Development and Validation of a Predictive Score for Surgical Site Infections (SPRED)
Primary Purpose
Colon or Colorectal Resection, Partial or Total Gastrectomy, Pancreaticoduodenectomy
Status
Recruiting
Phase
Phase 3
Locations
France
Study Type
Interventional
Intervention
Peripheral venous blood samples
Sponsored by
About this trial
This is an interventional other trial for Colon or Colorectal Resection
Eligibility Criteria
Inclusion Criteria:
Patients will be included:
- Aged 18 and over
- Having undergone elective major digestive surgery:
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
- Having expressed their non-opposition to participate in the study
- Being affiliated to a French health insurance
Exclusion Criteria:
Patients with the following criteria will not be included:
- Aged under 18
- Having an ASA 4 or more, in palliative care
- Having an expected duration of hospitalization < 24 hours
- Not speaking French, illiterate patient
- Having expressed their opposition to participate in the study
- Current pregnancy or breastfeeding
- Absence of affiliation to social security plan
- Being deprived of liberty or under guardianship
Sites / Locations
- La pitiè Salpâtrière Hospital
- Saint Antoine HospitalRecruiting
- Saint Joseph Hospital
- FOCH HospitalRecruiting
Arms of the Study
Arm 1
Arm Type
Other
Arm Label
Patients with major elective digestive surgery
Arm Description
The size of the cohort is 240 patients Population: Patients with major elective digestive surgery (eg, colon or colorectal resection, partial or total gastrectomy, pancreaticoduodenectomy, hepatectomy).
Outcomes
Primary Outcome Measures
Preoperative Prediction Score Performance of Surgical Site Infectious Complications
Primary Endpoint:
Preoperative Prediction Score Performance of Surgical Site Infectious Complications Defined as Superficial, Deep and Organ Surgical Site Infection as per CDC 2021 definition within 30 days post-operatively.
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.
Secondary Outcome Measures
Performance of Preoperative Lung Infection Prediction Score
defined by prescribing antibiotics with one or more of the following: sputum sputumnew or changed, new or changed lung opacities on chest x-ray, fever > 38°C, leukocytes >12 × 109 /L within 30 postoperative days.
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.
Performance of the preoperative prediction score for urinary tract infections
Performance of the preoperative prediction score for urinary tract infections (according to the definition of the CDC - 2021) within 30 days post-operative.
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: The score ranges from 0.5 to 1 where 1 is the best score and 0.5 means the model is as good as random.
Performance of the post-operative prediction score (D1) of infectious surgical site complications
Performance of the post-operative prediction score (D1) of infectious surgical site complications defined as superficial, deep and organ infection of the surgical site according to the CDC 2021 definition within within 30 days post-operative.
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.
Intra-hospital mortality assessed from patient medical records
It will be assessed from patient medical records
Length of hospital stay
It will be assessed from patient medical records
Cost of stay (GHS)
Data ( GHS, GHM, cost) will be collected upon the discharge of the patient from the hospital via the medical information departments (DIM) based on the PMSI of each establishment.
The score results
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).
Full Information
NCT ID
NCT05523713
First Posted
August 5, 2022
Last Updated
November 21, 2022
Sponsor
Hopital Foch
Collaborators
surge2surgery
1. Study Identification
Unique Protocol Identification Number
NCT05523713
Brief Title
Development and Validation of a Predictive Score for Surgical Site Infections
Acronym
SPRED
Official Title
Development and Validation of a Predictive Score for Surgical Site Infections (SSI): a Prospective Preoperative Trial in Major Digestive Surgery
Study Type
Interventional
2. Study Status
Record Verification Date
November 2022
Overall Recruitment Status
Recruiting
Study Start Date
October 6, 2022 (Actual)
Primary Completion Date
December 1, 2023 (Anticipated)
Study Completion Date
December 1, 2023 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Hopital Foch
Collaborators
surge2surgery
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes
5. Study Description
Brief Summary
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.
Detailed Description
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.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Colon or Colorectal Resection, Partial or Total Gastrectomy, Pancreaticoduodenectomy, Hepatectomy
7. Study Design
Primary Purpose
Other
Study Phase
Phase 3
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
240 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Patients with major elective digestive surgery
Arm Type
Other
Arm Description
The size of the cohort is 240 patients
Population: Patients with major elective digestive surgery (eg, colon or colorectal resection, partial or total gastrectomy, pancreaticoduodenectomy, hepatectomy).
Intervention Type
Biological
Intervention Name(s)
Peripheral venous blood samples
Intervention Description
10 ml in a sodium heparin tube and 5 ml in an EDTA tube
Primary Outcome Measure Information:
Title
Preoperative Prediction Score Performance of Surgical Site Infectious Complications
Description
Primary Endpoint:
Preoperative Prediction Score Performance of Surgical Site Infectious Complications Defined as Superficial, Deep and Organ Surgical Site Infection as per CDC 2021 definition within 30 days post-operatively.
