High-sensitivity cardiac troponin T (hs-cTnT) 0-hour/1-hour algorithm

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

The high-sensitivity cardiac troponin T (hs-cTnT) 0-hour/1-hour algorithm uses hs-cTnT blood concentration at presentation and its absolute 1h change to stratify patients suspected of acute myocardial infarction.

The Calculator is intended to be used for patients presenting to the Emergency Department with Chest Pain aged 18 years or older.

Research authors: Reichlin T, Schindler C, Drexler B, Twerenbold R, Reiter M, Zellweger C, Moehring B, Ziller R, Hoeller R, Gimenez MR, Haaf P, Potocki M, Wildi K, Balmelli C, Freese M, Stelzig C, Freidank H, Osswald S, and Mueller C.

Version: 1.41

Public
Cardiology
{{ modelType }}

Versions

Version {{ version.major }}.{{ version.minor }}

V-1.41-2426.23.12.18

(01)08719327522776(8012)v1.41(4326)231218(240)2426

Details
Intended purpose
Electronic label
Release Notes

Details
Intended purpose
Electronic label
Release Notes

Calculate the result

This model does not calculate automatically.
Please provide all the needed parameters and press calculate.

Set more parameters to perform the calculation

Absolute change of hs-cTnT:

ng/L within the first hour

Set more parameters to perform the calculation

Absolute change of hs-cTnT: ng/L within the first hour

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

Conditional information

Model performance:
The high-sensitivity cardiac troponin T(hs-cTnT) 0-hour/1-hour algorithm was reported to achieve a very high negative predictive value for acute myocardial infarction in the rule-out zone, to achieve a high positive predictive value in the rule-in zone, and to be very effective by triaging approximately 75% of patients presenting with suspected acute myocardial infarction to the ED to either rule-out or rule-in classifications.^1,2

In 2016, the algorithm was further validated by Mueller et al. in an external mulicenter cohort of 1,282 patients with a 17% rate of acute myocardial infarction.³ Use of hs-cTn assays at presentation and 1 hour later in classified 63% of patients as having no acute myocardial infarction, with a 99.1% NPV (95% CI 98.2% to 99.7%); 14% as having acute myocardial infarction, with a PPV of 77% (95% CI 70.4% to 83.0%); and 22.5% as having an indeterminate classification after 1 hour of testing.

Related references:

PRO

Note

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

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

Underlying models Part of

Additional information

Details

Model author

Evidencio.Medical.Devices

Model ID

10306

Version

1.41

Revision date

2023-12-18

Specialty

Cardiology , Emergency medicine , Intensive care

Model type

Custom model ^{(Calculation)}

MeSH terms

ST Elevation Myocardial Infarction

Troponin C

Clinical Decision-Making

Status

Public

Formula

Study characteristics

Additional information

Background: High-sensitivity cardiac troponin (hs-cTn) assays seem to improve the early diagnosis of acute myocardial infarction (AMI), but it is unknown how to best use them in clinical practice. Our objective was to develop and validate an algorithm for rapid rule-out and rule-in of AMI.

Methods: A prospective multicenter study enrolling 872 unselected patients with acute chest pain presenting to the emergency department. High-sensitivity cardiac troponin T (hs-cTnT) was measured in a blinded fashion at presentation and after 1 hour. The final diagnosis was adjudicated by 2 independent cardiologists. An hs-cTnT algorithm incorporating baseline values as well as absolute changes within the first hour was derived from 436 randomly selected patients and validated in the remaining 436 patients. The primary prognostic end point was death during 30 days of follow-up.

Results: Acute myocardial infarction was the final diagnosis in 17% of patients. After applying the hs-cTnT algorithm developed in the derivation cohort to the validation cohort, 259 patients (60%) could be classified as “rule-out,” 76 patients (17%) as “rule-in,” and 101 patients (23%) as in the “observational zone” within 1 hour. Overall, this resulted in a sensitivity and negative predictive value of 100% for rule-out, a specificity and positive predictive value of 97% and 84%, respectively, for rule-in, and a prevalence of AMI of 8% in the observational zone group. Cumulative 30-day survival was 99.8%, 98.6%, and 95.3% (P < .001) in patients classified as rule-out, observational zone, and rule-in, respectively.

