Does my patient have chronic Chagas disease? Development and temporal validation of a diagnostic risk score

Brasil, Pedro Emmanuel Alvarenga Americano do; Xavier, Sérgio Salles; Holanda, Marcelo Teixeira de; Hasslocher‐Moreno, Alejandro Marcel; Braga, José Ueleres

doi:10.1590/0037-8682-0196-2016

Cited by 7 publications

(9 citation statements)

References 22 publications

(20 reference statements)

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“…Our first example considers the minimum sample size required for developing a diagnostic model for predicting a binary outcome (disease: yes or no). Brasil et al developed a logistic regression model containing 14 predictor parameters for predicting the risk of having chronic Chagas disease in patients with suspected Chagas disease . Upon external validation in a cohort of 138 participants containing 24 with Chagas disease, the model had an estimated C statistic of 0.91 and an

R_{normalNagelkerke_app}^{2}

of 0.48.…”

Section: Worked Examplesmentioning

confidence: 99%

Minimum sample size for developing a multivariable prediction model: PART II ‐ binary and time‐to‐event outcomes

Riley

Snell

Ensor

et al. 2018

Statistics in Medicine

519

530

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When designing a study to develop a new prediction model with binary or time‐to‐event outcomes, researchers should ensure their sample size is adequate in terms of the number of participants (n) and outcome events (E) relative to the number of predictor parameters (p) considered for inclusion. We propose that the minimum values of n and E (and subsequently the minimum number of events per predictor parameter, EPP) should be calculated to meet the following three criteria: (i) small optimism in predictor effect estimates as defined by a global shrinkage factor of ≥0.9, (ii) small absolute difference of ≤ 0.05 in the model's apparent and adjusted Nagelkerke's R2, and (iii) precise estimation of the overall risk in the population. Criteria (i) and (ii) aim to reduce overfitting conditional on a chosen p, and require prespecification of the model's anticipated Cox‐Snell R2, which we show can be obtained from previous studies. The values of n and E that meet all three criteria provides the minimum sample size required for model development. Upon application of our approach, a new diagnostic model for Chagas disease requires an EPP of at least 4.8 and a new prognostic model for recurrent venous thromboembolism requires an EPP of at least 23. This reinforces why rules of thumb (eg, 10 EPP) should be avoided. Researchers might additionally ensure the sample size gives precise estimates of key predictor effects; this is especially important when key categorical predictors have few events in some categories, as this may substantially increase the numbers required.

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R_{normalNagelkerke_app}^{2}

of 0.48.…”

Section: Worked Examplesmentioning

confidence: 99%

Minimum sample size for developing a multivariable prediction model: PART II ‐ binary and time‐to‐event outcomes

Riley

Snell

Ensor

et al. 2018

Statistics in Medicine

519

530

View full text Add to dashboard Cite

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“… 22 This lack of familiarity with ChD in the medical community poses significant barriers to accessing appropriate and timely healthcare for ChD patients. 2 , 23…”

Section: Discussionmentioning

confidence: 99%

“…Pertinent questions about the patient include birthplace, countries of long-term residence, country of birth mother’s residence, and history of blood transfusions/organ transplantation. 2 Since 2016, an online calculator has been available to aid clinicians in predicting a patient’s risk of chronic ChD. 2 Certain characteristics associated with the CCM patient can also help physicians: most are young (30–50 years of age) and present with atypical chest pain, palpitations, bradycardia, syncope, symptoms of congestive heart failure, or thromboembolic manifestations.…”

Section: Discussionmentioning

confidence: 99%

“…Chagas disease (ChD) has become a global public health problem due to high rates of immigration from endemic to non-endemic countries. 1 , 2 An estimated 7–8 million individuals worldwide are infected with ChD, mostly in Latin America. 3 , 4 In the United States there are >300,000 ChD-infected individuals, of whom 30,000–45,000 are estimated to have undiagnosed Chagas cardiomyopathy (CCM), the primary form of chronic ChD.…”

Section: Introductionmentioning

confidence: 99%

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Chagas Disease-induced Sudden Cardiac Arrest

Neeki¹,

Park²,

Sandhu³

et al. 2017

CPC-EM

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Sudden cardiac death (SCD) is the most common cause of death in patients with Chagas disease (ChD). There are over 300,000 ChD-infected individuals living in the United States, of whom 10–15% have undiagnosed Chagas cardiomyopathy (CCM). CCM patients have a higher risk of SCD compared to non-CCM patients, although early and appropriate treatment of CCM patients can result in a 95% relative risk reduction of SCD. Emergency physicians have a unique opportunity to improve outcomes among these patients by becoming more vigilant in recognizing the signs and symptoms of CCM in patients who present in sudden cardiac arrest. We report the case of a patient presenting to the emergency department with pulseless ventricular tachycardia and an undiagnosed history of CCM.

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“…In 2016, Brasil et.al. 7 developed and validated a diagnostic decision support tool to decide about proceed or not to diagnostic investigations for chronic Chagas disease. The following predictors were identified: sex, age, referral from blood bank, history of living in a rural area, recognizing the kissing bug from pictures, systemic hypertension, number of siblings with Chagas disease, number of relatives with history of stroke, electrocardiogram with low voltage, anterior superior divisional block, pathologic Q wave, right bundle branch block, and extrasystoles.…”

mentioning

confidence: 99%