逻辑回归模型结果
该数据集包含脑出血相关肺炎（ICHAP）逻辑回归模型结果，基于498例急性脑出血患者分析预测因素并评估模型性能（AUC 0.819，准确率81.5%）。
基本信息
资源简介
逻辑回归模型结果
【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 5.63 KB，主题涵盖 timely preventive use、receiver operating characteristic、multivariate regression analyses、lt ;&# 8201、conducted univariate analyses，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《Logistic regression model results.》。源站首次发布：2025-02-20。
【数据内容】
源站原始描述：Stroke-associated pneumonia (SAP) is a common complication leading to death and disability after a stroke. Currently, more studies tend to focus on stroke-associated pneumonia in patients with ischemic stroke, while there are few studies on predictors of intracerebral hemorrhage-associated pneumonia (ICHAP). It is necessary to discover new predictors to build more accurate prediction models for ICHAP. We continuously collected 498 patients with acute intracerebral hemorrhage and then divided the…
中文译文（机器翻译，仅供快速理解，请以原文为准）：卒中相关性肺炎（SAP）是卒中后导致死亡和残疾的常见并发症。目前，更多研究倾向于关注缺血性卒中患者的卒中相关性肺炎，而关于脑出血相关性肺炎（ICHAP）预测因素的研究很少。有必要发现新的预测因素，为ICHAP建立更准确的预测模型。我们连续收集了498例急性脑出血患者，然后将其分为ICHAP组和非ICHAP组。随后对收集的数据进行单因素分析和多因素回归分析。之后，发现了ICHAP的新预测因素并设计了预测模型。在498例患者中，158例被诊断为ICHAP。高龄（比值比=1.031；95%置信区间，1.015–1.047；P<0.001）、高NIHSS评分（比值比=1.081；95%置信区间，1.038–1.126；P<0.001）、吞咽困难（比值比=4.191；95%置信区间，2.240–7.841；P<
【数据结构与技术规格】
文件数 1 个，合计 5.63 KB。Table 2.xls：application/vnd.ms-excel，5.63 KB。数据集 DOI：10.1371/journal.pone.0318455.t002。
【主题与分类】
源站学科分类：Medicine、Genetics、Biotechnology、Biological Sciences not elsewhere classified、Information Systems not elsewhere classified、Mathematical Sciences not elsewhere classified。主题标签：timely preventive use、receiver operating characteristic、multivariate regression analyses、lt ;&# 8201、conducted univariate analyses、common complication leading、240 &# 8211、019 &# 8211、015 &# 8211、novel prediction method。
【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/Logistic_regression_model_results_/28453612
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Li, Ya-ming; Chen, Yue; Yao, Mei-fen; Wang, Guo-jiang; Pan, Yi-ni; Chen, Hui; et al. (2025). Logistic regression model results.. PLOS ONE. Dataset
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：Logistic regression model results.
- DOI：10.1371/journal.pone.0318455.t002
- 发布日期：2025-02-20
- 文件数：1 个
- 文件总体积：5.63 KB
- 源站页面：https://plos.figshare.com/articles/dataset/Logistic_regression_model_results_/28453612
命令行下载
curl -L -o "Table 2.xls" "https://ndownloader.figshare.com/files/52506832"
文件清单
Table 2.xls（5.63 KB）
文件总体积 5.63 KB（源站 API 实测）。
数据说明
Stroke-associated pneumonia (SAP) is a common complication leading to death and disability after a stroke. Currently, more studies tend to focus on stroke-associated pneumonia in patients with ischemic stroke, while there are few studies on predictors of intracerebral hemorrhage-associated pneumonia (ICHAP). It is necessary to discover new predictors to build more accurate prediction models for ICHAP. We continuously collected 498 patients with acute intracerebral hemorrhage and then divided them into ICHAP and non-ICHAP groups. Then we conducted univariate analyses and multivariate regression analyses on the collected data. Afterward, the new predictors of ICHAP were found and the predictive model was designed. Of the 498 patients, 158 were diagnosed with ICHAP. Advanced age (odds ratio = 1.031; 95% confidence interval, 1.015–1.047; P < 0.001), high NIHSS score (odds ratio = 1.081; 95% confidence interval, 1.038–1.126; P < 0.001), dysphagia (odds ratio = 4.191; 95% confidence interval, 2.240–7.841 P < 0.001), and fast pulse (odds ratio = 1.038; 95% confidence interval, 1.019–1.057; P < 0.001) were risk factors for ICHAP. The predictive model (P < 0.001) included age, NIHSS, dysphagia, and pulse. After that, the receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) were used to measure their predictive accuracy. The prediction ability of the model (AUC: 0.819) which contained age, NIHSS, dysphagia, and pulse was higher than that of advanced age (AUC = 0.670), high NIHSS score (AUC = 0.761), and fast pulse (AUC = 0.609). The predictive accuracy of the model was 81.5%. These findings might help identify high-risk patients for ICHAP and provide a reference for the timely preventive use of antibiotics.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0318455.t002（source: https://plos.figshare.com/articles/dataset/Logistic_regression_model_results_/28453612）。
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