ArticleIntensive care medicine2013
Visual anatomical lung CT scan assessment of lung recruitability.
Article in Intensive care medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07328997 (Exploration of Diagnosis and Treatment Strategies and Prognostic Prediction Models for Acute Respiratory Distress Syndrome Based on Radiographic Evaluations Assessed by Artificial Intelligence), which is not on this map. Cited by 29 papers.
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.
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.
Exploration of Diagnosis and Treatment Strategies and Prognostic Prediction Models for Acute Respiratory Distress Syndrome Based on Radiographic Evaluations Assessed by Artificial Intelligence
Who cites it
29 citing papers in PubMed, 44 citations in OpenAlex.
- Trial
- Low-dose chest computed tomography for quantitative and visual anatomical analysis in patients with acute respiratory distress syndrome.Intensive care medicine · 2014Trial
- Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography.Intensive care medicine experimental · 2026Review
- "Tailored" vs. "one-size-fits-all": current knowledge of individualized PEEP and constant PEEP strategy during the perioperative period.European journal of medical research · 2025Review
- Lung re-aeration assessment by ultrasound during mechanical ventilation: Current knowledge of literature review.Multidisciplinary respiratory medicine · 2025Article
- Real-time stress and strain monitoring at the bedside: new frontiers in mechanical ventilation.Frontiers in medicine · 2025Review
- Shape Anisotropy-Governed High-Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs.Small (Weinheim an der Bergstrasse, Germany) · 2024Article
- Lung Imaging and Artificial Intelligence in ARDS.Journal of clinical medicine · 2024Review
- Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS.Intensive care medicine experimental · 2023Article
- Precision Medicine Using Simultaneous Monitoring and Assessment with Imaging and Biomarkers to Manage Mechanical Ventilation in ARDS.Intensive care research · 2023Review
- A structured narrative review of clinical and experimental studies of the use of different positive end-expiratory pressure levels during thoracic surgery.The clinical respiratory journal · 2022Review
- Imaging the acute respiratory distress syndrome: past, present and future.Intensive care medicine · 2022Review
- Continuous Lower Abdominal Compression as a Therapeutic Intervention in COVID-19 ARDS.Clinical medicine insights. Circulatory, respiratory and pulmonary medicine · 2021Article
- Transpulmonary pressures in obese and non-obese COVID-19 ARDS.Annals of intensive care · 2020Article
- Mechanical Ventilation Strategies Targeting Different Magnitudes of Collapse and Tidal Recruitment in Porcine Acid Aspiration-Induced Lung Injury.Journal of clinical medicine · 2019Article
- Tailoring the cure: still science fiction?Journal of thoracic disease · 2019Article
- Lung recruitment: What has computed tomography taught us in the last decade?Annals of intensive care · 2019Article
- Ultra-low-dose sequential computed tomography for quantitative lung aeration assessment-a translational study.Intensive care medicine experimental · 2017Article
- Reliability of transpulmonary pressure-time curve profile to identify tidal recruitment/hyperinflation in experimental unilateral pleural effusion.Journal of clinical monitoring and computing · 2017Article
- Lung imaging: how to get better look inside the lung.Annals of translational medicine · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe computation of lung recruitability in acute respiratory distress syndrome (ARDS) is advocated to set positive end-expiratory pressure (PEEP) for preventing lung collapse. The quantitative lung CT scan, obtained by manual image processing, is the reference method but it is time consuming. The aim of this study was to evaluate the accuracy of a visual anatomical analysis compared with a quantitative lung CT scan analysis in assessing lung recruitability.
methodsFifty sets of two complete lung CT scans of ALI/ARDS patients computing lung recruitment were analyzed. Lung recruitability computed at an airway pressure of 5 and 45 cm H(2)O was defined as the percentage decrease in the collapsed/consolidated lung parenchyma assessed by two expert radiologists using a visual anatomical analysis and as the decrease in not aerated lung regions using a quantitative analysis computed by dedicated software.
resultsLung recruitability was 11.3 % (interquartile range 7.39-16.41) and 15.5 % (interquartile range 8.18-21.43) with the visual anatomical and quantitative analysis, respectively. In the Bland-Altman analysis, the bias and agreement bands between the visual anatomical and quantitative analysis were -2.9 % (-11.8 to +5.9 %). The ROC curve showed that the optimal cutoff values for the visual anatomical analysis in predicting high versus low lung recruitability was 8.9 % (area under the ROC curve 0.9248, 95 % CI 0.8550-0.9946). Considering this cutoff, the sensitivity, specificity, and diagnostic accuracy were 0.96, 0.76, and 0.86, respectively.
conclusionsVisual anatomical analysis can classify patients into those with high and low lung recruitability allowing more intensivists to get access to lung recruitability assessment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.