Table 1 Articles included in the review depicting the applications of dPCR for infection diagnosis and management in critical care medicine
From: Digital PCR applications for the diagnosis and management of infection in critical care medicine
Study | Year | Usage | Entity | Objective | References |
|---|---|---|---|---|---|
Hu et al. | 2021 | Bacterial identification in blood or plasma | Sepsis | Identification of DNA from bacterial pathogens and antimicrobial resistance genes in blood from patients BSI | [10] |
Yamamoto et al. | 2018 | Bacterial identification in blood or plasma | Sepsis | Identification of Mycobacterium tuberculosis through the detection of circulating cell-free DNA | [14] |
Shin et al. | 2021 | Bacterial identification in blood or plasma | BSI | Diagnosis of Gram-Negative pathogens and antimicrobial resistance genes in plasma from patients with BSIs | [15] |
Zheng et al. | 2021 | Bacterial identification in blood or plasma | Sepsis | Identification of DNA from Acinetobacter baumannii and Klebsiella pneumoniae in blood from patients BSI | [16] |
Chen et al. | 2021 | Fungal identification in blood | BSI | Diagnosis of Candida spp in blood from patients with BSI | [18] |
Zhou et al. | 2021 | Bacterial and fungal identification in other clinical samples | Pleural or peritoneal infections | Identification of pathogens from pleural or peritoneal infections | [19] |
Simms et al. | 2021 | Viral identification | COVID-19 | Confirmation of detection of SARS-CoV-2 in renal allograft and lung tissue (initially detected by immunohistochemistry) | [20] |
Alteri et al. | 2020 | Viral identification | COVID-19 | Quantification of SARS-CoV-2 viral load in plasma of patients with negative qPCR results | [21] |
Jiang et al. | 2020 | Viral identification | COVID-19 | Quantification of SARS-CoV-2 in plasma and hospital environment | [22] |
Ziegler et al. | 2019 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | Sepsis | Quantification of DNA load overtime in patients with Staphylococcus aureus BSIs | [29] |
Ziegler et al. | 2019 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | Sepsis | Quantification of DNA from bacterial pathogens load (16S rDNA) overtime in patients BSI to access patients’ progression | [30] |
Bialasiewicz et al. | 2019 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | Sepsis | Quantification of DNA in blood from Capnocytophaga canimorsus to access patients progression | [31] |
Dickson et al. | 2020 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | VAP | Quantification of bacteria DNA burden in the lung and association with disease progression and outcomes | [32] |
Goh et al. | 2020 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | Sepsis sCAP | Quantification of EBV (to detect reactivation) in patients with sepsis to monitor disease progression | [33] |
Veyer et al. | 2021 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | COVID-19 | Quantification of SARS-CoV-2 viral load in plasma and correlation with disease severity | [34] |
Chen et al. | 2021 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | COVID-19 | Quantification of SARS-CoV-2 viral load in plasma and correlation with disease severity | [35] |
Bermejo-Martin et al. | 2020 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | COVID-19 | Quantification of SARS-CoV-2 viral load in plasma and correlation with disease severity | [36] |
Ram-Mohan et al. | 2021 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | COVID-19 | Quantification of SARS-CoV-2 viral load in plasma and correlation with disease severity | [37] |
Tedim et al. | 2021 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | COVID-19 | Quantification of SARS-CoV-2 viral load in plasma, comparison with qPCR | [38] |
Martin-Vicente et al. | 2022 | Quantification of microbial burden to assess severity, prognosis and treatment guidance | COVID-19 | Quantification of SARS-CoV-2 viral load in plasma | [39] |
Bruneau et al. | 2021 | Quantification of microbial burden to assess severity, prognosis and treatment guidance Host Response | COVID-19 | Quantification of SARS-CoV-2 viral load and host biomarkers in plasma to predict disease severity | [40] |
Chanderraj et al. | 2022 | Microbial ecology studies | Sepsis | Quantification of bacterial density in rectal swabs and risk of extraintestinal infection | [41] |
Brooks et al. | 2018 | Microbial ecology studies | Microbiological burden and microbiome | Quantification of total microbiological burden in hospital neonates ICU and correction with microbiome establishment | [42] |
Tamayo et al. | 2014 | Host Response | Sepsis | Quantification of the expression of the constant region of the mu heavy chain of IgM in blood to differentiate sepsis from SIRS | [46] |
Almansa et al. | 2019 | Host Response | Sepsis | Gene expression ratio between MMP8 or LCN2 with HLA-DRA to differentiate surgical patients with sepsis from those with no sepsis | [47] |
Almansa et al. | 2018 | Host Response | Sepsis | Ratio between HLA-DRA expression and procalcitonin to differentiate surgical patients with sepsis from those with no sepsis | [48] |
Link et al. | 2020 | Host Response | Sepsis | Quantification of miRNA in blood for the early diagnosis of sepsis | [49] |
Martin-Fernandez et al. | 2020 | Host Response | Sepsis | Quantification of emergency granulopoiesis gene expression to stratify severity in patients with infection, sepsis and septic shock | [50] |
Menéndez et al. | 2019 | Host Response | sCAP | Gene expression levels of the immunological synapse genes to identify patients with sCAP | [52] |
Almansa et al. | 2018 | Host Response | VAP | Gene expression levels of the immunological synapse genes to identify VAP | [53] |
Busani et al. | 2020 | Host Response | Sepsis | Quantification of mtDNA in patients with Septic shock cause by MDR pathogens predicts disease severity | [54] |
Sabbatinelli et al. | 2021 | Host Response | COVID-19 | Quantification of miRNA associated with inflammation and aging (Inflammaging) to predict COVID-19 disease progression | [56] |