mmed_data
该数据集包含152名儿童结核病患者的治疗记录及医疗工作者访谈，用于分析治疗启动时间和影响因素。
基本信息
资源简介
mmed_data
【数据集背景】
本数据集源站标题为《mmed_data.》。源站首次发布：2025-04-16。
【数据内容】
源站原始描述：Background Tuberculosis (TB) remains a leading cause of mortality worldwide, with childhood TB posing unique diagnostic challenges due to its pauci bacillary nature. The World Health Organization emphasizes that these diagnostic difficulties hinder early detection, contributing to delays in treatment initiation, disease progression, and increased morbidity and mortality. Addressing these challenges is critical to achieving the global goal of ending TB as a public health threat by 2030. This stud…
【数据结构与技术规格】
文件数 1 个，合计 40.63 KB。pone.0321620.s001.xlsx：application/vnd.openxmlformats-officedocument.spreadsheetml.sheet，40.63 KB。数据集 DOI：10.1371/journal.pone.0321620.s001。
【主题与分类】
源站学科分类：Medicine、Cell Biology、Biotechnology、Cancer、Infectious Diseases、Computational Biology。主题标签：rapid diagnostic tools、public health threat、pauci bacillary nature、inadequate diagnostic equipment、healthcare workers involved、estimated using kaplan、bacteriologically confirmed cases、31 &# 8211、early tuberculosis treatment、retrospective cohort mixed。
【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/mmed_data_/28807815
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Muzeyi, Wani; Babirekere, Esther; Kalibbala, Dennis; Katamba, Achilles; Nangendo, Joanita; Semitala, Fred C.; et al. (2025). mmed_data.. PLOS ONE. Dataset
下载信息
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暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取（Figshare）
- 源站标题：mmed_data.
- DOI：10.1371/journal.pone.0321620.s001
- 发布日期：2025-04-16
- 文件数：1 个
- 文件总体积：40.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/mmed_data_/28807815
命令行下载
curl -L -o "pone.0321620.s001.xlsx" "https://ndownloader.figshare.com/files/53708430"
文件清单
pone.0321620.s001.xlsx（40.63 KB）
文件总体积 40.63 KB（源站 API 实测）。
数据说明
Background
Tuberculosis (TB) remains a leading cause of mortality worldwide, with childhood TB posing unique diagnostic challenges due to its pauci bacillary nature. The World Health Organization emphasizes that these diagnostic difficulties hinder early detection, contributing to delays in treatment initiation, disease progression, and increased morbidity and mortality. Addressing these challenges is critical to achieving the global goal of ending TB as a public health threat by 2030. This study aimed to determine the median time to TB treatment initiation and explore the factors influencing early treatment among children under 15 years at Kisenyi Health Center IV.
Methods
We conducted a retrospective cohort mixed-methods study. Quantitative data were obtained through a retrospective review of medical records for 152 children under 15 years treated for TB at Kisenyi Health Center IV between February 1, 2021, and February 28, 2023. The median time to treatment initiation was estimated using Kaplan-Meier survival analysis, while Cox proportional hazards regression identified determinants of treatment initiation. Qualitative data were collected through key informant interviews with healthcare workers involved in childhood TB care. Thematic analysis, guided by the Capability, Opportunity, and Motivation Behavior (COM-B) model, was used to identify barriers to early TB treatment.
Results
A total of 152 children were included in the study. The median time to TB treatment initiation was 39.5 days (IQR: 30,80.9). Pulmonary bacteriologically confirmed TB was the only significant determinant of early treatment initiation (HR: 0.54, 95% CI: 0.31–0.88). Key barriers to timely TB treatment included caregivers’ poor knowledge of childhood TB, referral of children under five to the national referral hospital, inadequate diagnostic equipment and supplies, loss of community follow-up contacts, and high patient volumes.
Conclusion
Children with TB experience significant treatment delays, underscoring the urgent need for more accessible and rapid diagnostic tools to increase the proportion of bacteriologically confirmed cases and reduce treatment initiation time. Strengthening de
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0321620.s001（source: https://plos.figshare.com/articles/dataset/mmed_data_/28807815）。
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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