Back

Performance evaluation of new fluorescent-based lateral flow immunoassay for quantification of HbA1c in diabetic patients

Younes, N.; Al Ghwairi, M.; Majdalawieh, A. F.; Al-Dweik, N.; Nasrallah, G.

2022-10-27 health systems and quality improvement
10.1101/2022.10.27.22281596 medRxiv
Show abstract

BackgroundRapid and constant HbA1c level monitoring is essential in slowing the progression of Type 2 diabetes. This need becomes challenging in low resources countries where the social burden of the disease is overwhelming. Recently, fluorescent-based lateral flow immunoassays (LFIAs) gained wide attention for small or non-laboratory settings and population surveillance. AimThis study aim to evaluate the performance of novel fluorescence-based LFIA Finecare HbA1c Rapid Quantitative Test for quantitative measurement of HbA1c along with its reader (Model No. FS-113). MethodsWe conducted a retrospective study using 147 samples (fingerstick and venepuncture whole blood samples) analysed by Finecare HbA1c Rapid Quantitative Test. For validating Finecare measurements, results were compared with results of the reference assay: Roche Cobas Pro c 503. ResultsFinecare showed 92.7% sensitivity and 94.7% specificity compared to the Roche Cobas Pro c 503 using fingerstick whole blood samples. On the other hand, Finecare showed 98.7% sensitivity and 100% specificity compared to the Roche Cobas Pro c 503 using venepuncture blood samples. Cohens Kappa statistic denoted excellent agreement with Roche Cobas Pro c 503, with values being 0.84 (95% CI: 0.72-0.97) and 0.97 (95% CI: 0.92-1.00) using fingerstick whole blood samples and venous blood, respectively. In addition, a strong correlation was observed between Finecare/Roche Cobas Pro c 503 (r>0.9, p<0.0001) with fingerstick and venous blood samples. Most importantly, Finecare showed a significant difference between the normal, pre-diabetic, and diabetic samples (p<0.001). ConclusionFinecare is a reliable assay and can be easily implemented for long-term monitoring of HbA1c in diabetic patients, particularly in none or small laboratory settings.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.