New Research Challenges How Doctors Monitor Kidney Disease Decline

For decades, doctors have used complex mathematical equations to estimate how well a person’s kidneys are working. But a landmark study published in the British Medical Journal reveals that these equations may be missing something crucial: they consistently underestimate how quickly kidney function actually declines over time. This finding could fundamentally change how patients with chronic kidney disease are monitored and treated.

The research, which examined thousands of patients across the UK, Canada, and Denmark, suggests that doctors and patients have been relying on a flawed approach. Rather than focusing solely on a single glomerular filtration rate (GFR) reading—essentially a snapshot of kidney function at one moment—clinicians should prioritise understanding the speed at which kidney function is deteriorating. This distinction matters far more for treatment decisions, risk assessment, and preparation for future kidney replacement therapy than anyone previously realised.

The glomerular filtration rate is one of the most important markers in medicine. It measures how well the kidneys are filtering waste from the blood, with measurements expressed in millilitres per minute per 1.73 square metres of body surface area. For nearly 20 years, researchers have been refining equations that estimate this figure based on blood creatinine levels and other biomarkers.

These equations have genuinely improved care. They have standardised how chronic kidney disease is classified and enabled better communication between hospitals and GP surgeries across the country. However, the new research highlights a critical limitation: the equations work well at providing a single snapshot but fail to accurately capture whether kidney function is declining slowly or rapidly—arguably the most clinically important question.

The BMJ study examined patients in moderate-stage chronic kidney disease (stage 3, with GFR readings between 30-59 mL/min/1.73 m²). Researchers assessed three different equations recommended by KDIGO (Kidney Disease: Improving Global Outcomes), an internationally respected guideline organisation. These equations used creatinine alone, cystatin C alone, or a combination of both.

The findings were striking. When researchers followed patients over several years, the equations consistently underestimated how fast renal function was declining. This means that using current equations, a patient might appear to be losing kidney function slowly when in reality their kidneys are failing more rapidly. Such errors could lead to delayed referrals to kidney specialists and missed opportunities for early intervention.

The commentary notes a specific example: an 80-year-old man with an eGFR of 30 mL/min/1.73 m² and elevated protein in his urine. Using existing equations, his five-year risk of kidney failure would be estimated at 10%—just above the threshold for nephrology referral. Yet newer prediction models suggest his actual risk may be substantially different, potentially triggering diverging treatment decisions.

The central clinical insight here is deceptively simple: in chronic kidney disease care, the crucial question is often not “what is the GFR today?” but rather “how fast is it falling?” A person whose kidney function drops from 40 to 38 in six months is in a very different situation than someone whose GFR falls from 40 to 20 over the same period, even if both started at the same point.

This matters for several practical reasons. First, it affects when patients should be referred to nephrology specialists. Second, it influences discussions about kidney replacement therapy options and timing. Third, it determines what medications might be most appropriate. Fourth, it affects whether a patient should be placed on a transplant waiting list.

By underestimating the slope of decline, current equations may inadvertently delay appropriate specialist care for many patients. Conversely, for those whose kidneys are actually declining more slowly than the equations suggest, unnecessary alarm and aggressive treatment might be avoided.

The research also highlighted the emergence of newer prediction tools, such as KDpredict, which uses machine learning algorithms to account for multiple factors including age, sex, kidney function, protein in the urine, diabetes status, and cardiovascular disease. These advanced models demonstrated better accuracy than traditional equations in predicting both kidney failure risk and mortality risk—a critical consideration since many people with advanced kidney disease die from cardiovascular causes before their kidneys fail completely.

The implications extend beyond simple number-crunching. As populations age and conditions like diabetes and high blood pressure become more common, improving our ability to predict which patients will progress to kidney failure becomes increasingly important for healthcare systems. Early, accurate identification allows for preventative strategies and timely planning.

The BMJ commentary emphasises that whilst standardised equations have value, they must be interpreted within the context of an individual patient’s disease trajectory. Future monitoring strategies should place greater emphasis on the trend of declining kidney function over time, potentially using multiple measurements to establish the rate of change rather than relying too heavily on single readings.

This doesn’t mean existing tests are useless. Rather, it suggests they should be one piece of a more sophisticated assessment that considers how quickly a patient’s kidneys are failing.

Key Takeaways

• Current equations for measuring kidney function may underestimate how fast the kidneys are declining over time
• Clinicians should focus more on the rate of kidney function decline rather than single test measurements when making treatment decisions
• Newer prediction tools using machine learning appear more accurate at identifying patients at highest risk of kidney failure
• This research could lead to earlier specialist referrals and more personalised treatment planning for people with chronic kidney disease

What This Means for Kent Residents

If you have been diagnosed with chronic kidney disease, this research suggests your GP and specialist should be looking beyond your single GFR number. Ask your healthcare team about your kidney function trend—how has it changed over the last six months or year? This information is increasingly important for planning your care.

NHS Kent and Medway ICB commissions kidney services across the region, with major nephrology centres at Maidstone and Tunbridge Wells NHS Trust and East Kent Hospitals University NHS Foundation Trust. If you have chronic kidney disease, your GP can arrange tests to monitor your kidney function. If you’re concerned about your kidney health, or if you’ve been told you have declining kidney function, discuss referral to a nephrologist with your GP. Early specialist input, guided by accurate understanding of your disease progression, can make a significant difference in slowing decline and planning for future treatments.