官方服务：
资源简介：
该数据源为任丘市议论堡镇卫生院在履行基本公共卫生服务职能过程中产生，包含：姓名、性别、民族、年龄、责任医生等信息，可用于本院对辖区慢阻肺患者统计及健康管理。
应用场景：
提供机构：
任丘市议论堡镇卫生院相关数据集
The impact of seat-height on 1-minute sit to stand test performance in COPD: A randomised cross-over trial
Study question: Is there a difference in the number of repetitions on the 1-minute sit to stand (1MSTS) test using an individually adapted seatheight to 90-degree knee flexion (1MSTSIND), compared wit
Mendeley Data2024-05-10 更新90
General characteristics, functional status and severity of the COPD groups.
Values are mean ±SD or frequency. Abbreviations: BMI = body mass index; FVC = forced vital capacity; FEV1 = forced expiratory volume in 1 second; IC = inspiratory capacity; SpO2 = oxyhemoglobin satura
NIAID Data Ecosystem70
Table_2_Associative analysis of multi-omics data indicates that acetylation modification is widely involved in cigarette smoke-induced chronic obstructive pulmonary disease.XLS
We aimed to study the molecular mechanisms of chronic obstructive pulmonary disease (COPD) caused by cigarette smoke more comprehensively and systematically through different perspectives and aspects
NIAID Data Ecosystem60
Main characteristics of subjects.
Values are expressed as mean±SD or median (25th percentile, 75th percentile). Abbreviations: BMI, body mass index; FFMI, fat-free mass index; FEV1, forced expiratory volume in one second; FVC, forced
NIAID Data Ecosystem90
Data from: Age, gender, neck circumference, and Epworth sleepiness scale do not predict obstructive sleep apnea (OSA) in moderate to severe chronic obstructive pulmonary disease (COPD): the challenge to predict OSA in advanced COPD
The combination of chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA) is associated with substantial morbidity and mortality. We hypothesized that predictors of OSA among p
DataONE2017-06-06 更新70
