A recommendation for the use of electrical biosensing technology in neonatology
Bibliographic record
Abstract
Non-invasive cardiac output monitoring, via electrical biosensing technology (EBT), provides continuous, multi-parameter hemodynamic variable monitoring which may allow for timely identification of hemodynamic instability in some neonates, providing an opportunity for early intervention that may improve neonatal outcomes. EBT encompasses thoracic (TEBT) and whole body (WBEBT) methods. Despite the lack of relative accuracy of these technologies, as compared to transthoracic echocardiography, the use of these technologies in neonatology, both in the research and clinical arena, have increased dramatically over the last 30 years. The European Society of Pediatric Research Special Interest Group in Non-Invasive Cardiac Output Monitoring, a group of experienced neonatologists in the field of EBT, deemed it appropriate to provide recommendations for the use of TEBT and WBEBT in the field of neonatology. Although TEBT is not an accurate determinant of cardiac output or stroke volume, it may be useful for monitoring longitudinal changes of hemodynamic parameters. Few recommendations can be made for the use of TEBT in common neonatal clinical conditions. It is recommended not to use WBEBT to monitor cardiac output. The differences in technologies, study methodologies and data reporting should be addressed in ongoing research prior to introducing EBT into routine practice. IMPACT STATEMENT: TEBT is not recommended as an accurate determinant of cardiac output (CO) (or stroke volume (SV)). TEBT may be useful for monitoring longitudinal changes from baseline of hemodynamic parameters on an individual patient basis. TEBT-derived thoracic fluid content (TFC) longitudinal changes from baseline may be useful in monitoring progress in respiratory disorders and circulatory conditions affecting intrathoracic fluid volume. Currently there is insufficient evidence to make any recommendations regarding the use of WBEBT for CO monitoring in neonates. Further research is required in all areas prior to the implementation of these monitors into routine clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".