Prolonged, documented home‐monitoring of oxygenation in infants and children
Bibliographic record
Abstract
RATIONALE: Although home cardiorespiratory monitors have been used for a few decades, they do not give information on oxygenation status during events. Pulse oximeters with low false-alarm rates are now available but with no standards for alarm adjustment. OBJECTIVE: To determine, in a population of children monitored at home with a pulse oximeter, whether the chosen alarm levels could safely identify potentially significant events early on but also limit the number of alarms for non-significant events. METHODS: Retrospective cohort study of all children monitored at home with a pulse oximeter (n = 37) between 2002 and 2007. Clinical information and Hb-O(2) saturation (SpO(2)) recordings were reviewed. Audible alarm was set-up when SpO(2) reached 85% with a delay of 5 or 10 sec. RESULTS: A total of 24,127 hr of valid data were available for analysis. There were 13,228 events >4 sec of which 9177 (69%) were events lasting <10 sec. We determine that, with an audible alarm being triggered when SpO(2) reached 85% with no delay or a delay of 5 or 10 sec, audible alarms would have occurred at a rate of 3.6, 0.9, and 0.2 alarm/night (median), respectively. Thirteen patients needed intervention following alarms. Ten patients were readmitted to the hospital on the basis of increased frequency of alarms confirmed as true events on the recordings, but in the absence of clinical deterioration. CONCLUSION: The monitor was able to alert parents as to potentially dangerous events while the alarm adjustment limited the number of alarms for non-significant events.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".