受伤患者的人口统计学特征
喀麦隆创伤登记处2017-2019年9,635名创伤患者的人口统计学、影像学检查与生存结局数据。
基本信息
资源简介
受伤患者的人口统计学特征
【数据集背景】
本数据集源站标题为《Demographics of injured patients.》。源站首次发布：2023-08-18。
【数据内容】
源站原始描述：Despite having the highest rates of injury-related mortality in the world, trauma system capacity in sub-Saharan Africa remains underdeveloped. One barrier to prompt diagnosis of injury is limited access to diagnostic imaging. As part of a larger quality improvement initiative and to assist priority setting for policy makers, we evaluated trauma outcomes among patients who did and did not receive indicated imaging in the Emergency Department (ED). We hypothesize that receiving imaging is associa…
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 1.xls：undefined，5.63 KB。数据集 DOI：10.1371/journal.pgph.0001951.t001。
【主题与分类】
源站学科分类：Medicine、Cell Biology、Biotechnology、Environmental Sciences not elsewhere classified、Immunology、Biological Sciences not elsewhere classified。主题标签：xlink "> despite、trauma system capacity、multivariate regression adjusted、multivariate logistic regression、lower socioeconomic status、32 &# 8211、trauma patients enrolled、injured cameroonian patients、635 injured patients、increased early mortality。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://plos.figshare.com/articles/dataset/Demographics_of_injured_patients_/23990200
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Driban, Matthew; Dissak-Delon, Fanny N.; Carvalho, Melissa; Mbianyor, Mbiarikai; Etoundi-Mballa, Georges A.; Kingue, Thompson; et al. (2023). Demographics of injured patients.. PLOS Global Public Health. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：Demographics of injured patients.
- DOI：10.1371/journal.pgph.0001951.t001
- 发布日期：2023-08-18
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/Demographics_of_injured_patients_/23990200
命令行下载
curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/42070051"
文件清单
Table 1.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
Despite having the highest rates of injury-related mortality in the world, trauma system capacity in sub-Saharan Africa remains underdeveloped. One barrier to prompt diagnosis of injury is limited access to diagnostic imaging. As part of a larger quality improvement initiative and to assist priority setting for policy makers, we evaluated trauma outcomes among patients who did and did not receive indicated imaging in the Emergency Department (ED). We hypothesize that receiving imaging is associated with increased early injury survival. We evaluated patterns of imaging performance in a prospective multi-site trauma registry cohort in Cameroon. All trauma patients enrolled in the Cameroon Trauma Registry (CTR) between 2017 and 2019 were included, regardless of injury severity. Patients prescribed diagnostic imaging were grouped into cohorts who did and did not receive their prescribed study. Patient demographics, clinical course, and outcomes were compared using chi-squared and Kruskal-Wallis tests. Multivariate logistic regression was used to explore associations between radiologic testing and survival after injury. Of 9,635 injured patients, 47.5% (4,574) were prescribed at least one imaging study. Of these, 77.8% (3,556) completed the study (COMPLETED) and 22.2% (1,018) did not receive the prescribed study (NC). Compared to COMPLETED patients, NC patients were younger (p = 0.02), male (p<0.01), and had markers of lower socioeconomic status (SES) (p<0.01). Multivariate regression adjusted for age, sex, SES, and injury severity demonstrated that receiving a prescribed study was strongly associated with ED survival (OR 5.00, 95% CI 3.32–7.55). Completing prescribed imaging was associated with increased early survival in injured Cameroonian patients. In a resource-limited setting, subsidizing access to diagnostic imaging may be a feasible target for improving trauma outcomes.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pgph.0001951.t001（source: https://plos.figshare.com/articles/dataset/Demographics_of_injured_patients_/23990200）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
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