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Record W4387108073 · doi:10.1016/j.yjpso.2023.100070

Creation of an enhanced recovery after surgery protocol for children with Wilms tumours in low- and middle-income countries

2023· article· en· W4387108073 on OpenAlexafffund
Mercedes Pilkington, Mary Brindle, Godfrey Sama Philipo

Bibliographic record

VenueJournal of Pediatric Surgery Open · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of CalgarySickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersUniversity of British Columbia
KeywordsMedicinePerioperativeProtocol (science)Delphi methodNephrectomyInclusion (mineral)Intensive care medicineGeneral surgeryFamily medicineSurgeryAlternative medicineInternal medicinePathologyPsychology

Abstract

fetched live from OpenAlex

Enhanced Recovery After Surgery guidelines have been developed and shown to improve outcomes for many surgical procedures. Most existing guidelines have been created for patients in high-resource settings. There is a dearth of guidelines for pediatric populations particularly in low- and middle-income countries (LMIC). All children with Wilms tumours require resection for cure and therefore a perioperative care pathway can streamline care for all curative-intent nephrectomies. A two-round Delphi consensus of clinicians in LMICs was utilized to determine the scope and content of recommendations for an enhanced recovery protocol for children with Wilms tumours undergoing nephrectomy in LMICs. Consensus was predefined a priori as ≥70% of panelists indicating a topic or recommendation should be included. Twenty-six topics met consensus for inclusion and were consolidated into twenty recommendations for implementation in the preoperative, intraoperative, and postoperative setting. Predominant themes included perioperative nutrition, surgical safety, anesthetic concerns, and interdisciplinary oncology care. Ten participants completed round one and six completed round two. All recommendations met consensus for inclusion after two rounds. A consensus-derived perioperative care pathway for children with Wilms tumours in low-resource settings is presented. Recommendations share many priorities with high-resource pathways, but also contain unique considerations for a low-resource setting.

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)0.003
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 score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.304
Teacher spread0.283 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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