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Record W2043045425 · doi:10.1016/j.ijscr.2015.01.013

Aldosterone deficiency after unilateral adrenalectomy for Conn’s syndrome: a case report and literature review

2015· article· en· W2043045425 on OpenAlexaff
Ekua Yorke, Sara Stafford, Daniel T. Holmes, Sachiv Sheth, Adrienne Melck

Bibliographic record

VenueInternational Journal of Surgery Case Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsProvidence Health CareSurrey Memorial HospitalSt. Paul's Hospital
Fundersnot available
KeywordsMedicineHypoaldosteronismAdrenalectomyPrimary aldosteronismAldosteroneHyperaldosteronismPopulationSurgeryInternal medicineBlood pressureRenin–angiotensin system

Abstract

fetched live from OpenAlex

INTRODUCTION: Approximately 35% of cases of Conn's syndrome (primary aldosteronism) result from a solitary functioning adrenal adenoma, and these patients are best managed by adrenalectomy. Postoperative hypoaldosteronism after unilateral adrenalectomy is uncommon. CASE PRESENTATION: We present a case and literature review of hypoaldosteronism after unilateral adrenalectomy for Conn's syndrome, which demonstrates the insidious and sometimes delayed presentation. DISCUSSION: In this clinical case we summarize the previously published cases of post-adrenalectomy hypoaldosteronism based on a PUBMED and EBSCOhost search of all peer-reviewed publications (original articles and reviews) on this topic. A few cases of aldosterone insufficiency post-adrenalectomy for Conn's syndrome were identified. The etiological factors for prolonged selective suppression of aldosterone secretion after unilateral adrenalectomy remain unclear. CONCLUSION: It is important to be aware of the risk of postoperative hypoaldosteronism in this patient population. Close postoperative follow-up is necessary and strongly recommended, especially in patients with certain risk factors. Patients may need mineralocorticoid supplementation during this period.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.045
GPT teacher head0.318
Teacher spread0.273 · 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 designCase report
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

Citations12
Published2015
Admission routes1
Has abstractyes

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