Miranda José P, Osorio Javiera, Silva Marcia, Silva Carola, Madrid Victoria, Camponovo Rossana, Henríquez-Henríquez Marcela
Bupa Lab, part of Bupa, La Florida, Santiago, Chile.
Advanced Center for Chronic Diseases (ACCDiS), Pontificia Universidad Católica de Chile & Universidad de Chile, Santiago, Chile.
Heliyon. 2025 Jan 2;11(1):e41623. doi: 10.1016/j.heliyon.2025.e41623. eCollection 2025 Jan 15.
The SARS-CoV-2 pandemic caused millions of infections worldwide. Among the strategies for effective containment, frequent and massive testing was fundamental. Although sample pooling allows multiplying the installed analysis capacity, the definition of the number of samples to include in a pool is commonly guided more by economic parameters than analytical quality.
We developed a mathematical model to determine the pooling conditions that maximize reagent efficiency and analytical sensitivity. We evaluated 30 samples individually and in 2-sample to 12-sample pools. Using Passing Bablok regressions, we estimated the shift of Ct values in the RT-qPCR reaction for each pool size. With this Ct shift, we estimated sensitivity in the context of the distribution of 1,030 individually evaluated positive samples.
Our results showed that the most significant gain in efficiency occurred in the 4-sample pool, while at pools greater than 8-sample, there was no considerable reagent savings. Sensitivity significantly dropped to 87.18 %-92.52 % for a 4-sample pool and reached as low as 77.09 %-80.87 % in a 12-sample pooling.
Our results suggest that a 4-sample pooling maximizes reagent efficiency and analytical sensitivity. These considerations are essential to increase testing capacity and efficiently detect and contain contagious.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）大流行在全球范围内导致了数百万例感染。在有效的防控策略中，频繁且大规模的检测至关重要。尽管样本混合可以成倍提高现有分析能力，但样本池中样本数量的确定通常更多地受经济参数而非分析质量的指导。
我们开发了一个数学模型来确定能使试剂效率和分析灵敏度最大化的混合条件。我们对30个样本进行了单独检测，并将其组成2样本至12样本的样本池进行检测。通过Passing Bablok回归分析，我们估计了每个样本池大小在逆转录定量聚合酶链反应（RT-qPCR）反应中Ct值的变化。利用这种Ct值变化，我们在1030个单独评估的阳性样本分布的背景下估计了灵敏度。
我们的结果表明，4样本池的效率提升最为显著，而在大于8样本的样本池中，并没有可观的试剂节省。4样本池的灵敏度显著降至87.18% - 92.52%，在12样本混合时低至77.09% - 80.87%。
我们的结果表明，4样本混合可使试剂效率和分析灵敏度最大化。这些考量对于提高检测能力以及有效检测和控制传染性至关重要。
