Analytical Concordance Between The Modified Hodge Test, Carba NP, And Immunochromatographic Lateral Flow Assays For KPC And NDM Detection In Clinical Enterobacterales: A Systematic Review And Meta-Analysis Of Bench Validation Studies

Abstract

Background: Rapid identification of KPC and NDM carbapenemases in Enterobacterales is essential for targeted therapy and infection prevention. Objective: To evaluate and compare the analytical performance and concordance of three assays—Modified Hodge Test (MHT), Carba NP, and lateral-flow immunochromatographic assays (LFIAs)—against molecular reference standards. Methods: We conducted a PRISMA-2020–compliant systematic review of PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL (January 2010–October 2025) with PROSPERO registration. Eligible studies were bench or diagnostic-accuracy evaluations of clinical Enterobacterales with PCR/sequencing confirmation.

Two reviewers screened, extracted 2×2 data, and assessed quality using QUADAS-2. Accuracy was summarized with bivariate random-effects and HSROC models; analyses examined heterogeneity, subgroup effects (enzyme, species, setting, matrix), meta-regression, and Deeks’ test for small-study effects. Results: Across evaluations, LFIAs achieved the highest and most consistent accuracy for KPC and NDM with rapid turnaround and excellent concordance with PCR. Carba NP provided high specificity and good sensitivity under optimized buffers, inoculum, and readout but showed protocol-dependent variability.

 MHT yielded acceptable KPC detection in enriched panels yet demonstrated poor specificity for NDM and substantial heterogeneity, consistent with its archival status in standards. Sensitivity analyses and head-to-head comparisons supported the hierarchy LFIA ≥ optimized Carba NP ≫ MHT. Conclusions: LFIAs should be prioritized as the frontline test for KPC/NDM typing, with standardized Carba NP as an alternative where needed and molecular confirmation for discrepant or high-consequence results. Retiring MHT from screening workflows and adopting LFIA-anchored algorithms can shorten time to targeted therapy, strengthen infection-prevention measures, and improve surveillance fidelity across resource settings.