, The European Union (HEALTH-F7-305507 HOMAGE) and the European Research Council (Advanced Researcher grant 2011-294713-EPLORE and Proof-of-Concept grant 713601-uPROPHET) and the European Research Area Net for Cardiovascular Diseases (JTC2017-046-PROACT) supported research at the Studies Coordinating Centre, AON 10-216) and by the Societé Française d' Anesthésie-Réanimation

C. -n-deye, . Fauvaux, C. Mebazaa, . Damoisel, and . Payen, The French and European Outcome Registry in Intensive Care Unit Investigators Hôpital Lariboisière (Paris)

H. Louis-;-paris, ). Azoulay, . Moreau, . Jacob, and . Marie,

H. Bichat, ;. Paris, ). Wolf, . Sonneville, and . Bronchard,

, Hôpital Beaujon (Clichy)-I Rennuit, C Paugam

H. Cochin, ;. Paris, ). Mira, . Cariou, and . Tesnières,

H. Bicêtre-(le-kremlin-bicêtre, ). Dufour, N. Anguel, . Guérin, C. Duranteau et al.,

P. Hôpital-raymond,

H. Saint, -. Baudel, and B. Guidet,

L. Hôpital-de, ;. Pitié-salpêtrière, J. Lu, N. Gu, and . Brechot,

. -s-jaber, Y. Pradel, and . Coisel,

P. Hôpital-ambroise,

;. Chu-carémeau, ). Nîmes, L. Lefrant, . Elotmani, . Ayral et al.,

). Hôpital-jean-minjoz-;-besançon, . Pily-flouri, and . Pretalli,

V. -pf-laterre, . Montiel, C. Mf-dujardin, and . Berghe,

H. Wunsch, C. Guerra, A. E. Barnato, D. C. Angus, G. Li et al., Threeyear outcomes for Medicare beneficiaries who survive intensive care, J Am Med Assoc, vol.303, pp.849-56, 2010.

S. P. Keenan, P. Dodek, K. Chan, R. S. Hogg, K. Craib et al., Intensive care unit admission has minimal impact on long-term mortality, Crit Care Med, vol.30, pp.501-508, 2002.

T. A. Williams, G. J. Dobb, J. C. Finn, M. W. Knuiman, E. Geelhoed et al., Determinants of long-term survival after intensive care, Crit Care Med, vol.36, pp.1523-1553, 2008.

S. S. Lim, T. Vos, A. D. Flaxman, G. Danaei, K. Shibuya et al., A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010 : a systematic analysis for the Global Burden of Disease Study, Lancet, vol.380, pp.2224-60, 2010.

D. C. Angus and J. Carlet, Brussels Roundtable Participants: surviving intensive care: a report from the 2002 Brussels Roundtable, pp.368-77, 2002.

S. V. Desai, T. L. Law, and D. M. Needham, Long-term complications of critical care, Crit Care Med, vol.39, pp.371-380, 2011.

D. M. Needham, J. Davidson, H. Cohen, R. O. Hopkins, C. Weinert et al., Improving long-term outcomes after discharge from intensive care unit: report from a stakeholders conference, Crit Care Med, vol.40, pp.502-511, 2012.

E. Gayat, A. Cariou, N. Deye, A. Vieillard-baron, S. Jaber et al., Determinants of long-term outcome in ICU survivors: results from the FROG-ICU study, Crit Care, vol.22, p.8, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01791634

H. Mischak, A. Vlahou, and J. P. Ioannidis, Technical aspects and inter-laboratory variability in native peptide profiling : the CE-MS experience, Clin Biochem, vol.46, pp.432-475, 2013.

A. Latosinska, J. Siwy, H. Mischak, and M. Frantzi, Peptidomics and proteomics based on CE-MS as a robust tool in clinical application: the past, the present, and the bright future, Electrophoresis, vol.40, 2019.

A. Mebazaa, M. C. Casadio, E. Azoulay, B. Guidet, S. Jaber et al., Post-ICU discharge and outcome: rationale and methods of the The French and euRopean Outcome reGistry in Intensive Care Units (FROG-ICU) observational study, BMC Anesthesiol, vol.15, p.143, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01768461

G. L. Sternbach, The Glasgow Coma Scale, J Emerg Med, vol.19, pp.67-71, 2000.

M. E. Charlson, P. Pompei, K. L. Ales, and C. R. Mackenzie, A method of classifying prognostic comorbidity in longitudinal studies: development and validation, J Chron Dis, vol.40, pp.373-83, 1987.

C. E. Roffman, J. Buchanan, and G. T. Allison, Charlson Comorbidity Index. J Physiother, vol.32, p.171, 2016.

L. Ferreira, F. Bota, D. P. Bross, A. Mélot, C. Vincent et al., Serial evaluation of the SOFA score to predict outcome in critically ill patients, J Am Med Assoc, vol.286, pp.1754-1762, 2001.

L. A. Inker, C. H. Schmid, H. Tighiouart, J. H. Eckfeldt, H. I. Feldman et al., Estimating glomerular filtration rate from serum creatinine and cystatin C, N Engl J Med, vol.367, pp.20-29, 2012.

