. Cases met the primary inclusion criteria if the patient was exposed to at least 1 nephrotoxic drug for a minimum of 24 hours prior to AKI onset. Cases were clinically adjudicated, and inter-rater reliability (IRR) was measured using Krippendorff's alpha. Variables associated with DI-AKI were identified using L1 regularized multivariable logistic regression. Model performance was assessed using the area under the receiver operating characteristic curve (ROC AUC). Results: A total of 314 AKI cases met the eligibility criteria for this analysis, and 271 (86%) cases were adjudicated as DI-AKI. The majority of the AKI cases were recruited from the United States (68%). The most frequent causal nephrotoxic drugs were vancomycin (48.7%), nonsteroidal antiinflammatory drugs (18.2%), and piperacillin/tazobactam (17.8%). The IRR for DI-AKI adjudication was 0.309. The multivariable model identified age, vascular capacity, hyperglycemia, infections, pyuria, serum creatinine (SCr) trends, and contrast media as significant predictors of DI-AKI with good performance (ROC AUC 0.86). Conclusion: The identification of DI-AKI is challenging even with comprehensive adjudication by experienced nephrologists. Our analysis identified key clinical characteristics and outcomes of DI-AKI compared to other AKI etiologies. Keywords: drug-induced acute kidney injury; nephrotoxicity.