Detection Rate Of Pathogens Research Articles

Analysis of respiratory pathogens in pediatric acute respiratory infections in Lanzhou, Northwest China, 2019-2024

ObjectiveThis study aimed to assess the prevalence and distribution of respiratory pathogens in children under 18 years old with Acute Respiratory Infections (ARTIs) in Lanzhou, Northwest China, from July 2019 to January 2024.MethodsThe respiratory pathogens studied were FluA, FluB, PIV, RSV, ADV, MP, CP, CB, and LP, detected by indirect immunofluorescence assay (IIF). Data were obtained from the laboratory information system (LIS) of the Lanzhou University Second Hospital. As in Lanzhou, NPIs were implemented in January 2020, and were lifted in December 2022, data were divided into pre-NPIs (July 2019 to December 2019), NPIs (January 2020 to December 2022) and post-NPIs (January 2023 to January 2024) periods for analysis. Pearson’s chi-square test, ANOVA, and Fisher’s exact test were used to evaluate statistical significance in variable differences, with P < 0.05 considered significant.ResultsA total of 29,659 children diagnosed with ARTIs were included in the study, with 13030(43.93%) test positive for at least one pathogen. Single-pathogen infections predominated (33.10%), while co-detection of MP and PIV was the most common among multi-pathogen cases (52.96%). Pathogen detection rates were notably higher in female children (50.62%) and preschool-aged children (53.45%) and exhibited seasonal variations, with a pronounced increase in winter (47.61%) and a peak in November (48.92%). MP had the highest detection rate (38.59%), followed by PIV (10.18%). Detection rates significantly increased following the lifting of NPIs, rising from 33.82% (SD ± 13.13) during NPIs to 64.42% (SD ± 4.67) (P < 0.001), with 2023 showing the highest detection rate (64.61%) and largest participant count (9,591). In November 2023, detection rates reached their highest level at 73.09%. Post-NPI, most pathogens, except CB and LP, demonstrated significantly higher prevalence (P<0.001).ConclusionIn the Lanzhou region, MP and PIV were identified as the most prevalent respiratory pathogens among children with ARTIs, with peak detection rates during the winter season. Boys and school-age children exhibited higher susceptibility to these infections. NPIs played a critical role in reducing respiratory pathogen transmission. Once NPIs were lifted, a marked resurgence in pathogen incidence highlighted their impact on controlling infection spread.

Resurgence of common respiratory viruses and mycoplasma pneumoniae after ending the zero-COVID policy in Shanghai

China has adhered to policies of zero-COVID for almost three years since the outbreak of COVID-19, which has remarkably affected the circulation of respiratory pathogens. However, China has begun to end the zero-COVID policies in late 2022. Here, we reported a resurgence of common respiratory viruses and Mycoplasma pneumoniae with unique epidemiological characteristics among children after ending the zero-COVID policy in Shanghai, China, 2023. Children hospitalized with acute respiratory tract infections were enrolled from January 2022 to December 2023. Nine common respiratory viruses and 2 atypical bacteria were detected in respiratory specimens from the enrolled patients using a multiplex PCR-based assay. The data were analyzed and compared between the periods before (2022) and after (2023) ending the zero-COVID policies. A total of 8550 patients were enrolled, including 6170 patients in 2023 and 2380 patients in 2022. Rhinovirus (14.2%) was the dominant pathogen in 2022, however, Mycoplasma pneumoniae (38.8%) was the dominant pathogen in 2023. Compared with 2022, the detection rates of pathogens were significantly increased in 2023 (72.9% vs. 41.8%, p < 0.001). An out‐of-season epidemic of respiratory syncytial virus was observed during the spring and summer of 2023. The median age of children infected with respiratory viruses in 2023 was significantly greater than that in 2022. Besides, mixed infections were more frequent in 2023 (23.8% vs. 28.9%, p < 0.001). China is now facing multiple respiratory pathogen epidemics with changing seasonality, altered age distribution, and increasing mixed infection rates among children in 2023. Our finding highlights the need for public health interventions to prepare for the respiratory pathogen outbreaks in the post-COVID-19 era.

Epidemiological and pathological characterization of acute respiratory infections.

