Accuracy and Safety of a Continuous Noninvasive Blood Pressure Monitor in Neonates
Bibliographic record
Abstract
INTRODUCTION: Accurate and continuous blood pressure (BP) monitoring in neonates is crucial in the intensive care unit. Invasive arterial lines (IALs), oscillometric cuffs, and current noninvasive continuous BP monitoring devices have significant limitations. The Boppli® device is a novel, continuous, noninvasive BP device that requires no calibration, designed for neonates. METHODS: This prospective, multicenter study evaluated the performance, usability, and safety of the Boppli device in neonates <5 kg. We compared mean arterial pressure (MAP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) measurements from the Boppli with IAL reference values by calculating average values of mean average error (MAE) and standard deviation (SD) for each patient, then averaging those means. Safety and usability were evaluated by analysis of adverse events and survey data, respectively. RESULTS: The Boppli device demonstrated good performance, meeting the FDA requirements of MAE and SD of the entire cohort: MAE (SD) 0.7 (5.3) mm Hg for MAP, -0.8 (7.7) mm Hg for SBP, and 1.4 (4.7) mm Hg for DBP. Patients with elevated MAPs, Asian ethnicity, and lower extremity IALs were the subgroups with MAE >±5 mm Hg. Various subgroups had SDs >8 mm Hg attributed to low sample sizes. The device received high usability scores from clinicians and parents. No serious adverse events were reported. CONCLUSION: The Boppli device is a promising alternative for continuous noninvasive BP monitoring in neonates, offering good accuracy and usability. The device, which received 510(k) clearance in September 2023, was well received by clinicians and parents, with a low-risk profile.
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".