Discovery of a Latent Entropy-Based Physiologic State Variable Governing Multisystem Instability in Critical Illness

This dataset contains all code, intermediate tables, and outputs used to compute the Energy Index (EI), its time-derivative (EI_slope), and associated cross-correlation and regression analyses on patient vital signs. The files correspond exactly to Phases 03 and 04 of the computational workflow.

Contents:

notebook/ – A full Google Colab notebook exported as HTML and IPYNB, containing the exact code used for data cleaning, EI computation, EI_slope derivation, cross-correlation analysis, and multivariable regression.

tables/ – CSV files of the processed ei_full dataframe, the xcorr_df table (lag-based cross-correlation results), and the ss_df table (two-variable OLS models for EI_slope).

figures/ – Auto-generated plots of EI trajectories and regression diagnostics (if any were produced).

metadata/ – Variable dictionaries, version information for Python, NumPy, Pandas, Statsmodels, and notes on reproducibility.

Source data:
All raw clinical data originate from the MIMIC-IV database (PhysioNet) and are not redistributed here. Users must obtain their own access credentials to PhysioNet. This repository contains only derived variables and reproducible code.

File format:
ZIP archive. All files are UTF-8 encoded. Python 3.12 environment.

Purpose:
To allow full replication of the statistical pipeline for computing EI, EI_slope, and evaluating their associations with physiological variables in a real EHR dataset.

本数据集包含用于计算能量指数（Energy Index, EI）及其时间导数（EI_slope）的全部代码、中间表格与输出结果，同时涵盖针对患者生命体征开展的相关互相关分析与回归分析内容。本仓库文件完全对应计算流程的第03与04阶段。

内容清单：
notebook/：导出为HTML与IPYNB格式的完整Google Colab笔记本，包含用于数据清洗、EI计算、EI_slope推导、互相关分析及多变量回归的全部精准代码。
tables/：包含处理后的ei_full数据框、xcorr_df表（基于时滞的互相关分析结果）以及ss_df表（针对EI_slope的双变量普通最小二乘（Ordinary Least Squares, OLS）模型）的CSV文件。
figures/：自动生成的EI轨迹图与回归诊断图（若已生成）。
metadata/：变量字典、Python、NumPy、Pandas、Statsmodels的版本信息，以及可复现性说明。

源数据：
所有原始临床数据均源自MIMIC-IV数据库（PhysioNet），本仓库未对其进行二次分发。用户需自行获取PhysioNet的访问权限。本仓库仅包含衍生变量与可复现代码。

文件格式：
本数据集为ZIP压缩归档文件，所有文件均采用UTF-8编码，运行环境为Python 3.12。

数据集用途：
本数据集旨在实现针对真实电子健康记录（Electronic Health Record, EHR）数据集的完整统计分析流程复现，以计算EI、EI_slope并评估二者与生理变量的关联关系。