SAPS III: Simplified acute physiology score 3

Evidencio uses JavaScript for many of its features. Please enable JavaScript to enable calculations

The Simplified Acute Physiology Score III (SAPS 3) is an ICU scoring system and is used to predict the mortality risk for patients presenting at the ICU.

Research authors: Philipp G.H. Metnitz, Rui P. Moreno, Eduardo Almeida, Barbara Jordan, Peter Bauer, Ricardo Abizanda Campos, Gaetano Iapichino, David Edbrooke, Maurizia Capuzzo, Jean-Roger Le Gall, on behalf of the SAPS 3 investigators

Details Formula Study characteristics Files & References

★★★★

Model author

Evidencio Community

Model ID

1114

Version

1.33

Revision date

2018-08-27

Specialty

Intensive care

MeSH terms

Intensive Care Unit

Model type

Custom model (Conditional)

Status

public

Rating

★ ★ ★ ★

Condition	Formula

Additional information

A total of 22,791 admissions were recorded in the 309 participating ICUs during the study period. For patients who were admitted more than once (n=1,455), only the first admission was included, giving 21,336 admitted patients. Patients who were <16 years of age (n=628), those without ICU admission or discharge data (n=1,074), and those with records that lacked an entry in the field “ICU outcome” (n=57) were excluded. The Basic SAPS 3 Cohort thus comprises 19,577 patients from 307 ICUs.

For the development of a predictive model for hospital mortality as outcome, patients with a missing entry in the field of “vital status at hospital discharge” (n=2,540) or an entry of “still in the hospital” at the end of the follow-up period (n=253) were further excluded. The SAPS 3 Hospital Outcome Cohort thus comprises 16,784 patients from 303 ICUs.

Study Population

Total population size: 19559

Males: {{ model.numberOfMales }}

Females: {{ model.numberOfFemales }}

Continuous characteristics

Name	Q1	Median	Q3	Unit
Age	49	63	74	years
ICU Length of Stay	1	2	6	days
SAPS II score	20	30	42	score
SOFA score	6	9	11	score

Categorical characteristics

Name	Subset / Group	Nr. of patients
Origin	Home	2810
	Same hospital	13926
	Chronic care facility	74
	Public place	519
	Other hospital	2125
	Other	80
	Missing	43
Intra-hospital location before ICU admission	Operating room	7537
	Other	552
	Other ICU	698
	Recovery room	482
	Ward	3411
	Missing	916
	Emergency room	5419
	Intermediate care unit/ high dependency unit	562
ICU admission status	Planned admission	6750
	Unplanned admission	12338
	Missing	489
Acute infection at ICU admission	No infection	15254
	Clinically improbable/colonization	342
	Clinically probable/documented	2761
	Microbiologically documented	1206
	Missing	13
Surgical status	No surgical procedure	8437
	Scheduled surgery	6800
	Emergency surgery	3321
	Missing	1019
ICU discharge - destination	Home	438
	Same hospital	14946
	Other hospital	1029
	Missing	3164
Intrahospital discharge	IMCU/HDU	2222
	Other	303
	Other ICU	583
	Recovery room	306
	Ward	12250
	Missing	3855
ICU discharge - status	Planned discharge	14872
	Unplanned discharge	1595
	Missing	3110
Outcome	ICU mortality (%)	15.2

	SAPS III: Simplified acute physiology score 3
	V-1.33-1114.18.08.27
	Refer to Intended Use for instructions before use
	Evidencio B.V., Irenesingel 19, 7481 GJ, Haaksbergen, the Netherlands

Related files

Preview

Name

Supporting Publications

Title or description

The predicted mortality risk in the ICU is:
... %

Result

Note

Notes are only visible in the result download and will not be saved by Evidencio

The predicted mortality risk in the ICU is: %

Outcome stratification

Result interval {{ additionalResult.min }} to {{ additionalResult.max }}

Conditional information

Result interpretation

The SAPS 3 is an externally validated tool that accurately predicts ICU mortality. The score was evaluated and compared with the APACHE II and the SAPS 2. The performance of the SAPS 3 was similar to that of the APACHE II and the SAPSII
Discrimination of the SAPS 3 model showed c-statistics up to 0.89. The C-SAPS 3 score appeared to have the best calibration curve on visual inspection.

Y Sakr, C. Krauss, ACKB Amaral, et al. Comparison of the performance of SAPS II, SAPS 3, APACHE II, and their customized prognostic models in a surgical intensive care unit, BJA: British Journal of Anaesthesia, Volume 101, Issue 6, 1 December 2008, Pages 798–803

Calculations alone should never dictate patient care, and are no substitute for professional judgement. See our full disclaimer.

Comments

Rating

Comment

Please enter a comment of rating

Comments are visible to anyone

Model feedback

No feedback yet 1 Comment {{ model.comments.length }} Comments

Not rated | On {{ comment.created_at }} {{ comment.user.username }} a no longer registered author wrote:

Validate model Download report

Save input Load input

Recent Intensive care Models

APACHE II score

Corrected QT interval and corresponding risk of torsades de pointes in drug-induced QT prolongation

Predicting critical illness on initial diagnosis of COVID-19: Development and validation of the PRIORITY model for outpatient applicability.

Risk score to assess host susceptibility to develop severe COVID-19 - during hospital stay

Risk score to assess host susceptibility to develop severe cases of COVID-19 - at admission

All Intensive care Models

Please sign in to enable Evidencio print features

In order to use the Evidencio print features, you need to be logged in.
If you don't have an Evidencio Community Account you can create your free personal account at:

https://www.evidencio.com/registration

Printed results - Examples {{ new Date().toLocaleString() }}

Evidencio Community Account Benefits

With an Evidencio Community account you can:

Create and publish your own prediction models.
Share your prediction models with your colleagues, research group, organization or the world.
Review and provide feedback on models that have been shared with you.
Validate your models and validate models from other users.
Find models based on Title, Keyword, Author, Institute, or MeSH classification.
Use and save prediction models and their data.
Use patient specific protocols and guidelines based on sequential models and decision trees.
Stay up-to-date with new models in your field as they are published.
Create your own lists of favorite models and topics.

A personal Evidencio account is free, with no strings attached! Join us and help create clarity, transparency, and efficiency in the creation, validation, and use of medical prediction models.

Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.

Additional information

Study Population

Continuous characteristics

Categorical characteristics

Related files

Supporting Publications

The predicted mortality risk in the ICU is:
... %

{{ model.survival.PITTitle }}

{{ model.survival.YNETitle }}

The predicted mortality risk in the ICU is: %

Outcome stratification

Conditional information

Result interpretation

Model feedback

Please sign in to enable Evidencio print features

Printed results - Examples {{ new Date().toLocaleString() }}

Evidencio Community Account Benefits

{{ variable.title }}

Additional information

Study Population

Continuous characteristics

Categorical characteristics

Related files

Supporting Publications

The predicted mortality risk in the ICU is: ... %

{{ model.survival.PITTitle }}

{{ model.survival.YNETitle }}

The predicted mortality risk in the ICU is: %

Outcome stratification

Conditional information

Result interpretation

Model feedback

Please sign in to enable Evidencio print features

Printed results - Examples {{ new Date().toLocaleString() }}

Evidencio Community Account Benefits

{{ variable.title }}

The predicted mortality risk in the ICU is:
... %