Quantitative Assessment of Significant Hematological Parameters Deviation from Healthy State for Sepsis Clinical Monitoring

Summary

This study proposes a novel quantitative metric based on the Euclidean distance of three significant hematological parameters (Hb, Lymph%, PDW) from a healthy state to assess sepsis severity. Results demonstrate a strong correlation with SOFA scores, offering a simple, objective tool for monitoring sepsis using routine blood tests.

Abstract

Sepsis, a life-threatening condition, requires improved diagnostics and severity assessment. Based on long-term clinical observation, Hemoglobin (Hb), lymphocyte percentage (Lymph%), and platelet distribution width (PDW) change significantly during sepsis. This study aimed to evaluate these three Complete Blood Count (CBC) parameters for distinguishing sepsis patients from healthy individuals and to develop a novel quantitative metric based on their combined deviation from a healthy state to assess sepsis severity. This retrospective case-control study included 496 sepsis patients (diagnosed according to Sepsis-3 criteria upon admission) and 1136 healthy controls. Initial Hb, Lymph%, and PDW were z-score standardized. The healthy cohort's 3D centroid was calculated and each sepsis patient's Euclidean distance from this centroid was computed. Group differences and correlation with SOFA scores were analyzed. 3D scatter plots visualized these relationships. Hb, Lymph%, and PDW differed significantly between sepsis patients and controls (p < 0.001), with sepsis showing lower Hb/Lymph% and higher PDW. The calculated Euclidean distance from the healthy centroid was significantly greater in sepsis patients (p < 0.001). This distance strongly correlated with SOFA scores (r = 0.45, p < 0.001) and was larger in patients with higher disease severity. 3D visualization confirmed group separation, with color intensity reflecting this distance and correlating with increasing deviation from the healthy centroid. The Euclidean distance of key CBC parameters from a healthy cohort's centroid effectively quantifies deviation from a healthy state and correlates with disease severity. This approach using routine CBC data offers a promising, simple tool for sepsis severity assessment and monitoring.

Introduction

Sepsis, as a systemic inflammatory response syndrome caused by infection, can lead to severe organ dysfunction and remains one of the leading causes of death in intensive care units worldwide^1,2. Despite advances in diagnostic and treatment technologies in recent years, sepsis mortality rates remain high at 20%-40%³. Timely identification and accurate assessment of sepsis severity are crucial for clinical decision-making and improving prognosis⁴.

Currently, sepsis diagnosis and severity assessment primarily rely on scoring systems such....

Protocol

This study was a retrospective case-control investigation approved by the Ethics Committee of Sunsimiao Hospital, Beijing University of Chinese Medicine (approval number: SSMYY-KYPJ-2024-065). All participants or their legal representatives signed informed consent forms.

Study design and participants
The study included 496 patients diagnosed with sepsis (according to Sepsis-3 criteria³) and 1136 healthy controls from the health examination center during the period from January 2024 to March 2025. Exclusion criteria for the observation group included: (1) age < 18 years; (2) pregnant women; ....

Results

Significance analysis
Based on long-term clinical practice, it has been observed that as sepsis progresses, patients show significantly decreased hemoglobin levels and lymphocyte percentages, along with significantly increased platelet distribution width^12,16. Through analysis of these three key hematological indicators -- hemoglobin, lymphocyte percentage, and platelet distribution width -- significant differ.......

Discussion

New method for sepsis assessment based on key hematological indicators
This study proposes a new method for assessing sepsis severity based on three key hematological indicators (hemoglobin, lymphocyte percentage, and platelet distribution width). This method quantifies the degree of deviation of hematological indicators from the healthy state by calculating the Euclidean distance of patient samples from the center point of the healthy population, providing a new assessment tool for clinical monito.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
MATLAB	MathWorks	2023B	Computing and visualization
The Multivariate State Colorful Scatter Plot	Intelligent  Entropy	Multivariate State V1.0	Beijing Intelligent Entropy Science & Technology Co Ltd. Modeling for multivariate State