{{ section.description }}
How this model should be used:
This model can be applied to predict heart failure in the large domain of the elderly with shortness of breath. Therewith, it could help general practitioners to select those needing echocardiography.
Model limitations:
In total, 366 participants (62.6%) underwent echocardiography. Not performing echocardiography in those with a normal ECG in combination with NTproBNP levels below 14.75 pmol/L may have caused partial verification bias.
Model performance:
Evaluation of the discriminative power of te model resulted in a concordance index (c-index) of 0.88 (range: 0.85-0.90). In addition, the model showed high accuracy with a negative predictive value of 87% and a positive predictive value of 73%.
Model generalisability:
Evaluating the improved rule in the derivation set and an independent set of patients with type 2 diabetes aged 60 years or older showed satisfying generalisability of the rule.
Source:
van Riet EE, Hoes AW, Limburg A, et al. Extended prediction rule to optimise early detection of heart failure in older persons with non-acute shortness of breath: a cross-sectional study. BMJ Open 2016;6:e008225.
This algorithm is provided for educational, training and information purposes. It must not be used to support medical decision making, or to provide medical or diagnostic services. Read our full disclaimer.
With an Evidencio Community account you can:
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 algorithms.
{{ (typeof row === 'object') ? row.label : row }} |
{{ column }} | |
---|---|
{{ row.label }} | {{ value }} |
{{ error }}
Please enter a password
A password has to be at least 8 characters.
A password cannot be longer then 64 characters.
Choose a password with at least one capital letter.
Choose a password with at least one special character (@$!%*#?&)
Please agree to the Terms & Conditions and the Disclaimer
Please provide your e-mail address and we'll send you a link to reset your password.
Email Address
Please enter a valid email
If an account was registered with this email address you will receive a recovery link in your mail.
Please use the reset password link in it to set your new password.
Didn't receive the email yet? Please check your spam folder, or resend the email.