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Record W4317435710 · doi:10.3390/jcm12030795

Validation of Noninvasive Assessment of Pulmonary Gas Exchange in Patients with Chronic Obstructive Pulmonary Disease during Initial Exposure to High Altitude

2023· article· en· W4317435710 on OpenAlexaff
Benoît Champigneulle, Lukas Reinhard, Maamed Mademilov, Mathieu Marillier, Tanja Ulrich, Arcangelo F. Carta, Philipp M. Scheiwiller, Saltanat Shabykeeva, Ulan Sheraliev, Ainura Abdraeva, Kamila Magdieva, Gulzada Mirzalieva, Aijan Taalaibekova, Aigul Ozonova, Aidai Erkinbaeva, Nurdin Shakiev, Syimyk Azizbekov, Philip N. Ainslie, Talant Sooronbaev, Silvia Ulrich, Konrad E. Bloch, Samuel Vergès, Michaël Furian

Bibliographic record

VenueJournal of Clinical Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAgence Nationale de la RechercheFondation Université Grenoble Alpes
KeywordsMedicinePulmonary diseaseInternal medicineCardiologyEffects of high altitude on humansAltitude (triangle)Intensive care medicine

Abstract

fetched live from OpenAlex

Investigation of pulmonary gas exchange efficacy usually requires arterial blood gas analysis (aBGA) to determine arterial partial pressure of oxygen (mPaO2) and compute the Riley alveolar-to-arterial oxygen difference (A-aDO2); that is a demanding and invasive procedure. A noninvasive approach (AGM100), allowing the calculation of PaO2 (cPaO2) derived from pulse oximetry (SpO2), has been developed, but this has not been validated in a large cohort of chronic obstructive pulmonary disease (COPD) patients. Our aim was to conduct a validation study of the AG100 in hypoxemic moderate-to-severe COPD. Concurrent measurements of cPaO2 (AGM100) and mPaO2 (EPOC, portable aBGA device) were performed in 131 moderate-to-severe COPD patients (mean ±SD FEV1: 60 ± 10% of predicted value) and low-altitude residents, becoming hypoxemic (i.e., SpO2 < 94%) during a short stay at 3100 m (Too-Ashu, Kyrgyzstan). Agreements between cPaO2 (AGM100) and mPaO2 (EPOC) and between the O2-deficit (calculated as the difference between end-tidal pressure of O2 and cPaO2 by the AGM100) and Riley A-aDO2 were assessed. Mean bias (±SD) between cPaO2 and mPaO2 was 2.0 ± 4.6 mmHg (95% Confidence Interval (CI): 1.2 to 2.8 mmHg) with 95% limits of agreement (LoA): −7.1 to 11.1 mmHg. In multivariable analysis, larger body mass index (p = 0.046), an increase in SpO2 (p < 0.001), and an increase in PaCO2-PETCO2 difference (p < 0.001) were associated with imprecision (i.e., the discrepancy between cPaO2 and mPaO2). The positive predictive value of cPaO2 to detect severe hypoxemia (i.e., PaO2 ≤ 55 mmHg) was 0.94 (95% CI: 0.87 to 0.98) with a positive likelihood ratio of 3.77 (95% CI: 1.71 to 8.33). The mean bias between O2-deficit and A-aDO2 was 6.2 ± 5.5 mmHg (95% CI: 5.3 to 7.2 mmHg; 95%LoA: −4.5 to 17.0 mmHg). AGM100 provided an accurate estimate of PaO2 in hypoxemic patients with COPD, but the precision for individual values was modest. This device is promising for noninvasive assessment of pulmonary gas exchange efficacy in COPD patients.

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)0.005
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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.039
GPT teacher head0.388
Teacher spread0.349 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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