Evidence map›Paper›PMID 41586891›Full record

ReviewIntensive care medicine2026

The next frontier in sepsis: connected ICU data for real-world clinical decision making.

Ricardo Simon Carbajo, Julia Palma, Ignacio Martin-Loeches

Abstract readReview
In one paragraph

Review in Intensive care medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. ASP-COMPLEX: redefining antimicrobial stewardship to improve outcomes in high-risk patients with severe infections.Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia · 2026
    Review
  2. Clarithromycin for treating sepsis in adults.The Cochrane database of systematic reviews · 2026
    Article
  3. 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

3 authors.

Ricardo Simon CarbajoCeADAR: Ireland's Centre for AI, University College Dublin, Dublin, Ireland.
Julia PalmaCeADAR: Ireland's Centre for AI, University College Dublin, Dublin, Ireland.
Ignacio Martin-LoechesDepartment of Intensive Care Medicine, Multidisciplinary Intensive Care Research Organization (MICRO), St James's Hospital, Dublin, Ireland. drmartinloeches@gmail.com.ORCID 0000-0002-5834-4063

Funding

HORIZON EUROPE Framework Programme 101167778
6 · The paper itself

Abstract

backgroundFragmented and locally siloed data limit progress in critical care research and education. The European Health Data Space (EHDS) proposes a federated, privacy-preserving framework to connect intensive care units (ICUs) across Europe. Sepsis is an ideal model condition given its heterogeneity, high mortality, and persistent gaps in standardization and outcomes.

objectivesThis narrative review explores how federated and synthetic data can transform sepsis research, quality improvement, and education within the EHDS. It aims to outline both the opportunities and practical limitations of building a European-wide, learning ICU network.

methodsRecent literature, European policy documents, and federated data initiatives were reviewed to synthesize conceptual, technical, and ethical aspects of implementing federated learning in intensive care.

resultsFederated infrastructures enable joint analysis of distributed ICU data without sharing patient-level information, supporting benchmarking and surveillance while maintaining privacy. Synthetic data add value for simulation, algorithm testing, and training but cannot replace real-world complexity. Major barriers include data harmonization, interoperability, and governance. Ongoing projects demonstrate that transparent, secure frameworks can make responsible data sharing feasible.

conclusionsThe EHDS offers a realistic foundation for connecting ICUs across Europe through ethically governed federated systems. Combining clinical, engineering, and data science expertise will be key to transforming fragmented ICU information into shared intelligence that supports sepsis research, education, and personalized critical care.

Indexed as

Clinical Decision-MakingIntensive Care UnitsSepsisEuropeFederated LearningHumansInformation DisseminationArtificial intelligenceData governanceEuropean Health Data SpaceFederated dataIntensive care unitSepsisSynthetic data

Identifiers

PMID41586891
PMCPMC12971731

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.