Evidence map›Paper›PMID 40340157›Full record

ArticleBritish journal of anaesthesia2025

Deep learning model to identify and validate hypotension endotypes in surgical and critically ill patients. Comment on Br J Anaesth 2025; 134: 308-16.

Michaela Hardt, Michael Koeppen

Abstract readLetter
In one paragraph

Article in British journal of anaesthesia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Michaela HardtMedical Data Integration Center (meDIC), University Hospital of Tübingen, Tübingen, Germany.
Michael KoeppenDepartment of Anesthesiology and Intensive Care Medicine, University Hospital of Tübingen, Tübingen, Germany. Electronic address: michael.koeppen@med.uni-tuebingen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

deep learninghaemodynamic managementhypotensionmachine learningmethodological transparency

Identifiers

PMID40340157
PMCPMC12597442

What OpenQuestion holds

Textmetadata
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.