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Development of a predictive model for risk stratification of acute kidney injury in patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy.
Krause, Martin; Mehdipour, Soraya; Veerapong, Jula; Baumgartner, Joel M; Lowy, Andrew M; Gabriel, Rodney A.
Afiliação
  • Krause M; Division of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 80203, USA. makrause@health.ucsd.edu.
  • Mehdipour S; Division of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 80203, USA.
  • Veerapong J; Division of Surgical Oncology, Department of Surgery, University of California San Diego, San Diego, CA, USA.
  • Baumgartner JM; Division of Surgical Oncology, Department of Surgery, University of California San Diego, San Diego, CA, USA.
  • Lowy AM; Division of Surgical Oncology, Department of Surgery, University of California San Diego, San Diego, CA, USA.
  • Gabriel RA; Division of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 80203, USA.
Sci Rep ; 14(1): 6630, 2024 03 19.
Article em En | MEDLINE | ID: mdl-38503776
ABSTRACT
Acute kidney injury (AKI) following hyperthermic intraperitoneal chemotherapy (HIPEC) is common. Identifying patients at risk could have implications for surgical and anesthetic management. We aimed to develop a predictive model that could predict AKI based on patients' preoperative characteristics and intraperitoneal chemotherapy regimen. We retrospectively gathered data of adult patients undergoing HIPEC at our health system between November 2013 and April 2022. Next, we developed a model predicting postoperative AKI using multivariable logistic regression and calculated the performance of the model (area under the receiver operating characteristics curve [AUC]) via tenfold cross-validation. A total of 412 patients were included, of which 36 (8.7%) developed postoperative AKI. Based on our multivariable logistic regression model, multiple preoperative and intraoperative characteristics were associated with AKI. We included the total intraoperative cisplatin dose, body mass index, male sex, and preoperative hemoglobin level in the final model. The mean area under the receiver operating characteristics curve value was 0.82 (95% confidence interval 0.71-0.93). Our risk model predicted AKI with high accuracy in patients undergoing HIPEC in our institution. The external validity of our model should now be tested in independent and prospective patient cohorts.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Injúria Renal Aguda / Hipertermia Induzida Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Injúria Renal Aguda / Hipertermia Induzida Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos