Evidence map›Paper›PMID 35512457›Full record

Observational studyRespiratory medicine2022

Macklin effect on baseline chest CT scan accurately predicts barotrauma in COVID-19 patients.

Gianluca Paternoster, Gianfranco Belmonte, Enrico Scarano, Pietro Rotondo, Diego Palumbo, Alessandro Belletti, Francesco Corradi, Pietro Bertini, Giovanni Landoni, Fabio Guarracino and 1 more

Registry-linked trialOpen access · bronzeAbstract readObservational Study
In one paragraph

Observational study in Respiratory medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05816954 (Artificial Intelligence-based Identification of Imaging Biomarkers of Lung FRAILty in Patients With Acute Respiratory Distress Syndrome.), which is not on this map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
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.

NCT05816954 recruitingnot on this mapstarted 2023, after this paper: background citation

Artificial Intelligence-based Identification of Imaging Biomarkers of Lung FRAILty in Patients With Acute Respiratory Distress Syndrome.

TypeobservationalSponsorUniversità Vita-Salute San RaffaeleRan2023 to 2027Enrolled100ConditionsAcute Respiratory Distress Syndrome, BarotraumaArmsChest Computed Tomography Scan per normal clinical practice
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
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  12. Observational
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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

11 authors at 4 institutions in 1 country.

Gianluca PaternosterDepartment of Cardiovascular Anesthesia and Intensive Care, San Carlo Hospital, Potenza, Italy. Electronic address: paternostergianluca@gmail.com.
Gianfranco BelmonteDepartment of Radiology, San Carlo Hospital, Potenza, Italy.
Enrico ScaranoDepartment of Radiology, San Carlo Hospital, Potenza, Italy.
Pietro RotondoDepartment of Radiology, San Carlo Hospital, Potenza, Italy.
Diego PalumboDepartment of Radiology, IRCCS San Raffaele Scientific Institute, Milan, Italy; School of Medicine, Vita-Salute San Raffaele University, Milan, Italy.
Alessandro BellettiDepartment of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Francesco CorradiDepartment of Surgical-Medical Molecular Pathology and Critical Care Medicine, University of Pisa, Italy.
Pietro BertiniDepartment of Anesthesia e Critical Care Medicine, Cardiothoracic-Vascular Anesthesia and Intensive Care, Azienda Ospedaliero Universitaria Pisana, Italy.
Giovanni LandoniSchool of Medicine, Vita-Salute San Raffaele University, Milan, Italy; Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Fabio GuarracinoDepartment of Anesthesia e Critical Care Medicine, Cardiothoracic-Vascular Anesthesia and Intensive Care, Azienda Ospedaliero Universitaria Pisana, Italy.
COVID-Macklin Study Group
Vita-Salute San Raffaele University · ITOspedale San Carlo · ITAzienda Ospedaliera Universitaria Pisana · ITUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo validate the role of Macklin effect on chest CT imaging in predicting subsequent occurrence of pneumomediastinum/pneumothorax (PMD/PNX) in COVID-19 patients. MATERIALS AND

methodsThis is an observational, case-control study. Consecutive COVID-19 patients who underwent chest CT scan at hospital admission during the study time period (October 1st, 2020-April 31st, 2021) were identified. Macklin effect accuracy for prediction of spontaneous barotrauma was measured in terms of sensitivity, specificity, positive (PPV) and negative predictive values (NPV).

resultsOverall, 981 COVID-19 patients underwent chest CT scan at hospital arrival during the study time period; 698 patients had radiological signs of interstitial pneumonia and were considered for further evaluation. Among these, Macklin effect was found in 33 (4.7%), including all 32 patients who suffered from barotrauma lately during hospital stay (true positive rate: 96.9%); only 1/33 with Macklin effect did not develop barotrauma (false positive rate: 3.1%). No barotrauma event was recorded in patients without Macklin effect on baseline chest CT scan. Macklin effect yielded a sensitivity of 100% (95% CI: 89.1-100), a specificity of 99.85% (95% CI: 99.2-100), a PPV of 96.7% (95% CI: 80.8-99.5), a NPV of 100% and an accuracy of 99.8% (95% CI: 99.2-100) in predicting PMD/PNX, with a mean advance of 3.2 ± 2.5 days. Moreover, all Macklin-positive patients developed ARDS requiring ICU admission and, in 90.1% of cases, invasive mechanical ventilation.

conclusionsMacklin effect has high accuracy in predicting PMD/PNX in COVID-19 patients; it is also an excellent predictor of disease severity.

Indexed as

BarotraumaCOVID-19Mediastinal EmphysemaPneumothoraxCase-Control StudiesHumansTomography, X-Ray ComputedAcute respiratory distress syndromeBarotraumaComputed tomographyIntensive careMechanical ventilationPneumomediastinumPneumothorax

Identifiers

PMID35512457
PMCPMC9020841
OpenAlexW4224271308

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.