Circulating dipeptidyl peptidase 3 on intensive care unit admission is a predictor of organ dysfunction and mortality.
Biomarker
Cardiac arrest
Circulating dipeptidyl peptidase 3
Intensive care
Mortality
Organ dysfunction
Sepsis
Trauma
Journal
Journal of intensive care
ISSN: 2052-0492
Titre abrégé: J Intensive Care
Pays: England
ID NLM: 101627304
Informations de publication
Date de publication:
24 Aug 2021
24 Aug 2021
Historique:
received:
26
04
2021
accepted:
16
06
2021
entrez:
25
8
2021
pubmed:
26
8
2021
medline:
26
8
2021
Statut:
epublish
Résumé
Our aim was to investigate the prognostic potential of circulating dipeptidyl peptidase 3 (cDPP3) to predict mortality and development of organ dysfunction in a mixed intensive care unit (ICU) population, and for this reason, we analysed prospectively collected admission blood samples from adult ICU patients at four Swedish hospitals. Blood samples were stored in a biobank for later batch analysis. The association of cDPP3 levels with 30-day mortality and Sequential Organ Failure Assessment (SOFA) scores on day two was investigated before and after adjustment for the simplified acute physiology score III (SAPS-3), using multivariable (ordinal) logistic regression. The predictive power of cDPP3 was assessed using the area under the receiver operating characteristic curve (AUROC). Of 1978 included consecutive patients in 1 year (2016), 632 fulfilled the sepsis 3-criteria, 190 were admitted after cardiac arrest, and 157 because of trauma. Admission cDPP3 was independently (of SAPS-3) associated with 30-day mortality with odds ratios of 1.45 (95% confidence interval (CI) 1.28-1.64) in the entire ICU population, 1.30 (95% CI 1.08-1.57) in the sepsis subgroup and 2.28 (95% CI 1.50-3.62) in cardiac arrest. For trauma, there was no clear association. Circulating DPP3 alone was a moderate predictor of 30-day mortality with AUROCs of 0.68, 0.62, and 0.72 in the entire group, the sepsis subgroup, and the cardiac arrest subgroup, respectively. By adding cDPP3 to SAPS-3, AUROC improved for the entire group, the sepsis subgroup, and the cardiac arrest subgroup (p = 0.023). Circulating DPP3 on admission is a SAPS-3 independent prognostic factor of day-two organ dysfunction and 30-day mortality in a mixed ICU population and needs further evaluation.
Sections du résumé
BACKGROUND
BACKGROUND
Our aim was to investigate the prognostic potential of circulating dipeptidyl peptidase 3 (cDPP3) to predict mortality and development of organ dysfunction in a mixed intensive care unit (ICU) population, and for this reason, we analysed prospectively collected admission blood samples from adult ICU patients at four Swedish hospitals. Blood samples were stored in a biobank for later batch analysis. The association of cDPP3 levels with 30-day mortality and Sequential Organ Failure Assessment (SOFA) scores on day two was investigated before and after adjustment for the simplified acute physiology score III (SAPS-3), using multivariable (ordinal) logistic regression. The predictive power of cDPP3 was assessed using the area under the receiver operating characteristic curve (AUROC).
RESULTS
RESULTS
Of 1978 included consecutive patients in 1 year (2016), 632 fulfilled the sepsis 3-criteria, 190 were admitted after cardiac arrest, and 157 because of trauma. Admission cDPP3 was independently (of SAPS-3) associated with 30-day mortality with odds ratios of 1.45 (95% confidence interval (CI) 1.28-1.64) in the entire ICU population, 1.30 (95% CI 1.08-1.57) in the sepsis subgroup and 2.28 (95% CI 1.50-3.62) in cardiac arrest. For trauma, there was no clear association. Circulating DPP3 alone was a moderate predictor of 30-day mortality with AUROCs of 0.68, 0.62, and 0.72 in the entire group, the sepsis subgroup, and the cardiac arrest subgroup, respectively. By adding cDPP3 to SAPS-3, AUROC improved for the entire group, the sepsis subgroup, and the cardiac arrest subgroup (p = 0.023).
CONCLUSION
CONCLUSIONS
Circulating DPP3 on admission is a SAPS-3 independent prognostic factor of day-two organ dysfunction and 30-day mortality in a mixed ICU population and needs further evaluation.
