By Azandizibusiso Mbonambi
Heart failure is an insidious condition in which the heart can no longer pump enough blood to meet the body’s needs. If you can cast your mind back to biology class, the heart is arguably the most vital organ in the body; to the point that clinical death is classified by the cessation of the heart pumping. So, if heart failure is such a life-threatening condition surely medical scientists have found a cure, right? I mean we’ve landed on the moon, we’ve made enormous medical advancements and we’re on the precipice of getting GTA 6 for goodness’ sake! Surely heart failure should have been solved by now.
Unfortunately, not.
Heart failure affects approximately 64 million people worldwide per year and that statistic is set to rise over the next few years as populations age. Although modern medicine has made tremendous progress, heart failure remains a progressive disease. The current treatment for heart failure focuses on slowing the disease, reducing the symptoms and easing the workload on the heart rather than curing it. This means that unless a patient qualifies for a heart transplant, heart failure is often a lifelong condition.
As grim as that sounds, and I don’t want to perpetuate any fear mongering, but this raises an uncomfortable reality. Even with treatment, many patients with chronic heart failure still face a significant risk of dying within just a few years of diagnosis. This burden is even greater in low- and middle-income countries, where access to specialist care, medications and advanced therapies is often limited.
This presents clinicians with a difficult challenge. Two patients may both have heart failure, yet one may live another ten years while the other deteriorates rapidly. So how do doctors decide who requires more aggressive treatment, closer monitoring, or referral for advanced therapies?
Ideally, patients at the highest risk should receive the most intensive care, while those at lower risk may not require the same level of intervention. However, research has shown a phenomenon known as the risk-treatment paradox, where lower-risk patients receive more aggressive treatment than those who need it the most. In resource-constrained healthcare systems, where every hospital bed and every specialist appointment counts, accurately identifying high-risk patients becomes even more important.
In 2013, a team of researchers led by medical statistician Dr Stuart Pocock set out to answer a simple but important question:
Can we accurately predict the survival of patients living with heart failure?
They collected data from 39,372 patients across 30 international heart failure studies. By analysing these data, they aimed to identify which clinical measurements best predicted a patient’s risk of death and combine them into a user-friendly bedside tool known as the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) risk score.
Without diving into the labour-intensive statistical modelling behind the scenes, the researchers essentially compared dozens of clinical characteristics to determine which ones consistently predicted survival. They began with 31 possible predictors and eventually identified 13 independent predictors that best estimated a patient’s risk of dying.
These predictors included factors such as age, heart pumping function (ejection fraction), kidney function, blood pressure, diabetes, smoking status, body mass index, chronic lung disease, and whether patients were receiving certain heart failure medications (shown in Figure 2).
The final result was remarkably simple. Instead of asking clinicians to perform complex statistical calculations, the researchers converted their findings into an easy-to-use scoring system. By adding together points assigned to each predictor, doctors could estimate a patient’s probability of dying within one or three years.
The score successfully separated patients into low- and high-risk groups, with predicted three-year mortality ranging from approximately 10% in the lowest-risk patients to almost 70% in the highest-risk patients (shown in Figure 3).
At first glance, this seems like a remarkable achievement. However, there is one important limitation that caught my attention.
Although the MAGGIC score was developed using over 39,000 patients, there was no evidence that the original development cohort included a South African population. While the model included patients from numerous international studies, most originated from Europe and North America. This raises an important question: Can a tool developed elsewhere accurately predict outcomes in South African patients, whose disease profiles, healthcare systems, and access to treatment may differ considerably?
That question is precisely why external validation studies are so important.
Rather than developing entirely new prediction tools, current research is increasingly focused on validating existing models in different populations and improving them by incorporating new biomarkers or artificial intelligence. If the MAGGIC risk score performs well in South African patients, it could become a valuable clinical tool to improve risk stratification and guide resource allocation in our overburdened healthcare system.
So, can we predict who will survive heart failure?
This study suggests that, to a meaningful degree, we can. While no prediction model can replace clinical judgement, tools like the MAGGIC risk score bring us one step closer to personalised medicine and helping clinicians make more informed decisions, ensuring that the right patients receive the right care at the right time.
References
Pocock, S.J., Ariti, C.A., McMurray, J.J.V., Maggioni, A., Køber, L., Squire, I.B., Swedberg, K., Dobson, J., Poppe, K.K., Whalley, G.A. and Doughty, R.N. (2012). Predicting survival in heart failure: a risk score based on 39 372 patients from 30 studies. European Heart Journal, 34(19), pp.1404–1413. doi:10.1093/eurheartj/ehs337.
Ponikowski, P., Anker, S. D., Alhabib, K. F., Cowie, M. R., Force, T. L., Hu, S., Jaarsma, T., Krum, H., Rastogi, V., Rohde, L. E., Samal, U. C., Shimokawa, H., Siswanto, B. B., Sliwa, K., & Filippatos, G. (2014). Heart Failure: Preventing Disease and Death Worldwide. ESC Heart Failure, 1(1), 4–25. https://doi.org/10.1002/ehf2.12005
Sliwa, K., Stewart, S., Viljoen, C., Allie, S., Hahnle, J., Damasceno, A., Jessen, N., Sani, M., Nel, G., Smith, D., Davison, B., & Cotter, G. (2025). Generating Important Insights into the Spectrum and Outcomes of Acute Heart Failure Across the African Continent: The Sub-Saharan Africa Survey of Heart Failure (THESUS-HF II). Global Heart, 20(1), 64. https://doi.org/10.5334/gh.1449
Mbanze, I., Spracklen, T. F., Jessen, N., Damasceno, A., & Sliwa, K. (2025). Heart failure in low-income and middle-income countries. Heart, 111(8), 341–351. https://doi.org/10.1136/heartjnl-2024-324176
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