Skin autofluorescence as a novel predictor of acute kidney injury after liver resection.


Journal

World journal of surgical oncology
ISSN: 1477-7819
Titre abrégé: World J Surg Oncol
Pays: England
ID NLM: 101170544

Informations de publication

Date de publication:
15 Sep 2021
Historique:
received: 12 04 2021
accepted: 03 09 2021
entrez: 16 9 2021
pubmed: 17 9 2021
medline: 18 9 2021
Statut: epublish

Résumé

Skin autofluorescence (SAF) reflects accumulation of advanced glycation end-products (AGEs). The aim of this study was to evaluate predictive usefulness of SAF measurement in prediction of acute kidney injury (AKI) after liver resection. This prospective observational study included 130 patients undergoing liver resection. The primary outcome measure was AKI. SAF was measured preoperatively and expressed in arbitrary units (AU). AKI was observed in 32 of 130 patients (24.6%). SAF independently predicted AKI (p = 0.047), along with extent of resection (p = 0.019) and operative time (p = 0.046). Optimal cut-off for SAF in prediction of AKI was 2.7 AU (area under the curve [AUC] 0.611), with AKI rates of 38.7% and 20.2% in patients with high and low SAF, respectively (p = 0.037). Score based on 3 independent predictors (SAF, extent of resection, and operative time) well stratified the risk of AKI (AUC 0.756), with positive and negative predictive values of 59.3% and 84.0%, respectively. In particular, SAF predicted AKI in patients undergoing major and prolonged resections (p = 0.010, AUC 0.733) with positive and negative predictive values of 81.8%, and 62.5%, respectively. AGEs accumulation negatively affects renal function in patients undergoing liver resection. SAF measurement may be used to predict AKI after liver resection, particularly in high-risk patients.

Sections du résumé

BACKGROUND BACKGROUND
Skin autofluorescence (SAF) reflects accumulation of advanced glycation end-products (AGEs). The aim of this study was to evaluate predictive usefulness of SAF measurement in prediction of acute kidney injury (AKI) after liver resection.
METHODS METHODS
This prospective observational study included 130 patients undergoing liver resection. The primary outcome measure was AKI. SAF was measured preoperatively and expressed in arbitrary units (AU).
RESULTS RESULTS
AKI was observed in 32 of 130 patients (24.6%). SAF independently predicted AKI (p = 0.047), along with extent of resection (p = 0.019) and operative time (p = 0.046). Optimal cut-off for SAF in prediction of AKI was 2.7 AU (area under the curve [AUC] 0.611), with AKI rates of 38.7% and 20.2% in patients with high and low SAF, respectively (p = 0.037). Score based on 3 independent predictors (SAF, extent of resection, and operative time) well stratified the risk of AKI (AUC 0.756), with positive and negative predictive values of 59.3% and 84.0%, respectively. In particular, SAF predicted AKI in patients undergoing major and prolonged resections (p = 0.010, AUC 0.733) with positive and negative predictive values of 81.8%, and 62.5%, respectively.
CONCLUSIONS CONCLUSIONS
AGEs accumulation negatively affects renal function in patients undergoing liver resection. SAF measurement may be used to predict AKI after liver resection, particularly in high-risk patients.

Identifiants

pubmed: 34526025
doi: 10.1186/s12957-021-02394-0
pii: 10.1186/s12957-021-02394-0
pmc: PMC8444415
doi:

Substances chimiques

Biomarkers 0
Glycation End Products, Advanced 0

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

276

Subventions

Organisme : Narodowe Centrum Nauki (PL)
ID : 2017/26/D/NZ5/00733

Informations de copyright

© 2021. The Author(s).

