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P43 Diaphragmatic ultrasound as a marker of clinical status and early readmissions after acute exacerbations of COPD: preliminary results from a prospective cohort study

2021· article· en· W3123561157 on OpenAlexaff
Aileen Kharat, Martin Girard, B.-P. Dubé

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineCOPDExacerbationProspective cohort studyInternal medicineRespiratory failureCohortEmergency departmentCardiology

Abstract

fetched live from OpenAlex

Introduction The management of acute exacerbation of COPD (AECOPD) is complicated by the lack of a specific biomarker related to clinical course and readmission/treatment failure risk. As AECOPD are characterized by an acute worsening of lung hyperinflation and increased respiratory work, which can lead to diaphragm weakness and/or fatigue, we hypothesized that the serial monitoring of diaphragm function during an AECOPD could provide clinically relevant information on the clinical status of patients and their treatment failure risk. Methods Patients with AECOPD requiring hospitalization in our center were prospectively recruited. Diaphragm thickening fraction (reported as the ratio of tidal to maximal thickening fractions of the diaphragm – TF%max) was measured using ultrasonography within 24h of admission and within 24h of discharge. The difference in TF%max value between admission and discharge was reported as ΔTF. In addition to clinical and demographic characteristics, National Early Warning Score (NEWS), COPD Assessment Test (CAT) and blood gases were retrieved at the time of admission. Treatment failure was defined as a readmission to the emergency department/hospital <30 days after discharge. Results 18 patients were recruited [mean (±standard deviation) age 74±7 years, FEV139±17%, residual volume 153±69% and CAT score 26±6]. Mean TF%max decreased from 54±20% on admission to 43±19% at discharge (p=0.06). Mean ΔTF was -10±50%. 5 patients (28%) were readmitted within 30 days. In these patients, TF%max at the time of discharge and the change in TF%max during hospitalization were significantly different than in those without readmission (65±7 vs 35±16%, p=0.001 and 30±66 vs -27±35%, p=0.02, respectively) (figure 1). ΔTF was significantly correlated to length of hospital stay (rho=0.49, p=0.04), but TF%max, NEWS, CAT score and pCO2 measured on admission were not (all p>0.05). Conclusions TF%max, measured using ultrasonography, is responsive to clinical evolution during episodes of AECOPD, and may be able to predict the risk of early readmission. Further data is required to better delineate the role of diaphragm ultrasound in this setting and to identify clinically relevant threshold values associated with negative outcomes.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.026
GPT teacher head0.369
Teacher spread0.343 · 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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Published2021
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