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Record W2000883062 · doi:10.5489/cuaj.977

The diagnosis and treatment of primary adrenal lipomatous tumors in Chinese patients: a 31-year follow-up study

2014· article· en· W2000883062 on OpenAlexvenueno aff
Fukang Sun, Juping Zhao, Xiaolong Jing, Wenlong Zhou, Xin Huang, Haofei Wang, Yu Zhu, Fei Yuan, Zhoujun Shen

Bibliographic record

VenueCanadian Urological Association Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLiposarcomaAdrenal glandMyelolipomaLipomaTeratomaSurgeryRadiologyPathologySarcoma

Abstract

fetched live from OpenAlex

INTRODUCTION: Adrenal lipomatous tumours (ALTs) are rarely encountered in clinical practice and consequently little is known about their clinical features. METHODS: We analyze the clinical features, diagnosis and treatment of ALTs based on cases presenting at a single centre over a 31-year period. We reviewed clinical data from patients with primary adrenal tumours treated at the Ruijin Hospital, Shanghai between January 1980 and December 2010. RESULTS: A total of 73 cases of primary ALTs in 22 men and 51 women (mean age 51.1±14.2 years) were reviewed. The ALTs included 65 myelolipomas (89.0%), 3 lipomas (4.1%), 2 angiomyolipomas (2.7%), 2 teratomas (2.7%), and 1 liposarcoma (1.4%). Of the total 73 patients, 24 of them had tumours in the left adrenal gland, 47 in the right gland and 2 had bilateral tumours. In total, 51 patients underwent open surgery and 22 laparoscopic surgery. CONCLUSION: Myelolipoma is predominant among the various types of lipomatous adrenal gland tumours; it accounts for about 90% of all cases. Surgery is recommended for tumours ≥3.5 cm in diameter, for all cases of symptomatic tumour, and for cases of teratoma or liposarcoma identified by preoperative imaging.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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

Citations24
Published2014
Admission routes1
Has abstractyes

Explore more

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