Back

Point-of-care prognostication in moderate Covid-19: analytical validation and diagnostic accuracy of a soluble urokinase plasminogen activator receptor (suPAR) rapid test

Chandna, A.; Mahajan, R.; Gautam, P.; Mwandigha, L.; Dittrich, S.; Kumar, V.; Osborn, J.; Kumar, P.; Koshiaris, C.; Varghese, G. M.; Lubell, Y.; Burza, S.

2022-11-27 infectious diseases
10.1101/2022.11.25.22282755 medRxiv
Show abstract

The soluble urokinase plasminogen activator receptor (suPAR) has been proposed as a biomarker for the risk stratification of patients presenting with acute infections. However, most studies evaluating suPAR have used platform-based assays, the diagnostic accuracy of which may differ from point-of-care tests capable of informing timely patient triage in settings without established laboratory capacity. Using samples and data collected during a prospective cohort study of 425 patients presenting with moderate Covid-19 to two hospitals in India, we evaluated the analytical performance and diagnostic accuracy of a commercially-available rapid diagnostic test (RDT) for suPAR, using an enzyme-linked immunoassay (ELISA) as the reference standard. Although agreement between the two tests was limited (bias = -2.46 ng/mL [95% CI = -2.65 to -2.27 ng/mL]), diagnostic accuracy to predict progression to supplemental oxygen requirement was comparable, whether suPAR was used alone (area under the receiver operating characteristic curve [AUC] of RDT = 0.73 [95% CI = 0.68 to 0.79] vs. AUC of ELISA = 0.70 [95% CI = 0.63 to 0.76]; p = 0.12) or as part of a previously published multivariable clinical prediction model (AUC of RDT-based model = 0.74 [95% CI = 0.66 to 0.83] vs. AUC of ELISA-based model = 0.72 [95% CI = 0.64 to 0.81]; p = 0.78). Lack of agreement between the suPAR RDT and ELISA in our cohort warrants further investigation and highlights the importance of assessing candidate point-of-care tests to ensure management algorithms reflect the assay that will ultimately be used to inform patient care. The availability of a quantitative point-of-care test for suPAR opens the door to suPAR-guided risk stratification of patients with Covid-19 and other acute infections in settings with limited laboratory capacity.

Matching journals

The top 10 journals account 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.