KEEP THE FIRST READING: AN ARGUMENT FOR THE IMPORTANCE OF THE FIRST OFFICE BLOOD PRESSURE READING IN CHILDREN
Bibliographic record
Abstract
Objective: Lately, clinicians are using oscillometric devices with repeated blood pressure (BP) measurements (on the same occasion) to diagnose hypertension in children. It is unclear which of these measurements, or which combination of measurements, is the most predictive of ambulatory hypertension. Our objective was to determine which measurements of office BP correlate best with the 24-hour automated BP (ABPM). Design and method: We consecutively enrolled all pediatric patients, aged 1–18 years, who underwent ABPM in the last 3 years at The Children's Hospital of Eastern Ontario; all patients also had 3 consecutive oscillometric office blood pressure readings at the same time. We compared the first, second, and third and the average of all three measurements as well as the average of the last 2 readings with daytime BP from ABPM. All BP readings were converted to Z-scores based on published, normative paediatric data for office and ABPM. Results: Two-hundred and forty-five children (male=133) were included in the study. The median [IQR] of first, second and third systolic BP Z-scores (SBPz) were 2.29[1.44,3.21], 1.91[1.13,2.72] and 1.65[0.82, 2.47], respectively, and all were significantly different from one another (p < 0.001). The largest difference/effect size was noted between the first and third measurement of SBPz (Cohen-d 0.51). Similar differences were observed in diastolic blood pressure Z-scores (DBPz), with medians [IQR] of 0.97[0.00, 1.87], 0.77[-0.19, 1.75] and 0.55[-0.37, 1.54] respectively (p < 0.001, Cohen-d between first and third reading 0.32). On multivariate analysis, the only significant predictor of systolic daytime BP was the first office systolic BP reading (p = 0.001, relative importance 43%). Similarly, the only significant predictor of diastolic daytime BP was the first office diastolic BP reading (p < 0.001, relative importance 43%). The first office SBPz and DBPz were also the best predictors of daytime systolic (ABPM SBPz > 1.65) and diastolic (ABPM DBPz > 1.65) hypertension on ROC with area under the curve (AUC) analysis (SBPz AUC = 0.69, DBPz AUC = 0.81). Conclusions: We observed significant differences between first, second and third office BP measurements. The first office systolic and diastolic BP readings appear to be the best predictors of ABPM daytime systolic and diastolic BP.
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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 | 0.064 | 0.231 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| 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".