Evidence map›Paper›PMID 39860355›Full record

ArticleJournal of clinical medicine2025

Machine Learning Models for the Early Real-Time Prediction of Deterioration in Intensive Care Units-A Novel Approach to the Early Identification of High-Risk Patients.

Dominik Thiele, Reitze Rodseth, Richard Friedland, Fabian Berger, Chris Mathew, Caroline Maslo, Vanessa Moll, Christoph Leithner, Christian Storm, Alexander Krannich and 1 more

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. From Narrative to Navigation-A Translational Roadmap for AI-enabled Early Sepsis Prediction: Comment on Shanmugam et al.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025
    Article
  4. Review
  5. Review
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

11 authors.

Dominik ThieleDepartment of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany.
Reitze RodsethNetcare Limited, Johannesburg 2196, South Africa.ORCID 0000-0002-3779-7805
Richard FriedlandNetcare Limited, Johannesburg 2196, South Africa.
Fabian BergerNetcare Limited, Johannesburg 2196, South Africa.
Chris MathewNetcare Limited, Johannesburg 2196, South Africa.ORCID 0009-0003-9164-5225
Caroline MasloNetcare Limited, Johannesburg 2196, South Africa.ORCID 0000-0002-0145-3672
Vanessa MollDepartment of Anesthesiology, Division of Critical Care Medicine, University of Minnesota School of Medicine, Minneapolis, MN 55455, USA.
Christoph LeithnerDepartment of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany.
Christian StormTCC Analytics, Telehealth Competence Center (TCC) GmbH, 22083 Hamburg, Germany.
Alexander KrannichTCC Analytics, Telehealth Competence Center (TCC) GmbH, 22083 Hamburg, Germany.
Jens NeeDepartment of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, 22083 Berlin, Germany.ORCID 0000-0001-9888-4358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

deteriorationhigh-risk patientsICUmachine learningreal-time prediction

Identifiers

PMID39860355
PMCPMC11766095

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.