Identifiants
pubmed: 34429159
doi: 10.1186/s40560-021-00561-9
pii: 10.1186/s40560-021-00561-9
pmc: PMC8386069
doi:
Types de publication
Journal Article
Langues
eng
Pagination
52Subventions
Organisme : Government funding of clinicalresearch within the Swedish National Health Services (ALF)
ID : 2019:YF0053
Informations de copyright
© 2021. The Author(s).
Références
Ellis S, Nuenke J. Dipeptidyl arylamidase iii of the pituitary. purification and characterization. J Biol Chem. 1967; 242(20):4623–9.
doi: 10.1016/S0021-9258(18)99503-7
Prajapati S, Chauhan S. Dipeptidyl peptidase III: a multifaceted oligopeptide N-end cutter. FEBS J. 2011; 278(18):3256–76.
doi: 10.1111/j.1742-4658.2011.08275.x
Lee C, Snyder S. Dipeptidyl-aminopeptidase iii of rat brain. selective affinity for enkephalin and angiotensin. J Biol Chem. 1982; 257(20):12043–50.
doi: 10.1016/S0021-9258(18)33674-3
Baršun M, Jajčanin N, Vukelić B, Špoljarić J, Abramić M. Human dipeptidyl peptidase iii acts as a post-proline-cleaving enzyme on endomorphins. Biol Chem. 2007; 388(3):343.
doi: 10.1515/BC.2007.039
Kumar P, Reithofer V, Reisinger M, Wallner S, Pavkov-Keller T, Macheroux P, Gruber K. Substrate complexes of human dipeptidyl peptidase III reveal the mechanism of enzyme inhibition. Sci Rep. 2016; 6:23787.
doi: 10.1038/srep23787
Rehfeld L, Funk E, Jha S, Macheroux P, Melander O, Bergmann A. Novel Methods for the Quantification of Dipeptidyl Peptidase 3 (DPP3) Concentration and Activity in Human Blood Samples. J Appl Lab Med. 2019; 3(6):943–53.
doi: 10.1373/jalm.2018.027995
Deniau B, Rehfeld L, Santos K, Dienelt A, Azibani F, Sadoune M, Kounde P, Samuel J, Tolpannen H, Lassus J, Harjola V, Vodovar N, Bergmann A, Hartmann O, Mebazaa A, Blet A. Circulating dipeptidyl peptidase 3 is a myocardial depressant factor: dipeptidyl peptidase 3 inhibition rapidly and sustainably improves haemodynamics. Eur J Heart Fail. 2020; 22(2):290–9.
doi: 10.1002/ejhf.1601
Takagi K, Blet A, Levy B, Deniau B, Azibani F, Feliot E, Bergmann A, Santos K, Hartmann O, Gayat E, Mebazaa A, Kimmoun A. Circulating dipeptidyl peptidase 3 and alteration in haemodynamics in cardiogenic shock: results from the OptimaCC trial. Eur J Heart Fail. 2020; 22(2):279–86.
doi: 10.1002/ejhf.1600
Bossuyt P, Reitsma J, Bruns D, Gatsonis C, Glasziou P, Irwig L, Lijmer J, Moher D, Rennie D, de Vet H, Kressel H, Rifai N, Golub R, Altman D, Hooft L, Korevaar D, Cohen J, Alonzo T, Altman D, Azuara-Blanco A, Bachmann L, Blume J, Bossuyt P, Boutron I, Bruns D, B?ller H, Buntinx F, Byron S, Chang S, Cohen J, Cooper R, de Groot J, Deeks J, Dendukuri N, Dinnes J, Fleming K, Gatsonis C, Glasziou P, Golub R, Guyatt G, Heneghan C, Hilden J, Hooft L, Horvath R, Hunink M, Hyde C, Ioannidis J, Janes H, Kleijnen J, Knottnerus A, Korevaar A, Kressel H, Lange S, Leeflang M, Lijmer J, Lord S, Lumbreras B, Macaskill P, Magid E, Mallett S, McInnes M, McNeil B, McQueen M, Moher D, Moons K, Morris K, Mustafa R, Obuchowski N, Ochodo E, Onderdonk A, Overbeke J, Pai N, Peeling R, Pepe M, Petersen S, Price C, Ravaud P, Reitsma J, Rennie D, Rifai N, Rutjes A, Schunemann H, Simel D, Simera I, Smidt N, Steyerberg E, Straus S, Summerskill W, Takwoingi Y, Thompson M, van de Bruel A, van Maanen H, Vickers A, Virgili G, Walter S, Weber W, Westwood M, Wilczynski N, Ziegler A. STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies. BMJ. 2015; 351:5527.
