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Record W2804444401 · doi:10.1186/s13049-018-0497-y

One-year and three-year mortality prediction in adult major blunt trauma survivors: a National Retrospective Cohort Analysis

2018· article· en· W2804444401 on OpenAlex
Ting Hway Wong, Nivedita Nadkarni, Hai V. Nguyen, Gek Hsiang Lim, David B. Matchar, Dennis Seow, Nicolas Kon Kam King, Marcus Eng Hock Ong

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.

Bibliographic record

VenueScandinavian Journal of Trauma Resuscitation and Emergency Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineBlunt traumaInjury Severity ScoreNomogramBluntLogistic regressionRetrospective cohort studyComorbidityPopulationInternal medicineCohortInjury preventionPoison controlEmergency medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Survivors of trauma are at increased risk of dying after discharge. Studies have found that age, head injury, injury severity, falls and co-morbidities predict long-term mortality. The objective of our study was to build a nomogram predictor of 1-year and 3-year mortality for major blunt trauma adult survivors of the index hospitalization. METHODS: Using data from the Singapore National Trauma Registry, 2011-2013, we analyzed adults aged 18 and over, admitted after blunt injury, with an injury severity score (ISS) of 12 or more, who survived the index hospitalization, linked to death registry data. The study population was randomly divided 60/40 into separate construction and validation datasets, with the model built in the construction dataset, then tested in the validation dataset. Multivariable logistic regression was used to analyze 1-year and 3-year mortality. RESULTS: Of the 3414 blunt trauma survivors, 247 (7.2%) died within 1 year, and 551 (16.1%) died within 3 years of injury. Age (OR 1.06, 95% CI 1.05-1.07, p < 0.001), male gender (OR 1.53, 95% CI 1.12-2.10, p < 0.01), low fall from 0.5 m or less (OR 3.48, 95% CI 2.06-5.87, p < 0.001), Charlson comorbidity index of 2 or more (OR 2.26, 95% CI 1.38-3.70, p < 0.01), diabetes (OR 1.31, 95% CI 1.68-2.52, p = 0.04), cancer (OR 1.76, 95% CI 0.94-3.32, p = 0.08), head and neck AIS 3 or more (OR 1.79, 95% CI 1.13-2.84, p = 0.01), length of hospitalization of 30 days or more (OR 1.99, 95% CI 1.02-3.86, p = 0.04) were predictors of 1-year mortality. This model had a c-statistic of 0.85. Similar factors were found significant for the model predictor of 3-year mortality, which had a c-statistic of 0.83. Both models were validated on the second dataset, with an overall accuracy of 0.94 and 0.84 for 1-year and 3-year mortality respectively. CONCLUSIONS: Adult survivors of major blunt trauma can be risk-stratified at discharge for long-term support.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.328
Teacher spread0.291 · 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