Probability of heart failure in frail elderly with dyspnea
This model calculates the probability of heart failure in frail elderly with complaints of dyspnea.  
 
Research authors: Bertens LC, Moons KG, Rutten FH, van Mourik Y, Hoes AW, Reitsma JB
Details Formula Study characteristics Files & References
Model author
Model ID
753
Version
1.12
Revision date
2018-04-24
Specialty
MeSH terms
  • Clinical Prediction Rule
  • Heart Failure
  • Model type
    Logistic regression (Calculation)
    Status
    public
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    Formula
    No Formula defined yet
    Condition Formula

    Additional information

    Study summary:
    The study population was derived from a cluster randomized trial in which community-dwelling frail elderly with complaints of dyspnea and/or reduced exercise tolerance were evaluated. Frailty was defined as three of more comorbidities or the chronic use of five or more drugs. A total of 376 frail elderly with complaints of dyspnea were included in the study. A nomogram was developed to calculate the probability for heart failure or individual patients.

    Source: 
    Bertens LC, Moons KG, Rutten FH, et al. A nomogram was developed to enhance the use of multinomial logistic regression modeling in diagnostic research. J Clin Epidemiol. 2016;71:51-7

    Study Population

    Total population size: 376

    Additional characteristics

    No additional characteristics defined

    Individual probability of heart failure in frail elderly with dyspnea:
    ...

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    Result
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    Individual probability of heart failure in frail elderly with dyspnea:

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    Outcome stratification

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    Conditional information

    Result interpretation

    How this model should be used: 
    This model calculates the probability of chronic obstructive pulmonary disease (COPD) in frail elderly with complaints of dyspnea. 

    Model performance: 
    In the underlying study population consisting of 376 frail elderly with complaints of dyspnea, prevalence of heart failure was 20% (n=75). No internal and/or external model validation were performed so far. 

    Model limitations: 
    External model validation is needed before it can be considered for application in clinical practice.


    Source: 
    Bertens LC, Moons KG, Rutten FH, et al. A nomogram was developed to enhance the use of multinomial logistic regression modeling in diagnostic research. J Clin Epidemiol. 2016;71:51-7

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

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