Lengquist M, Lundberg O, Spångfors M, Annborn M, Levin H, Friberg H, Frigyesi A. Sepsis is underreported in Swedish intensive care units: A retrospective observational multicentre study. Acta Anaesthesiol Scand. 2020; 64(8):1167–76.
doi: 10.1111/aas.13647
Metnitz P, Moreno R, Almeida E, Jordan B, Bauer P, Campos R, Iapichino G, Edbrooke D, Capuzzo M, Le Gall J. Saps 3–from evaluation of the patient to evaluation of the intensive care unit. part 1: Objectives, methods and cohort description. Intensive Care Med. 2005; 31(10):1336–44. https://doi.org/10.1007/s00134-005-2762-6 .
doi: 10.1007/s00134-005-2762-6
Moreno R, Metnitz P, Almeida E, Jordan B, Bauer P, Campos R, Iapichino G, Edbrooke D, Capuzzo M, Le Gall J. SAPS 3–from evaluation of the patient to evaluation of the intensive care unit. part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med. 2005; 31(10):1345–55. https://doi.org/10.1007/s00134-005-2763-5 .
doi: 10.1007/s00134-005-2763-5
Ferreira F, Bota D, Bross A, Mélot C, Vincent J. Serial evaluation of the SOFA score to predict outcome in critically ill patients. JAMA. 2001; 286(14):1754–8.
doi: 10.1001/jama.286.14.1754
Hosmer D, Lemeshow S, Sturdivant R. Applied Logistic Regression, 3rd. Hoboken: Wiley & Sons Inc.; 2004, pp. 157–68.
Hothorn T, Möst L, Bühlmann P. Most likely transformations. Scand J Stat. 2018; 45(1):110–34. https://doi.org/10.1111/sjos.12291 .
doi: 10.1111/sjos.12291
Fawcett T. An introduction to ROC analysis. Pattern Recognit Lett; 27(8):861–74. https://doi.org/10.1016/j.patrec.2005.10.010. .
DeLong E, DeLong D, Clarke-Pearson D. Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. Biom. 1988; 3:837.
doi: 10.2307/2531595
Dépret F, Amzallag J, Pollina A, Fayolle-Pivot L, Coutrot M, Chaussard M, Santos K, Hartmann O, Jully M, Fratani A, Oueslati H, Cupaciu A, Benyamina M, Guillemet L, Deniau B, Mebazaa A, Gayat E, Farny B, Textoris J, Legrand M. Circulating dipeptidyl peptidase-3 at admission is associated with circulatory failure, acute kidney injury and death in severely ill burn patients. Crit Care. 2020; 24(1):168.
doi: 10.1186/s13054-020-02888-5
Khorashadi M, Beunders R, Pickkers P, Legrand M. Proenkephalin: A New Biomarker for Glomerular Filtration Rate and Acute Kidney Injury. Nephron. 2020; 144(12):655–61.
doi: 10.1159/000509352
Nolan J, Soar J, Cariou A, Cronberg T, Moulaert V, Deakin C, Bottiger B, Friberg H, Sunde K, Sandroni C. European Resuscitation Council and European Society of Intensive Care Medicine Guidelines for Post-resuscitation Care 2015: Section 5 of the European Resuscitation Council Guidelines for Resuscitation 2015. Resuscitation. 2015; 95:202–22.
doi: 10.1016/j.resuscitation.2015.07.018
Holmgren G, Andersson P, Jakobsson A, Frigyesi A. Artificial neural networks improve and simplify intensive care mortality prognostication: a national cohort study of 217,289 first-time intensive care unit admissions. J Intensive Care. 2019; 7:44.
doi: 10.1186/s40560-019-0393-1