Evidence map›Paper›PMID 34545029›Full record

ReviewCurrent opinion in critical care2021

Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes.

Franck Verdonk, Jakob Einhaus, Amy S Tsai, Julien Hedou, Benjamin Choisy, Dyani Gaudilliere, Cindy Kin, Nima Aghaeepour, Martin S Angst, Brice Gaudilliere

Abstract readReview
In one paragraph

Review in Current opinion in critical care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Inflammatory Stewardship-A Perspective for Active Management of Acute Inflammation.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Observational
  15. Article
  16. Review
  17. Review
  18. Observational
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Franck VerdonkDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
Jakob EinhausDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
Amy S TsaiDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
Julien HedouDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
Benjamin ChoisyDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
Dyani GaudilliereDepartment of Surgery, Stanford University School of Medicine.
Cindy KinDepartment of Surgery, Stanford University School of Medicine.
Nima AghaeepourDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
Martin S AngstDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
Brice GaudilliereDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.

Funding

SPRINT: Signature for Pain Recovery IN TeensR61NS114926 · NINDS · STANFORD UNIVERSITY · PI SIMONS, LAURA E · 2019 to 2019
$5.4M
Dietary Modulation of Neuroinflammation in Age-Related Memory DisordersR01AG058417 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SLOAN, RICHARD P, SMALL, SCOTT A · 2018 to 2022
$4.2M
SPRINT: Signature for Pain Recovery IN TeensR33NS114926 · NINDS · STANFORD UNIVERSITY · PI SIMONS, LAURA E · 2023 to 2024
$4.1M
Building a Platform for Precision Anesthesia for the Geriatric Surgical PatientR33AG065744 · NIA · STANFORD UNIVERSITY · PI DROVER, DAVID RAYMOND · 2022 to 2024
$2.3M
Machine Learning for Integrative Modeling of the Immune System in Clinical SettingsR35GM138353 · NIGMS · STANFORD UNIVERSITY · PI AGHAEEPOUR, NIMA · 2020 to 2024
$2.2M
Harnessing the human monocyte system to improve surgical recoveryR35GM137936 · NIGMS · STANFORD UNIVERSITY · PI GAUDILLIERE, BRICE · 2020 to 2024
$2.0M
Building a Platform for Precision Anesthesia for the Geriatric Surgical PatientR21AG065744 · NIA · STANFORD UNIVERSITY · PI DROVER, DAVID RAYMOND · 2020 to 2020
$423k
NIA NIH HHS R01 AG058417NIA NIH HHS R21 AG065744NIA NIH HHS R33 AG065744NIGMS NIH HHS R35 GM137936NIGMS NIH HHS R35 GM138353NINDS NIH HHS R33 NS114926NINDS NIH HHS R61 NS114926
6 · The paper itself

Abstract

purpose of reviewPostoperative complications including infections, cognitive impairment, and protracted recovery occur in one-third of the 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on our healthcare system. However, the accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain as major clinical challenges. RECENT

findingsAlthough multifactorial in origin, the dysregulation of immunological mechanisms that occur in response to surgical trauma is a key determinant of postoperative complications. Prior research, primarily focusing on inflammatory plasma markers, has provided important clues regarding their pathogenesis. However, the recent advent of high-content, single-cell transcriptomic, and proteomic technologies has considerably improved our ability to characterize the immune response to surgery, thereby providing new means to understand the immunological basis of postoperative complications and to identify prognostic biological signatures. SUMMARY: The comprehensive and single-cell characterization of the human immune response to surgery has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers, ultimately providing patients and surgeons with actionable information to improve surgical outcomes. Although recent studies have generated a wealth of knowledge, laying the foundation for a single-cell atlas of the human immune response to surgery, larger-scale multiomic studies are required to derive robust, scalable, and sufficiently powerful models to accurately predict the risk of postoperative complications in individual patients.

Indexed as

Postoperative ComplicationsProteomicsBiomarkersHumansImmunityPrognosisBiomarkers

Identifiers

PMID34545029
PMCPMC8585713

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.