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Record W4406978491 · doi:10.1016/j.hpb.2025.01.015

Laparoscopic versus open pancreaticoduodenectomy outcomes in patients ≥ 75 years old: an NSQIP analysis of 4343 patients

2025· article· en· W4406978491 on OpenAlexaff
Noreen Shahbaz, Kevin Verhoeff, Tyrell Wees, Sukhdeep Jatana, Douglas Quan, Juan Glinka, Anton Skaro, Ephraim Tang

Bibliographic record

VenueHPB · 2025
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity of AlbertaWestern University
Fundersnot available
KeywordsMedicinePancreaticoduodenectomyGeneral surgerySurgeryResection

Abstract

fetched live from OpenAlex

BACKGROUND: The benefits of MIS in older adults are conflicting. This study evaluates demographics and early outcomes, for older patients (≥75) undergoing minimally invasive (MIS) versus open pancreaticoduodenectomy (PD). METHOD: We categorized elderly patients who underwent PD from 2017 to 2021 NSQIP databases by surgical approach (open vs MIS). Baseline characteristics were examined with bivariate analysis, and multivariate logistic regression assessed the independent effect of minimally invasive surgery on 30-day serious complications and mortality. RESULTS: Amongst 4137 patients, 150 (3.63 %) underwent MIS PD. Patients demographics were similar. Open cohorts were older (79.1 vs 78.4 years; p = 0.011) with greater tumor invasion (36.6 % vs. 27.0 %; p = 0.018). MIS had longer operations (133.1 vs 119.6 min; p < 0.001). Multivariate analysis demonstrated that MIS approach was associated with increased serious complications (OR 2.21; p < 0.001), but not mortality (OR 2.11; p = 0.173). Post hoc analysis excluding cases converted to open demonstrated no difference in serious complications (OR 1.94; p = 0.070) or mortality (OR 3.58; p = 0.094). PSM analysis estimated a 14.7 % higher rate of serious complications in MIS but similar mortality (p = 0.291). CONCLUSIONS: MIS PD uptake in elderly patients remains limited, with early findings indicating longer operations and higher complications. Further research on patient selection differences, technique modifications, and center expertise is required.

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 score0.012
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.036
GPT teacher head0.395
Teacher spread0.359 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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