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Oscillating Positive Expiratory Pressure (OPEP) Devices and Airway Clearance Therapy in the Covid-19 Patient Care Pathway: A Review of Where There May Be Clinical Value

2021· review· en· W3176667984 on OpenAlexaff
Jason Suggett, Vladimir Kushnarev

Bibliographic record

Venuenot available
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsTrudell Medical International (Canada)
Fundersnot available
KeywordsMedicineIntensive care medicineRespiratory systemCoronavirus disease 2019 (COVID-19)Continuous positive airway pressureAirwayInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

RATIONALE: In the Covid-19 environment it is unclear what role airway clearance devices such as OPEP have in therapy. Hence, it would be useful to assess the care pathway of a Covid-19 patient and review the evidence available to support (or otherwise) the use of OPEP devices. METHODS: The assessment distinguished between two types of care pathway: a) Covid patients with an existing respiratory condition associated with excess mucus production, and b) Covid patients with no underlying respiratory condition. Within each of these two types there was further segregation into i) pre-infection, ii) infection being managed at home/in hospital, and iii) recovery post infection. The evidence-based positioning of OPEP therapy in each was evaluated. RESULTS: For patients with a pre-existing respiratory condition, if they were pre-infection and had presence of excess mucus, evidence exists to support use of OPEP therapy to manage their chronic condition and therefore reduce likelihood of needing to seek medical attention with consequent risk of exposure to Covid-19. Similarly, for post infection recovery, use of OPEP to manage excess mucus associated with the pre-existing respiratory condition may reduce risk of early re-entry to hospital system. Use of OPEP while Covid positive and admitted to hospital may still be beneficial in order to manage underlying respiratory condition, however it would need to be undertaken in line with local hospital protocols to protect against airborne contamination. When assessing Covid-19 pathway for patients with no underlying chronic respiratory condition, there is no evidence to support use of OPEP pre-infection. Post-infection, there is limited evidence. For example, if the patient has been ventilated or immobile for an extended period of time there is some adjacent evidence associated with reduced post-operative complications when using OPEP. As a treatment for Covid-19, OPEP therapy is not proven, and the infection is not typically associated with excess mucus, however a couple of references advocate the use of OPEP as required in those instances where airway clearance may be beneficial. CONCLUSIONS: Management of Covid-19 is a complex and not fully understood area. Patients with a pre-existing chronic respiratory condition exhibiting excess mucus will likely benefit from use of an appropriate OPEP device. The evidence is less clear for those patients without pre-existing respiratory conditions, with further evidence beneficial to support OPEP in treatment and post infection rehabilitation.

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)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.112
GPT teacher head0.415
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2021
Admission routes1
Has abstractyes

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