Peripheral venous blood samples
Biological10 ml in a sodium heparin tube and 5 ml in an EDTA tube
NCT Number: NCT05523713
More than 8 millions surgical interventions are carried out each year in France. Postoperative complications, in particular infectious, can occur in 10 to 60% of cases and are the cause of postoperative revision in 30% of cases, an increase in mortality, length of stay, readmissions and lead to significant additional socio-economic costs. Currently, improvements in surgical practices have not reduced the incidence of surgical site complications. In this context, the development of predictive scores for the risk of post-operative complication becomes urgent in order to implement new interventions (pre-habilitation) or to modify surgical decisions (timing, approach) in order to reduce the risk of complications before surgery. Several recent studies highlights the importance of the immune response in postoperative prognosis. In particular, an imbalance between the adaptive and innate response involving MDSCs has been demonstrated in patients with postoperative complications.Thanks to new techniques for analyzing the immune system, in-depth analysis of the immune system before surgery is a very promising approach aimed at identifying predictive biomarkers of postoperative prognosis.
Our team has developed and patented a multivariate model integrating mass cytometry data, proteomics and clinical data collected before surgery to accurately predict the occurrence of a surgical site complication (AUC = 0.94, p<10e-7) in a monocentric cohort of 43 patients to major abdominal surgery (Stanford University).
The objective of the present study is to generalize and validate this preoperative predictive score of infectious complications of the surgical site in the 30 days following major digestive surgery on a larger workforce within a multicenter cohort and to validate this score at using a machine learning method.
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Notify Me18 year–99 year
All sexes
Interventional
Not applicable
La pitiè Salpâtrière Hospital, Paris, France
Research hypothesis and expected impact:
Postoperative complications are frequent and associated with excess mortality and increased costs for the health system. But, it is possible to avoid a significant number of these complications through prehabilitation programs, in particular to prepare patients at risk, and to reduce these postoperative events by 30%. However, it is currently not possible to predict, before surgery, which patients are at risk of developing a complication. Current predictive clinical scores such as the one developed by the American College of Surgeons are unsatisfactory (AUC = 68%).
This study will be a reference study to define the groups of patients at risk of complications in order to develop, in a second step, personalized patient pathways in order to optimize their health before surgery and thus improve post-operative results.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Patients will be included:
Major surgery defined according to the recent recommendations of the European Surgical Association - PMID: 32172309 by a rate of infectious or cognitive complications between 20 and 30% according to the ACS risk calculator
Exclusion criteria
Patients with the following criteria will not be included:
10 ml in a sodium heparin tube and 5 ml in an EDTA tube
Time frame: 30 days
Defined as superficial or deep surgical site infection and organ as defined by CDC 2021.
The performance of the score will be evaluate based on the F1 score criterion and the AUROC.
F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Defined as superficial or deep surgical site infection and organ as defined by CDC 2021.
The performance of the score will be evaluate based on the F1 score criterion and the AUROC.
F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Defined by the prescription of antibiotics with one or more of the following elements: new or altered sputum, new or altered lung opacities on chest X-ray, fever > 38°C, leukocytes >12 × 109 /L.
The performance of the score will be evaluate based on the F1 score criterion and the AUROC.
F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
As defined by CDC 2021.
The performance of the score will be evaluate based on the F1 score criterion and the AUROC.
F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Defined according to Sepsis-3 criteria: Sepsis-related Organ Failure Assessment score ≥ 2, persistent hypotension requiring vasopressors to maintain mean arterial pressure ≥ 65 mmHg and serum lactate > 2 mmol/L despite adequate volume resuscitation.
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Defined as arrhythmia, cardiac arrest, acute coronary syndrome and acute heart failure.
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Confirmed by imaging (angioscanner for pulmonary embolism and echo-doppler for deep vein thrombosis).
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Defined by an increase of creatinine > 1.5 times of the baseline value or diuresis < 0.5 ml/kg/h for 6 to 12 hours.
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Requiring surgical intervention or blood transfusion.
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Defined as failure to resume transit within 72 hours of surgery.
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Defined as disturbed attention and disturbed consciousness, with cognitive impairment not explained by a pre-existing neurological pathology.
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Based on the Comprehensive Complication Index (CCI), with a severity threshold at CCI ≥ 20.
The performance of the score will be evaluate based on the evaluation of the F1 score criterion and the AUROC. F1: score ranges from 0 to 1, where 0 is the worst and 1 is the best possible score.
AUROC: Score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Time frame: 30 days
Assessed from patient medical records
Time frame: 30 days
Assessed from patient medical records
Time frame: 30 days
From Groupe Homogène de Séjours ( GHS) collected in the medical information departments (DIM) based on the Programme de médicalisation des systèmes d'information (PMSI) of each establishment.
Time frame: 30 days
The score is calculated using a machine learning method integrating immune, plasma protein and clinical data. The aim is to validate and generalize the score result (AUC = 0,94, p<10e-7) of a multivariate model already developed in a monocentric cohort of 43 patients undergoing major abdominal surgery (Stanford University).
Time frame: 30 days
An intermediate analysis will be performed after 165 inclusions (55% of the total cohort). The cohort will be randomized into training and validation cohorts. We will use a cross-validation training scheme on 135 patients. The trained algorithm will use logistic regression techniques including L1 and L2 regularization (Lasso and Elastic Net).
Hopital Foch
Other
Development and Validation of a Predictive Score for Surgical Site Infections (SSI): a Prospective Preoperative Trial in Major Digestive Surgery
Acronym: SPRED
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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