Details

Autor(en) / Beteiligte

• Serpa Neto, Ary
• Bos, Lieuwe D
• Campos, Pedro P.Z.A
• Hemmes, Sabrine N.T
• Bluth, Thomas
• Calfee, Carolyn S
• Ferner, Marion
• Güldner, Andreas
• Hollmann, Markus W
• India, Inmaculada
• Kiss, Thomas
• Laufenberg-Feldmann, Rita
• Sprung, Juraj
• Sulemanji, Demet
• Unzueta, Carmen
• Vidal Melo, Marcos F
• Weingarten, Toby N
• Tuip-de Boer, Anita M
• Pelosi, Paolo
• Gama de Abreu, Marcelo
• Schultz, Marcus J

Titel

Association between pre-operative biological phenotypes and postoperative pulmonary complications: An unbiased cluster analysis

Ist Teil von

• European journal of anaesthesiology, 2018-09, Vol.35 (9), p.702-709

Ort / Verlag

England: European Society of Anaesthesiology

Erscheinungsjahr

2018

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• BACKGROUNDBiological phenotypes have been identified within several heterogeneous pulmonary diseases, with potential therapeutic consequences. OBJECTIVETo assess whether distinct biological phenotypes exist within surgical patients, and whether development of postoperative pulmonary complications (PPCs) and subsequent dependence of intra-operative positive end-expiratory pressure (PEEP) differ between such phenotypes. SETTINGOperating rooms of six hospitals in Europe and USA. DESIGNSecondary analysis of the ‘PROtective Ventilation with HIgh or LOw PEEP’ trial. PATIENTSAdult patients scheduled for abdominal surgery who are at risk of PPCs. INTERVENTIONSMeasurement of pre-operative concentrations of seven plasma biomarkers associated with inflammation and lung injury. MAIN OUTCOME MEASURESWe applied unbiased cluster analysis to identify biological phenotypes. We then compared the proportion of patients developing PPCs within each phenotype, and associations between intra-operative PEEP levels and development of PPCs among phenotypes. RESULTSIn total, 242 patients were included. Unbiased cluster analysis clustered the patients within two biological phenotypes. Patients with phenotype 1 had lower plasma concentrations of TNF-α (3.8 [2.4 to 5.9] vs. 10.2 [8.0 to 12.1] pg ml; P < 0.001), IL-6 (2.3 [1.5 to 4.0] vs. 4.0 [2.9 to 6.5] pg ml; P < 0.001) and IL-8 (4.7 [3.1 to 8.1] vs. 8.1 [6.0 to 13.9] pg ml; P < 0.001). Phenotype 2 patients had the highest incidence of PPC (69.8 vs. 34.2% in type 1; P < 0.001). There was no interaction between phenotype and PEEP level for the development of PPCs (43.2% in high PEEP vs. 25.6% in low PEEP in phenotype 1, and 73.6% in high PEEP and 65.7% in low PEEP in phenotype 2; P for interaction = 0.503). CONCLUSIONPatients at risk of PPCs and undergoing open abdominal surgery can be clustered based on pre-operative plasma biomarker concentrations. The two identified phenotypes have different incidences of PPCs. Biologic phenotyping could be useful in future randomised controlled trials of intra-operative ventilation. TRIAL REGISTRATIONThe PROtective Ventilation with HIgh or LOw PEEP trial, including the substudy from which data were used for the present analysis, was registered at ClinicalTrials.gov (NCT01441791).