A model for acute kidney injury in severe burn patients
| Autor: | Cem Aydogan, Emre Karakaya, Cihat Burak Sayin, Ebru H. Ayvazoglu Soy, Mehmet Haberal, Sait Can Yücebaş, Omar Alshalabi, Aydincan Akdur, Emin Turk |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
medicine.medical_specialty Resuscitation Burn injury medicine.medical_treatment Critical Care and Intensive Care Medicine 030207 dermatology & venereal diseases 03 medical and health sciences chemistry.chemical_compound 0302 clinical medicine Oliguria Internal medicine Medicine Humans Medical history Renal replacement therapy Retrospective Studies Creatinine business.industry Acute kidney injury 030208 emergency & critical care medicine General Medicine Acute Kidney Injury medicine.disease Renal Replacement Therapy chemistry Emergency Medicine Surgery medicine.symptom business Burns Kidney disease |
| Zdroj: | Burns : journal of the International Society for Burn Injuries. 48(1) |
| ISSN: | 1879-1409 |
| Popis: | Introduction In patients with severe burns, morbidity and mortality are high. One factor related to poor prognosis is acute kidney injury. According to the AKIN criteria, acute kidney injury has 3 stages based on urine output, serum creatinine level, and renal replacement therapy. In this study, we aimed to create a decision tree for estimating risk of acute kidney injury in patients with severe burn injuries. Methods We retrospectively evaluated 437 adult patients with ≥20% total burn surface area injury who were treated at the Baskent University Ankara and Konya Burn Centers from January 2000 to March 2020. Patients who had high-voltage burn and previous history of kidney disease were excluded. Patient demographics, medical history, mechanism of injury, presence of inhalation injury, depth of burn, laboratory values, presence of oliguria, need for renal replacement therapy, central venous pressure, and prognosis were evaluated. These data were used in a “decision tree method” to create the Baskent University model to estimate risk of acute kidney injury in severe burn patients. Results Our model provided an accuracy of 71.09% for risk estimation. Of 172 patients, 78 (45%) had different degrees of acute kidney injury, with 26 of these (15.1%) receiving renal replacement therapy. Our model showed that total burn surface area was the most important factor for estimation of acute kidney injury occurrence. Other important factors included serum creatinine value, burn injury severity score, hemoglobin value, neutrophil-to-lymphocyte ratio, and platelet count. Conclusion The Baskent University model for acute kidney injury may be helpful to determine risk of acute kidney injury in burn patients. This determination would allow appropriate treatment to be given to high-risk patients in the early period, reducing the incidence of acute kidney injury. |
| Databáze: | OpenAIRE |
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