Conclusions: Using a simple algorithm incorporating hs-cTnT baseline values and absolute changes within the first hour allowed a safe rule-out as well as an accurate rule-in of AMI within 1 hour in 77% of unselected patients with acute chest pain. This novel strategy may obviate the need for prolonged monitoring and serial blood sampling in 3 of 4 patients.

Reference:
Reichlin T, Schindler C, Drexler B, et al. One-hour rule-out and rule-in ofacute myocardial infarction using high-sensitivity cardiac troponin T. Arch Intern Med. 2012;172:1211-1218.

Study Population

Total population size: 436

Males: {{ model.numberOfMales }}

Females: {{ model.numberOfFemales }}

Continuous characteristics

Name	LL	Q1	Median	Q3	UL	Unit
Age		52	65	75		years
Creatinine clearance		69	89	106		mL/min/m2

Categorical characteristics

Name	Subset / Group	Nr. of patients
Hypertension	Yes	295
Hypertension	No	141
Hypercholesterolemia	Yes	205
Hypercholesterolemia	No	231
Diabetes	Yes	87
Diabetes	No	349
Current smoking	Yes	107
Current smoking	No	329
Coronary artery disease	Yes	164
Coronary artery disease	No	272
Previous myocardial infarction	Yes	116
Previous myocardial infarction	No	320
Previous revascularization	Yes	124
Previous revascularization	No	312
Peripheral artery disease	Yes	26
Peripheral artery disease	No	410
Previous stroke	Yes	27
Previous stroke	No	409
Final diagnosis of AMI	Yes	75
Final diagnosis of AMI	No	361

Supporting Publications

Title or description

Related files

Preview

Name

This model has been certified as a medical device

V-1.41-2426.23.12.18

Medical Devices

Evidencio offers CE-certified MDSWs (Medical Device Software) of both widely adopted and new ground breaking algorithms. Evidencio provides an easy, sustainable and scalable way to be compliant in your use of algorithms and AI for clinical decision support, shared decision making, patient monitoring, etc.

The model High-sensitivity cardiac troponin T (hs-cTnT) 0-hour/1-hour algorithm has been certified as a medical device and is only available to qualified Evidencio subscribers.

In general, the prediction models and algorithms that are freely available on Evidencio are intended for research and education purposes only.

Some of the medical prediction models and algorithms that are available on Evidencio are classified as (e.g. CE) Medical Devices.
This implies that these models may be used for clinical decision making by medical professionals, as long as this use strictly adheres to the model’s Intended Purpose statements.

{{ collapsed.intendedUse ? $t('show_intended_use') : $t('hide_intended_use') }}

In order for Evidencio to comply with legislation regarding the use of medical devices, we must monitor use of these medical devices to the greatest extent to prevent mis-use. Therefore, the Medical Devices on Evidencio can only be used by named Evidencio Subscribers.

To access this model you will need an Evidencio Pro Subscription

Visit our library for more prediction models

Already have an account? Log in Go back Sign Up

This is a paid model

The model High-sensitivity cardiac troponin T (hs-cTnT) 0-hour/1-hour algorithm is only available for users that are subscribed to it.

Visit our library for more prediction models

Evidencio Pro

€9,99 / Month

This functionality is reserved for Pro subscribers.
Please support us by registering as Evidencio Pro.

Clinical & Commercial use licence

Create licenced models

Unlimited Patient specific reports

Create direct access for peer reviewers.

Use licensed models

Cancel at any time

For a complete list of all the benefits, see Use & Licensing

Looking to manage Teams Or EHR integration? Get in touch with our team.

Signup for Pro subscription

Select the version you want to duplicate Are you sure you want to duplicate this model?

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.

Login

Sign Up

Calculate the result

Absolute change of hs-cTnT: ng/L within the first hour

Conditional information

Details

Study characteristics

Additional information

Study Population

Continuous characteristics

Categorical characteristics

Supporting Publications

Related files

This model has been certified as a medical device

This is a paid model

Select the version you want to duplicate Are you sure you want to duplicate this model?

Please sign in to enable Evidencio print features

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

Evidencio Community Account Benefits

{{ variable.title }}

	Evidencio B.V., Irenesingel 19, 7481 GJ Haaksbergen, The Netherlands
	V-1.41-2426.23.12.18
	(01)08719327522776(8012)v1.41(4326)231218(240)2426
	Medical device