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Forced oscillation technique used for monitoring of covid-19 pneumonia

2022· article· en· W4313027338 on OpenAlexaboutno aff
Immanuels Taivāns, L Grima, N Jurka, G Strazda, V Gordjusina

Bibliographic record

Venue10.01 - Respiratory infections and bronchiectasis · 2022
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PneumoniaForced oscillation2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Oscillation (cell signaling)Computer scienceVirologyMedicineEngineeringElectrical engineeringChemistryInternal medicine

Abstract

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<b>Background:</b> Forcrd oscillation technique (FOT) is a non-invasive method for investigation of lung mechanics without active participation of the patient. The objectives of the study were to find out whether FOT method could be used for monitoring of covid-19 pneumonia (CVP) course and how FOT indices correlate with other, commonly used indicators of disease severity. <b>Methods:</b> During the hospital stay and 3 months after the discharge from hospital repeated measurements of lung mechanics were performed with portable device Tremoflo-100 (Thorasys, Canada). <b>Results:</b> Most relevant differences between disease stages reflected the lung reactance indices - Fres and AX. Indices characterizing the airflow resistance didn’t reach the significance level. Correlation analysis also was performed between FOT indices and CT score, body mass index (BMI), patients age, blood CRP and ferritin levels, duration of hospital stay and patients oxygen demand (FiO2). Significant correlations were found only between the last two. The highest significance showed Fres % pred and AX % pred. Fres correlated to FiO2 with R=0,498 and p-0,0000004, but AX% with r=0,502 <b>Conclusions:</b> The study has shown that FOT method reflects the changes in lung mechanics occurring during acute phase and recovery period from covid-19 pneumonia. FOT indices correlate with patients oxygen demand and hospital stay-time.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.279
Teacher spread0.251 · 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 designBench or experimental
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

Citations0
Published2022
Admission routes1
Has abstractyes

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