Clinical descriptive analysis of severe
            <i>Pneumocystis jirovecii</i>
            pneumonia in renal transplantation recipients

Xie, Dan; Xu, Wen; You, Jingya; Yuan, Xiaofeng; Li, Mingliang; Bi, Xiaogang; Zhang, Kouxing; Xian, Ying

doi:10.1080/21655979.2021.1911203

Cited by 8 publications

(4 citation statements)

References 38 publications

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“…However, 29.08% of the strains were still not detected. This analysis is related to the following factors: (1) In clinical diagnosis and treatment, the positive or negative results of mNGS in a specific site cannot be the sole basis for clinical diagnosis, which affects the diagnosis and treatment of pathogenic microorganisms (16,17); (2) The process of extracting, trans- porting, and testing BALF takes a significant amount of time and covers a large area. Incorrect preservation or handling increases the risk of decreased sensitivity and specificity.…”

Section: Discussionmentioning

confidence: 99%

Exploring the pathogen diagnosis and prognostic factors of severe COVID-19 using metagenomic next-generation sequencing: A retrospective study

Zeng,

Liang,

et al. 2024

J Med Biochemistry

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Background: This study aimed to identify pathogens and factors that predict the outcome of severe COVID-19 by utilizing metagenomic next-generation sequencing (mNGS) technology. Methods: We retrospectively analyzed data from 56 severe COVID-19 patients admitted to our hospital between December 2022 and March 2023. We analyzed the pathogen types and strains detected through mNGS and conventional microbiological testing and collected general patient information. Results: In this study, 42 pathogens were detected using mNGS and conventional microbiological testing. mNGS had a significantly higher detection rate of 90.48% compared to 71.43% for conventional testing (P=0.026). A total of 196 strains were detected using both methods, with a significantly higher detection rate of 70.92% for mNGS compared to 49.49% for conventional testing (P=0.000). The 56 patients were divided into a survival group (33 cases) and a death group (23 cases) based on clinical outcomes. The survival group had significantly lower age, number of pathogens detected by mNGS, number of pathogens detected by conventional testing, APACHE-II score, SOFA score, high-sensitivity troponin, creatine kinase-MB subtype, and lactate dehydrogenase compared to the death group (P<0.05). Multivariate logistic regression analysis showed that these factors were risk factors for mortality in severe COVID-19 patients (P<0.05). In contrast, ROC curve analysis revealed that these factors had diagnostic values for mortality, with AUC values ranging from 0.657 to 0.963. The combined diagnosis of these indicators had an AUC of 0.924. Conclusion: The use of mNGS technology can significantly enhance the detection of pathogens in severe cases of COVID-19 and also has a solid ability to predict clinical outcomes.

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Section: Discussionmentioning

confidence: 99%

Exploring the pathogen diagnosis and prognostic factors of severe COVID-19 using metagenomic next-generation sequencing: A retrospective study

Zeng,

Liang,

et al. 2024

J Med Biochemistry

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“…27 Metagenomic next-generation sequencing is relatively a newer modality for diagnosing PJP and has shown promising results. 28…”

Section: Diagnosismentioning

confidence: 99%

Pneumocystis jiroveci Pneumonia: A Review of Management in Human Immunodeficiency Virus (HIV) and Non-HIV Immunocompromised Patients

Ibrahim

Chattaraj²,

Iqbal³

et al. 2023

Avicenna J Med

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Pneumocystis jirovecii pneumonia is an opportunistic fungal infection that was mainly associated with pneumonia in patients with advanced human immunodeficiency virus (HIV) disease. There has been a decline in Pneumocystis jirovecii pneumonia incidence in HIV since the introduction of antiretroviral medications. However, its incidence is increasing in non-HIV immunocompromised patients including those with solid organ transplantation, hematopoietic stem cell transplantation, solid organ tumors, autoimmune deficiencies, and primary immunodeficiency disorders. We aim to review and summarize the etiology, epidemiology, clinical presentation, diagnosis, and management of Pneumocystis jirovecii pneumonia in HIV, and non-HIV patients. HIV patients usually have mild-to-severe symptoms, while non-HIV patients present with a rapidly progressing disease. Induced sputum or bronchoalveolar lavage fluid can be used to make a definitive diagnosis of Pneumocystis jirovecii pneumonia. Trimethoprim-sulfamethoxazole is considered to be the first-line drug for treatment and has proven to be highly effective for Pneumocystis jirovecii pneumonia prophylaxis in both HIV and non-HIV patients. Pentamidine, atovaquone, clindamycin, and primaquine are used as second-line agents. While several diagnostic tests, treatments, and prophylactic regimes are available at our disposal, there is need for more research to prevent and manage this disease more effectively.

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“…Excluding P. jirovecii, which is generally unculturable, out of the remaining 274 fungi detected by NGS, only 105 (~38%) were recovered by fungal culture from the same or different specimens from the respective patients [26,[29][30][31][32][33][34][35][36][37][38][39]43,45,46,49,52,54,57,59,62,64,66,67,71,73,76,77]. The majority of P. jirovecii infections diagnosed by NGS were reported in case series [34,36,39,41,48,53,55,58,62,64,65,67,72,75]. All the patients unanimously suffered from pneumonia.…”

Section: Laboratory Diagnosis Of Fungal Infections By Ngsmentioning

confidence: 99%

Rapid Genomic Diagnosis of Fungal Infections in the Age of Next-Generation Sequencing

Tsang

Teng

Lau

et al. 2021

JoF

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Next-generation sequencing (NGS) technologies have recently developed beyond the research realm and started to mature into clinical applications. Here, we review the current use of NGS for laboratory diagnosis of fungal infections. Since the first reported case in 2014, >300 cases of fungal infections diagnosed by NGS were described. Pneumocystis jirovecii is the predominant fungus reported, constituting ~25% of the fungi detected. In ~12.5% of the cases, more than one fungus was detected by NGS. For P. jirovecii infections diagnosed by NGS, all 91 patients suffered from pneumonia and only 1 was HIV-positive. This is very different from the general epidemiology of P. jirovecii infections, of which HIV infection is the most important risk factor. The epidemiology of Talaromyces marneffei infection diagnosed by NGS is also different from its general epidemiology, in that only 3/11 patients were HIV-positive. The major advantage of using NGS for laboratory diagnosis is that it can pick up all pathogens, particularly when initial microbiological investigations are unfruitful. When the cost of NGS is further reduced, expertise more widely available and other obstacles overcome, NGS would be a useful tool for laboratory diagnosis of fungal infections, particularly for difficult-to-grow fungi and cases with low fungal loads.

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Clinical descriptive analysis of severe Pneumocystis jirovecii pneumonia in renal transplantation recipients

Cited by 8 publications

References 38 publications

Exploring the pathogen diagnosis and prognostic factors of severe COVID-19 using metagenomic next-generation sequencing: A retrospective study

Exploring the pathogen diagnosis and prognostic factors of severe COVID-19 using metagenomic next-generation sequencing: A retrospective study

Pneumocystis jiroveci Pneumonia: A Review of Management in Human Immunodeficiency Virus (HIV) and Non-HIV Immunocompromised Patients

Rapid Genomic Diagnosis of Fungal Infections in the Age of Next-Generation Sequencing

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