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A Survival Prediction Logistic Regression Models for Blunt Trauma Victims in Japan

Overview
Journal Acute Med Surg
Specialty Critical Care
Date 2017 Nov 11
PMID 29123836
Citations 4
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Abstract

Aim: This research aimed to propose a logistic regression model for Japanese blunt trauma victims.

Methods: We tested whether the logistic regression model previously created from data registered in the Japan Trauma Data Bank between 2005 and 2008 is still valid for the data from the same data bank between 2009 and 2013. Additionally, we analyzed whether the model would be highly accurate even when its coefficients were rounded off to two decimal places.

Results: The model was proved to be highly accurate (94.56%) in the recent data (2009-2013). We also showed that the model remains valid without respiratory rate data and the simplified model would maintain high accuracy.

Conclusion: We propose the equation of survival prediction of blunt trauma victims in Japan to be Ps = 1/(1+e), where b = -0.76 + 1.03 × Revised Trauma Score - 0.07 × Injury Severity Score - 0.04 × age.

Citing Articles

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De Los Rios-Perez A, Garcia A, Gomez P, Arias J, Fandino-Losada A Front Pediatr. 2024; 12:1481467.

PMID: 39726535 PMC: 11669499. DOI: 10.3389/fped.2024.1481467.


On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry.

Bakidou A, Caragounis E, Hagiwara M, Jonsson A, Sjoqvist B, Candefjord S BMC Med Inform Decis Mak. 2023; 23(1):206.

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Validation of the Conventional Trauma and Injury Severity Score and a Newly Developed Survival Predictive Model in Pediatric Patients with Blunt Trauma: A Nationwide Observation Study.

Toida C, Muguruma T, Gakumazawa M, Shinohara M, Abe T, Takeuchi I Children (Basel). 2023; 10(9).

PMID: 37761503 PMC: 10529461. DOI: 10.3390/children10091542.


Validation of age-specific survival prediction in pediatric patients with blunt trauma using trauma and injury severity score methodology: a ten-year Nationwide observational study.

Toida C, Muguruma T, Gakumazawa M, Shinohara M, Abe T, Takeuchi I BMC Emerg Med. 2020; 20(1):91.

PMID: 33208094 PMC: 7672914. DOI: 10.1186/s12873-020-00385-0.

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