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Record W4404620233 · doi:10.1136/bmjopen-2024-090158

Pulmonary complications and mortality among COVID-19 patients undergoing a surgery: a multicentre cohort study

2024· article· en· W4404620233 on OpenAlexafffundabout
Éva Amzallag, Thanushka Panchadsaram, Martin Girard, Vincent Lecluyse, Étienne J. Couture, Frédérick D’Aragon, Stanislas Kandelman, Alexis F. Turgeon, Caroline Jodoin, Pierre Beaulieu, Philippe Richebé, François Martin Carrier

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsFrancophone University AssociationMcGill University Health CentreUniversité de SherbrookeUniversité LavalUniversité de MontréalHôpital du Sacré-Cœur de MontréalCentre Hospitalier de l’Université de Montréal
FundersFonds de Recherche du Québec - SantéInstitut universitaire de cardiologie et de pneumologie de Québec, Université LavalUniversité de MontréalUniversité de SherbrookeUniversité Laval
KeywordsMedicineAsymptomaticPerioperativePneumoniaAtelectasisContext (archaeology)Cohort studyCohortSurgeryInternal medicineLung

Abstract

fetched live from OpenAlex

OBJECTIVES: Our primary objective was to assess the association between symptoms at the time of surgery and postoperative pulmonary complications and mortality in patients with COVID-19. Our secondary objective was to compare postoperative outcomes between patients who had recovered from COVID-19 and asymptomatic patients and explore the effect of the time elapsed between infection and surgery in the former. Our hypotheses were that symptomatic patients had a higher risk of pulmonary complications, whereas patients who had recovered from the infection would exhibit outcomes similar to those of asymptomatic patients. BACKGROUND: Managing COVID-19-positive patients requiring surgery is complex due to perceived heightened perioperative risks. However, Canadian data in this context remains scarce. DESIGN: To address this gap, we conducted a multicentre observational cohort study. SETTING: Across seven hospitals in the province of Québec, the Canadian province was most affected during the initial waves of the pandemic. PARTICIPANTS: We included adult surgical patients with either active COVID-19 at the time of surgery or those who had recovered from the disease, from March 22, 2020 to April 30, 2021. OUTCOMES: We evaluated the association between symptoms or recovery time and postoperative pulmonary complications and hospital mortality using multivariable logistic regression and Cox models. The primary outcome was a composite of any postoperative pulmonary complication (atelectasis, pneumonia, acute respiratory distress syndrome and pneumothorax). Our secondary outcome was hospital mortality, assessed from the date of surgery up to hospital discharge. RESULTS: We included 105 patients with an active infection (47 were symptomatic and 58 were asymptomatic) at the time of surgery and 206 who had recovered from COVID-19 prior to surgery in seven hospitals. Among patients with an active infection, those who were symptomatic had a higher risk of pulmonary complications (OR 3.19, 95% CI 1.12 to 9.68, p=0.03) and hospital mortality (HR 3.67, 95% CI 1.19 to 11.32, p=0.02). We did not observe any significant effect of the duration of recovery prior to surgery on patients who had recovered from their infection. Their postoperative outcomes were also similar to those observed in asymptomatic patients. INTERPRETATION: Symptomatic status should be considered in the decision to proceed with surgery in COVID-19-positive patients. Our results may help optimise surgical care in this patient population. STUDY REGISTRATION: ClinicalTrials.gov Identifier: NCT04458337 registration date: 7 July 2020.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.244
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.194
GPT teacher head0.499
Teacher spread0.306 · 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".

Quick stats

Citations2
Published2024
Admission routes3
Has abstractyes

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