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Marburg Heart Score (MHS)

Calculators  Cardiovascular
Marburg Heart Score (MHS) is quick and practical tool utilized to eliminate coronary heart disease (CHD) in patients presenting with chest pain
Female ≥65 years or male ≥55 years
No 0
Yes 1
Known CAD, cerebrovascular disease, or peripheral vascular disease
No 0
Yes 1
Pain worse with exercise
No 0
Yes 1
Pain reproducible with palpation
No 1
Yes 0
Patient assumes pain is cardiac
No 0
Yes 1
Result:

Background

Measured Factor
Marburg Heart Score
Measured Factor Disease
  • Coronary artery disease
Measured Factor Detail
Marburg Heart Score (MHS) is used for the assessment of cardiovascular disease. It is used to enclose the coronary artery disease with chest pain. The calculation takes into account patient features such as gender, Pain worse during exercise, pain reproducible with palpation and pain is cardiac.
Speciality
Cardiologist
Body System
Cardiovascular
Measured Factor Low Impact
  • Score 0-2 illustrates low risk of unstable CAD
  • Need of outpatient evaluation
Measured Factor High Impact
  • Score ≥3 indicates high risk of CAD
  • Consider inpatient admission

Result Interpretation

Ranges Ranges
  • Critical High: ≥3
  • Normal: 2-3
  • Normal Adult Male: 2-3
  • Normal Adult Female: 2-3
  • Normal Geriatric Male: 2-3
  • Normal Geriatric Female: 2-3
Result High Conditions
  • Coronary artery disease
  • Chest pain
False Positive
  • Anxiety
  • Morbidity from additional testing
References: 2
Test Limitations
Not to be used for a positive diagnosis of angina or CAD
References: 3

Studies

Study Validation 1
The purpose of the study was to evaluate the accuracy of Marburg Heart Score (MHS) in patients suffering from chest pain. This score can aid in physicians to take the management decisions more adequately. A total of 844 patients aged ≥ 35 years presented with chest pain were enrolled in this study conducted between 2009 and February 2010. Each patient was assigned with MHS score and measures of area under the receiver operating characteristic curve (AUC), sensitivity, specificity, likelihood ratios, and predictive values were evaluated. Results showed that sensitivity of score was 89.1% (95% CI = 81.1% to 94.0%), and specificity was found to be of 63.5% (95% CI = 60.0% to 66.9%). AUC came with value of 0.84. This study concludes that MHS can be considered to physicians to diagnose the patients presented with chest pain.
References: 4
Study Validation 2
The objective of the study was to determine the effectiveness of MHS score in clinical judgment made by general practitioners. This score can provide additional help to GP in ruling out coronary heart disease (CHD) in subjects with chest pain. A total 832 patients with chest pain were scrutinized in the study. MHS was utilized based on three diagnostic approaches: diagnosis based purely on the MHS; using the MHS as a triage test; and GP's clinical judgment assisted by the MHS. Results of the study showed sensitivity and specificity of the GPs' unaided clinical judgment was 82.9% when compared with other both approaches. This study concluded that utilizing MHS for initial triage can strengthen the judgment made by physicians in patients with chest pain
References: 5
Study Additional 1
This study aimed to validate the performance of CAD score in ruling out chances of coronary heart disease in patients who are presented with chest pain at primary care. A total of 672 consecutive patients with chest pain were recruited in the study. Risk factors assessed for the development of clinical score were cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease. Primary variables observed in patients were age, gender, duration and location of chest pain, absence of tenderness point at palpation, CV risk factors. 413 patients were considered as low risk for developing the coronary heart disease. Results showed were sensitivity and specificity of CAD score were 85.6% and 47.2% respectively. This study concluded that MHS score can be important tool for ruling out coronary heart disease in primary care patients presented with chest pain.
References: 6
Study Additional 2
This study was aimed to develop and validate a simple prediction rule to exclude the Coronoary heart disease in patients complaining of chest pain. For this 1249 patients were recruited at primary care in Germany. Their symptoms and observations were recorded by the physicians. Prediction rule was based on the five variables: age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation and score ranged from 0-5 which was based on the presence of above symptoms. Results showed that AUC (receiver operating characteristic curve) was 0.87 with 95% CI. Cut off value of score 3 showed best overall discrimination (positive result 3-5 points; negative result <or= 2 points). The sensitivity and specificity were found to be 87.1% and 80.8% respectively. This study concluded that this prediction rule can aid physicians to rule out CHD in patients who are complaining about chest pain.
References: 7

References

  1. Bösner S1, Haasenritter J, Becker A, Karatolios K, Vaucher P, Gencer B, Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.CMAJ. 2010 Sep 7;182(12):1295-300. doi: 10.1503/cmaj.100212. Epub 2010 Jul 5.
  2. Haasenritter J, Donner-banzhoff N, Bösner S. Chest pain for coronary heart disease in general practice: clinical judgement and a clinical decision rule. Br J Gen Pract. 2015;65(640):e748-53.
  3. Cayley Jr WE. Chest pain--tools to improve your in-office evaluation. Journal of Family Practice. 2014 May 1;63(5):246-52.
  4. Haasenritter J, Bösner S, Vaucher P, Herzig L, Heinzel-Gutenbrunner M, Baum E, et al. Ruling out coronary heart disease in primary care: external validation of a clinical prediction rule. Br J Gen Pract. 2012 Jun;62(599):e415-21. doi: 10.3399/bjgp12X649106.
  5. Haasenritter J, Donner-Banzhoff N, Bösner S. Chest pain for coronary heart disease in general practice: clinical judgement and a clinical decision rule. Br J Gen Pract. 2015 Nov;65(640):e748-53. doi: 10.3399/bjgp15X687385.
  6. Gencer B, Vaucher P, Herzig L, Verdon F, Ruffieux C, Bösner S, Burnand B, Bischoff T, Donner-Banzhoff N, Favrat B. Ruling out coronary heart disease in primary care patients with chest pain: a clinical prediction score. BMC Med. 2010 Jan 21;8:9. doi: 10.1186/1741-7015-8-9.
  7. Aerts M, Minalu G, Bösner S, Buntinx F, Burnand B, Haasenritter J, Herzig L, et al. Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care. J Clin Epidemiol. 2017 Jan;81:120-128. doi: 10.1016/j.jclinepi.2016.09.011.