This research comprehensively investigates the epidemiological features and pathogen profile of acute respiratory infections (ARI) in Shihezi City, Xinjiang. A pivotal aspect of this study is the construction of a Bayes discriminant function for principal pathogen infections. This innovative methodology aims to furnish a robust scientific basis for the prevention and clinical management of ARI, potentially guiding more effective strategies in both public health and clinical settings. We compiled and examined data from January 2020 to June 2023, pertaining to patients admitted with acute respiratory infections at the First Affiliated Hospital of Shihezi University. This investigation focused on discerning patterns in epidemiology and pathogen etiology. Among 2110 cases of acute respiratory infections (ARI), 1736 underwent pathogenetic testing. Of these, 595 cases tested positive for at least one pathogen, marking a positivity rate of 34.27%. Viral detections, at a rate of 27.47%, were notably higher than bacterial detections, which stood at 6.51%. The most prevalent viruses identified were Human respiratory syncytial virus (hRSV), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and Human adenovirus (HAdV), while the dominant bacterial pathogens included Klebsiella pneumoniae, Haemophilus influenzae, and Staphylococcus aureus. Co-infections were observed in 76 cases, accounting for 12.77% of positive diagnoses, predominantly involving hRSV in conjunction with other pathogens. In cases of acute bronchiolitis, hRSV was the most frequent pathogen, contributing to 23.10% of such cases. Similarly, in severe pneumonia cases, SARS-CoV-2 was predominant, accounting for 25.4% of these infections. The group with bacterial positivity exhibited elevated levels of C-reactive protein (CRP, 19.17 mg/L) and neutrophilic granulocyte percentage (NE%, 54.7%). The Bayes discriminant function demonstrated an initial validation accuracy of 74.9% and a cross-validation accuracy of 63.7%. The study underscores that hRSV, SARS-CoV-2, and HAdV are the primary pathogens in acute respiratory infections in the Shihezi region. Pathogen susceptibility exhibits variation across different age groups, with a higher pathogen detection rate in children compared to adults. The Bayes discriminant function shows significant promise in the classification and diagnosis of major pathogenic infections.

Comparison of the Impact of tNGS with mNGS on Antimicrobial Management in Patients with LRTIs: A Multicenter Retrospective Cohort Study.

tNGS and mNGS are valuable tools for diagnosing pathogens in lower respiratory tract infections (LRTIs), which subsequently influence treatment strategies. However, the impact of tNGS and mNGS on antimicrobial stewardship in patients with LRTIs remains unclear. Patients diagnosed with LRTIs who underwent tNGS or mNGS between June 2021 and January 2024 were included. Patients who underwent both tNGS and conventional microbiologic tests (CMTs) were grouped into the tNGS group, the others were divided into the mNGS group. Then, the diagnostic efficacy of tNGS and mNGS was compared, along with their impact on antimicrobial management and clinical outcomes. 548 patients with an initial diagnosis of LRTIs who underwent tNGS or mNGS were evaluated. Finally, 321 patients were analyzed, with 117 patients in tNGS group and 204 patients in mNGS group. The overall pathogen detection rates for tNGS and mNGS were 89.74% and 89.71% (P=0.991). The distribution of detected pathogens was similar between tNGS and mNGS, with bacteria being the predominant microorganisms. The proportions of patients who underwent antimicrobial agent changes and received targeted therapy were not significantly different between tNGS and mNGS groups (P=0.270; P=0.893). Additionally, no significant differences were noted in the rates of antibiotic de-escalation, escalation, or changes in the opposite direction (all P>0.05). The same results was observed in the proportions of patients with addition or reductions in antiviral, antifungal, and antibacterial agents (all P>0.05). Hospital stays, improvement rate and mortality rate were also similar (all P>0.05). tNGS and mNGS demonstrate comparable overall pathogen yield rates in patients with LRTIs. Furthermore, tNGS is also comparable to mNGS in terms of adjusting antimicrobial treatments and clinical outcomes, tNGS meets the clinical needs of most patients with LRTIs and can be firstly used for these patients.

Application of metagenomic next-generation sequencing in pathogen detection for patients with lower respiratory tract infections caused bymultidrug-resistant organisms and analysis ofrelated factors.

The incidence of lower respiratory tract infections (LRTIs) caused by multidrug-resistant organisms (MDRO) has been high in recent years. However, traditional etiological detection methods have not been able to meet the needs for clinical diagnosis and prognosis of LRTIs. The rapid development of metagenomic next-generation sequencing (mNGS) provides new insights for diagnosis and treatment ofLRTIs. We conducted a retrospective study on 95 patients with lower respiratory tract infections caused by MDRO admitted to our respiratory department from January 2022 to December 2023. Thesepatients underwent mNGS testing and conventional culture testing. Additionally, 150 patients without lower respiratory tract infections caused by MDRO during the same period were included as thenon-MDRO group. General information was collected, and Logistic regression analysis was performed to identify risk factors for MDRO infections in patients with lower respiratory tract infections. Our results show that the time to pathogen detection by mNGS was 50.76 ± 1.730 h, that is significantly shorter than 55.53 ± 2.782 h required for conventional culture testing. The pathogen detection rate by mNGS was 89.47% (85/95), higher than the 67.37% (64/95) identified by conventional testing. In terms of pathogen genus distribution, mNGS detected a total of 279 pathogens, while conventional testing detected 121 pathogens. Logistic multivariate regression analysis identified that the use of more thantwo antibiotics, invasive procedures, invasive mechanical ventilation for ≥7 days, and stay in therespiratory intensive care unit (RICU) for ≥7 days were the main influencing factors for lower respiratory tract infections caused by MDRO (P < 0.05).

