Search...

⌘K

Try AI Medical Scribe

Save 2+ hours daily with instant clinal dicumentation.

Start Free Trial

All tools /

APACHE II Score

APACHE II Score

Severity-of-disease classification system that predicts ICU mortality risk based on physiological measurements, age, and chronic health conditions

All tools /

APACHE II Score

APACHE II Score

Severity-of-disease classification system that predicts ICU mortality risk based on physiological measurements, age, and chronic health conditions

Temperature (°C)
Mean Arterial Pressure (mm Hg)
Heart Rate (beats/min)
Respiratory Rate (breaths/min)
Oxygenation: A-aDO₂ (FiO₂ ≥ 0.5) or PaO₂ (FiO₂ < 0.5) (mm Hg)
Arterial pH
Serum Sodium (mEq/L)
Serum Potassium (mEq/L)
Serum Creatinine (mg/dL)
Double the score if acute renal failure (use clinical judgment for acute kidney injury)
Hematocrit (%)
White Blood Cell Count (x10³/μL)
Glasgow Coma Scale
Age (years)
Chronic Health Points
For severe organ insufficiency or immunocompromised state
Type of Admission
Acute Renal Failure
Note: "acute renal failure" was not defined in the original study. Use clinical judgment to determine whether patient has acute kidney injury.
APACHE II Score — — 0% estimated nonoperative mortality
0/16 answered · tap options to update (0–71)

Instructions

The APACHE II score is calculated using acute physiological measurements, age, and chronic health status. Clinicians should collect vital parameters such as temperature, mean arterial pressure, heart rate, respiratory rate, oxygenation status, arterial pH, sodium, potassium, creatinine, hematocrit, white blood cell count, and Glasgow Coma Scale (GCS). Each variable is scored based on severity, with higher deviations from normal values receiving higher points. Additional points are assigned for age and severe chronic health conditions. The total score reflects illness severity and is used to predict hospital mortality in critically ill patients.

Overview
When to use
Why use
Evidences

Interpretation

APACHE II Score

Estimated Mortality Risk

0–4

~4%

5–9

~8%

10–14

~15%

15–19

~25%

20–24

~40%

25–29

~55%

30–34

~73%

≥35

~85%

APACHE II (Acute Physiology and Chronic Health Evaluation II) was introduced in 1985 as a general ICU severity-of-disease system that sums points from 12 physiologic variables (worst values in first 24 h), age, and chronic health status to yield a 0–71 score strongly correlated with hospital mortality across 5,815 ICU admissions in 13 hospitals
https://pubmed.ncbi.nlm.nih.gov/3928249/

In a trauma cohort analysis, APACHE II predicted mortality with AUROC 0.77 and outperformed ISS and TRISS, with somewhat higher discrimination in penetrating trauma (AUROC 0.81) than blunt trauma (0.76)

https://pmc.ncbi.nlm.nih.gov/articles/PMC2752660/

Serial/dynamic reassessment can improve prognostication; in one study, the day‑3 APACHE II had higher AUROC (0.666 on day 3 vs ~0.58 on days 1–2), with further gains by days 7–28, suggesting early re-evaluation refines risk estimates

https://pmc.ncbi.nlm.nih.gov/articles/PMC8826444/

Comparative studies show APACHE II has similar discrimination to SAPS II in some cohorts and often better discrimination than SOFA for mortality prediction when used as a single baseline score

https://pmc.ncbi.nlm.nih.gov/articles/PMC5325910/

Intercenter evaluations highlight the need for standardized data collection; scoring inaccuracies and case-mix differences can affect calibration and reliability, reinforcing the importance of training and local validation when using APACHE II for benchmarking

https://associationofanaesthetists-publications.onlinelibrary.wiley.com/doi/10.1046/j.1365-2044.2001.01763.x

Overview
When to use
Why use
Evidences

The APACHE II scoring system is one of the most widely used critical care severity indices in intensive care units (ICUs). It was first introduced in 1985 as an update to the original APACHE model to improve prediction accuracy and simplify use in clinical practice. The score integrates a combination of physiological variables, patient age, and chronic health conditions into a single index that quantifies severity of illness.

The score ranges from 0 to 71, with higher values indicating greater disease severity and higher predicted mortality risk. It is not disease-specific but rather designed as a general prognostic tool for critically ill patients with a wide variety of conditions, including sepsis, respiratory failure, trauma, and multi-organ dysfunction.

APACHE II is most commonly applied within the first 24 hours of ICU admission, using the worst values for each parameter recorded during that period. This ensures that the model reflects the most severe physiological derangements early in the ICU stay.

