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Nocturnal Oximetry Reference Values in Healthy Term Infants Aged 1-6 Months

2023· article· en· W4387970664 on OpenAlexaboutno aff
Maria Eleni Liagkaki, Anastasia Polytarchou, Angeliki Moudaki, Georgia Koltsida, Christina Kanaka‐Gantenbein, Athanasios G. Kaditis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHypoxemiaPediatricsAirway obstructionNocturnalPulse oximetryPolysomnographyApneaReference valuesInternal medicineAnesthesiaAirway

Abstract

fetched live from OpenAlex

Although nocturnal oximetry has been used for OSAS management in resource-limited settings, little evidence is available regarding reference values in infancy. Our aim was to summarize reference values for oximetry parameters in healthy infants aged 1-6 months. Methods: Prospectively collected oximetry data from full-term infants without history of apnea, upper airway obstruction (UAO), craniofacial abnormalities, neuromuscular disorders, genetic syndromes or lung disease were analyzed. Summary statistics of oxyhemoglobin desaturation (≥3%) index (ODI3),baseline SpO2, and cumulative nocturnal hypoxemia score ([%recording time-%RT with SpO2 90–94%]X1 + [%RT with SpO2 85–89%]X2 + [%RT with SpO2 80–84%]X3 + [%RT with SpO2 ≤79%]X4) as well as frequency of abnormal McGill Oximetry Score (MOS>1) were calculated. Results: Data from 51 infants (median age 2.8 months; range 1-6.6) were analyzed (Table). ODI3 decreased linearly with age (P=.01) and MOS was abnormal in an appreciable proportion of participants. Conclusions: In the first 1-6 months of life, nocturnal baseline SpO2 is above 95% and-in contrast to older children-ODI3 decreases with age while MOS is frequently abnormal in the absence of UAO.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.110
GPT teacher head0.444
Teacher spread0.334 · 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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Citations1
Published2023
Admission routes1
Has abstractyes

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