Evidence map›Paper›PMID 34016056›Full record

ArticleBMC anesthesiology2021

The repurposed use of anesthesia machines to ventilate critically ill patients with coronavirus disease 2019 (COVID-19).

Maurizio Bottiroli, Angelo Calini, Riccardo Pinciroli, Ariel Mueller, Antonio Siragusa, Carlo Anelli, Richard D Urman, Ala Nozari, Lorenzo Berra, Michele Mondino and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC anesthesiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 14% 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.

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

6 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 2 countries.

Maurizio BottiroliDepartment of Anesthesia and Critical Care, ASST Grande Ospedale Metropolitano Niguarda, P.zza Ospedale Maggiore, 3-, 20162, Milan, Italy. maurizio.bottiroli@gmail.com.
Angelo CaliniDepartment of Anesthesia and Critical Care, ASST Grande Ospedale Metropolitano Niguarda, P.zza Ospedale Maggiore, 3-, 20162, Milan, Italy.
Riccardo PinciroliDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Ariel MuellerDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Antonio SiragusaDepartment of Anesthesia and Critical Care, ASST Grande Ospedale Metropolitano Niguarda, P.zza Ospedale Maggiore, 3-, 20162, Milan, Italy.
Carlo AnelliDepartment of Anesthesia and Critical Care, ASST Grande Ospedale Metropolitano Niguarda, P.zza Ospedale Maggiore, 3-, 20162, Milan, Italy.
Richard D UrmanDepartment of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Ala NozariDepartment of Anesthesiology, Boston Medical Center, Boston, MA, USA.
Lorenzo BerraDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Michele MondinoDepartment of Anesthesia and Critical Care, ASST Grande Ospedale Metropolitano Niguarda, P.zza Ospedale Maggiore, 3-, 20162, Milan, Italy.
Roberto FumagalliDepartment of Anesthesia and Critical Care, ASST Grande Ospedale Metropolitano Niguarda, P.zza Ospedale Maggiore, 3-, 20162, Milan, Italy.
Ospedale Maggiore · ITMassachusetts General Hospital · USBoston Medical Center · USBrigham and Women's Hospital · USHarvard University · USUniversity of Milano-Bicocca · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe surge of critically ill patients due to the coronavirus disease-2019 (COVID-19) overwhelmed critical care capacity in areas of northern Italy. Anesthesia machines have been used as alternatives to traditional ICU mechanical ventilators. However, the outcomes for patients with COVID-19 respiratory failure cared for with Anesthesia Machines is currently unknow. We hypothesized that COVID-19 patients receiving care with Anesthesia Machines would have worse outcomes compared to standard practice.

methodsWe designed a retrospective study of patients admitted with a confirmed COVID-19 diagnosis at a large tertiary urban hospital in northern Italy. Two care units were included: a 27-bed standard ICU and a 15-bed temporary unit emergently opened in an operating room setting. Intubated patients assigned to Anesthesia Machines (AM group) were compared to a control cohort treated with standard mechanical ventilators (ICU-VENT group). Outcomes were assessed at 60-day follow-up. A multivariable Cox regression analysis of risk factors between survivors and non-survivors was conducted to determine the adjusted risk of death for patients assigned to AM group.

resultsComplete daily data from 89 mechanically ventilated patients consecutively admitted to the two units were analyzed. Seventeen patients were included in the AM group, whereas 72 were in the ICU-VENT group. Disease severity and intensity of treatment were comparable between the two groups. The 60-day mortality was significantly higher in the AM group compared to the ICU-vent group (12/17 vs. 27/72, 70.6% vs. 37.5%, respectively, p = 0.016). Allocation to AM group was associated with a significantly increased risk of death after adjusting for covariates (HR 4.05, 95% CI: 1.75-9.33, p = 0.001). Several incidents and complications were reported with Anesthesia Machine care, raising safety concerns.

conclusionsOur results support the hypothesis that care associated with the use of Anesthesia Machines is inadequate to provide long-term critical care to patients with COVID-19. Added safety risks must be considered if no other option is available to treat severely ill patients during the ongoing pandemic. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

AgedAnesthesiologyCOVID-19Critical IllnessFemaleHumansItalyMaleMiddle AgedRespiration, ArtificialRetrospective StudiesAnesthesia machineARDSCOVID-19Intensive care unitMechanical ventilation

Identifiers

PMID34016056
PMCPMC8134805
OpenAlexW3132024565

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.