Bibliographic record
Abstract
A 6-year-old previously well boy presented with symptoms of obstructive sleep apnoea (OSA) the week before major changes to health-care delivery were implemented due to the COVID-19 pandemic. Examination revealed body mass index 23.3 kg/m2 (>99th percentile) and grade 3 tonsils. Home overnight oximetry was consistent with severe OSA, with a McGill Oximetry Score of 4.1 Usual management of urgent ear, nose and throat review for consideration of adenotonsillectomy was unavailable as routine surgical procedures were suspended due to concerns about high risk of viral exposure during ear, nose and throat clinical contact and surgery. Due to the evolving pandemic, alternative management strategies were considered. Airway stabilisation with continuous positive airway pressure (CPAP) delivered non-invasively is an alternative management option for OSA. This is usually second-line treatment after adenotonsillectomy. Polysomnography was discontinued in our centre in line with the Australasian Sleep Association guidelines due to the COVID-19 pandemic at the same time as elective surgery was suspended, so management of this boy was guided by clinical history and oximetry. Concern regarding CPAP as an aerosol generating procedure had resulted in institutional advice to avoid CPAP in the hospital setting if possible.2 Our patient was started on autotitrating CPAP (autoCPAP) as an outpatient after an initial face-to-face education and mask-fitting session, with the mask not attached. AutoCPAP differs from regular CPAP as it varies the pressure delivered based on feedback algorithms of upper airway resistance.3 Pressure can alter with changes in patient position and sleep state.4 Mean autoCPAP pressure and average device pressure ≤90% was obtained by remotely downloading a modem attached to the autoCPAP using Care Orchestrator (Philips Respironics, Inc., Murrysville, PA, USA). Initial pressure settings were 4–8 cmH2O and downloaded data the following day revealed mean pressure of 6.1 cmH2O and 90% pressure of 8 cmH2O. On the subsequent night the pressure range was increased to 4–12 cmH2O, with resulting mean pressure of 6 cmH2O and 90% pressure of 9 cmH2O. Repeat oximetry on the higher pressure range was normal (Fig. 1). Subsequent compliance downloads showed a mean nightly use of over 9 h and symptomatically the patient is much improved. Depending on COVID-19-related restrictions this patient will remain on nocturnal CPAP until adenotonsillectomy can be performed. Although caution should be taken when relying on oximetry for diagnosis, when oximetry is positive in typically developing older children, autoCPAP can be used to treat OSA if surgery is unavailable or delayed.
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 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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.046 | 0.024 |
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".