MétaCan
Menu
Back to cohort
Record W4387380480 · doi:10.1210/jendso/bvad114.640

FRI127 Delay Of A Decade In The Diagnosis Of Primary Aldosteronism In Patients With Onset Of Hypertension ≤ 40 Yo

2023· article· en· W4387380480 on OpenAlexaff
Stéfanie Parisien‐La Salle, André Lacroix, Isabelle Bourdeau

Bibliographic record

VenueJournal of the Endocrine Society · 2023
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineHypokalemiaSecondary hypertensionPrimary aldosteronismDiabetes mellitusPediatricsAtrial fibrillationInternal medicineCoronary artery diseaseCardiologyBlood pressureEndocrinology

Abstract

fetched live from OpenAlex

Abstract Disclosure: S. Parisien-La Salle: None. A. Lacroix: None. I. Bourdeau: None. Introduction: Primary aldosteronism (PA) is a frequent and underdiagnosed cause of secondary hypertension. Mean age at diagnosis is 50-55 years old (yo), however, hypertension often precedes the diagnosis of PA by many years [1,2]. Objective: To evaluate the delay between the diagnosis of hypertension and the diagnosis of PA in patients with onset of hypertension ≤ 40 yo. Methods: We retrospectively collected the clinical information of patients with PA who were diagnosed with hypertension at ≤ 40 yo from our specialized genetics adrenal clinic. Results: We identified 47 patients with PA who presented with hypertension at ≤ 40 yo. Twenty-one patients (44.7%) were female. At diagnosis of PA, 76.6% (36/47) had hypokalemia, 29.8% (14/47) had sleep apnea, 17% (8/47) had type 2 diabetes, 8.5% (4/47) had coronary artery disease and 4.3% (2/47) had atrial fibrillation. More than half of patients (53.2%) were on 3 or more anti-hypertensive drugs. Mean age at diagnosis of hypertension was 30.8 and mean age at diagnosis of PA was 43.5 yo with an average delay of 12.7 years and a median delay of 10 years (IQR: 4,10,19,37).In the group diagnosed with PA within 10 years of the diagnosis of hypertension (n: 24), the average number of anti-hypertensive drugs per patient was 2.3 and 79.2% (19/24) had hypokalemia. In the group diagnosed with PA more than 10 years after the diagnosis of hypertension (n: 23), the average number of anti-hypertensive drugs per patient was higher at 3.4 with a similar prevalence of hypokalemia (73.9% (17/23)).In patients with hypertension diagnosed ≤ 30 yo (n: 23), the mean age at diagnosis of hypertension was 25.3 yo with a median of 28, and the mean age at diagnosis of PA was of 39.2 yo with a median of 34. Thus, the average delay was 13.9 years and the median was 10 years (IQR: 1.5, 10, 26.5, 37). However, in patients with hypertension diagnosed ≤ 20 yo (n: 5), the mean age at diagnosis of hypertension was 16.8 yo with a median of 18, and the mean age at diagnosis of PA was of 25.4 yo with a median of 21 yo. Thus, the average delay was 8.6 years and the median was 3 years (IQR: 2,3,10,28). Conclusion: We demonstrate that in our cohort the median delay is approximately of 10 years between the diagnosis of hypertension and PA for patients diagnosed with hypertension between 30 and 40 yo. Neither the number of antihypertensive drugs, nor the presence of hypokalemia seemed to determine a shorter delay of diagnosis. However, patients diagnosed with hypertension ≤ 20 yo had shorter delays of diagnosis of PA with a median of 3 years. Bibliography: 1. Alam, S.; Kandasamy, D.; et al. High prevalence and a long delay in the diagnosis of primary aldosteronism among patients with young-onset hypertension. Clin Endocrinol (Oxf)2021, 94, 895-903, doi:10.1111/cen.14409.2. Turcu, A.F.; Yang, J.; Vaidya, A. Primary aldosteronism - a multidimensional syndrome. Nat Rev Endocrinol2022, 18, 665-682, doi:10.1038/s41574-022-00730-2. Presentation: Friday, June 16, 2023

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.029
GPT teacher head0.257
Teacher spread0.228 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Endocrine SocietySame topicHormonal Regulation and HypertensionFrench-language works237,207