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Record W4313366721 · doi:10.1097/hjh.0000000000003326

A meta-analysis of the haemodynamics of primary hypertension in children and adults

2022· review· en· W4313366721 on OpenAlexaff
Ye Li, Emily Haseler, Ryan McNally, Manish D. Sinha, Phil Chowienczyk

Bibliographic record

VenueJournal of Hypertension · 2022
Typereview
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsSt. Thomas Hospital
FundersBritish Heart FoundationMedical Research CouncilNational Institute for Health and Care Research
KeywordsMedicineVascular resistanceCardiac outputInternal medicineCardiologyHemodynamics

Abstract

fetched live from OpenAlex

We performed a systematic review and meta-analysis to determine the relative contributions of elevated cardiac output and systemic vascular resistance to hypertension in children and adults. This included 27 studies on 11 765 hypertensive and normotensive children and adults in whom cardiac output was measured. Cardiac output but not systemic vascular resistance was elevated in hypertensive compared to normotensive children and young adults (difference in means 1.15 [0.78-1.52] l/min, P < 0.001). In older hypertensive adults, both were elevated compared to normotensive individuals (0.40 [0.26-0.55] l/min, P < 0.001 and 3.21 [1.91-4.51] mmHg min/l, P < 0.001 for cardiac output and systemic vascular resistance, respectively). The main haemodynamic alteration in primary hypertension (including obesity-hypertension) in both children and young to middle-aged adults is an elevation of cardiac output. With longer duration and greater severity of hypertension there may be progression from a 'cardiac' to a 'vascular' phenotype with increased systemic vascular resistance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.026
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.142
GPT teacher head0.299
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations23
Published2022
Admission routes1
Has abstractyes

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