儿童肺炎门诊低氧血症临床评分数据集
基于孟加拉国和马拉维儿童肺炎门诊数据，构建并验证低氧血症临床评分模型的数据集。
基本信息
资源简介
儿童肺炎门诊低氧血症临床评分数据集
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集，收录 1 个文件、合计 300.80 KB，主题涵盖 hypoxia、clinical decision rules、pediatrics、primary health care、low-income countries，可用于统计建模、特征工程与队列分析，CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Datasheet1_Clinical hypoxemia score for outpatient child pneumonia care lacking pulse oximetry in Africa and South Asia.pdf》。配套论文《Predictive value of pulse oximetry for mortality in infants and children presenting to primary care with clinical pneumonia in rural Malawi: A data linkage study》发表于 PLOS Medicine（2020），DOI：10.1371/journal.pmed.1003300。源站首次发布：2023-11-03。
【数据内容】
源站原始描述：BackgroundPulse oximeters are not routinely available in outpatient clinics in low- and middle-income countries. We derived clinical scores to identify hypoxemic child pneumonia. MethodsThis was a retrospective pooled analysis of two outpatient datasets of 3–35 month olds with World Health Organization (WHO)-defined pneumonia in Bangladesh and Malawi. We constructed, internally validated, and compared fit & discrimination of four models predicting SpO2 12,712 observations were included. The inde…
【数据结构与技术规格】
文件数 1 个，合计 300.80 KB。Datasheet1_Clinical hypoxemia score for outpatient child pneumonia care lacking pulse oximetry in Africa and South Asia.pdf：application/pdf，300.80 KB。数据集 DOI：10.3389/fped.2023.1233532.s001。
【主题与分类】
源站学科分类：Foetal Development and Medicine、Obstetrics and Gynaecology、Paediatrics、Paediatrics and Reproductive Medicine not elsewhere classified。主题标签：hypoxia、clinical decision rules、pediatrics、primary health care、low-income countries、respiratory tract infection (RTI)。
【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://frontiersin.figshare.com/articles/dataset/Datasheet1_Clinical_hypoxemia_score_for_outpatient_child_pneumonia_care_lacking_pulse_oximetry_in_Africa_and_South_Asia_pdf/24496306
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Schuh, Holly B.; Hooli, Shubhada; Ahmed, Salahuddin; King, Carina; Roy, Arunangshu D.; Lufesi, Norman; et al. (2023). Datasheet1_Clinical hypoxemia score for outpatient child pneumonia care lacking pulse oximetry in Africa and South Asia.pdf. Frontiers. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：Datasheet1_Clinical hypoxemia score for outpatient child pneumonia care lacking pulse oximetry in Africa and South Asia.pdf
- DOI：10.3389/fped.2023.1233532.s001
- 发布日期：2023-11-03
- 文件数：1 个
- 文件总体积：300.80 KB
- 源站页面：https://frontiersin.figshare.com/articles/dataset/Datasheet1_Clinical_hypoxemia_score_for_outpatient_child_pneumonia_care_lacking_pulse_oximetry_in_Africa_and_South_Asia_pdf/24496306
命令行下载
curl -L -o "Datasheet1_Clinical hypoxemia score for outpatient child pneumonia care lacking pulse oximetry in Africa and South Asia.pdf" "https://ndownloader.figshare.com/files/43036138"
文件清单
Datasheet1_Clinical hypoxemia score for outpatient child pneumonia care lacking pulse oximetry in Africa and South Asia.pdf（300.80 KB）
文件总体积 300.80 KB（源站 API 实测）。
数据说明
BackgroundPulse oximeters are not routinely available in outpatient clinics in low- and middle-income countries. We derived clinical scores to identify hypoxemic child pneumonia.
MethodsThis was a retrospective pooled analysis of two outpatient datasets of 3–35 month olds with World Health Organization (WHO)-defined pneumonia in Bangladesh and Malawi. We constructed, internally validated, and compared fit & discrimination of four models predicting SpO2 12,712 observations were included. The independent and composite LASSO models discriminated moderately (both C-statistic 0.77) between children with a SpO2 2 2 2 In the absence of pulse oximeters, both LASSO models better identified outpatient hypoxemic pneumonia cases than the WHO guidelines. Score external validation and implementation are needed.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fped.2023.1233532.s001（source: https://frontiersin.figshare.com/articles/dataset/Datasheet1_Clinical_hypoxemia_score_for_outpatient_child_pneumonia_care_lacking_pulse_oximetry_in_Africa_and_South_Asia_pdf/24496306）。
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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