Sex differences in diastolic blood pressure changes with age using 24-hour ABPM in 30,513 patients
Bibliographic record
Abstract
Abstract Background We have previously shown, using 24-hour ABPM monitoring, that diastolic blood pressure (DBP) in a large referral population, containing both males and females, increases until age 42 years, following which DBP falls progressively. This occurs in the hypertensive population some 13 years sooner than previous general population studies. There is conflicting emerging data on sex differences in the lifelong trajectory of both systolic and diastolic blood pressure. Purpose To examine sex-specific patterns of diastolic blood pressure throughout the lifespan of patients referred for 24-hour ABPMs. Methods Our database was searched for all 24-hour ABPMs. We used the average 24-hour SBP and DBP for this analysis. Scatter grams were produced for age versus systolic BP (SBP) and DBP for both males and females. Second order polynomial regression was performed on the DBP scatter grams for both genders and their inflection points calculated. The inflection point is the age at which the DBP on the polynomial curve where the slope changes from positive to negative. This, inflection point, corresponds to the age at which DBP begins to decrease. The DBP polynomial curves for males and females were then superimposed to show any gender differences. Results There were 30,513 24-hour analysable ABPMs over 24 years, representing 97% of all ABPMs. There were 15,913 females aged 60.8±14.6 years (range 15–97 years) and 14,600 males aged 58.8±14.2 years (range 15–100 years). As can be seen from the charts below, in females DBP begins to fall at a very early age of 22.3 years, whereas in males the diastolic BP begins to fall at 46.5 years. Conclusions There are significant sex differences in the changes in DBP with increasing age. For the first 35 years DBP is higher in women, thereafter DBP is lower in females and only intersects again much later in life at 95 years. The significance of this sex difference is unclear but may explain the increased prevalence of systolic hypertension in elderly females. Figure 1 Funding Acknowledgement Type of funding source: None
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".