Performance of metagenomic next-generation sequencing for microbiological diagnosis of infectious uveitis.

Introduction. Diagnosis of uveitis is challenging due to the multitude of possible pathogenies. Identifying infectious and non-infectious uveitis is of great clinical significance. Recently, metagenomic next-generation sequencing (mNGS) was used to detect infectious and non-infectious uveitis, but its efficacy has not been widely evaluated.Hypothesis. Compared with routine diagnostic tests (RDTs), mNGS is more effective in identifying infectious and non-infectious uveitis.Aim. To describe the microbiological diagnostic performance of mNGS in detecting infectious and non-infectious uveitis.Methodology. Patients with suspected infectious uveitis of uncertain pathogenesis were tested by mNGS and RDTs. Infectious and non-infectious uveitis were grouped according to the final diagnosis based on comprehensive analysis of the test results and the effect of therapy. The test results were used to assess the performance of mNGS in actual clinical practice.Results. Fifty-eight cases were enrolled in this project, including 32 cases of infectious uveitis and 26 cases of non-infectious uveitis. The sensitivity of mNGS was 96.88%, which was much higher than that of RDTs. The detected pathogenic micro-organisms included bacteria, fungi, viruses, Toxoplasma gondii and Bartonella. Consequently, mNGS showed a high negative predictive value (NPV) of 94.74%, indicating that an mNGS negative should be a true negative result most of the time, but a low positive predictive value (PPV) of 79.49%.Conclusions. mNGS showed extremely high sensitivity but low specificity, which increased the detection rate of infectious uveitis pathogens but might result in false positives. The excellent NPV suggested that the identification of non-infectious uveitis is of considerable clinical importance.

Diagnostic value of metagenomic next-generation sequencing for bronchoalveolar lavage diagnostics in patients with lower respiratory tract infections

BackgroundCurrent diagnostic methods of lower respiratory tract infections (LRTIs) often lack specificity, underscoring the necessity for advanced technologies such as metagenomic next-generation sequencing (mNGS). MethodsThis retrospective study compared bronchoalveolar lavage fluid (BALF) analysis using mNGS and conventional microbiological tests (CMT) to evaluate their effectiveness in pathogen identification and alignment with clinical diagnoses. ResultsIn this study involving 369 patients suspected of LTRIs, mNGS identified pathogens in 342 cases (92.7%), showing superior diagnostic performance compared to CMT (58.8%). The positive agreement and negative agreement rates of mNGS were 92.7% and 96.3%, respectively, both significantly higher than those of CMT (both p<0.001). The sensitivity, specificity, positive predictive value, and negative predictive value of mNGS were significantly higher than those of CMT, with values of 99.7% vs. 57.1%, 68.4% vs. 26.3%, 96.5% vs. 87.1%, and 96.3% vs. 6.3%, respectively (all p<0.001). Pathogen detection rates among the patients showed that 89.7% had evidence of LRTIs, with bacterial infections (20.1%), mycoplasma (13.6%), mycobacterium (4.3%), fungal (4.1%), viral (3.3%), and mixed infections (44.4%) being the most common. Furthermore, the study also differentiated the distribution of pathogens between adults and pediatric patients, and assessed the impact of pathogen types on severe outcomes using multivariate logistic regression, revealing that viral and fungal infections were more likely associated with severe symptoms, whereas mycoplasma infections typically presented with milder symptoms. ConclusionsBALF mNGS proves effective for rapid, comprehensive pathogen detection in LRTIs, warranting its early use for enhanced diagnosis and management, especially across different age groups.

Streptococcus salivarius pneumonia-associated pneumomediastinum: a case report and literature review

