Mr Kartik Kishore
Research Data Scientist
Baker Department of Cardiometabolic Health
25 Scholarly works
2 Projects
HIGHLIGHTS
2026
Journal article
Effect of preoperative SGLT2 inhibitor use on postoperative acute kidney injury in patients with type 2 diabetes undergoing surgery: A causal inference study using routinely collected data
DOI: 10.1111/dom.705092026
Journal article
RenoTrue: A diabetes-specific machine learning model to estimate glomerular filtration rate for people with diabetes
DOI: 10.1016/j.diabres.2026.1131372026
Journal article
Limitation of existing GFR estimating equations and application of artificial intelligence in improving GFR estimation and chronic kidney disease progression in people with diabetes
DOI: 10.1016/j.diabres.2026.1131522025
Journal article
Hallucinations and disturbed behaviour in the critically ill: incidence, patient characteristics, associations, trajectory, and outcomes
DOI: 10.1186/s13054-025-05290-12025
Journal article
Ketosis and ketoacidosis in hospitalized patients receiving SGLT2 inhibitor therapy
DOI: 10.1111/dom.700292022
Research Grant
3F ACADI - Impact of Glycemic Extremes on Quality of Sleep and QOL
2022
Research grants (other domestic)
Australian Centre for Accelerating Diabetes Innovations (ACADI)
RECENT SCHOLARLY WORKS
2025
Journal article
400-P: A Novel Genetic Risk Score Can Identify People at Risk of Diabetes Complications
DOI: 10.2337/db25-400-p2025
Journal article
The Use of Antipsychotic Medications in Cardiac Surgery: Prevalence, Trajectory, Risk Factors and Outcomes
DOI: 10.1016/j.hlc.2025.02.1042025
Journal article
Association of low-dose ketamine with hallucinations in critically ill patients: a target trial emulation
DOI: 10.1007/s00134-025-07926-w2025
Journal article
Comparative performance of CKD-EPI equations in people with diabetes: An international pooled analysis of individual participant data
DOI: 10.1016/j.diabres.2025.1121042024
Journal article
Development and validation of ‘Patient Optimizer’ (POP) algorithms for predicting surgical risk with machine learning
DOI: 10.1186/s12911-024-02463-w