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Record W4388041261 · doi:10.3390/diagnostics13213351

Laparoscopic Adrenalectomy: Tailoring Approaches for the Optimal Resection of Adrenal Tumors

2023· article· en· W4388041261 on OpenAlexaff
Ionela Mihai, Adrian Boicean, Cosmin Adrian Teodoru, Nicolae Grigore, Gabriela Mariana Iancu, Horațiu Dura, Dan Bratu, Mihai Roman, Cosmin Ioan Mohor, Samuel Bogdan Todor, Cristian Ichim, Ciprian Bacilă, Nicolae Bacalbașa, Ciprian Bolca, Adrian Hașegan

Bibliographic record

VenueDiagnostics · 2023
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsUniversité de Sherbrooke
FundersUniversitatea "Lucian Blaga" din Sibiu
KeywordsMedicineAdrenalectomyBlood lossSurgeryResectionLaparoscopy

Abstract

fetched live from OpenAlex

In this study, we investigated the outcomes of laparoscopic approaches for adrenal tumor resection in 67 patients from a single center with a median age of 51 (range 40–79). Predominantly comprising women, the majority of patients were overweight or obese. Adrenal tumors larger than 6 cm were mostly treated using the laparoscopic transperitoneal method (p < 0.001). Our results revealed that patients subjected to the retroperitoneal approach exhibited quicker recovery, as evidenced by faster resumption of oral intake and ambulation, along with reduced intraoperative blood loss and shorter hospitalization (p-value < 0.05). In contrast, patients subjected to the transperitoneal approach experienced minimal complications, though not statistically significant, despite the technique’s intricacy and slower recovery. These findings emphasize the significance of tailoring the surgical approach to individual patient characteristics, with particular emphasis on the tumor size. The choice between the retroperitoneal and transperitoneal methods should be informed by patient-specific attributes to optimize surgical outcomes. This study underscores the need for a comprehensive evaluation of factors such as tumor characteristics and postoperative recovery when determining the most suitable laparoscopic approach for adrenal tumor resection. Ultimately, the pursuit of individualized treatment strategies will contribute to improved patient outcomes in adrenal tumor surgery.

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 score0.300
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.075
GPT teacher head0.299
Teacher spread0.224 · 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

Citations20
Published2023
Admission routes1
Has abstractyes

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