Evidence map›Paper›PMID 41794732›Full record

ReviewCritical care (London, England)2026

Mechanical ventilation in ARDS: navigating the fine line with real-time monitoring.

Lorenzo Ball, Giulia Benzi, Denise Battaglini, Chiara Robba, Nicolò Patroniti, Pedro L Silva, John J Marini, Patrícia Rieken Macedo Rocco

Abstract readReview
In one paragraph

Review in Critical care (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Lorenzo BallDipartimento di Scienze Chirurgiche e Diagnostiche Integrate, Università degli Studi di Genova, Genova, Italy. lorenzo.ball@unige.it.
Giulia BenziDipartimento di Scienze Chirurgiche e Diagnostiche Integrate, Università degli Studi di Genova, Genova, Italy.
Denise BattagliniDipartimento di Scienze Chirurgiche e Diagnostiche Integrate, Università degli Studi di Genova, Genova, Italy.
Chiara RobbaDipartimento di Scienze Chirurgiche e Diagnostiche Integrate, Università degli Studi di Genova, Genova, Italy.
Nicolò PatronitiDipartimento di Scienze Chirurgiche e Diagnostiche Integrate, Università degli Studi di Genova, Genova, Italy.
Pedro L SilvaLaboratory of Pulmonary Investigation, Carlos Chagas Filho Institute of Biophysics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
John J MariniDepartment of Pulmonary and Critical Care Medicine, University of Minnesota, Minneapolis, St Paul, MN, USA.
Patrícia Rieken Macedo RoccoLaboratory of Pulmonary Investigation, Carlos Chagas Filho Institute of Biophysics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil. prmrocco@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute respiratory distress syndrome (ARDS) is a heterogeneous and rapidly evolving condition in which mechanical ventilation must balance adequate gas exchange with lung protection and hemodynamic stability. Over the past decades, the traditional one-size-fits-all approach to ARDS management has been progressively replaced by precision strategies guided by patient-specific physiological characteristics. However, conventional ventilatory and hemodynamic management continues to rely on intermittent measurements that fail to capture the physiological fluctuations typical of ARDS. Recent advances, including sensor miniaturization, high-resolution continuous data acquisition, advanced waveform analysis, and expanded computational capabilities, now enable real-time assessment of respiratory mechanics and cardiopulmonary interactions. These technologies allow clinicians to track the dynamic interactions among ventilation, lung mechanics, and cardiovascular function, supporting more precise and timely adjustments in ventilatory support. Artificial intelligence systems can integrate these high-density data streams, enhance data quality assessment, and provide decision support; however, they also raise concerns regarding information overload and the need to ensure that outputs translate into meaningful, patient-centered decisions. This review summarizes recent advances in real-time monitoring of respiratory mechanics and cardiopulmonary interactions in ARDS, emphasizing how technological innovation is reshaping bedside physiological assessment and enabling a more precise, adaptive approach to ventilatory support.

Indexed as

Respiration, ArtificialRespiratory Distress SyndromeHumansMonitoring, PhysiologicRespiratory MechanicsHemodynamicsImagingMonitoring of respiratory mechanicsPrecision medicineRegional ventilation

Identifiers

PMID41794732
PMCPMC13045135

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.