Assessment of a rapid diagnostic test to exclude bacteraemia and effect on clinical decision-making for antimicrobial therapy

Rapid and precise identification of bloodstream infections using a pre-treatment protocol combined with high-throughput multiplex genetic detection system

Background

Bloodstream infection (BSI) is a life-threatening condition with high morbidity and mortality rates worldwide. Early diagnosis of BSI is critical to avoid the unnecessary application of antimicrobial agents and for proper treatment. However, the current standard methods based on blood culture are time-consuming, thus failing to provide a timely etiological diagnosis of BSI, and common PCR-based detection might be inhibited by matrix components.

Methods

The current study explored an integrated pre-analytical treatment protocol for whole blood samples, wherein pathogens are enriched and purified by incubation and concentration, and inhibitors are inactivated and removed. Further, this study developed and evaluated a novel high-throughput multiplex genetic detection system (HMGS) to detect 24 of the most clinically prevalent BSI pathogens in blood culture samples and pre-treated whole blood samples. The specificity and sensitivity were evaluated using related reference strains and quantified bacterial/fungal suspensions. The clinical utility of BSI-HMGS combined with the pre-analytical treatment protocol was verified using blood cultures and whole blood samples.

Results

The combined pre-treatment protocol and BSI-HMGS was highly specific for target pathogens and possessed a low detection limit for clinical whole blood samples. The pre-treatment protocol could deplete the PCR inhibitors effectively. For blood culture samples, the current method showed 100.0% negative percent agreements and > 87.5% positive percent agreements compared to the reference results based on blood culture findings. For whole blood samples, the current method showed 100.0% negative percent agreements and > 80.0% positive percent agreements compared to the reference results for most pathogens. The turnaround time was ≤ 8 h, and all the procedures could be conducted in a general clinical laboratory.

Conclusion

The BSI-HMGS combined with the pre-treatment protocol was a practical and promising method for early and precise detection of BSIs, especially for areas without access to advanced medical facilities.

Blood Cultures and Molecular Diagnostics in Intensive Care Units to Diagnose Sepsis: A Bayesian Latent Class Model Analysis

Background

Confirmation of sepsis by standard blood cultures (STD) is often inconclusive due to slow growth and low positivity. Molecular diagnostics (MOL) are faster and may have higher positivity, but test performance can be inaccurately estimated if STD methods are used as comparators. Bayesian latent class models (LCMs) can evaluate diagnostic methods when there is no "gold standard." Intensive care unit studies that have used LCMs to combine and compare STD and MOL method performance and estimate the prevalence of sepsis have not been described.

Patients and methods

Results from an ICU sepsis study that used both tests simultaneously were analyzed. Bayesian LCMs combined prior prevalence of sepsis, prior diagnostic characteristics of the two methods, and the study results to estimate the posterior prevalence and diagnostic characteristics. Sensitivity analyses were performed using objective (published studies) and subjective (expert opinion) prior parameters. Positive predictive values (PPVs) of the prevalence of sepsis were estimated for all combinations of test results.

Results

The range of posterior estimates was: sepsis prevalence (0.38-0.88), sensitivities (STD: 0.2-0.35, MOL: 0.56-0.86), and specificities (STD: 0.87-0.99, MOL: 0.72-0.95). The PPV (sepsis) of both tests being positive was (0.72-0.99).

Conclusion

LCMs combined two imperfect methods to estimate prevalence, PPV, and diagnostic characteristics. The posterior estimates (STD sensitivity < MOL and STD specificity > MOL) seem to reflect the clinical experience appropriately. The high PPV when both methods show positive results can be useful for ruling in disease.

How to cite this article

Sampath S, Baby J, Krishna B, Dendukuri N, Thomas T. Blood Cultures and Molecular Diagnostics in Intensive Care Units to Diagnose Sepsis: A Bayesian Latent Class Model Analysis. Indian J Crit Care Med 2021;25(12):1402-1407.