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Cardiorespiratory Monitoring Data during Sleep in Healthy Canadian Infants

2020· article· en· W3043548131 on OpenAlexaffabout
Kevin Vézina, Jennifer Mariasine, Rochelle Young, Myrtha E. Reyna, Zihang Lu, Padmaja Subbarao, Theo J. Moraes, Allan B. Becker, Stuart E. Turvey, Malcolm R. Sears, Diana L. Lefebvre, Meghan B. Azad, Carmen Rasmussen, Jacqueline Pei, Indra Narang, Piush J. Mandhane

Bibliographic record

VenueAnnals of the American Thoracic Society · 2020
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversity of AlbertaChildren's Hospital Research Institute of ManitobaUniversity of ManitobaSickKids FoundationUniversity of TorontoMcMaster UniversityAlberta Health ServicesUniversity of British ColumbiaHospital for Sick Children
Fundersnot available
KeywordsMedicineCardiorespiratory fitnessPercentilePolysomnographyApneaNasal cannulaOxygen saturationSleep (system call)Sleep apneaPlethysmographRespiratory rateHeart ratePhysical therapyPediatricsAnesthesiaBlood pressureInternal medicineSurgeryStatisticsCannula

Abstract

fetched live from OpenAlex

Abstract Rationale Sleep study interpretation in children needs to be based on age-specific normal values. Although several studies have reported normal cardiorespiratory parameters during sleep in children and adolescents, few have included younger children. Objectives To describe cardiopulmonary indices, specifically oxygen saturation and heart rate, as well as frequency of obstructive and central apneas in healthy 1-year-old Canadian infants during sleep. Methods Home sleep cardiorespiratory monitoring was performed among infants participating in the Edmonton subcohort of the CHILD (Canadian Healthy Infant Longitudinal Development) study at their 1-year follow-up visit. A portable sleep monitoring device, which included a nasal pressure cannula, an oronasal thermal airflow sensor, a pulse oximeter, and respiratory inductance plethysmography belts, was used to collect sleep architecture and cardiorespiratory data during one night of monitoring in the home. Sleep scoring was done in blocks of 5 minutes using a novel pilot sleep scoring algorithm. Results Among the 562 subjects (mean ± standard deviation age 1.1 ± 0.2 yr) who attempted home sleep cardiorespiratory monitoring, 91% provided technically acceptable data with no loss of signal preventing analysis of any parameter. Obstructive and central apneas were rare, with a median obstructive apnea index of 0.0 events/h (10th percentile, 0.0; 90th percentile, 0.5) and a median central apnea index of 2.5 events/h (10th percentile, 0.6; 90th percentile, 7.1). Median oxygen saturation was 97.0% (10th percentile, 95.4; 90th percentile, 97.9). The oxygen desaturation index was 6.7 events/h (10th percentile, 1.4; 90th percentile, 15.8), with infants spending only 0.1% (10th percentile, 0.0; 90th percentile, 0.6) of the time with an oxygen saturation below 92%. Conclusions These results provide important reference data for healthy infants undergoing cardiorespiratory monitoring during sleep.

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)0.001
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 score0.066
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.197
GPT teacher head0.444
Teacher spread0.247 · 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".

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Citations21
Published2020
Admission routes2
Has abstractyes

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