BackgroundStreptococcus salivarius is an opportunistic pathogen, and there have been no reported cases of Streptococcus salivarius pneumonia to date. Pneumomediastinum is usually secondary to tracheal or esophageal injury and is very rare as a complication of pneumonia. We report a case of Streptococcus salivarius pneumonia complicated by pneumomediastinum, aiming to enhance clinicians’ awareness of rare pathogens and uncommon complications in pneumonia.Case presentationThe patient, a 36-year-old male, presented with a persistent cough and sputum production for one week, accompanied by a sore throat that had developed just one day prior. Chest computed tomography (CT) disclosed pneumomediastinum alongside obstructive atelectasis in the left lower lobe. Streptococcus salivarius infection was conclusively identified through bronchoalveolar lavage metagenomic next-generation sequencing (mNGS), as well as smear and culture analyses. The patient was administered intravenous amoxicillin-clavulanate potassium for a duration of seven days as part of the anti-infection regimen. Given the stability of the patient’s respiratory and circulatory systems, a tube drainage procedure was deemed unnecessary. Post-treatment, the patient’s clinical symptoms notably improved. A subsequent chest CT scan revealed the re-expansion of the left lower lung and near-complete resolution of pneumomediastinum.ConclusionThere are numerous pathogens that can cause pneumonia. While focusing on common pathogens, it is important not to overlook rare ones. When considering infections from rare pathogens, it is recommended to promptly perform a bronchoscopy and submit bronchoalveolar lavage fluid for mNGS to improve pathogen detection rates. During the diagnosis and treatment of pneumonia, it is crucial to be vigilant for rare complications. When a patient presents with symptoms such as dyspnea or subcutaneous emphysema, it is advisable to immediately perform a chest CT scan to rule out pneumomediastinum.

Can bone SPECT/CT determine optimal sites for microbiological identification in post-traumatic or chronic osteomyelitis of extremities?

IntroductionAccurate microbiological identification is crucial when managing chronic osteomyelitis (COM) and post-traumatic osteomyelitis (PTO). Although bone single photon emission computed tomography/computed tomography (SPECT/CT) has helped in localizing osteomyelitis lesions, its effectiveness in guiding microbiological sampling remains unclear. This study aimed to determine whether bone SPECT/CT can improve microbiological identification rates in COM or PTO of the extremities. Patients and methodsFrom February 2020 to August 2024, 53 patients with suspected COM or PTO in the extremities were retrospectively analyzed. All patients underwent bone SPECT/CT, followed by microbiological sampling during surgery. Tissue samples were taken from the areas of high SPECT/CT uptake or based on intraoperative findings where no uptake was observed. Microorganism identification rates were analyzed, including a sub-group analysis based on antibiotic discontinuation. ResultsOf the 53 patients, 42 had positive bone SPECT/CT scan findings, with pathogen identification in 30 patients (71.4 %). In contrast, pathogen identification occurred in one out of twelve patients (9.1 %) with negative findings (odds ratio 25, p< 0.001). Bone SPECT/CT demonstrated a sensitivity of 96.8 % and an overall accuracy of 75.5 %. When antibiotics had been discontinued for ≥2 weeks, the pathogen identification rate increased to 90 %, compared with 50 % for <2 weeks of discontinuation (odds ratio 10.0, p= 0.006). In a sub-group of 30 patients with adequate antibiotic discontinuation duration, a positive bone SPECT/CT scan yielded a pathogen identification rate of 90.1 % (odds ratio 60.0, p= 0.001). ConclusionBone SPECT/CT effectively identifies optimal sites for microbiological sampling in COM and PTO of the extremities, particularly when antibiotics have been discontinued for ≥2 weeks, enhancing pathogen detection rates.

Spatial-Temporal Patterns in the Enteric Pathogen Contamination of Soil in the Public Environments of Low- and Middle-Income Neighborhoods in Nairobi, Kenya.

Public spaces in countries with limited societal development can be contaminated with feces containing pathogenic microbes from animals and people. Data on contamination levels, spatial distribution, and the diversity of enteric pathogens in the public settings of low- and middle-income neighborhoods are crucial for devising strategies that minimize the enteric infection burden. The objective of this study was to compare spatial-temporal differences in the detection rate and diversity of enteric pathogens in the public spaces of low- and middle-income neighborhoods of Nairobi, Kenya. TaqMan array card (TAC) molecular assays were employed to analyze soil samples for 19 enteropathogens, along with a selective bacterial culture for pathogenic Enterobacteriaceae. An observational assessment was conducted during every site visit to document the hygienic infrastructure and sanitation conditions at the sites. We detected at least one pathogen in 79% (127/160) and ≥2 pathogens in 67.5% (108/160) of the soil samples tested. The four most frequently detected pathogens were EAEC (67.5%), ETEC (59%), EPEC (57.5%), and STEC (31%). The detection rate (91% vs. 66%) and mean number of enteric pathogens (5 vs. 4.7) were higher in low-income Kibera than in middle-income Jericho. The more extensive spatial distribution of pathogens in Kibera resulted in increases in the detection of different enteric pathogens from within-site (area < 50 m2) and across-site (across-neighborhood) movements compared to Jericho. The pathogen detection rates fluctuated seasonally in Jericho but remained at sustained high levels in Kibera. While better neighborhood conditions were linked with lower pathogen detection rates, pathogenic E. coli remained prevalent in the public environment across both neighborhoods. Future studies should focus on identifying how the sources of pathogen contamination are modified by improved environmental sanitation and hygiene and the role of these contaminated public environments in enteric infections in children.

