Evidence map›Paper›PMID 41598714›Full record

ArticleJournal of clinical medicine2026

Machine Learning Model for Sepsis Prediction in Prolonged and Chronic Critical Illness: Development and Validation Using Retrospective Real-World ICU Data.

Mikhail Ya Yadgarov, Olga Yu Rebrova, Levan B Berikashvili, Petr A Polyakov, Kristina K Kadantseva, Alexey A Yakovlev, Andrey V Grechko, Valery V Likhvantsev

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2026. 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

8 authors.

Mikhail Ya YadgarovFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.
Olga Yu RebrovaPirogov Russian National Research Medical University, Moscow 117997, Russia.ORCID 0000-0002-6733-0958
Levan B BerikashviliFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.
Petr A PolyakovFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.ORCID 0009-0009-6185-349X
Kristina K KadantsevaFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.
Alexey A YakovlevFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.
Andrey V GrechkoFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.
Valery V LikhvantsevFederal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow 107031, Russia.ORCID 0000-0002-5442-6950

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

chronic critical illnessintensive care unitmachine learningreal-world dataright-aligned modelsepsis predictionSHAP

Identifiers

PMID41598714
PMCPMC12841784

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.