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Record W2089404812 · doi:10.1097/sla.0000000000001098

International Consensus on Standardization of Data Collection for Complications Associated With Esophagectomy

2015· article· en· W2089404812 on OpenAlexaff
Donald E. Low, Derek Alderson, Ivan Cecconello, Andrew C. Chang, Gail Darling, Xavier Benoît D’Journo, S M Griffin, Arnulf H. Hölscher, Wayne L. Hofstetter, Blair A. Jobe, Yuko Kitagawa, John C. Kucharczuk, Simon Ying Kit Law, Nick Maynard, Manuel Pera, Jeffrey H. Peters, C.S. Pramesh, John V. Reynolds, B. Mark Smithers, J. Jan B. van Lanschot

Bibliographic record

VenueAnnals of Surgery · 2015
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineEsophagectomyPerioperativeEsophageal cancerGeneral surgeryIntensive care medicineDelphi methodSurgeryDelphiChylothoraxChecklistInternal medicineCancer

Abstract

fetched live from OpenAlex

In Brief Introduction: Perioperative complications influence long- and short-term outcomes after esophagectomy. The absence of a standardized system for defining and recording complications and quality measures after esophageal resection has meant that there is wide variation in evaluating their impact on these outcomes. Methods: The Esophageal Complications Consensus Group comprised 21 high-volume esophageal surgeons from 14 countries, supported by all the major thoracic and upper gastrointestinal professional societies. Delphi surveys and group meetings were used to achieve a consensus on standardized methods for defining complications and quality measures that could be collected in institutional databases and national audits. Results: A standardized list of complications was created to provide a template for recording individual complications associated with esophagectomy. Where possible, these were linked to preexisting international definitions. A Delphi survey facilitated production of specific definitions for anastomotic leak, conduit necrosis, chyle leak, and recurrent nerve palsy. An additional Delphi survey documented consensus regarding critical quality parameters recommended for routine inclusion in databases. These quality parameters were documentation on mortality, comorbidities, completeness of data collection, blood transfusion, grading of complication severity, changes in level of care, discharge location, and readmission rates. Conclusions: The proposed system for defining and recording perioperative complications associated with esophagectomy provides an infrastructure to standardize international data collection and facilitate future comparative studies and quality improvement projects. Complications affect every major outcome parameter after major cancer surgery. No internationally accepted system for documenting complications after esophagectomy currently exists. Using the Delphi process, high-volume esophageal surgeons from 14 countries have reached a consensus on a standardized list of complications, quality measures, and definitions for specific complications.

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)0.477
metaresearch head score (Gemma)0.435
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.477
Threshold uncertainty score0.645

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4770.435
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0140.011
Science and technology studies0.0030.009
Scholarly communication0.0090.007
Open science0.0100.016
Research integrity0.0090.015
Insufficient payload (model declined to judge)0.0030.003

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 head0.508
GPT teacher head0.463
Teacher spread0.045 · 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.

Study designNot applicable
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

Citations1,119
Published2015
Admission routes1
Has abstractyes

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