The clinical application of metagenomic next-generation sequencing in immunocompromised patients with severe respiratory infections in the ICU.

Early targeted antibiotic therapy is crucial for improving the prognosis of immunocompromised patients with severe respiratory infections (SRIs) in the intensive care unit (ICU). Metagenomic next-generation sequencing (mNGS) has shown significant value in pathogen detection, but research on lower respiratory tract microorganisms remains limited. This study enrolled 234 patients with SRIs in the ICU, and individuals were categorized into immunocompromised and immunocompetent groups. We compared the diagnostic performance of mNGS using bronchoalveolar lavage fluid (BALF) with conventional microbiological tests (CMTs) and analyzed the value of mNGS in immunocompromised patients with SRIs in the ICU. Among all patients, the pathogenic microorganism detection rate of mNGS was higher than that of CMTs (94.02% vs 66.67%, P < 0.05), both in the immunocompromised group (95.0% vs 58.75%, P < 0.05) and the immunocompetent group (93.51% vs 71.43%, P < 0.05). mNGS detected more pathogens than CMTs did (167 vs 51), identifying 116 organisms that were missed by CMTs. The proportion of antibiotic regimen adjustments based on mNGS results was significantly higher compared to CMTs in both the immunocompromised (70.00% vs 17.50%, P < 0.05) and immunocompetent groups (48.70% vs 15.58%, P < 0.05). In the immunocompromised group, patients who had their antibiotic treatment adjusted on mNGS results had improved prognosis, with significantly lower ICU mortality (8.93% vs 50%, P < 0.05) and 28-day mortality rates (30.36% vs 68.75%, P < 0.05) than CMTs. In the immunocompetent group, no statistically significant differences were observed in ICU mortality or 28-day mortality (20.00% vs 33.33%, P > 0.05; 42.67% vs 45.83%, P > 0.05). mNGS shows significant value in detecting pathogens in immunocompromised patients with SRIs in ICU. For immunocompromised patients who respond poorly to empirical treatment, mNGS can provide an etiological basis, helping adjust antibiotic regimens more precisely and thereby improving patient prognosis.

Artificial Intelligence Applications in Medical Mycology: Current and Future

The application of artificial intelligence (AI) in the medical mycology field represents a new era in the diagnosis and management of fungal infections. AI technologies, particularly machine learning (ML) and deep learning (DL) methods, enhance diagnostic accuracy by leveraging large datasets and complex algorithms. This review examines current applications of AI in laboratory and clinical settings for fungal diagnostics. In the laboratory, AI models analyze microscopic images from potassium hydroxide (KOH) examinations, fungal culture tests, and histopathologic slides, which improves the detection rates of fungal pathogens significantly. In the clinical setting, AI assists the diagnosis of fungal infections using medical images, exhibiting high efficacy in binary classification tasks. However, challenges include small sample sizes, class imbalances, reliance on expert-labeled data, and the black box nature of AI models. Explainable AI offers potential solutions by providing human-comprehensible insights into AI decisionmaking processes. In addition, human-computer collaboration can enhance diagnostic accuracy, particularly for less experienced clinicians. The development of generative AI models, e.g., large language models and multimodal AI, promises to create extensive datasets and integrate various data sources for comprehensive diagnostics. Addressing these limitations through prospective clinical validation and continuous feedback will be essential for realizing the full potential of AI in medical mycology.

Pathogen detection by targeted next-generation sequencing test in adult hematological malignancies patients with suspected infections.

