Perioperative Acute Kidney Injury in Hip and Knee Arthroplasties - Incidence, Risk Factors, Diagnostic Methods and Machine Learning

Aug 4, 2026

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Perioperative acute kidney injury is a common adverse condition with a multifactorial mechanism and multiple risk factors. Incidence estimates range from 0.3–15% in elective hip and knee arthroplasties and 8.4–24% in emergency procedures, with clear impacts on postoperative care and mortality. Chronic kidney disease is closely linked and shares similar risk factor profiles. Traditionally, diagnosis has relied on increased serum creatinine, while decreased urine output has often been underused due to measurement challenges. Machine learning approaches aim to predict acute kidney injury, though research remains early-stage.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages188

Reading Time7 h 54 min

AccessFree to download

Abstract

Background and significance

Diagnostic criteria

Machine learning approach

Study aims and methods

Outcomes and conclusions

OULU 2025 D 1850 UNIVERSITAT IS OULU ENSIS D MEDICA Okke Nikkinen PERIOPERATIVE ACUTE KIDNEY INJURY IN HIP AND KNEE ARTHROPLASTIES INCIDENCE, RISK FACTORS, DIAGNOSTIC METHODS AND MACHINE LEARNING UNIVERSITY OF OULU GRADUATE SCHOOL; UNIVERSITY OF OULU, FACULTY OF MEDICINE; MEDICAL RESEARCH CENTER OULU ACTA A C T A U N I V E R S I T A T I S O U L U E N S I SD Medic a 1850 OKKE NIKKINEN PERIOPERATIVE ACUTE KIDNEY INJURY IN HIP AND KNEE ARTHROPLASTIES Incidence, risk factors, diagnostic methods and machine learning Academic dissertation to be presented with the assent of the Doctoral Programme Committee of Health and Biosciences of the University of Oulu for public defence in Auditorium 4 of Oulu University Hospital (Kajaanintie 50), on 19 September 2025, at 12 noon UNIVERSITY OF OULU, OULU 2025 Copyright © 2025 Acta Univ. Oul. D 1850, 2025 Supervised by Docent Merja Vakkala Professor Seppo Alahuhta Reviewed by Docent Teemu Luostarinen Docent Mikko Haapio Opponent Docent Maija Kaukonen ISBN 978-952-62-4567-6 (Paperback) ISBN 978-952-62-4568-3 (PDF) ISSN 0355-3221 (Printed) ISSN 1796-2234 (Online) Cover Design Raimo Ahonen PUNAMUSTA TAMPERE 2025 Nikkinen, Okke, Perioperative acute kidney injury in hip and knee arthroplasties. Incidence, risk factors, diagnostic methods and machine learning University of Oulu Graduate School; University of Oulu, Faculty of Medicine; Medical Research Center Oulu Acta Univ. Oul. D 1850, 2025 University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland Abstract Perioperative acute kidney injury is a common adverse condition. It is a multifactorial process and has multiple risk factors. Its incidence has been approximated to be between 0.3 and 15% in elective hip and knee arthroplasties and 8.4–24% in emergency arthroplasties. It increases mortality and affects the postoperative care. Chronic kidney disease is closely related to acute kidney injury, and they share similar risk factors. Traditionally, perioperative acute kidney injury has been defined by increased serum creatinine. The other important diagnostic criteria, decreased urine output, has been almost completely omitted in medical research due to difficulties assessing it. Machine learning methods are increasingly being utilized in medical research. Acute kidney injury is one of the challenges that have been tried to be resolved by building predicting machine learning models. As a whole, the research is still in its early stages. The aim of this doctoral thesis was to study perioperative acute kidney injury in hip and knee arthroplasties. The study focused on incidence, risk factors, outcomes and assessing the effect of using urine output as an acute kidney injury definition. The aim was also to develop a machine learning model predicting acute kidney injury. Two retrospective cohort materials were collected and used. The first one included hip and knee arthroplasty patients operated in Oulu University Hospital and Oulaskangas Hospital in 2014. These patients were over 65 years of age. The second material had hip and knee arthroplasty patients operated in Oulu in 2016 and 2017 . The main outcomes of the study were that the risk factors of acute kidney injury are the same as previously studied: preoperatively decreased kidney function, age, diabetes, high body mass index, cardiovascular diseases and emergency arthroplasty. The risk factors of elective and emergency hip patients seem to differ. Using urine output as a diagnostic criterion significantly increases acute kidney injury incidence and isolated oliguria is associated with mortality. The main conclusion of the machine learning development was that the algorithms we used, RUSBoost and Naïve Bayes, worked well on our material with promising results, but at the same time, we were only able to build preliminary models. This is in line with the current early stage of machine learning development i

FAQs

What is perioperative acute kidney injury and why is it clinically important in hip and knee arthroplasty patients?

It is a common adverse condition with multiple risk factors that increases mortality and affects postoperative care. It occurs across both elective and emergency arthroplasties.

How is perioperative acute kidney injury traditionally diagnosed in medical research?

Traditionally, it has been defined by increased serum creatinine. Decreased urine output is an additional important criterion but is often omitted due to difficulties assessing it.

What factors were identified as key risk factors, and how did using urine output affect incidence?

Risk factors include preoperatively decreased kidney function, age, diabetes, high body mass index, cardiovascular diseases, and emergency arthroplasty. Using urine output as a diagnostic criterion significantly increases incidence, and isolated oliguria is associated with mortality.

Aug 4, 2026

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