Logistic regression modeling for evaluation of factors affecting trauma outcome in a level I trauma center in Shiraz

Joint Authors

Yadollahi, Mahnaz
Anvar, Mehrdad
Ghaem, Haleh
Bolandparvaz, Shahram
Paydar, Shahram
Izianloo, Fateme

Source

Iranian Red Crescent Medical Journal

Issue

Vol. 19, Issue 1 (31 Jan. 2017), pp.1-9, 9 p.

Publisher

Iranian Hospital

Publication Date

2017-01-31

Country of Publication

United Arab Emirates

No. of Pages

9

Main Subjects

Medicine

Abstract EN

Background: Since injury-related mortality is preventable, identifying factors that inversely affect trauma outcome are important initial steps towards reducing injury burden.

Objectives: This study aims to determine independent risk factors of early/late in-hospital mortality among adult trauma victims with equal injury characteristics and severity at Shahid Rajaee (Emtiaz) Hospital during 2013 and 2014.

PatientsandMethods: Across-sectional study of adult trauma patients (age 15 years) sustaining injury through traffic accidents, violence, andunintentional incidentswasconducted.

Informationwasretrievedfromthree hospital administrative databases.

Data on demographics, injury mechanisms, injured body regions, injury descriptions, outcomes of hospitalization, and development of nosocomial infections were recorded.

Injury severity score was calculated by cross walking from international classification of diseases (ICD-10) injury diagnosis codes to abbreviated injury scale (AIS-98) severity codes.

Two multiple logistic regression models were employed to reflect the partial effect of each covariate on early (within 48 hours) and late (beyond 48 hours) deaths.

Results: There were 47,295 hospitalized patients (male/female ratio: 2.7:1.0) with a median age of 30 years (interquartile range 23 - 44 years).

A crude mortality rate of 1% (454 cases) was observed and 52% of deaths occurred within 48 hours of hospital arrival.

One percent developed a nosocomial infection in the course of admission.

After adjusting for covariates, sustaining a thoracic injury (OR 8.5, 95% CI [4.7 - 15.2]), ISS over 16 (OR 6.4, 95% CI [3.6 - 11.4]) and age over 65 years (OR 5.1, 95% CI [3.0 - 8.8]) were the most important independent risk factors of early trauma death.

Presence of a hospital-acquired infection (OR 12.7, 95% CI [8.9 - 18.1]), age over 65 years (OR 7.4 95% CI [4.5 - 12.1]), and ISS of more than 16 (OR 14.6, 95% CI [6.2 - 34.3]) were independent predictors of late death.

Conclusions: Age, injury severity, injured body region, and hospital-acquired infections are important determinants of trauma outcome in our center.

Timely recognition of factors affecting trauma mortality is crucial for monitoring changes of trauma quality of care.

Our findings suggest the need to allocate resources for trauma prevention along with a potential focus on reducing inhospital complications.

American Psychological Association (APA)

Yadollahi, Mahnaz& Anvar, Mehrdad& Ghaem, Haleh& Bolandparvaz, Shahram& Paydar, Shahram& Izianloo, Fateme. 2017. Logistic regression modeling for evaluation of factors affecting trauma outcome in a level I trauma center in Shiraz. Iranian Red Crescent Medical Journal،Vol. 19, no. 1, pp.1-9.
https://search.emarefa.net/detail/BIM-766366

Modern Language Association (MLA)

Yadollahi, Mahnaz…[et al.]. Logistic regression modeling for evaluation of factors affecting trauma outcome in a level I trauma center in Shiraz. Iranian Red Crescent Medical Journal Vol. 19, no. 1 (Jan. 2017), pp.1-9.
https://search.emarefa.net/detail/BIM-766366

American Medical Association (AMA)

Yadollahi, Mahnaz& Anvar, Mehrdad& Ghaem, Haleh& Bolandparvaz, Shahram& Paydar, Shahram& Izianloo, Fateme. Logistic regression modeling for evaluation of factors affecting trauma outcome in a level I trauma center in Shiraz. Iranian Red Crescent Medical Journal. 2017. Vol. 19, no. 1, pp.1-9.
https://search.emarefa.net/detail/BIM-766366

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 8-9

Record ID

BIM-766366