Infections in patients with hematological malignancies (HM) are a significant cause of morbidity and mortality. Timely and effective empirical anti-infective treatment can reduce the infection-related mortality rate. Targeted next-generation sequencing (tNGS) offers a rapid diagnostic approach for identifying diverse pathogens in these patients. However, relevant research is still limited to adult patients with HM. We conducted a retrospective analysis of adult HM patients admitted to our hospital from March 2023 to September 2023, focusing on their clinical characteristics and the results of both tNGS and conventional microbiological tests (CMTs). We evaluated the performance of tNGS and CMTs in pathogenic diagnosis and described the distribution characteristics of pathogens in adult HM patients with infections. The study included 209 samples collected from 137 patients. Results showed that the overall pathogen detection rate differed significantly between tNGS and CMTs (60.3% vs. 24.4%, p < 0.001). The sensitivity (69.7% vs. 35.9%), negative predictive value (NPV) (48.2% vs. 42.4%), and accuracy (66.5% vs. 56.5%) of pathogen detection were notably superior with tNGS compared to CMTs. Among the 142 samples with clinically diagnosed infections, tNGS combined with CMTs identified a definite or probable microbial etiology in 114 samples (80.3%). Of the 36 samples with concordant positive results from both tNGS and CMTs, 72.2% (26/36) exhibited full or partial agreement. Our study further showed the highest detection rate for viral infections (57.0%), predominantly for Epstein-Barr virus (DNA-V, 18.3%). Followed by bacterial infections (46.5%), the detection rate of Gram-negative bacteria (G+, 35.9%) was higher than that of Gram-positive bacteria (G-, 21.8%) in this study. Klebsiella pneumoniae (G-, 12.7%) had the highest detection rate among these emerging bacteria, followed by Pseudomonas aeruginosa (G-, 10.6%) and Enterococcus faecium (G+, 7.7%). Bacterial-viral coinfections were the most common type of mixed infection (35.5%). In conclusion, tNGS outperforms CMTs in both sensitivity and pathogen spectrum. Therefore, it can serve as an adjunct to CMTs to facilitate the precise adjustment of anti-infective regimens for adult HM patients. Our findings establish a basis for formulating empirical anti-infective therapy strategies tailored to the pathogen distribution in this patient population.

Diagnostic Benefit of Molecular Imaging in Patients Undergoing Heart Valve Surgery for Infective Endocarditis.

(1) Background: The successful treatment of infective endocarditis (IE) relies on detecting causative pathogens to administer targeted antibiotic therapy. In addition to standard microbiological cultivation of pathogens from tissue obtained during heart valve surgery, the potential of molecular biological methods was evaluated. (2) Methods: A retrospective study was performed on heart valve tissue from 207 patients who underwent heart valve surgery for IE. FISHseq (fluorescence in situ hybridization combined with 16S rRNA gene PCR and sequencing) was performed in addition to conventional culture-based microbiological diagnostics. The diagnostic performance of FISHseq was compared with the conventional methods and evaluated in the clinical context. (3) Results: Overall, FISHseq provided a significantly higher rate of specific pathogen detection than conventional valve culture (68.1% vs. 33.3%, p < 0.001). By complementing the findings from blood culture and valve culture, FISHseq was able to provide a new microbiological diagnosis in 10% of cases, confirm the cultural findings in 24.2% of cases and provide greater diagnostic accuracy in 27.5% of cases. FISHseq could identify a pathogen in blood-culture-negative IE in 46.2% of cases, while valve culture provided only 13.5% positive results (p < 0.001). (4) Conclusions: This study demonstrates that using FISHseq as an additional molecular biological technique for diagnostics in IE adds substantial diagnostic value, with potential implications for the treatment of IE. It provides pathogen detection, especially in cases where conventional microbiological cultivation is negative or inconclusive.

Optimization of the Diagnosis of Central Nervous System Infections in Vietnamese Hospitals: Results From a Retrospective Multicenter Study.

Central nervous system infections pose significant health challenges, particularly in low- and middle-income countries, because of high morbidity and mortality rates. Rapid and accurate diagnosis is essential for effective treatment to prevent adverse outcomes. Traditional culture-based diagnostics are often slow and lack specificity. This study evaluates the BioFire FilmArray Meningitis/Encephalitis (FAME) Panel against standard diagnostics in Vietnam to assess its clinical impact and suitability for local epidemiology. We conducted a prospective study involving 330 patients with suspected central nervous system infections at 4 hospitals in northern Vietnam from July 2022 to April 2023. Cerebrospinal fluid samples were analyzed using routine culture methods and FAME. We compared pathogen detection rates and assessed the potential clinical impact of FAME results on patient management. Of the 330 cerebrospinal fluid specimens, 64 (19%) were positive by either conventional diagnostics (n = 48) and/or FAME (n = 33). The agreement between FAME and conventional diagnostics was 87%. Key pathogens Mycobacterium tuberculosis (n = 7), Klebsiella pneumoniae (n = 5), Streptococcus suis (n = 5), Epstein-Barr virus (n = 3), Acinetobacter baumannii (n = 1), and Trichosporon asahii (n = 1) were not detected by FAME. Classical meningitis parameter clinical symptoms, altered glucose, protein, and pleocytosis were good predictors of FAME positivity, indicating their utility in optimizing local diagnostic algorithms. FAME complements traditional diagnostics by offering rapid and broad pathogen detection, crucial for timely and appropriate therapy. However, its effectiveness varies with local epidemiology, and it should not replace conventional methods entirely. Tailoring diagnostic panels to regional pathogen prevalence is recommended to enhance diagnostic accuracy and clinical outcomes in low- and middle-income countries.

Clinical value of macrogenome next-generation sequencing on infections.

