Authors :
Innocent Obinna Okpara; Roseline Toyin Abah; Mary O. Durojaye
Volume/Issue :
Volume 11 - 2026, Issue 8 - August
Google Scholar :
https://tinyurl.com/bdu9fpx4
DOI :
https://doi.org/10.38124/ijisrt/26aug1493
Note : A published paper may take 4-5
working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and
ResearchGate.
Abstract :
Background:
Transparent cohort characterization is a prerequisite for reliable sepsis prediction research, yet case definitions,
admission units, outcome windows, and leakage controls vary considerably across studies.
Methods:
We conducted a retrospective descriptive analysis of adult hospital admissions in MIMIC-IV version 3.1. Admissions
were identified using an explicit ICD-coded sepsis phenotype. The primary modelling population was defined as the
chronologically first eligible coded-sepsis admission per patient; all eligible admissions were retained for descriptive
analyses. Outcomes included in-hospital, 30-day, and 90-day mortality. We summarized demographic characteristics, ICU
involvement, coded severity, first ICU care unit, and the availability of ten candidate physiological variables. Unadjusted
mortality differences and risk ratios were calculated from the reported stratum counts.
Keywords :
Sepsis; Mortality; MIMIC-IV; Retrospective Cohort; Intensive Care; Missing Data; Electronic Health Records.
References :
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Background:
Transparent cohort characterization is a prerequisite for reliable sepsis prediction research, yet case definitions,
admission units, outcome windows, and leakage controls vary considerably across studies.
Methods:
We conducted a retrospective descriptive analysis of adult hospital admissions in MIMIC-IV version 3.1. Admissions
were identified using an explicit ICD-coded sepsis phenotype. The primary modelling population was defined as the
chronologically first eligible coded-sepsis admission per patient; all eligible admissions were retained for descriptive
analyses. Outcomes included in-hospital, 30-day, and 90-day mortality. We summarized demographic characteristics, ICU
involvement, coded severity, first ICU care unit, and the availability of ten candidate physiological variables. Unadjusted
mortality differences and risk ratios were calculated from the reported stratum counts.
Keywords :
Sepsis; Mortality; MIMIC-IV; Retrospective Cohort; Intensive Care; Missing Data; Electronic Health Records.