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Record W2617706798 · doi:10.3390/children4050041

Respiratory Care Considerations for Children with Medical Complexity

2017· review· en· W2617706798 on OpenAlexaff
Jackie Chiang, Reshma Amin

Bibliographic record

VenueChildren · 2017
Typereview
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsHospital for Sick ChildrenHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
Fundersnot available
KeywordsIntensive care medicineMedicineRespiratory careHealth careRespiratory systemIntensive careRespiratory diseaseHealth technologyLungInternal medicine

Abstract

fetched live from OpenAlex

Children with medical complexity (CMC) are a growing population of diagnostically heterogeneous children characterized by chronic conditions affecting multiple organ systems, the use of medical technology at home as well as intensive healthcare service utilization. Many of these children will experience either a respiratory-related complication and/or they will become established on respiratory technology at home during their care trajectory. Therefore, healthcare providers need to be familiar with the respiratory related complications commonly experienced by CMC as well as the indications, technical and safety considerations and potential complications that may arise when caring for CMC using respiratory technology at home. This review will outline the most common respiratory disease manifestations experienced by CMC, and discuss various respiratory-related treatment options that can be considered, including tracheostomy, invasive and non-invasive ventilation, as well as airway clearance techniques. The caregiver requirements associated with caring for CMC using respiratory technology at home will also be reviewed.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.184
GPT teacher head0.406
Teacher spread0.222 · 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

Citations32
Published2017
Admission routes1
Has abstractyes

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