Overview
When to use
Why use
Evidences

Interpretation

APACHE II Score

Estimated Mortality Risk

0–4

~4%

5–9

~8%

10–14

~15%

15–19

~25%

20–24

~40%

25–29

~55%

30–34

~73%

≥35

~85%

APACHE II (Acute Physiology and Chronic Health Evaluation II) was introduced in 1985 as a general ICU severity-of-disease system that sums points from 12 physiologic variables (worst values in first 24 h), age, and chronic health status to yield a 0–71 score strongly correlated with hospital mortality across 5,815 ICU admissions in 13 hospitals
https://pubmed.ncbi.nlm.nih.gov/3928249/

In a trauma cohort analysis, APACHE II predicted mortality with AUROC 0.77 and outperformed ISS and TRISS, with somewhat higher discrimination in penetrating trauma (AUROC 0.81) than blunt trauma (0.76)

https://pmc.ncbi.nlm.nih.gov/articles/PMC2752660/

Serial/dynamic reassessment can improve prognostication; in one study, the day‑3 APACHE II had higher AUROC (0.666 on day 3 vs ~0.58 on days 1–2), with further gains by days 7–28, suggesting early re-evaluation refines risk estimates

https://pmc.ncbi.nlm.nih.gov/articles/PMC8826444/

Comparative studies show APACHE II has similar discrimination to SAPS II in some cohorts and often better discrimination than SOFA for mortality prediction when used as a single baseline score

https://pmc.ncbi.nlm.nih.gov/articles/PMC5325910/

Intercenter evaluations highlight the need for standardized data collection; scoring inaccuracies and case-mix differences can affect calibration and reliability, reinforcing the importance of training and local validation when using APACHE II for benchmarking

https://associationofanaesthetists-publications.onlinelibrary.wiley.com/doi/10.1046/j.1365-2044.2001.01763.x

Frequently Asked Questions

Features and Services FAQs

Discover the full range of features and services we offer and how to use them.

When should APACHE II be calculated?+
Does APACHE II apply to all ICU patients?+
Can APACHE II predict individual patient outcomes?+
How does APACHE II compare to SOFA?+
Why is APACHE II still used if APACHE IV exists?+
Can APACHE II guide treatment decisions?+

Ready to Transform Your Practice?

Join thousands of clinicians saving hours daily with AI-powered documentation.

14-day free trial • No setup fees

Ready to Transform Your Practice?

Join thousands of clinicians saving hours daily with AI-powered documentation.

14-day free trial • No setup fees

Ready to Transform Your Practice?

Join thousands of clinicians saving hours daily with AI-powered documentation.

14-day free trial • No setup fees

DocScrib

AI-powered medical documentation platform revolutionizing clinical workflows through intelligent patient management and secure documentation.

Product

How It Works

Pricing

FAQ

Articles

Blog

Security

Support

Contact Support

Sales Inquiries

1-800-DOCSCRIB

Help Center

Comparisons

vs Soaper

vs Freed

vs ChartNote

vs NoteMD

vs Heidi

vs Nabla

vs Doximity

vs Suki

Legal

Privacy Policy

Terms of Service

Security & Compliance

Legal Inquiries

© 2025 DocScrib. All rights reserved.

Privacy

Terms

Security

DocScrib

AI-powered medical documentation platform revolutionizing clinical workflows through intelligent patient management and secure documentation.

Product

How It Works

Pricing

FAQ

Articles

Blog

Security

Support

Contact Support

Sales Inquiries

1-800-DOCSCRIB

Help Center

Comparisons

vs Soaper

vs Freed

vs ChartNote

vs NoteMD

vs Heidi

vs Nabla

vs Doximity

vs Suki

Legal

Privacy Policy

Terms of Service

Security & Compliance

Legal Inquiries

© 2025 DocScrib. All rights reserved.

Privacy

Terms

Security

DocScrib

AI-powered medical documentation platform revolutionizing clinical workflows through intelligent patient management and secure documentation.

Product

How It Works

Pricing

FAQ

Articles

Blog

Security

Support

Contact Support

Sales Inquiries

1-800-DOCSCRIB

Help Center

Comparisons

vs Soaper

vs Freed

vs ChartNote

vs NoteMD

vs Heidi

vs Nabla

vs Doximity

vs Suki

Legal

Privacy Policy

Terms of Service

Security & Compliance

Legal Inquiries

© 2025 DocScrib. All rights reserved.

Privacy

Terms

Security

Model for End-Stage Liver Disease (Combined MELD)