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Record W2757803884

Secondary Hypertension: Discovering the Underlying Cause.

2017· article· en· W2757803884 on OpenAlexaff
Lesley Charles, Jean Triscott, Bonnie Dobbs

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineSecondary hypertensionRenal artery stenosisRenovascular hypertensionInternal medicineHyperaldosteronismCardiologyBlood pressureCoarctation of the aortaACE inhibitorEtiologyPediatricsKidneyRenal arteryAngiotensin-converting enzymeAortaAldosterone
DOInot available

Abstract

fetched live from OpenAlex

Most patients with hypertension have no clear etiology and are classified as having primary hypertension. However, 5% to 10% of these patients may have secondary hypertension, which indicates an underlying and potentially reversible cause. The prevalence and potential etiologies of secondary hypertension vary by age. The most common causes in children are renal parenchymal disease and coarctation of the aorta. In adults 65 years and older, atherosclerotic renal artery stenosis, renal failure, and hypothyroidism are common causes. Secondary hypertension should be considered in the presence of suggestive symptoms and signs, such as severe or resistant hypertension, age of onset younger than 30 years (especially before puberty), malignant or accelerated hypertension, and an acute rise in blood pressure from previously stable readings. Additionally, renovascular hypertension should be considered in patients with an increase in serum creatinine of at least 50% occurring within one week of initiating angiotensin-converting enzyme inhibitor or angiotensin receptor blocker therapy; severe hypertension and a unilateral smaller kidney or difference in kidney size greater than 1.5 cm; or recurrent flash pulmonary edema. Other underlying causes of secondary hypertension include hyperaldosteronism, obstructive sleep apnea, pheochromocytoma, Cushing syndrome, thyroid disease, coarctation of the aorta, and use of certain medications.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.157
GPT teacher head0.293
Teacher spread0.136 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations132
Published2017
Admission routes1
Has abstractyes

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