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
Secondary Outcome Measure Information:
Title
Performance of Preoperative Lung Infection Prediction Score
Description
defined by prescribing antibiotics with one or more of the following: sputum sputumnew or changed, new or changed lung opacities on chest x-ray, fever > 38°C, leukocytes >12 × 109 /L within 30 postoperative days.
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
Title
Performance of the preoperative prediction score for urinary tract infections
Description
Performance of the preoperative prediction score for urinary tract infections (according to the definition of the CDC - 2021) within 30 days post-operative.
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: The 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
Title
Performance of the post-operative prediction score (D1) of infectious surgical site complications
Description
Performance of the post-operative prediction score (D1) of infectious surgical site complications defined as superficial, deep and organ infection of the surgical site according to the CDC 2021 definition within within 30 days post-operative.
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
Title
Intra-hospital mortality assessed from patient medical records
Description
It will be assessed from patient medical records
Time Frame
30 days
Title
Length of hospital stay
Description
It will be assessed from patient medical records
Time Frame
30 days
Title
Cost of stay (GHS)
Description
Data ( GHS, GHM, cost) will be collected upon the discharge of the patient from the hospital via the medical information departments (DIM) based on the PMSI of each establishment.
Time Frame
30 days
Title
The score results
Description
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
10. Eligibility
Sex
All
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
99 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Patients will be included:
Aged 18 and over
Having undergone elective major digestive surgery:
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
Having expressed their non-opposition to participate in the study
Being affiliated to a French health insurance
Exclusion Criteria:
Patients with the following criteria will not be included:
Aged under 18
Having an ASA 4 or more, in palliative care
Having an expected duration of hospitalization < 24 hours
Not speaking French, illiterate patient
Having expressed their opposition to participate in the study
Current pregnancy or breastfeeding
Absence of affiliation to social security plan
Being deprived of liberty or under guardianship
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Morgan LE GUEN
Phone
00 33 1 46 25 24 33
Email
m.leguen@hopital-foch.com
First Name & Middle Initial & Last Name or Official Title & Degree
FRANCK VERDONK
Phone
00 33 6 77 78 38 77
Email
fverdonk@surge2surgery.com
Facility Information:
Facility Name
La pitiè Salpâtrière Hospital
City
Paris
Country
France
Individual Site Status
Not yet recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Antoine Monsel, MD
Facility Name
Saint Antoine Hospital
City
Paris
Country
France
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Franck VERDONK, MD
Facility Name
Saint Joseph Hospital
City
Paris
Country
France
Individual Site Status
Not yet recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Pascal Alfonsi, MD
Facility Name
FOCH Hospital
City
Suresnes
Country
France
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Morgan LE GUEN, MD
12. IPD Sharing Statement
Plan to Share IPD
No
Citations:
PubMed Identifier
30229870
Citation
Storesund A, Haugen AS, Hjortas M, Nortvedt MW, Flaatten H, Eide GE, Boermeester MA, Sevdalis N, Softeland E. Accuracy of surgical complication rate estimation using ICD-10 codes. Br J Surg. 2019 Feb;106(3):236-244. doi: 10.1002/bjs.10985. Epub 2018 Sep 18.
Results Reference
background
PubMed Identifier
21817889
Citation
Hawn MT, Vick CC, Richman J, Holman W, Deierhoi RJ, Graham LA, Henderson WG, Itani KM. Surgical site infection prevention: time to move beyond the surgical care improvement program. Ann Surg. 2011 Sep;254(3):494-9; discussion 499-501. doi: 10.1097/SLA.0b013e31822c6929.
Results Reference
background
PubMed Identifier
28816846
Citation
Gaudilliere B, Angst MS, Hotchkiss RS. Deep Immune Profiling in Trauma and Sepsis: Flow Is the Way to Go! Crit Care Med. 2017 Sep;45(9):1577-1578. doi: 10.1097/CCM.0000000000002594. No abstract available.
Results Reference
background
PubMed Identifier
20643302
Citation
Zhu X, Herrera G, Ochoa JB. Immunosupression and infection after major surgery: a nutritional deficiency. Crit Care Clin. 2010 Jul;26(3):491-500, ix. doi: 10.1016/j.ccc.2010.04.004.
Results Reference
background
PubMed Identifier
25253674
Citation
Gaudilliere B, Fragiadakis GK, Bruggner RV, Nicolau M, Finck R, Tingle M, Silva J, Ganio EA, Yeh CG, Maloney WJ, Huddleston JI, Goodman SB, Davis MM, Bendall SC, Fantl WJ, Angst MS, Nolan GP. Clinical recovery from surgery correlates with single-cell immune signatures. Sci Transl Med. 2014 Sep 24;6(255):255ra131. doi: 10.1126/scitranslmed.3009701.
Results Reference
background
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Development and Validation of a Predictive Score for Surgical Site Infections
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