Global Hypertension Guidelines; Are Central Haemodynamics Critical and Neglected?
Bibliographic record
Abstract
Abstract Background: Hypertension (HTN) is an elevated blood pressure (BP) compared to normative data. However, physiologically it is a product of the central haemodynamic variables of stroke volume (SV), cardiac output (CO) and systemic vascular resistance (SVR) (BP = (SV x HR) x SVR). Multiple global clinical guidelines recommend anti-hypertensive therapy to reduce BP, yet effective BP control of people diagnosed with HTN remains persistently dismal at ~25% while central haemodynamics are ignored. BP is a cornerstone of HTN practice, yet is an insensitive measure of circulation and sheds little light on the critical therapeutic central haemodynamic variables of SV, CO and SVR, and ultimately may limit our understanding of the pathophysiology of HTN and its management. Methods: Word searches were conducted on Australian, Canadian, Chinese, European, Japanese, Singaporean, UK, US and International hypertension guidelines using the Adobe or Microsoft word count function, with specific searches made for BP, and central haemodynamic parameters, and the results tabulated. Results: A total of 695 pages and 478,537 words were published in nine HTN guidelines by representative global organisations, with BP parameters mentioned 7,535 times, and central haemodynamic parameters mentioned 47 times. All guidelines recommended BP target values and pressure-led therapies, while no central haemodynamic targets were noted. Conclusions: Although physiologically core to the aetiology and treatment of HTN, central haemodyanmic parameters are ignored in current practice guidelines. Poor global outcomes suggest the inclusion of central haemodynamics in everyday practice may improve our understanding of HTN and facilitate the delivery of precise anti-hypertensive therapy.
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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 | 0.012 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".