12 BLOOD PRESSURE MEASUREMENT USING A CUFFLESS SMARTWATCH / SMARTPHONE VERSUS CONVENTIONAL CUFFED-BASED: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
Aims: This study aimed to compare blood pressure (BP) measurement results between cuffless and conventional cuffed-based devices. Methods: Systematic literature searches of PubMed, Science Direct, Proquest, and Springer Link databases were performed on June 2021. Studies comparing data of in- office BP measurement, including systolic blood pressure (SBP) and diastolic blood pressure (DBP), in healthy adult subjects using cuffless and conventional cuffed- based devices are included. BP measurement should be conducted twice and alternately using both devices at one time. Studies that reported only one outcome parameter were also included. Two reviewers evaluate the quality of included studies using The Newcastle-Ottawa Scale. A random-effects meta-analysis of mean difference (MD) was conducted. A publication bias test was conducted using a funnel plot for outcomes that have ten studies included. Results: We identified eleven studies comprising of 2344 healthy adult subjects which three studies only reported SBP data. The included studies tend to have reporting and attrition bias. The meta-analysis results showed that cuffless device measured lower than conventional cuffed-based device for SBP by 2.64 mmHg (MD -2.64, 95%CI - 4.83 to -0.46, p=0.02; I2 74.5%). However, DBP results have no difference for both devices (MD -0.43, 95%CI -3.88 to 3.02, p=0.81; I2 91.1%). The funnel plot demonstrated slightly asymmetrical distribution of studies that indicating lower measurements for SBP most likely found in study with large samples. Conclusion: The cuffless device measured lower SBP compared than the conventional cuffed-based device whereas there is no difference in DBP. Nevertheless, the heterogeneity between studies was high.
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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 | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".