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Record W2974794074 · doi:10.1136/bmjopen-2019-031319

Passive versus active intra-abdominal drainage following pancreatic resection: does a superior drainage system exist? A protocol for systematic review

2019· article· en· W2974794074 on OpenAlexafffund
Lily Park, Laura Baker, Heather Smith, Alexandra Davies, Jad Abou Khalil, Guillaume Martel, Fady Balaa, Kimberly A. Bertens

Bibliographic record

VenueBMJ Open · 2019
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsMedicineDrainageProtocol (science)Abdominal surgerySurgeryGeneral surgeryPathologyAlternative medicine

Abstract

fetched live from OpenAlex

Background Clinically relevant postoperative pancreatic fistula (CR-POPF) is the most common cause of major morbidity following pancreatic resection. Intra-abdominal drains are frequently positioned adjacent to the pancreatic anastomosis or transection margin at the time of surgery to aid in detection and management of CR-POPF. Drains can either evacuate fluid by passive gravity (PG) or be attached to a closed suction (CS) system using negative pressure. There is controversy as to whether one of these two systems is superior. The objective of this review is to identify and compare the incidence of adverse events (AEs) and resource utilisation associated with PG and CS drainage following pancreatic resections. Methods and analysis MEDLINE, EMBASE, CINAHL and Cochrane Central Registry of Controlled Trials will be searched from inception to April 2019, to identify interventional and observational studies comparing PG and CS drains following pancreatic resection. The primary outcome is POPF as defined by the International Study Group for Pancreatic Fistula in 2017. Secondary outcomes include postoperative AE, resource utilisation (length of stay, return to emergency department, readmission and reintervention), time to drain removal and quality of life. Study selection, data extraction and risk of bias assessment will be performed independently, by two reviewers. A meta-analysis will be conducted if deemed statistically appropriate. Subgroup analysis by study design will be performed. Study heterogeneity will be calculated with the χ 2 test and reported as I 2 statistics. Statistical analyses will be conducted and displayed using RevMan V.5.3 Ethics and dissemination Ethics approval is not required. The results of this study will be submitted to relevant conferences for presentation and peer-reviewed journals for publication. PROSPERO registration number CRD42019123647.

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)0.042
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.042
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.071
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0210.015
Bibliometrics0.0160.015
Science and technology studies0.0030.004
Scholarly communication0.0070.008
Open science0.0040.004
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0380.003

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 head0.087
GPT teacher head0.471
Teacher spread0.384 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations2
Published2019
Admission routes2
Has abstractyes

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