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Record W2980871224 · doi:10.1097/ccm.0000000000004027

Preoperative Diaphragm Function Is Associated With Postoperative Pulmonary Complications After Cardiac Surgery

2019· article· en· W2980871224 on OpenAlexaffabout
Yiorgos Alexandros Cavayas, Roberto Eljaiek, Yoan Lamarche, Martin Girard, Han Ting Wang, Sylvie Lévesque, André Denault

Bibliographic record

VenueCritical Care Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecMontreal Heart InstituteInnovation and Economic Development Trois RivièresCentre Hospitalier de l’Université de MontréalHôpital Charles-Le MoyneHôpital Maisonneuve-RosemontHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicineAtelectasisPulmonary function testingMechanical ventilationSurgeryPneumoniaCardiac surgeryDiaphragmatic breathingProspective cohort studyCardiologyInternal medicineLung

Abstract

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OBJECTIVES: Postoperative pulmonary complications increase mortality, length, and cost of hospitalization. A better diaphragmatic strength may help face an increased work of breathing postoperatively. We, therefore, sought to determine if a low preoperative diaphragm thickening fraction (TFdi) determined by ultrasonography helped predict the occurrence of postoperative pulmonary complications after cardiac surgery independently of indicators of frailty, sarcopenia, and pulmonary function. DESIGN: Prospective observational cohort study. SETTING: Montreal Heart Institute, an academic cardiac surgery center in Canada. PATIENTS: Adults undergoing nonemergency cardiac surgery. INTERVENTIONS: We measured the preoperative thickness of the right and left hemidiaphragms at their zone of apposition at end-expiration (Tdi,ee) and peak-inspiration (Tdi,ei) with ultrasonography. Maximal thickening fraction of the diaphragm during inspiration (TFdi,max) was calculated using the following formula: TFdi,max = (Tdi,ei-Tdi,ee)/Tdi,ee. We also evaluated other potential risk factors including demographic parameters, comorbidities, Clinical Frailty Scale, grip strength, 5-meter walk test, and pulmonary function tests. We repeated TFdi,max measurements within 24 hours of extubation. The primary composite outcome of this study was the occurrence of postoperative pulmonary complications, defined as pneumonia, clinically significant atelectasis, or prolonged mechanical ventilation (> 24 hr). MEASUREMENT AND MAIN RESULTS: Of the 115 patients included, 34 (29.6%) developed postoperative pulmonary complications, including two with pneumonia, four with prolonged mechanical ventilation, and 32 with clinically significant atelectasis. Those with postoperative pulmonary complications had prolonged ICU and hospital length of stays. They had a lower TFdi,max (37% [interquartile range, 31-45%] vs 44% [interquartile range, 33-58%]; p = 0.03). In multiple logistic regression, a TFdi,max less than 38.1% was associated with postoperative pulmonary complications (odds ratio, 4.9; 95% CI, 1.81-13.50; p = 0.002). All patients who developed pneumonia or prolonged mechanical ventilation had a TFdi,max less than 38.1%. Respiratory rate and diabetes were also independently associated with postoperative pulmonary complications, while pulmonary function tests and the assessed indicators of frailty and sarcopenia were not. CONCLUSIONS: A low preoperative TFdi,max can help to identify patients at increased risk of postoperative pulmonary complications after cardiac surgery.

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)0.004
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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

Citations51
Published2019
Admission routes2
Has abstractyes

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