Emergency physicians commonly use a combination of history, physical exam, EKG, labs, and imaging to help diagnose congestive heart failure (CHF) in the emergency department in patients who present with shortness of breath. However, sometimes it can be confusing and what initially looks like heart failure ends up being something else, such as pneumonia (1-3). Misdiagnosis can have real consequences, particularly when diuretics used to improve CHF result in worsened conditions such as a pulmonary embolus or other serious pathologies.
In a recent paper, Basset et al derived and validated a CHF clinical prediction rule called the Brest score (4) which is intended to improve the accuracy of a heart failure diagnosis in ED patients. They looked at 927 undifferentiated dyspneic patients in their ED to create it and externally validated it in 206 patients. The score relies on 11 variables based only on history, physical, and EKG to risk stratify patients into low, intermediate, and high probability groups.
The prevalence of confirmed CHF patients was 6.7% in the low probability group, 58% in the intermediate, and 91.5% in the high. The authors argue that these results are accurate enough when weighing risks and benefits to begin early treatment in the high risk group. Unlike many diagnoses made in the ED, a healthcare provider using this score may not necessarily have to wait for labs or radiology results to initiate management. On the other spectrum, with so few CHF patients in the low risk group, patients who are low risk by the Brest score should prompt the provider to search for other etiologies of dyspnea.
There were several limitations of the paper. The score still needs a prospective impact analysis validation, it was from a single center, and several pathologies may coexist in a single patient. Although the risk-benefit ratio skews towards treatment in the high risk group, the subsequent management of CHF is not benign especially in volume-depleted patients.
The Brest score represents an interesting adjunct in the early diagnosis of CHF in the undifferentiated dyspneic ED patient. With time being an important factor in management and disposition of CHF, the score stands alone in quickly risk stratifying the patient without waiting for labs or radiology results. Other CHF decision rules, such as the Boston criteria (5), Steingart and PRIDE (6,7) decision tools, rely on time-delaying lab results such as BNP or radiology results such as a CXR. The Framingham (8) and Gothenburg (9) scores were epidemiologic studies and utilize certain factors that are not readily obtainable at the bedside.
Along with decision rules, other data at the bedside can be helpful to diagnose CHF, such as lung ultrasound. A 2015 multi-center prospective study (n=1005) by Pivetta et al demonstrated a significantly higher accuracy than all other standards when using the clinical evaluation and bedside lung ultrasound. Sensitivity was reported at 97% with specificity being 97.4%. Perhaps a completely validated Brest score could improve the diagnosis when used in conjunction with lung ultrasound and move away from using data such as BNP or chest xray. It could result in an accurate, bedside diagnosis that does not rely on labs or imaging. Although not ready for prime time, it could significantly increase the accuracy of CHF diagnosis and accelerate management in the undifferentiated dyspneic ED patient.
Brest score:
|
Variables |
Points (+2) |
|
Age > 65 |
1 |
|
Anamnesis variables |
|
|
Sudden dyspnea |
2 |
|
Onset of symptoms at night |
1 |
|
Orthopnea |
1 |
|
Risk Factor variables |
|
|
Prior CHF episode |
2 |
|
Myocardial infarction |
1 |
|
Chronic pulmonary disease |
-2 |
|
Clinical Examination variables |
|
|
Pulmonary crackles |
2 |
|
Pitting leg edema |
1 |
|
EKG Abnormality variables |
|
|
ST segment abnormalities |
1 |
|
Atrial fibrillation/flutter |
1 |
|
Max score |
15 |
Low Risk: ≤ 3
Medium Risk: 4 - 8
High Risk: ≥ 9
The Brest score starts automatically with 2 points – perhaps a superstitious move by the authors to avoid an unlucky total of 13 points.
References:
- Remes J, Miettinen H, Reunanen A, Pyörälä K. Validity of clinical diagnosis of heart failure in primary health care. Eur Heart J 1991;12:315–21.
- Fuat A, Hungin AP, Murphy JJ. Barriers to accurate diagnosis and effective management of heart failure in primary care: qualitative study. BMJ 2003;326:196.
- Ansari M, Massi BM. Heart failure: how big is the problem? Who are the patients? What does the future hold? Am Heart J 2003;146:1–4.
- Basset A, et al, Development of a clinical prediction score for congestive heart failure diagnosis in the emergency care setting: The Brest score, Am J Emerg Med (2016), http://dx.doi.org/10.1016/j.ajem.2016.08.023
- Schocken DD, Arrieta MI, Leaverton PE, Ross EA. Prevalence and mortality rate of congestive heart failure in the United States. J Am Coll Cardiol 1992;20:301–6.
- Baggish AL, Sieber U, Lainchbury JG, Cameron R, Anwaruddin S, Chen A, et al. A validated clinical and biochemical score for the diagnosis of acute heart failure. The ProBNP Investigation of Dyspnea in the Emergency Department (PRIDE) Acute Heart Failure Score. Am Heart J 2006;151:48–54.
- Steinhart B, Thorpe KE, Bayoumi AM, Moe G, Januzzi Jr JL, Mazer CD. Improving the diagnosis of acute heart failure using a validated prediction model. J Am Coll Cardiol 2009;54:1515–21.
- McKee PA, Castel WP, McNamara PM, KannelWB. The natural history of congestive heart failure: the Framingham Study. N Engl J Med 1971;285:1441–6.
- Eriksson H, Caidahl K, Larsson B, Ohlson LO,Welin L,Wilhelmsen L, et al. Cardiac and pulmonary causes of dyspnoea–validation of a scoring test for clinical-epidemiological use: the Study of Men Born in 1913. Eur Heart J 1987;8:1007–14.
Will Denq, MD is an Emergency Medicine Resident at The George Washington University Hospital
