Perioperative Validation of the TensorTip™ MTX Device for Noninvasive Arterial Pressure Measurement: A Method Comparison Study
Bibliographic record
Abstract
Background: The noninvasive TensorTip™ MTX measures blood pressure by interpreting blood diffusion color of the finger skin. In addition to blood pressure, the device is able to measure various vital signs: heart rate, oxygen saturation, stroke volume, and cardiac output. Studies about accuracy and precision thus far available have only been conducted by the manufacturer. The aim of our study was to investigate the accuracy and precision of the TensorTip MTX in comparison to invasive radial artery blood pressure values. Methods: Forty-one patients scheduled for elective surgery were enrolled in this study. Placement of the arterial catheter had to be part of the standard of care. Once hemodynamic stable conditions were achieved, blood pressure was measured. Three measurements with the TensorTip MTX were averaged and compared with one invasive blood pressure measurement using Bland-Altman plot and error grid analysis. Results: Systolic, diastolic, and mean blood pressure had a bias of respectively 6.2, -6.9 and 4.4 mm Hg. Corresponding standard deviation were respectively 30.1, 17.0 and 22.2. Calculated percentage errors were 47.6%, 52.9% and 52.3%. Proportional bias was present in all Bland-Altman analyses. Error grid analysis showed 61.0% of systolic blood pressure measurements, and 46.3% of mean blood pressure measurements were in the clinical acceptable zone. Conclusions: The TensorTip MTX was not able to reliably measure blood pressure compared to blood pressure obtained with an arterial catheter and therefore, the measurement performance is not clinically acceptable. Moreover, a high malfunction rate makes the device unsuitable for use in perioperative period.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".