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Record W4310122191 · doi:10.1002/ehf2.14242

New insight: Particle Flow Rate from the Airways as an Indicator of Cardiac Failure in the Intensive Care Unit

2022· article· en· W4310122191 on OpenAlexfundno aff
Sandra Lindstedt, Snejana Hyllén

Bibliographic record

VenueESC Heart Failure · 2022
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsnot available
FundersKnut och Alice Wallenbergs StiftelseGeorge Cedric Metcalf Charitable Foundation
KeywordsMedicineEjection fractionHeart failureInotropeMechanical ventilationDobutamineCardiac function curveCardiologyCardiac outputInternal medicineCardiac surgeryIntensive care unitHemodynamicsAnesthesia

Abstract

fetched live from OpenAlex

AIMS: Exhaled breath particles have been explored for diagnosing different lung diseases. We recently showed in an experimental model that different cardiac output results in different particle flow rate (PFR) from the airways. Given the well-known close relationship between impaired cardiac function and respiratory failure, we hypothesized that PFR in exhaled air can be used to detect cardiac failure. METHODS: PFR was analysed using a customized PExA device. Particles in the range of 0.41-4.55 μm were measured. The included patients (n = 20) underwent cardiac surgery and received mechanical ventilation as a part of routine post-operative care. Ten patients with clinical signs of pronounced post-operative haemodynamic instability and need for inotrope or mechanical support had been selected to the cardiac failure group. The control group consisted of 10 patients without signs of cardiac failure. RESULTS: The patients in cardiac failure group required inotropic support in the form of dobutamine (9/10), epinephrine (2/10), or levosimendan (4/10) or use of an intra-aortic balloon pump (4/10). There was no use of inotropes or mechanical support devices among the controls. All patients in the cardiac failure group had pre-operative left ventricular ejection fraction ≤40% compared with the control group, whose pre-operative ejection fraction was ≥50%, P < 0.001. Patients with cardiac failure had significantly longer median total time in mechanical ventilation compared with the patients in the control group: 53.5 h (IQR 6.8-116101.0 h) and 4.5 h (IQR 4.0-5.5 h), respectively, P < 0.001, and the median length of stay in the ICU, 165 h (IQR 28-192 h) and 22 h (IQR 20-23.5 h), respectively, P = 0.007. Median PFR in patients with cardiac failure was higher than PFR in those with normal cardiac function: 80.9 particles/min (interquartile range (IQR) 25.8-336.6 particles/min), vs. 15.3 particles/min (IQR 8.1-17.7 particles/min), respectively, P < 0.001. Median particle mass was 8.95 ng (IQR 1.68-41.73 ng) in the cardiac failure group and 0.75 ng (IQR 0.18-1.45 ng) in the control group, P = 0.002. CONCLUSIONS: Patients with post-operative cardiac failure following cardiac surgery exhibited an increase in exhaled particle mass and PFR compared with the control group, indicating a significant difference between those two groups. The increase in particle mass and PFR in the absence of respiratory pathologies may indicate cardiac failure. In comparison with controls, impaired cardiac function was also associated with different composition of the particles regarding their size distribution.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.267
Teacher spread0.245 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations4
Published2022
Admission routes1
Has abstractyes

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