Clinical evaluation of droplet digital PCR in the early identification of suspected sepsis patients in the emergency department: a prospective observational study

Abstract

Background: Rapid and accurate diagnosis of the causative agents is essential for clinical management of bloodstream infections (BSIs) that might induce sepsis/septic shock. A considerable number of suspected sepsis patients initially enter the health-care system through an emergency department (ED), hence it is vital to establish an early strategy to recognize sepsis and initiate prompt care in ED. This study aimed to evaluate the diagnostic performance and clinical value of droplet digital PCR (ddPCR) assay in suspected sepsis patients in the ED.

Methods: This was a prospective single-centered observational study including patients admitted to the ED from 25 October 2022 to 3 June 2023 with suspected BSIs screened by Modified Shapiro Score (MSS) score. The comparison between ddPCR and blood culture (BC) was performed to evaluate the diagnostic performance of ddPCR for BSIs. Meanwhile, correlative analysis between ddPCR and the inflammatory and prognostic-related biomarkers were conducted to explore the relevance. Further, the health economic evaluation of the ddPCR was analyzed.

Results: 258 samples from 228 patients, with BC and ddPCR performed simultaneously, were included in this study. We found that ddPCR results were positive in 48.13% (103 of 214) of episodes, with identification of 132 pathogens. In contrast, BC only detected 18 positives, 88.89% of which were identified by ddPCR. When considering culture-proven BSIs, ddPCR shows an overall sensitivity of 88.89% and specificity of 55.61%, the optimal diagnostic power for quantifying BSI through ddPCR is achieved with a copy cutoff of 155.5. We further found that ddPCR exhibited a high accuracy especially in liver abscess patients. Among all the identified virus by ddPCR, EBV has a substantially higher positive rate with a link to immunosuppression. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity as well as prognosis. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.

Conclusions: The multiplexed ddPCR delivers precise and quantitative load data on the causal pathogen, offers the ability to monitor the patient's condition and may serve as early warning of sepsis in time-urgent clinical situations as ED.

Importance: Early detection and effective administration of antibiotics are essential to improve clinical outcomes for those with life-threatening infection in the emergency department. ddPCR, an emerging tool for rapid and sensitive pathogen identification used as a precise bedside test, has developed to address the current challenges of BSI diagnosis and precise treatment. It characterizes sensitivity, specificity, reproducibility, and absolute quantifications without a standard curve. ddPCR can detect causative pathogens and related resistance genes in patients with suspected BSIs within a span of three hours. In addition, it can identify polymicrobial BSIs and dynamically monitor changes in pathogenic microorganisms in the blood and can be used to evaluate antibiotic efficacy and survival prognosis. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.

Keywords: bloodstream infections; clinical validation; droplet digital PCR; emergency department; sepsis.

Figure 1

Flow diagram demonstrating definite interpretation of patients with BSI in the cohort. ddPCR, droplet digital PCR; BSI bloodstream infection.

Figure 2

Flow chart for patient enrollment and results analysis. MSS, Modified Shapiro Score, ddPCR droplet digital PCR.

Figure 3

Distribution of pathogens detected by blood culture and ddPCR testing. (A) Pathogens detected by ddPCR and blood culture. Blue bars represent the episodes in which the pathogens were detected by ddPCR, orange bars mean that the pathogens were detected by blood culture. The length of the bar represents the number of episodes. (B) Counts and percentages of co-infections in patients of ddPCR-positive. ddPCR droplet digital PCR.

Figure 4

The efficacy of ddPCR in diagnosing of BSI. The receiver operating characteristic curves (ROC) of ddPCR for diagnosis of bloodstream infection. P values were calculated using log-rank tests. ddPCR droplet digital PCR; BSI bloodstream infection.

Figure 5

Correlations between copies of pathogens detected by ddPCR and clinical characteristics. Heatmap shows the correlation between the copies of pathogens identified through ddPCR in BSIs and various markers of inflammation, coagulation, immunity and prognosis. *p<0.05, APACHE, II Acute Physiology and Chronic Health Evaluation II; SOFA, Sequential Organ Failure Assessment; MSS, Modified Shapiro Score; PLT platelet; RDW red blood cell volume distribution width; CRP, C-reactive protein; IL, Interleukin; SAA, Serumamyloid A; PCT, procalcitonin; HBP Heparin-Binding Protein; ESR, erythrocyte sedimentation rate; tPAIC, tissue Plasminogen Tctivator-inhibitor Complex; TM, thrombomodulin; PT, prothrombinTime; APTT, activated partial thromboplastin time; ddPCR, droplet digital PCR; G+, bacteria Gram-positive bacteria; G−, bacteria Gram-negative bacteria.

Figure 6

The efficacy of ddPCR in predicting 28-day survival prognosis. (A) The receiver operating characteristic (ROC) curve of ddPCR for 28-day survival of BSI. (B) Survival curves of patients with BSI according to copies of ddPCR. (C) Nomogram to predict the risk of 28-day mortality. P values were calculated using log-rank tests. NLCR, Neutrophil Lymphocyte count ratio.

Figure 7

Comparison of the health economic values between negative and positive groups divided by ddPCR assay. (A) Comparison of the hospitalization expenses between ddPCR positive and ddPCR negative patients. (B) Comparison of the antibiotic costs between ddPCR positive and ddPCR negative patients. (C) Comparison of the percentage of antibiotics costs in the total hospitalization expenses between ddPCR positive and ddPCR negative patients. *p<0.05, ***p<0.001, ddPCR, droplet digital PCR.