Synergus

LABKA and RLRR: Denmark’s Rich Laboratory Data Sources

Denmark has a long tradition of comprehensive health registries, and the laboratory databases LABKA and RLRR are prime examples. LABKA (the Clinical Laboratory Information System Research Database) was established at Aarhus University and initially captured routine lab test results for residents of North and Central Denmark regions starting in the late 1990s. RLRR (the Register of Laboratory Results for Research) is a newer national database that since the 2010s has collected laboratory results across all five Danish regions. In combination, these two resources offer an unparalleled depth and breadth of lab data: LABKA provides decades of historical results in its regions, while RLRR contains nationwide results (~5.8 million people) with complete country-wide coverage achieved by 2015. Together they include virtually all routine blood and urine analyses performed in Danish hospitals and primary care, from basic blood counts and electrolytes to kidney and liver function tests, lipids, and more. Each test record is tagged with a unique personal identifier (the CPR number), timestamp, standardized test codes, result values and units, allowing for precise longitudinal tracking of biomarker measurements for every individual. These features make LABKA and RLRR powerful real-world data sources for epidemiological research[1][2].

Researchers and industry analysts can use LABKA/RLRR to examine real-world patient outcomes, treatment effects, and disease prevalence with laboratory-confirmed definitions. For example, conditions that are often missed in diagnosis registries can be identified via abnormal lab results. A striking case was hyponatremia (low sodium): one study found that only ~2% of patients with critically low sodium levels in LABKA had a hyponatremia diagnosis recorded in the National Patient Registry. Laboratory data thus reveal important patient conditions that routine hospital codes overlook. Overall, the LABKA and RLRR databases provide a nationally comprehensive, population-based laboratory dataset covering millions of patients and billions of test results, enabling researchers to explore health phenomena that were previously infeasible to study at scale.

Linkage with Other Danish Health Registries for Powerful RWE

One of the greatest strengths of Danish data infrastructure is the ability to link disparate data sources at the individual level. Every Danish resident has a CPR number (unique personal ID) used across all health registries. LABKA and RLRR leverage this to link lab results with rich contextual data from other national databases. This means a patient’s lab values can be seamlessly connected to their hospital diagnoses (Patient Registry), prescription fills (National Prescription Registry), cancer registrations (Cancer Registry), vital status and cause of death, and more. The result is a 360-degree view of real-world patient outcomes.

By linking laboratory data with clinical and demographic data, researchers can define cohorts and outcomes with high precision. For instance, one can identify patients with chronic conditions (like diabetes or chronic kidney disease) based on lab criteria even if they lack an official diagnosis, or evaluate medication safety by observing lab-defined adverse events (e.g. elevated potassium or liver enzymes) following drug exposures. The linkage allows robust confounder adjustment and subgroup analyses: lab results add granularity on disease severity (such as HbA1c levels for glycemic control or creatinine for renal function), while registry data provide information on comorbidities, treatments, and long-term endpoints (hospitalizations, survival, etc.). In short, LABKA/RLRR combined with Denmark’s other health registries offers a powerful Real-World Evidence (RWE) platform that is population-wide, longitudinal, and capable of supporting advanced pharmacoepidemiology and outcomes research.

Driving Kidney Disease Research with Lab Data: CKD, AKI, and Hyperkalemia

A particularly impactful use of LABKA and RLRR has been in kidney disease research. Because kidney conditions are defined and monitored largely by lab measurements (creatinine, eGFR, electrolytes, etc.), these databases have enabled landmark RWE studies in this domain. Below we highlight a few examples of how Danish lab data have advanced understanding of kidney-related diseases:

