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Record W4396670568 · doi:10.1097/as9.0000000000000430

Patient and Hospital Characteristics Associated with Admission Among Patients With Minor Isolated Extremity Firearm Injuries: A Propensity-Matched Analysis

2024· article· en· W4396670568 on OpenAlex
Arielle Thomas, Regina Royan, Avery B. Nathens, Brendan T. Campbell, Susheel Reddy, Sarabeth A. Spitzer, Doulia Hamad, Angie Jang, Anne M. Stey

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

VenueAnnals of Surgery Open · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGun Ownership and Violence Research
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNational Heart, Lung, and Blood InstituteAgency for Healthcare Research and QualityNational Institutes of Health
KeywordsPropensity score matchingMedicineOdds ratioEmergency departmentConfidence intervalEmergency medicineLogistic regressionRetrospective cohort studyPoison controlComorbidityInjury Severity ScoreCohortInjury preventionCohort studyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Objective: To quantify the association between insurance and hospital admission following minor isolated extremity firearm injury. Background: The association between insurance and injury admission has not been examined. Methods: This was an observational retrospective cohort study of minor isolated extremity firearm injury captured in the Healthcare Cost and Utilization Project State Inpatient and Emergency Department Databases in 6 states (New York, Arkansas, Wisconsin, Massachusetts, Florida, and Maryland) from 2016 to 2017 among patients aged 16 years or older. The primary exposure was insurance. Admitted patients were propensity score matched to nonadmitted patients on age, extremity Abbreviated Injury Score, and Elixhauser Comorbidity Index with exact matching within hospital to adjust for selection bias. A general estimating equation logistic regression estimated the association between insurance and odds of admission in the matched cohort while controlling for sex, race, injury intent, injury type, hospital profit type, and trauma center designation with observations clustered by propensity score-matched pairs within hospital. Results: A total of 8151 patients presented to hospital with a minor isolated extremity firearm injury between 2016 and 2017 in 6 states. Patients were 88.0% male, 56.6% Black, and 71.7% aged 16 to 36 years old, and 22.1% were admitted. A total of 2090 patients were matched on propensity for admission. Privately insured matched patients had 1.70 higher adjusted odds of admission and 95% confidence interval of 1.30 to 2.22, compared with uninsured after adjusting for patient and hospital characteristics. Conclusions: Insurance was associated with hospital admission for minor isolated extremity firearm injury.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.073
GPT teacher head0.338
Teacher spread0.265 · 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