Evidence map›Paper›PMID 41090142›Full record

ArticleFrontiers in medicine2025

From

Daniele Roberto Giacobbe, Cristina Marelli, Marco Muccio, Sabrina Guastavino, Ylenia Murgia, Sara Mora, Alessio Signori, Nicola Rosso, Antonio Vena, Mauro Giacomini and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. A Theoretical Framework forInfection and drug resistance · 2026
    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

13 authors.

Daniele Roberto GiacobbeUO Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Cristina MarelliOncostat, CESP, Inserm U1018, Université Paris-Saclay, Labeled Ligue Contre le Cancer, Gustave Roussy, Villejuif, France.
Marco MuccioUO Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Sabrina GuastavinoDepartment of Mathematics (DIMA), University of Genoa, Genoa, Italy.
Ylenia MurgiaDepartment of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy.
Sara MoraUO Information and Communication Technologies, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Alessio SignoriSection of Biostatistics, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Nicola RossoUO Information and Communication Technologies, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Antonio VenaUO Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Mauro GiacominiDepartment of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy.
Cristina CampiDepartment of Mathematics (DIMA), University of Genoa, Genoa, Italy.
Michele PianaDepartment of Mathematics (DIMA), University of Genoa, Genoa, Italy.
Matteo BassettiUO Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of artificial intelligence (AI) and machine learning (ML) is progressively influencing clinical reasoning in infectious diseases, particularly in the management of septic shock where timely empirical antimicrobial therapy is crucial. In this perspective, we discuss how AI and ML approaches intersect with established clinical decision-making processes through two examples from our research and practice: prediction of bloodstream infection by carbapenem-resistant

Indexed as

artificial intelligencecarbapenem resistanceinvasive candidiasismachine learningprediction

Identifiers

PMID41090142
PMCPMC12515821

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.