Sepsis Survival Minimal Clinical Records
The dataset consists of 110,204 admissions of 84,811 hospitalized subjects between 2011 and 2012 in Norway who were diagnosed with infections, systemic inflammatory response syndrome, sepsis by causative microbes, or septic shock. The prediction task is to determine whether a patient survived or is deceased at a time of about 9 days after collecting their medical record at the hospital. This is an important prediction problem in clinical medicine. Sepsis is a life-threatening condition triggered by an immune overreaction to infection, leading to organ failure or even death. Sepsis is associated with immediate death risk, often killing patients within one hour. This renders many laboratory tests and hospital analyses impractical for timely diagnosis and treatment. Being able to predict the survival of patients within minutes with as few and easy-to-retrieve medical features as possible is very important.
Characteristics
Subject Area
Associated Tasks
Attribute Type
# Instances
# Attributes
Info
Primary cohort from Norway: - 4 features for 110,204 patient admissions - file: 's41598-020-73558-3_sepsis_survival_primary_cohort.csv' Study cohort (a subset of the primary cohort) from Norway: - 4 features for 19,051 patient admissions - file: 's41598-020-73558-3_sepsis_survival_study_cohort.csv' Validation cohort from South Korea: - 4 features for 137 patients - file: 's41598-020-73558-3_sepsis_survival_validation_cohort.csv' The validation cohort from South Korea was used by Chicco and Jurman (2020) as an external validation cohort to confirm the generalizability of their proposed approach.
Introductory Paper
Survival prediction of patients with sepsis from age, sex, and septic episode number alone
By D. Chicco, Giuseppe Jurman. 2020
Provided by
University of California, Irvine
Creators
- Davide Chicco
- Giuseppe Jurman
DOI
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Features
| Attribute Name | Role | Type | Demographic | Description | Units | Missing Values |
|---|---|---|---|---|---|---|
| age_years | Feature | Integer | Age | Age of the patient in years. | years | no |
| sex_0male_1female | Feature | Binary | Gender | Gender of the patient. Values are encoded as follows: {0: male, 1: female} | no | |
| episode_number | Feature | Integer | Number of prior Sepsis episodes | no | ||
| hospital_outcome_1alive_0dead | Target | Binary | Status of the patient after 9,351 days of being admitted to the hospital. Values are encoded as follows: {1: Alive, 0: Dead} | no |