Avaliação de parâmetros da mecânica respiratória pela técnica das oscilações forçadas em pequenos animais sob a presença de respiração espontânea.
Bibliographic record
Abstract
In this thesis we proposed an alternative approach to the signal processing when noise from spontaneous breathing efforts, consisting in a sharp drop in the output pressure signal within a short timescale, manifests during the Forced Oscillations Technique (FOT ) realization through a commercial device (flexiVent, SCIREQ, Montreal, Canada).Once the most widely used signal consists in 2 2-seconds epochs with a half period overlap, leading to a 3-seconds signal (QuickPrime-3 ), such noise in the first or in the last second of the signal would still have a full non-disrupted period.Therefore, we hypothesized that a single 2-second full period would be able to provide relevant physiological information in small animals even when disruptions from spontaneous breathing efforts manifest.Consequently, data sets that would have been discarded could be used, avoiding the sacrifice of more animals.We tested our hypothesis in a previous collected FOT dataset in mice under bronchoconstriction due to methacholine administration by bolus injections or continuous infusion in different doses or infusion rates.Disruption was computationally simulated as a sharp drop in pressure level within a short timescale.We assessed not only Constant Phase Model (CPM ) parameters but also model goodness of fit (Coefficient of Determination, COD) and the index of harmonic distortion, aiming to estimate system nonlinearity degree.We found no statistically significant difference between the original 3-s signal and the 2-s epoch without disruption in Constant Phase Model parameters (resistance, tissue damping and elastance) comparisons for both, bolus injections and continuous infusion of methacholine, in different doses or infusion rates.Furthermore, we also found that the difference between bronchoconstricted and baseline harmonic distortion index values in both signals do not show statistically significant differences.Hence we can conclude that although the proposed technique presents limitations, it is a simple and of easy implementation tool in order to extract physiological information from FOT data in which spontaneous breathing efforts manifest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".