ArticleFrontiers in cellular and infection microbiology2024
Deciphering the pathogen heterogeneity for precise diagnosis and personalized therapeutics of infections after kidney transplantation: insights from metagenomic next-generation sequencing.
Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Application of metagenomic next-generation sequencing as an adjunct to conventional microbiological testing for the diagnosis of infection in kidney transplant recipients.Frontiers in cellular and infection microbiology · 2026Article
- A framework of Microbial Genomic Database for clinical metagenomic pathogen diagnosis: development and multi-cohort evaluation.Frontiers in cellular and infection microbiology · 2026Article
- Pathogen spectrum of pulmonary infections in kidney transplant recipients and the diagnostic value of mNGS: a sputum and BALF study based on clinical decision-making.Frontiers in cellular and infection microbiology · 2026Article
- Metagenomic Next-Generation Sequencing-Assisted Risk Prediction and Stratification of Infections After Kidney Transplantation: A Case Study of COVID-19.Infection and drug resistance · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The aim of this study was to compare the detection performance of mNGS against that of conventional tests (CT) in patients suffering from infection after kidney transplantation. Methods: A total of 138 samples from 85 kidney transplant patients with acute or chronic infections were simultaneously analyzed using mNGS and CT from July 2021 to August 2023. Results: Compared with CT, mNGS demonstrated a higher sensitivity (95.96% vs. 27.27%) but lower specificity (48.72% vs. 84.62%) in pathogen detection. Moreover, mNGS exhibited significant advantages in detecting mixed and rare infections. The pathogens commonly identified in kidney transplant patients were severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), followed by Pneumocystis jirovecii and Cytomegalovirus (CMV). mNGS guided the precise clinical diagnosis in 89.13% of cases and assisted in altering therapeutics from empirical antibiotic approaches to personalized plans in 56.10% of cases, including treatment escalation (40.65%), initiation (11.38%), drug adjustment (3.25%), and de-escalation (0.81%). Discussion: Our study demonstrated the superior detection performance of mNGS and its significant clinical value. This reflected the great potential of mNGS as a complementary clinical detection technology for kidney transplant patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.