J. A. De-lemos, M. H. Drazner, T. Omland, C. R. Ayers, A. Khera et al., Association of troponin T detected with a highly sensitive assay and cardiac structure and mortality risk in the general population, JAMA, vol.304, pp.2503-2515, 2010.

T. Gassenmaier, S. Buchner, C. Birner, C. G. Jungbauer, M. Resch et al., High-sensitive troponin I in acute cardiac conditions: implications of baseline and sequential measurements for diagnosis of myocardial infarction, Atherosclerosis, vol.222, pp.116-138, 2012.

P. Caironi, R. Latini, J. Struck, O. Hartmann, A. Bergmann et al., Circulating biologically active adrenomedullin (bio-ADM) predicts hemodynamic support requirement and mortality during sepsis, Chest, vol.152, pp.312-332, 2017.

B. Dieplinger and T. Mueller, Soluble ST2 in heart failure, Clin Chim Acta, vol.443, pp.57-70, 2015.

P. Devarajan, Neutrophil gelatinase-associated lipocalin (NGAL), Scand J Clin Lab Invest Suppl, vol.241, pp.89-94, 2008.

H. Mischak, W. Kolch, M. Aivalotis, D. Bouyssie, M. Court et al., Comprehensive human urine standards for comparability and standardization in clinical proteome analysis, Proteomics Clin Appl, vol.4, pp.464-78, 2010.

G. Blom, Statistical estimates and transformed beta-variables, Biom J, vol.3, p.285, 1961.

M. J. Pencina, D. Sr, and E. W. Steyerberg, Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers, Stat Med, vol.30, pp.11-21, 2011.

J. Klein, J. Eales, P. Zürbig, A. Vlahou, H. Mischak et al., Proteasix : a tool for automated and large-scale prediction of proteases involved in naturally occurring peptide generation, Proteomics, vol.13, pp.1077-82, 2013.

A. Casteleiro, M. Klein, J. Stevens, and R. , The Proteasix ontology, J Biomed Semantics, vol.7, p.33, 2016.

I. Göcze, D. Jauch, M. Götz, P. Kennedy, B. Jung et al., Biomarker-guided intervention to prevent acute kidney injury after major surgery. The Prospective Randomized BigpAK Study, Ann Surg, vol.267, pp.1013-1033, 2018.

T. P. Simon, L. Martin, S. Doemming, A. Humbs, C. Bruells et al., Plasma adrenomedullin in critically ill patients with sepsis after major surgery : a pilot study, J Crit Care, vol.38, pp.68-72, 2017.

A. Mebazaa, C. Geven, A. Hollinger, X. Wittebole, B. G. Chousterman et al., Circulating adrenomedullin estimates survival and reversibility of organ failure in sepsis : the prospective observational multinational Adrenomedullin and Outcome in Sepsis and Septic Shoch-1 (AdrenOSS-1) Study, Crit Care, vol.22, p.354, 2019.

M. Lenz, K. A. Krychtiuk, G. Goliasch, K. Distelmaier, J. Wojta et al., N-terminal pro-brain natriuretic peptide and high-sensitivity troponin T exhibit additive prognostic value for the outcome of critically ill patients, Eur Heart J Acute Cardiovasc Care, 2018.

C. Mehta, B. Dara, Y. Mehta, A. Tariq, G. Joby et al., Retrospective study on prognostic importance of serum procalcitonin and aminoterminal pro-brain natriuretic peptide levels as compared to Acute Physiology and Chronic Health Evaluation IV Score on intensive care unit admission in a mixed intensive care unit population, Ann Card Anaesth, vol.19, pp.256-62, 2016.

J. Bauzá-martinez, F. Aletti, B. B. Pinto, V. Ribas, M. A. Odena et al., Proteolysis in septic shock patients: plasma peptidomic patterns are associated with mortality, Br J Anaesth, vol.121, pp.1065-74, 2018.

L. Bergenzaun, H. Öhlin, P. Gudmundsson, J. Düring, R. Willenheimer et al., High-sensitive cardiac troponin T is superior to echocardiography in predicting 1-year mortality in patients with SIRS and shock in intensive care, BMC Anesthesiol, vol.12, p.25, 2012.

M. Bender, M. Stein, E. Uhl, and M. Reinges, Troponin I as an early biomarker of cardiopulmonary parameters within the first 24 hours after nontraumatic subarachnoid hemorrhage in intensive care unit patients, J Intensive Care Med

B. Dieplinger, M. Egger, I. Leitner, F. Firlinger, W. Poelz et al., Interleukin 6, galectin 3, growth differentiation factor 15, and soluble ST2 for mortality prediction in critically ill patients, J Crit Care, vol.34, pp.38-45, 2016.

A. Mahmoodpoor, H. Hamishehkar, V. Fattah, S. Sanaie, P. Arora et al., Urinary versus plasma neutrophil gelatinase-associated lipocalin (NGAL) as a predictor of mortality for acute kidney injury in intensive care unit patients, J Clin Anesth, vol.44, pp.12-19, 2018.

G. Schley, C. Köberle, E. Manuilova, S. Rutz, C. Forster et al., Comparison of plasma and urine biomarker performance in acute kidney injury, PLoS One, vol.10, p.145042, 2015.