Intracranial infection (ICI) is a frequent and serious complication after neurosurgery. Macrogenome next-generation sequencing (mNGS) technology can provide reference for clinical diagnosis and treatment of ICI. This work aimed to explore the application value of mNGS technology in analyzing the clinical characteristics of human immunodeficiency virus (HIV) infection and ICI after neurosurgery. A total of 60 patients with ICI were enrolled as the research objects, all patients underwent routine cerebrospinal fluid analysis and traditional pathogen detection, followed by mNGS genome analysis. Using clinical diagnosis of ICI as the gold standard, the sensitivity, specificity, positive predictive value, and negative predictive value for both detection methods were calculated. Receiver operating characteristic curves were constructed to assess the area under the curve (AUC) for evaluating the clinical value of mNGS in suspected intracranial infectious pathogen diagnosis. Results showed a positivity rate of 71.67% (43 cases) with mNGS compared to 28.33% (17 cases) with traditional pathogen detection methods, demonstrating a significant difference (P < 0.05). The sensitivity of mNGS for detecting ICIs was 83.7%, significantly higher than the 34.88% observed with traditional methods (P < 0.05). The pathogen detection rate of mNGS was higher than traditional methods (P = 0.002), with an AUC of 0.856 (95% CI: 0.638-0.967), significantly greater than the AUC of 0.572 (95% CI: 0.350-0.792) for traditional methods (P < 0.05). mNGS successfully identified microorganisms such as Cryptococcus, Propionibacterium, Staphylococcus, Corynebacterium, Micrococcus, and Candida associated with ICIs. These findings underscore the clinical applicability of mNGS technology in analyzing the characteristics of HIV infection and ICI post-neurosurgical procedures. This technology enables more accurate diagnosis and treatment of ICIs, providing valuable insights for developing effective therapeutic strategies.

The clinical application value of multi-site mNGS detection of patients with sepsis in intensive care units

BackgroundSepsis remains a leading cause of mortality in intensive care units, and rapid and accurate pathogen detection is crucial for effective treatment. This study evaluated the clinical application of multi-site metagenomic next-generation sequencing (mNGS) for the diagnosis of sepsis, comparing its performance against conventional methods.MethodsA retrospective analysis was conducted on 69 patients with sepsis consecutively admitted to the Department of Intensive Care Medicine, Meizhou People’s Hospital. Samples of peripheral blood and infection sites were collected for mNGS and conventional method tests to compare the positive rate of mNGS and traditional pathogen detection methods and the distribution of pathogens. The methods used in this study included a comprehensive analysis of pathogen consistency between peripheral blood and infection site samples. Additionally, the correlation between the pathogens detected and clinical outcomes was investigated.ResultsOf the patients with sepsis, 57.97% experienced dyspnea, and 65.2% had underlying diseases, with hypertension being the most common. mNGS demonstrated a significantly higher pathogen detection rate (88%) compared to the conventional method tests (26%). The pathogen consistency rate was 60% between plasma and bronchoalveolar lavage fluid samples, and that of plasma and local body fluid samples was 63%. The most frequently detected pathogens were gram-negative bacteria, and Klebsiella pneumonia. There were no significant differences in the clinical features between the pathogens.ConclusionmNGS is significantly superior to conventional methods in pathogen detection. There was a notable high pathogen consistency detection between blood and local body fluid samples, supporting the clinical relevance of mNGS. This study highlights the superiority of mNGS in detecting a broad spectrum of pathogens quickly and accurately.Trial registrationNot applicable.

Analyzing infections caused by 11 respiratory pathogens in children: Pre‐ and post‐COVID‐19 pandemic trends in China

AbstractWith the lifting of coronavirus disease 2019 (COVID‐19) restrictions in December 2022 in China, the population was widely infected with COVID‐19. We aim to analyzed changes in the epidemiological characteristics of other respiratory pathogens in children before and after the COVID‐19 pandemic. We conducted a retrospective analysis of 44 704 children with acute respiratory infections who underwent 11 respiratory pathogen tests based on multiplex polymerase chain reaction between February and December in both 2022 and 2023. The total pathogen detection rate (24861, 74.80% vs. 6423, 56.01%; p = 0.000) and detection rates of coinfection (4059, 12.21% vs. 676, 5.89%; p = 0.000) in 2023 was significantly higher than that in 2022. The detection rates of influenza A (2567, 7.72% vs. 222, 1.94%; p = 0.000), influenza B (383, 1.15% vs. 37, 0.32%; p = 0.000), human parainfluenza virus (2175, 6.54% vs. 602, 5.25%; p = 0.000), human metapneumovirus (1354, 4.07% vs. 346, 3.01%; p = 0.000), respiratory syncytial virus (3148, 9.47% vs. 870, 7.59%; p = 0.000), and Mycoplasma pneumonia (MP; 9494, 28.56% vs. 1790, 15.61%; p = 0.000) in 2023 were significantly higher than those in 2022, whereas the detection rates of human adenovirus (1124, 3.38% vs. 489, 4.26%; p = 0.000) and human bocavirus (629, 1.89% vs. 375, 3.27%; p = 0.000) were significantly lower than those in 2022. Chlamydia, human rhinovirus, and human coronavirus showed similar detection rates between 2023 and 2022. In 2023, the influenza virus and human parainfluenza virus regained seasonal characteristic, an outbreak of MP infection occurred, the epidemic season of respiratory syncytial virus changed, and the proportion of children with acute respiratory infection aged 0–28 days and over 3 years old increased. Influenza B, metapneumovirus, and human bocavirus were detected in children aged 0–28 days in 2023, but not in 2022. After the COVID‐19 pandemic, we should be alert to the increase of respiratory diseases and the change of epidemic season and susceptible age.

