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Record W4384697481 · doi:10.1177/14604086231184505

Can we predict failure of non-operative management of blunt splenic injuries on arrival? A comparison of predictors of immediate splenectomy versus splenectomy secondary to non-operative management failure

2023· article· en· W4384697481 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTrauma · 2023
Typearticle
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsUniversity of TorontoCanadian Armed ForcesSt. Michael's Hospital
Fundersnot available
KeywordsMedicineSplenectomyInjury Severity ScoreSurgeryTrauma centerLogistic regressionBluntShock (circulatory)Blunt traumaRetrospective cohort studySpleenEmergency medicinePoison controlInjury preventionInternal medicine

Abstract

fetched live from OpenAlex

Aims and Background The spleen is the most frequently injured solid organ after blunt trauma and a trial non-operative management (NOM) has become the standard of care in hemodynamically stable patients. It remains uncertain which patients are at increased risk of non-operative management failure (NOMF) at initial presentation. We explored whether clinical variables including the contemporary rotational thromboelastography (ROTEM) parameters are predictive of NOMF. Materials and Methods Data for all adult patients with a blunt splenic injury was collected retrospectively at St. Michael’s Hospital in Toronto, Canada between 2005 and 2021. Those who underwent a splenectomy within 4 hours of presentation were classified as direct operative management (OM), while those who had a splenectomy after 4 hours of observation were classified as NOM failure. Vital signs on arrival and injury characteristics were collected. Logistic regression was used to identify predictors of OM and predictors of NOM failure. Results Seven hundred and seventeen patients were identified with splenic injury during our study period. The median Injury Severity Score (ISS) was 27 (IQR 17–36), and 19% ( n = 134) had a shock index of 1 or more. One hundred and eleven (15.5%) underwent direct operative management. A shock index above 1 and increasing spleen injury severity were strong predictors of patients undergoing direct OM. The remaining 606 patients underwent NOM of which 59% ( n = 357) of these were admitted to the ICU. NOM failure occurred in 7.4% ( n = 45) with a median time to NOM failure of 23 (IQR 8–72) hours. The American Association for the Surgery of Trauma (AAST) spleen injury severity was the major factor significantly associated with NOM failure. Conclusions The only major predictor of NOMF available on arrival is increased spleen injury grade. Other clinical variables such as age, vital signs on arrival, and bloodwork were not significantly able to predict NOM failure. Additional investigation is required to identify novel predictors of NOM failure.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.322
Teacher spread0.302 · 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