Cargando…
Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry
BACKGROUND: Road Traffic Injuries (RTIs) is considered as one of the main health challenges and causes of mortality, worldwide and especially in Iran. Predicting the place where RTIs-related death takes place is vital in decreasing this type of mortality. The purpose of the present study was to iden...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902731/ https://www.ncbi.nlm.nih.gov/pubmed/35260101 http://dx.doi.org/10.1186/s12873-022-00593-w |
_version_ | 1784664650487431168 |
---|---|
author | Homayoun, Sadeghi-Bazargani Milad, Jamali-Dolatabad Mina, Golestani Parvin, Sarbakhsh |
author_facet | Homayoun, Sadeghi-Bazargani Milad, Jamali-Dolatabad Mina, Golestani Parvin, Sarbakhsh |
author_sort | Homayoun, Sadeghi-Bazargani |
collection | PubMed |
description | BACKGROUND: Road Traffic Injuries (RTIs) is considered as one of the main health challenges and causes of mortality, worldwide and especially in Iran. Predicting the place where RTIs-related death takes place is vital in decreasing this type of mortality. The purpose of the present study was to identify the predictors of RTI fatalities with respect to the place of death (hospital vs. pre-hospital) during the recent decade in East Azerbaijan Province, Iran. METHODS: Overall, 7347 RTI fatalities were retrieved from the road traffic injuries registry which is supported by the Forensic Medicine Organization in East Azerbaijan. Among these cases, 2758(37.5%)) were hospital deaths. The registered variables of these cases were analysed using bivariate and multiple logistic regression (STATA version 15). RESULTS: Out of 7347 deaths, 5862 (79.8%) were men and the rest were women 1485 (20.2%).The mean age was 40.3 (SD = 20.8). Of the total number of cases, 2758 (37.5%) died in hospital death and the rest 4589 (62.5) were pre-hospital death. According to the results of the present study, inter-city RTI (OR = 1.7, CI 95% = (1.5–2)) and RTIs inside the city of Tabriz (OR = 1.4, CI 95% = (1.2–1.6)) increases the chance of hospitals death. In addition, having a heavy counterpart vehicle compared to no counterpart vehicle decreased the chances of hospitals death (OR = 0.46, CI 95% = (0.39–0.55)) while motorcycle or bike counterpart vehicle compared to no counterpart vehicle increased the chances of hospital death (OR = 2.26, CI 95% = (1.59–3.22)). Also the users of the motorcycle or bike vehicle compared to the pedestrians increased the chances of hospital death (OR = 1.43, CI 95% = (1.19–1.71)) while any the other vehicle users compared to the pedestrians have significantly lower chances for hospital death. Other factors that increased hospitals death were transferring injured people by ambulance (OR = 1.3, CI 95% = (1.1–1.6)) and being elderly (OR = 1.5, CI 95% = (1.2–1.7)). Moreover, it was found that the annual trend of change in hospital death is strongly affected by the above-identified factors. CONCLUSIONS: The effective predictors in hospital death were RTI location, type of counterpart vehicle, used vehicles and lighting condition. The identified factors related to the location of deaths by RTI can be divided into the RTI severity-related factors as well as factors related to the services quality and speed of delivery. According to the present results, through professional training of people in the field and providing immediate assistance in RTIs pre-hospital mortality can be significantly prevented. |
format | Online Article Text |
id | pubmed-8902731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89027312022-03-18 Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry Homayoun, Sadeghi-Bazargani Milad, Jamali-Dolatabad Mina, Golestani Parvin, Sarbakhsh BMC Emerg Med Research BACKGROUND: Road Traffic Injuries (RTIs) is considered as one of the main health challenges and causes of mortality, worldwide and especially in Iran. Predicting the place where RTIs-related death takes place is vital in decreasing this type of mortality. The purpose of the present study was to identify the predictors of RTI fatalities with respect to the place of death (hospital vs. pre-hospital) during the recent decade in East Azerbaijan Province, Iran. METHODS: Overall, 7347 RTI fatalities were retrieved from the road traffic injuries registry which is supported by the Forensic Medicine Organization in East Azerbaijan. Among these cases, 2758(37.5%)) were hospital deaths. The registered variables of these cases were analysed using bivariate and multiple logistic regression (STATA version 15). RESULTS: Out of 7347 deaths, 5862 (79.8%) were men and the rest were women 1485 (20.2%).The mean age was 40.3 (SD = 20.8). Of the total number of cases, 2758 (37.5%) died in hospital death and the rest 4589 (62.5) were pre-hospital death. According to the results of the present study, inter-city RTI (OR = 1.7, CI 95% = (1.5–2)) and RTIs inside the city of Tabriz (OR = 1.4, CI 95% = (1.2–1.6)) increases the chance of hospitals death. In addition, having a heavy counterpart vehicle compared to no counterpart vehicle decreased the chances of hospitals death (OR = 0.46, CI 95% = (0.39–0.55)) while motorcycle or bike counterpart vehicle compared to no counterpart vehicle increased the chances of hospital death (OR = 2.26, CI 95% = (1.59–3.22)). Also the users of the motorcycle or bike vehicle compared to the pedestrians increased the chances of hospital death (OR = 1.43, CI 95% = (1.19–1.71)) while any the other vehicle users compared to the pedestrians have significantly lower chances for hospital death. Other factors that increased hospitals death were transferring injured people by ambulance (OR = 1.3, CI 95% = (1.1–1.6)) and being elderly (OR = 1.5, CI 95% = (1.2–1.7)). Moreover, it was found that the annual trend of change in hospital death is strongly affected by the above-identified factors. CONCLUSIONS: The effective predictors in hospital death were RTI location, type of counterpart vehicle, used vehicles and lighting condition. The identified factors related to the location of deaths by RTI can be divided into the RTI severity-related factors as well as factors related to the services quality and speed of delivery. According to the present results, through professional training of people in the field and providing immediate assistance in RTIs pre-hospital mortality can be significantly prevented. BioMed Central 2022-03-08 /pmc/articles/PMC8902731/ /pubmed/35260101 http://dx.doi.org/10.1186/s12873-022-00593-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Homayoun, Sadeghi-Bazargani Milad, Jamali-Dolatabad Mina, Golestani Parvin, Sarbakhsh Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry |
title | Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry |
title_full | Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry |
title_fullStr | Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry |
title_full_unstemmed | Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry |
title_short | Predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an Iranian population: results from Tabriz integrated road traffic injury registry |
title_sort | predictors of pre-hospital vs. hospital mortality due to road traffic injuries in an iranian population: results from tabriz integrated road traffic injury registry |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902731/ https://www.ncbi.nlm.nih.gov/pubmed/35260101 http://dx.doi.org/10.1186/s12873-022-00593-w |
work_keys_str_mv | AT homayounsadeghibazargani predictorsofprehospitalvshospitalmortalityduetoroadtrafficinjuriesinaniranianpopulationresultsfromtabrizintegratedroadtrafficinjuryregistry AT miladjamalidolatabad predictorsofprehospitalvshospitalmortalityduetoroadtrafficinjuriesinaniranianpopulationresultsfromtabrizintegratedroadtrafficinjuryregistry AT minagolestani predictorsofprehospitalvshospitalmortalityduetoroadtrafficinjuriesinaniranianpopulationresultsfromtabrizintegratedroadtrafficinjuryregistry AT parvinsarbakhsh predictorsofprehospitalvshospitalmortalityduetoroadtrafficinjuriesinaniranianpopulationresultsfromtabrizintegratedroadtrafficinjuryregistry |