Clinical utility of metagenomic next-generation sequencing on bronchoalveolar lavage fluid in diagnosis of lower respiratory tract infections

BackgroundIn this study, we aimed to evaluate the clinical utility of Metagenomic Next-Generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) in diagnosis of Lower Respiratory Tract Infections (LRTIs).MethodsIn this study, we retrospectively analyzed 186 hospitalized patients who were suspected with LRTIs and performed mNGS (DNA) test of BALF simultaneously at The Fifth Affiliated Hospital of Sun Yat-Sen University from March 2023 to August 2023. Suspected LRTI was based on LRTI related clinical manifestations or imaging examination. Among them, 155 patients had undergone conventional culture and mNGS (DNA) testing simultaneously. Finally, 138 cases (89.03%,138/155) were diagnosed as LRTI and 17 cases (10.97%,17/155) were diagnosed as non-LRTI. Both detecting rate and diagnostic efficacy of mNGS and conventional culture were compared.ResultsThe positive detection rates of pathogens between mNGS and conventional culture were significant different (81.29% VS 39.35%, P < 0.05). Compared with paired conventional culture result, the sensitivity of mNGS in diagnosis of LRTIs was more superior (88.41% VS 43.48%; P < 0.05), the specificity was opposite (76.47% VS 94.12%; P > 0.05). Furthermore, 77.54% and 35.51% of LRTI cases were being etiologically diagnosed by mNGS and culture respectively. Importantly, mNGS directly led to a change of treatment regimen in 58 (37.42%) cases, including antibiotic adjustment (29.68%) and ruling out active infection (7.74%). Moreover, treatment regimen remained unchanged in 97 (62.58%) cases, considering the current antibiotic therapy already covered the detected pathogens (36.13%) or empirical treatment was effective (11.61%).ConclusionsmNGS can identify a wide range of pathogens in LRTIs, with improved sensitivity and being more superior at diagnosing LRTIs etiologically. mNGS has the potential to enhance clinical outcomes by optimizing the treatment regimens.

Analysis of Pathogen Detection Data in 898 Pediatric Patients Hospitalized with Community-Acquired Pneumonia

Introduction: The prevalence of community-acquired pneumonia (CAP) in pediatric patients has seen significant changes following the lifting of COVID-19 restrictions. This study examines the epidemiology and pathogen detection in children hospitalized with CAP at Beijing New Century Children's Hospital throughout 2023. Objective: To analyze the pathogen detection rates and distribution characteristics among 898 pediatric CAP patients admitted during 2023, focusing on age-related and seasonal variations. Methods: This retrospective study included 898 pediatric patients diagnosed with CAP between January 1 and December 31, 2023. Respiratory pathogen detection was performed using a combination of antigen detection kits, nucleic acid testing, and bacterial culture. The data were analyzed for pathogen distribution across different age groups and seasons. Results: Of the 898 CAP cases, pathogens were detected in 703 cases (78.3%). Mycoplasma pneumoniae was the most frequently identified pathogen (44.1%), with detection rates increasing significantly with age, particularly in school-aged children. Viral pathogens were detected in 42.7% of cases, with Respiratory Syncytial Virus (32.4%) being the most prevalent. Bacterial pathogens were identified in 49.5% of cases, with Streptococcus pneumoniae (34.1%) and Haemophilus influenzae (33.0%) being the most common. Mixed infections were observed in 64.4% of cases, with a higher prevalence in older children and during the autumn and winter seasons. Conclusions: The study highlights significant age and seasonal variations in pathogen distribution among pediatric CAP patients. Mycoplasma pneumoniae was more common in older children and during autumn, while bacterial infections peaked in winter. The findings emphasize the need for age and season-specific strategies in managing pediatric CAP and suggest that comprehensive diagnostic approaches are crucial to accurately identify the causative pathogens.