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arXiv · 2511.09584

Similarity Analysis of Blood Count Reference Intervals Across Continents Reveals No Reproducible Population or Geography-Linked Structure and Supports Personalised Values

Kunlin Wu·Abicumaran Uthamacumaran·Hector Zenil
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Abstract

Blood reference intervals (RIs) underpin diagnostic interpretation and therapeutic monitoring worldwide. However, many widely used RI systems originate from limited historical cohorts and have been propagated across health systems without harmonised derivation protocols, shared metadata, or cross-population validation. Consequently, the global RI landscape reflects a heterogeneous mixture of legacy standards and local laboratory practices rather than a biologically grounded framework. Here we examine published Complete Blood Count (CBC) reference intervals, one of the most commonly used laboratory panels worldwide. We compiled CBC RI data from 28 countries and analysed their similarity using variability mapping, hierarchical clustering, information-theoretic distances, cohesion benchmarking, and nonlinear manifold visualisation. Body mass index (BMI) served as a methodological positive benchmark and exhibited clear continent-level clustering (mean cohesion approximately 0.78-0.81). In contrast, CBC reference intervals showed no reproducible geography-linked clustering across methods, with uniformly high cohesion scores (mean approximately 1.27-1.30). Weak signals in red-cell indices (MCV, HGB) were unstable across sexes and distance metrics. This absence of structure should not be interpreted as evidence that current CBC reference intervals represent universal biological standards. Rather, it is more consistent with the fragmented and historically inherited nature of the global RI landscape. These findings indicate that published CBC reference intervals do not encode coherent global structure and provide limited support for universal population-based diagnostic thresholds. Instead, they support a transition toward recalibrated and personalised reference frameworks based on longitudinal individual baselines and harmonised derivation standards.

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Kunlin Wu, Abicumaran Uthamacumaran, Hector Zenil. 2025-11-12. Similarity Analysis of Blood Count Reference Intervals Across Continents Reveals No Reproducible Population or Geography-Linked Structure and Supports Personalised Values. https://arxiv.org/abs/2511.09584

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