K. Mori, H. T. Lee, D. Rapoport, I. R. Drexler, K. Foster et al., Endocytic delivery of lipocalin-siderophore-iron complex rescues the kidney from ischemia-reperfusion injury, J Clin Invest, vol.115, pp.610-631, 2005.

V. Hvidberg, C. Jacobsen, R. K. Strong, J. B. Cowland, S. K. Moestrup et al., The endocytic receptor megalin binds the iron transporting neutrophilgelatinase-associated lipocalin with high affinity and mediates its cellular uptake, FEBS Lett, vol.579, pp.773-780, 2005.

K. M. Schmidt-ott, Neutrophil gelatinase-associated lipocalin as a biomarker of acute kidney injury--where do we stand today?, Nephrol Dial Transplant, vol.26, pp.762-766, 2011.

M. Haase, P. R. Mertens, and A. Haase-fielitz, Renal stress in vivo in real-time--visualised by the NGAL reporter mouse, Nephrol Dial Transplant, vol.26, pp.2109-2120, 2011.

D. Geer, L. Fredrikson, M. Oscarsson, and A. , Amino-terminal pro-brain natriuretic peptide as predictor of outcome in patients admitted to intensive care. A prospective observational study, Eur J Anaesthesiol, vol.29, pp.275-284, 2012.

R. Pieper, C. L. Gatlin, A. M. Mcgrath, A. J. Makusky, M. Mondal et al., Characterization of the human urinary proteome : a method for high-resolution display of urinary proteins on two-dimensional electrophoresis gels with a yield of nearly 1400 distinct protein spots, Proteomics, vol.4, pp.1159-74, 2004.

J. J. Coon, P. Zürbig, M. Dakna, A. F. Dominiczak, S. Decramer et al., CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics, Proteomics Clin Appl, vol.2, pp.964-73, 2008.

D. M. Good, P. Zürbig, A. Argilés, H. W. Bauer, G. Behrens et al., Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease, Mol Cell Proteomics, vol.9, pp.2424-2461, 2010.

C. Delles, E. Schiffer, M. C. Von-zur, K. Peter, P. Rossing et al., Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals, J Hypertens, vol.28, pp.2316-2338, 2010.

Y. M. Gu, L. Thijs, Y. P. Liu, Z. Y. Zhang, J. Jacobs et al., The urinary proteome as correlate and predictor of renal function in a population study, Nephrol Dial Transplant, vol.29, pp.2260-2268, 2014.

C. Pontillo, Z. Y. Zhang, J. P. Schanstra, L. Jacobs, P. Zürbig et al., Prediction of chronic kidney disease stage 3 by CKD273, a urinary proteomic biomarker, KI Reports, vol.2, pp.1066-75, 2017.

T. Kuznetsova, H. Mischak, W. Mullen, and J. A. Staessen, Urinary proteome analysis in hypertensive patients with left ventricular diastolic dysfunction, Eur Heart J, vol.33, pp.2342-50, 2012.

Z. Y. Zhang, E. Nkuipou-kenfack, W. Y. Yang, F. F. Wei, N. Cauwenberghs et al., Epidemiologic observations guiding clinical application of the HF1 urinary peptidomic marker of diastolic left ventricular dysfunction, J Am Soc Hypertens, vol.12, pp.438-485, 2018.

E. Critselis, A. Vlahou, V. S. Stel, and R. L. Morton, Cost-effectiveness of screening type 2 diabetes patients for chronic kidney disease progression with the CKD273 urinary peptide classifier as compared to urinary albumin excretion, Nephrol Dial Transplant, vol.33, pp.441-450, 2018.

M. Lindhardt, F. Persson, G. Currie, C. Pontillo, J. Beige et al., Proteomic prediction and renin angiotensin aldosterone system inhibition prevention of early diabetic nephropathy in type 2 diabetic patients with normoalbuminuria (PRIORITY) : essential study design and rationale of a randomised clinical multicentre trial, Br Med J Open, p.10310, 2016.

N. Tofte, M. Lindhardt, K. Adamova, J. Beige, J. Beulens et al., Characteristics of high-and low-risk individuals in the PRIORITY study: urinary proteomics and mineralocorticoid receptor antagonism for prevention of diabetic nephropathy in type 2 diabetes, Diabet Med, vol.35, pp.1375-82, 2018.

F. Zannad, What is measured by cardiac fibrosis biomarkers and imaging? Circ Heart Fail, vol.7, pp.239-281, 2014.

H. Pei, W. Wang, D. Zhao, L. Wang, G. H. Su et al., The use of novel nonsteroidal mineralocorticoid receptor antagonist finerenone for the treatment of chronic heart failure. A systematic review and meta-analysis, Medicine (Baltimore), vol.97, p.254, 2018.

R. M. Burke, J. K. Lighthouse, D. M. Mickelsen, and E. M. Small, Sacubitril/valsartan decreases cardiac fibrosis in left ventricle pressure overload by restoring PKG signaling in cardiac fibroblasts, Circ Heart Fail, vol.12, 2019.

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