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Record W3097583629 · doi:10.1182/blood-2020-141996

Thrombotic Complications in a Canadian Population of Critically Ill Patients with COVID-19

2020· article· en· W3097583629 on OpenAlexaffabout
Camille Simard, Maral Koolian, Diana Escobar, Mark Blostein, Jed Lipes, Adelina Teona Avram, Ryan Kerzner, Helen Mantzanis, Mateo Porres Aguilar, Vicky Tagalakis

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsMedicineIntensive care unitThrombosisPopulationPulmonary embolismVenous thrombosisRetrospective cohort studyIntensive careInternal medicineEmergency medicineIntensive care medicine

Abstract

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Introduction Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), a virus strain that appeared in Wuhan China in December 2019, that has since spread to become pandemic. An increased risk of venous and arterial thromboembolism has been consistently reported in critically ill patients with COVID-19 in several countries. The mechanism is thought to be multifactorial, largely mediated by the interplay between inflammation and the coagulation system, or thromboinflammation. We aim to report the risk of thrombosis in a Canadian patient population admitted to the intensive care unit (ICU) with COVID-19. Method We conducted a retrospective cohort study of all consecutive patients with COVID-19 admitted to the ICU between March 1st, 2020 and May 10th, 2020 at the Jewish General Hospital (JGH) in Montreal, Canada. The JGH is a tertiary care centre in Montreal, the epicenter of the COVID-19 pandemic in Canada, and the JGH was the first designated hospitalization centre in Montreal for COVID-19 patients. Patients were followed from date of ICU admission to the earliest of the following: objectively confirmed venous or arterial thrombosis; discharge from hospital; death; or study end date (May 24th, 2020). We determined risk of venous (pulmonary embolism (PE) and deep vein thrombosis (DVT)) and arterial (myocardial infarction, cerebrovascular accident, arterial limb ischemia, and mesenteric ischemia) thrombotic events. Results During the study period, a total of 90 patients admitted to the ICU with COVID-19 were included. The median age was 66 years (standard deviation (SD) 13.8), and 41.1% of patients were female. The median body mass index was 30 kg/m2(SD 5.1), and 64% of patients were mechanically ventilated and 10.1% received continuous renal replacement therapy. The median duration of follow-up was 17.1 days (SD 13.4). In all, 98.9% of patients were prescribed anticoagulation, among whom 78.2% were on a prophylaxis dose, 15.0% intermediate dose, and 6.9% therapeutic dose. In all, 11 (12.2%) patients developed a thrombotic complication among whom 9 patients had objectively diagnosed pulmonary embolism (PE) and 2 patients had an arterial thromboembolism. Both arterial events were cerebrovascular accidents. All PE episodes involved segmental arteries. One PE was incidental, and 3 patients had a concomitant diagnosis of DVT. Overall, death was observed in 16.7% of cohort patients and 12.2% of patients were still admitted to hospital at study end date. Conclusion In this first Canadian study of critically ill patients with COVID-19, we found a 12.2% risk of thrombotic complications despite almost 100% use of anticoagulation primarily with standard prophylaxis dosing. This risk is considerably lower than most reported estimates to date from critical care COVID-19 cohorts in Europe, China and the United States. Our results fuel the ongoing discussion of optimal dose of anticoagulation in these patients. Disclosures No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.401
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes2
Has abstractyes

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