• Chronic Kidney Disease (CKD): Using LABKA/RLRR creatinine data, researchers conducted a population-based cohort study among ~1.5 million adults in North and Central Denmark to estimate CKD incidence and prevalence over 2011–2021. The study found that while CKD incidence showed a slight decline in the latter half of the decade, CKD prevalence actually increased, reflecting better survival and accumulation of CKD patients. Notably, CKD remained more common in women than men throughout the period. These trends provide valuable insights into the evolving CKD burden and have implications for healthcare planning[3].
• Acute Kidney Injury (AKI): LABKA and RLRR allow identification of AKI events directly from lab results (acute rises in creatinine). In a nationwide study of first-time AKI episodes (2010–2017), over 98,000 patients with serial creatinine measurements were analyzed. The findings revealed that an episode of AKI is often followed by an incomplete recovery of kidney function. Patients with normal pre-injury kidney function saw their long-term eGFR drop by a median of ~5.6 mL/min/1.73m² after AKI, indicating a persistent loss of renal function. Those with pre-existing CKD had smaller declines, and some even experienced a slight improvement in trajectory post-AKI. This granular analysis of eGFR slopes before and after AKI – only possible with serial lab data – has important implications for post-AKI care and risk stratification[4].
• Hyperkalemia (Elevated Potassium): Hyperkalemia is a potentially life-threatening electrolyte disturbance, often related to kidney dysfunction or certain medications. Danish lab databases have been used to characterize the epidemiology of hyperkalemia in large chronic disease populations. For example, one cohort study of ~300,000 CKD patients found that hyperkalemia (K⁺ >5.0 mmol/L) occurred at a rate of roughly 10% per year in the CKD population. In patients with heart failure and diabetes (studied separately), incidence rates were also significant (≈25% and 5% per year, respectively). The lab data further enabled stratification of hyperkalemia by severity: about 10% of CKD patients’ events reached >5.5 mmol/L (moderate/severe hyperkalemia). Such studies have shed light on risk factors (e.g. use of RAAS inhibitor medications) and prognosis following hyperkalemia in real-world settings. Importantly, they highlighted that a large proportion (~44%) of patients who experience one hyperkalemia episode have recurrent episodes, underscoring the need for vigilant monitoring and management[5]. These insights inform safer use of medications and better clinical guidelines for managing high potassium, especially in CKD and heart failure patients.

Conclusion

With their extensive and high-quality laboratory test data, the Danish LABKA and RLRR databases open up unique opportunities for real-world evidence generation. These resources provide national-scale lab results with individual-level linkage to other health registries, enabling researchers to study disease epidemiology, treatment effects, and patient outcomes with a level of detail and population coverage that is difficult to achieve elsewhere. The impact has been particularly evident in nephrology, where lab-defined conditions like CKD, AKI, and hyperkalemia can be studied in the entire population. But the potential extends to many other domains – from cardiology to endocrinology to oncology – wherever objective lab measures enrich our understanding of health and disease. For industry stakeholders, collaborations using Danish lab databases can yield valuable insights into real-world disease burden, therapy safety and effectiveness, and unmet needs in patient care. In an era increasingly focused on real-world data, LABKA and RLRR exemplify how investing in robust data infrastructure can translate into better evidence for decision-making in healthcare.

References

1. Arendt, Johan Frederik Håkonsen, Anette Tarp Hansen, Søren Andreas Ladefoged, Henrik Toft Sørensen, Lars Pedersen, and Kasper Adelborg. “Existing Data Sources in Clinical Epidemiology: Laboratory Information System Databases in Denmark.” Clinical Epidemiology 12 (2020): 469–75. https://doi.org/10.2147/CLEP.S245060.
2. Jensen, Simon Kok, Uffe Heide-Jørgensen, Søren Viborg Vestergaard, Henrik Toft Sørensen, and Christian Fynbo Christiansen. “Routine Clinical Care Creatinine Data in Denmark – An Epidemiological Resource for Nationwide Population-Based Studies of Kidney Disease.” Clinical Epidemiology Volume 14 (November 2022): 1415–26. https://doi.org/10.2147/CLEP.S380840.
3. Vestergaard, Anne Høy Seemann, Simon Kok Jensen, Uffe Heide-Jørgensen, Søren Andreas Ladefoged, Henrik Birn, and Christian Fynbo Christiansen. “Sex-Specific Temporal Trends in Incidence and Prevalence of Chronic Kidney Disease: A Danish Population-Based Cohort Study.” Clinical Kidney Journal 18, no. 1 (January 2025): sfae351. https://doi.org/10.1093/ckj/sfae351.
4. Jensen, Simon Kok, Uffe Heide-Jørgensen, Søren Viborg Vestergaard, Henrik Gammelager, Henrik Birn, Dorothea Nitsch, and Christian Fynbo Christiansen. “Kidney Function before and after Acute Kidney Injury: A Nationwide Population-Based Cohort Study.” Clinical Kidney Journal 16, no. 3 (March 2023): 484–93. https://doi.org/10.1093/ckj/sfac247.
5. Kim, Kun, Reimar Wernich Thomsen, Sia Kromann Nicolaisen, Lars Pål Hasvold, Eirini Palaka, and Henrik Toft Sørensen. “Healthcare Resource Utilisation and Cost Associated with Elevated Potassium Levels: A Danish Population-Based Cohort Study.” BMJ Open 9, no. 4 (April 1, 2019): e026465. https://doi.org/10.1136/bmjopen-2018-026465.