Références

World J Surg. 2013 Nov;37(11):2618-28
pubmed: 23959337
Am J Nephrol. 2020;51(9):676-692
pubmed: 32854097
BJS Open. 2019 Aug 02;3(4):549
pubmed: 31388648
Postgrad Med J. 2017 May;93(1099):289-294
pubmed: 28143896
Crit Care. 2017 Feb 9;21(1):24
pubmed: 28179018
Atherosclerosis. 2018 Jul;274:47-53
pubmed: 29751284
J Clin Med. 2020 Jun 05;9(6):
pubmed: 32516928
Br J Surg. 2015 Jun;102(7):805-12
pubmed: 25877255
J Gerontol A Biol Sci Med Sci. 2015 Jul;70(7):841-6
pubmed: 25589479
HPB (Oxford). 2015 Mar;17(3):258-64
pubmed: 25387727
Curr Opin Nephrol Hypertens. 2019 Nov;28(6):507-512
pubmed: 31589190
Front Physiol. 2019 Jul 23;10:880
pubmed: 31396093
HPB (Oxford). 2018 Sep;20(9):865-871
pubmed: 29691124
Br J Anaesth. 2017 Dec 1;119(6):1127-1134
pubmed: 29136086
Diabetes. 2016 Dec;65(12):3744-3753
pubmed: 27609106
HPB (Oxford). 2016 Jun;18(6):540-8
pubmed: 27317959
Oxid Med Cell Longev. 2020 Mar 18;2020:3818196
pubmed: 32256950
PLoS Med. 2020 Jul 13;17(7):e1003163
pubmed: 32658890
BMC Nephrol. 2014 Oct 23;15:169
pubmed: 25342079
Int J Environ Res Public Health. 2020 Sep 22;17(18):
pubmed: 32972023
BMC Nephrol. 2019 Jul 18;20(1):272
pubmed: 31319808
PLoS One. 2017 Jan 31;12(1):e0170778
pubmed: 28141808
Am J Med Sci. 2019 Jan;357(1):57-66
pubmed: 30466736
HPB (Oxford). 2020 Jan;22(1):144-150
pubmed: 31431415
Diabetes Care. 2018 Jun;41(6):1292-1294
pubmed: 29610272
PeerJ. 2020 Feb 25;8:e8583
pubmed: 32140301
Obes Surg. 2021 Mar;31(3):1055-1061
pubmed: 33123869
PLoS One. 2017 Oct 13;12(10):e0186336
pubmed: 29028816
Br J Surg. 2020 Jul;107(8):1023-1032
pubmed: 32026470
Diabetologia. 2004 Jul;47(7):1324-1330
pubmed: 15243705
Diab Vasc Dis Res. 2019 Sep;16(5):466-473
pubmed: 31064217
Ann Surg. 2004 Aug;240(2):205-13
pubmed: 15273542
Br J Anaesth. 2019 Jun;122(6):726-733
pubmed: 30916001
J Atheroscler Thromb. 2018 Dec 1;25(12):1274-1284
pubmed: 29962379
Atherosclerosis. 2016 Nov;254:291-299
pubmed: 27751506
Nat Commun. 2020 May 1;11(1):2148
pubmed: 32358497
Kidney Int. 2018 Apr;93(4):803-813
pubmed: 29477239
Ann Surg. 2009 Nov;250(5):720-8
pubmed: 19809295
Kidney Int. 2020 Jun;97(6):1117-1129
pubmed: 32409237
Nephrol Dial Transplant. 2009 Mar;24(3):710-3
pubmed: 19033250
Can J Surg. 2018 Oct 01;61(5):E11-E16
pubmed: 30247865
Diabetes Care. 2017 Apr;40(4):591-598
pubmed: 28148544

Auteurs

Maciej Krasnodębski (M)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland. mwkrasn@gmail.com.

Karolina Grąt (K)

Second Department of Clinical Radiology, Medical University of Warsaw, Warsaw, Poland.

Marcin Morawski (M)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

Jan Borkowski (J)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

Piotr Krawczyk (P)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

Andriy Zhylko (A)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

Michał Skalski (M)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

Piotr Kalinowski (P)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

Krzysztof Zieniewicz (K)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

Michał Grąt (M)

Department of General, Transplant and Liver Surgery, Medical University of Warsaw, Warsaw, Poland.

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