Comparison of estimated glomerular filtration rate using five equations to predict acute kidney injury following hip fracture surgery.

Acute kidney injury Estimated glomerular filtration rate Hip arthroplasty Hip fracture Intramedullary nail

Journal

Orthopaedics & traumatology, surgery & research : OTSR
ISSN: 1877-0568
Titre abrégé: Orthop Traumatol Surg Res
Pays: France
ID NLM: 101494830

Informations de publication

Date de publication:
04 Sep 2024
Historique:
received: 18 08 2022
revised: 22 07 2024
accepted: 03 09 2024
pubmed: 7 9 2024
medline: 7 9 2024
entrez: 6 9 2024
Statut: aheadofprint

Résumé

Decreased estimated glomerular filtration rate (eGFR) is associated with acute kidney injury (AKI) following hip fracture surgery. Delaying surgery for preoperative treatment of comorbidities is controversial in this patient population. The purpose of this study was 1) to assess differences in demographics and comorbidities between AKI and non-AKI groups, 2) to analyze equations used in calculating eGFR, and 3) to identify the equation which best predicts the development of AKI following hip fracture surgery. We hypothesize that one of the equations used to calculate eGFR will be superior to the others. 124,002 cases of hip fracture surgery were performed from 2012 to 2019, based upon a query of the National Surgical Quality Improvement Program (NSQIP). Preoperative eGFR was calculated using the following: Modification of Diet in Renal Disease (MDRD) II, re-expressed MDRD II, Chronic Kidney Disease Epidemiology Collaboration, Mayo quadratic, and Cockcroft-Gault equations. Independent associations between preoperative eGFR and postoperative renal failure were evaluated using multivariate regression analysis. The predictive ability of each equation was determined using the Akaike information criterion (AIC). AKI was diagnosed in 584 (0.71%) out of the 82,326 patients following hip fracture surgery. The AKI and no AKI cohorts differed significantly by patient sex (p = <0.001), race (p = <0.001), BMI (p = < 0.001), preoperative hematocrit (p = <0.001), preoperative albumin (p = <0.001), diabetes mellitus (p = <0.001), hypertension (p = <0.001), and congestive heart failure (p = <0.001). The Mayo equation (84.0 ± 23.7) was the equation with the highest calculated mean eGFR, followed by the CKD-EPI equation (83.6 ± 20.0), MDRD II equation (83.0 ± 38.9), CG equation (74.7 ± 35.5), and finally the re-expressed MDRD II equation (68.5 ± 36.0) which had the lowest calculated mean eGFR.. All five equations detected that a decrease in preoperative eGFR was associated with an increased risk of postoperative AKI. Lower preoperative eGFR, as calculated by each of the five equations, was significantly associated with an increased risk of AKI following surgical fixation of hip fracture. The AIC was the lowest in the Mayo equation, demonstrating the best fit of the equations to predict postoperative AKI CONCLUSIONS: We propose that using the equation that best identifies those at risk of developing postoperative AKI may help with perioperative decision making and treatment to improve outcomes, which we found to be the Mayo equation. The risk of postoperative AKI was independently associated with decreased preoperative eGFR. The results of this study may warrant further investigation utilizing prospective studies. III; retrospective cohort study.

Sections du résumé

BACKGROUND BACKGROUND
Decreased estimated glomerular filtration rate (eGFR) is associated with acute kidney injury (AKI) following hip fracture surgery. Delaying surgery for preoperative treatment of comorbidities is controversial in this patient population. The purpose of this study was 1) to assess differences in demographics and comorbidities between AKI and non-AKI groups, 2) to analyze equations used in calculating eGFR, and 3) to identify the equation which best predicts the development of AKI following hip fracture surgery. We hypothesize that one of the equations used to calculate eGFR will be superior to the others.
PATIENTS AND METHODS METHODS
124,002 cases of hip fracture surgery were performed from 2012 to 2019, based upon a query of the National Surgical Quality Improvement Program (NSQIP). Preoperative eGFR was calculated using the following: Modification of Diet in Renal Disease (MDRD) II, re-expressed MDRD II, Chronic Kidney Disease Epidemiology Collaboration, Mayo quadratic, and Cockcroft-Gault equations. Independent associations between preoperative eGFR and postoperative renal failure were evaluated using multivariate regression analysis. The predictive ability of each equation was determined using the Akaike information criterion (AIC).
RESULTS RESULTS
AKI was diagnosed in 584 (0.71%) out of the 82,326 patients following hip fracture surgery. The AKI and no AKI cohorts differed significantly by patient sex (p = <0.001), race (p = <0.001), BMI (p = < 0.001), preoperative hematocrit (p = <0.001), preoperative albumin (p = <0.001), diabetes mellitus (p = <0.001), hypertension (p = <0.001), and congestive heart failure (p = <0.001). The Mayo equation (84.0 ± 23.7) was the equation with the highest calculated mean eGFR, followed by the CKD-EPI equation (83.6 ± 20.0), MDRD II equation (83.0 ± 38.9), CG equation (74.7 ± 35.5), and finally the re-expressed MDRD II equation (68.5 ± 36.0) which had the lowest calculated mean eGFR.. All five equations detected that a decrease in preoperative eGFR was associated with an increased risk of postoperative AKI. Lower preoperative eGFR, as calculated by each of the five equations, was significantly associated with an increased risk of AKI following surgical fixation of hip fracture. The AIC was the lowest in the Mayo equation, demonstrating the best fit of the equations to predict postoperative AKI CONCLUSIONS: We propose that using the equation that best identifies those at risk of developing postoperative AKI may help with perioperative decision making and treatment to improve outcomes, which we found to be the Mayo equation. The risk of postoperative AKI was independently associated with decreased preoperative eGFR. The results of this study may warrant further investigation utilizing prospective studies.
LEVEL OF EVIDENCE METHODS
III; retrospective cohort study.

Identifiants

pubmed: 39241909
pii: S1877-0568(24)00268-8
doi: 10.1016/j.otsr.2024.103987
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103987

Informations de copyright

Copyright © 2024. Published by Elsevier Masson SAS.

Auteurs

Kevin L Mekkawy (KL)

From the Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: kevin.mekkawy@gmail.com.

Yash P Chaudhry (YP)

From the Department of Orthopaedic Surgery, Philadelphia College of Osteopathic Medicine, Philadelphia, PA, USA.

Colton Mowers (C)

From the Department of Orthopaedic Surgery, Rush University, Chicago, IL, USA.

Alyssa Wenzel (A)

From the Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Micheal Raad (M)

From the Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Sandesh S Rao (SS)

From the Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Rachel B Sotsky (RB)

From the Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Harpal S Khanuja (HS)

From the Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Raj M Amin (RM)

From the Department of Orthopaedic Surgery, Rush University, Chicago, IL, USA; From the Department of Orthopaedic Surgery, University of California San Francisco, University Orthopaedic Associates, Fresno, CA, USA.

Classifications MeSH