Interferences in Clinical Chemistry: A Neglected Cause of Laboratory Errors in Medical Practice in resource constrained settings

Abstract

Interferences—endogenous and exogenous factors that distort analytical measurements remain an under-recognized source of laboratory error, particularly in low-resource settings. In Nigeria and Sub-Saharan Africa (SSA), persistent limitations in laboratory infrastructure, workforce training, and quality management systems exacerbate vulnerabilities across the total testing process and increase the risk of clinically significant errors. This review aimed to examine the types, mechanisms, frequency, and clinical impact of common analytical interferences in clinical chemistry, with particular emphasis on haemolysis, lipaemia, and icterus (HIL); to identify key drivers of interference-related errors in SSA; and to propose pragmatic mitigation strategies tailored to resource-limited laboratories.

A narrative review of peer-reviewed literature and authoritative laboratory guidelines was conducted using PubMed and PubMed Central up to November 26, 2025. Search terms included “haemolysis,” “lipaemia,” “icterus,” “pre-analytical error,” “interference,” “clinical chemistry,” “Nigeria,” and “Africa.” Priority was assigned to studies originating from SSA or those directly relevant to low-resource laboratory settings, as well as to international consensus and professional guidelines.

Haemolysis, lipaemia, and icterus were consistently identified as the most frequent endogenous interferences and major contributors to pre-analytical and analytical errors. A systematic review of African laboratories reported a pooled pre-analytical error prevalence of approximately 17.5% (95% CI: 11.6–23.5%), substantially exceeding rates commonly reported in high-income countries, with haemolysis being the leading cause of sample rejection and analytical error. Despite limited sensitivity, visual inspection remains the predominant method for interference detection in many SSA laboratories, whereas automated HIL indices and assay-specific rejection thresholds demonstrably improve detection, standardization, and clinical decision-making. Contributing factors include inadequate phlebotomy training, delayed specimen transport, absence of standardized rejection policies, and lack of local verification of manufacturer interference limits.

Interference-related errors in clinical chemistry are common, clinically significant, and frequently overlooked in SSA. Implementing targeted phlebotomy training, simple workflow improvements, adoption or verification of HIL indices, method-by-method interference validation, and participation in external quality assessment can substantially reduce error rates and enhance patient safety, even within constrained resources.