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Record W2278226331 · doi:10.1016/j.amjsurg.2016.01.012

Open abdomen with negative pressure device vs primary abdominal closure for the management of surgical abdominal sepsis: a retrospective review

2016· review· en· W2278226331 on OpenAlexaff
M. Bleszynski, Tiffany Chan, Andrzej K. Buczkowski

Bibliographic record

VenueThe American Journal of Surgery · 2016
Typereview
Languageen
FieldMedicine
TopicAbdominal Surgery and Complications
Canadian institutionsUniversity of British ColumbiaVancouver General Hospital
Fundersnot available
KeywordsMedicineLaparotomyAbdomenOdds ratioSurgerySeptic shockDamage control surgeryNegative-pressure wound therapySepsisAbdominal surgeryIntensive care unitConfidence intervalMortality rateResuscitationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Open abdomen with temporary abdominal closure remains a controversial management strategy for surgical abdominal sepsis compared with primary abdominal closure (PAC) and on-demand laparotomy. The primary objective was to compare mortality between PAC and open abdomen with vacuum assisted closure (VAC). METHODS: Retrospective review of a tertiary center intensive care unit database (2006 to 2010) including suspected/diagnosed severe abdominal sepsis/septic shock requiring source control laparotomy. Groups were categorized according to closure method at index source control laparotomy. APACHE-IV was used as a measure of disease severity. RESULTS: Of 211 patients, 75 PAC and 136 VAC cases were included. Controlling for disease severity, adjusted odds ratio of mortality for VAC was .41 95% confidence interval (.21, .81; P = .01) compared with PAC. PAC and VAC APACHE-1V predicted mortality rate were both 45%. VAC mortality was lower than PAC (22.8% vs 38.6%; P = .012). CONCLUSIONS: Open abdomen with VAC is associated with significantly improved survival compared with PAC in abdominal sepsis requiring laparotomy.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.367
Teacher spread0.306 · 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 designObservational
Domainnot available
GenreReview

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

Citations37
Published2016
Admission routes1
Has abstractyes

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