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Updated: Mar 21, 2026
Dried Blood Spots - Preparing and Processing for Use in Immunoassays and in Molecular Techniques
Published on: March 13, 2015
Active tracking of rejected dried blood samples in a large program in Nigeria
Auchi Inalegwu1, Sunny Phillips1, Rawlings Datir1
1Auchi Inalegwu, Sunny Phillips, Rawlings Datir, Christopher Chime, Petronilla Ozumba, Samuel Peters, Charles Mensah, Alash'Le Abimiku, Patrick Dakum, Nicaise Ndembi, Institute of Human Virology, Abuja 900246, Federal Capital Territory, Nigeria.
Aim:
To study the impact of rejection at different levels of health care by retrospectively reviewing records of dried blood spot samples received at the molecular laboratory for human immunodeficiency virus (HIV) early infant diagnosis (EID) between January 2008 and December 2012.
Methods:
The specimen rejection rate, reasons for rejection and the impact of rejection at different levels of health care was examined. The extracted data were cleaned and checked for consistency and then de-duplicated using the unique patient and clinic identifiers. The cleaned data were ciphered and exported to SPSS version 19 (SPSS 2010 IBM Corp, New York, United States) for statistical analyses.
Results:
Sample rejection rate of 2.4% (n = 786/32552) and repeat rate of 8.8% (n = 69/786) were established. The mean age of infants presenting for first HIV molecular test among accepted valid samples was 17.83 wk (95%CI: 17.65-18.01) vs 20.30 wk (95%CI: 16.53-24.06) for repeated samples. HIV infection rate was 9.8% vs 15.9% for accepted and repeated samples. Compared to tertiary healthcare clinics, secondary and primary clinics had two-fold and three-fold higher likelihood of sample rejection, respectively (P < 0.05). We observed a significant increase in sample rejection rate with increasing number of EID clinics (r = 0.893, P = 0.041). The major reasons for rejection were improper sample collection (26.3%), improper labeling (16.4%) and insufficient blood (14.8%).
Conclusion:
Programs should monitor pre-analytical variables and incorporate continuous quality improvement interventions to reduce errors associated with sample rejection and improve patient retention.
