Diagnostic efficiency of metagenomic next-generation sequencing for suspected spinal tuberculosis in China: A multicenter prospective study

Diagnostic Role of Metagenomic Next-Generation Sequencing in Tubercular Orthopedic Implant-Associated Infection

Objective

The diagnosis of tubercular orthopedic implant-associated infection (TB-IAI) is challenging. This study evaluated the value of metagenomic next-generation sequencing (mNGS) for the diagnosis of TB-IAI and developed a standardized diagnostic procedure for TB-IAI.

Methods

The records of all patients with TB-IAI diagnosed and treated at our institution between December 2018 and September 2022 were retrospectively reviewed. Patient demographic characteristics, medical history, laboratory test, microbial culture, histopathology, and mNGS results, and time to diagnosis were recorded. The diagnostic efficiency of mNGS for TB-IAI was assessed by comparing the results and diagnostic time with that of other diagnostic modalities.

Results

Ten patients were included in the analysis, including eight with prosthetic joint infections and two with fracture-related infections. The mNGS positivity rate was 100% (10/10), which was higher than that of TB-antibody (11%, 1/9), real-time quantitative polymerase chain reaction (22%, 2/9), T-SPOT.TB (25%, 2/8), purified protein derivative (50%, 4/8), microbial culture (50%, 5/10), and histopathology (20%, 2/10). mNGS shortened the time to diagnosis of TB-IAI. A standardized diagnostic procedure for TB-IAI was developed based on the findings.

Conclusion

mNGS is useful for the diagnosis of TB-IAI. mNGS is recommended in cases where it is difficult to identify a pathogen using routine diagnostic tests. The standardized diagnostic procedure might improve TB-IAI diagnosis.

Importance

TB-IAI is a rare infection, which occurs after orthopedic surgery and hard to diagnose microbiologically. mNGS is a new detection technique not yet discussed in current literature as a means for TB-IAI diagnostics. Here we describe a cohort of patients with TB-IAI diagnosed by mNGS show high efficiency of mNGS for detection of this pathology and present a clinical algorithm supplementing conventional methods for TB-IAI assessment.

Utilizing metagenomic next-generation sequencing for pathogen detection and diagnosis in lower respiratory tract infections in real-world clinical practice

BACKGROUND

Infectious etiologies of lower respiratory tract infections (LRTIs) by the conventional microbiology tests (CMTs) can be challenging. Metagenomic next-generation sequencing (mNGS) has great potential in clinical use for its comprehensiveness in identifying pathogens, particularly those difficult-to-culture organisms.

METHODS

We analyzed a total of 205 clinical samples from 201 patients with suspected LRTIs using mNGS in parallel with CMTs. mNGS results were used to guide treatment adjustments for patients who had negative CMT results. The efficacy of treatment was subsequently evaluated in these patients.

RESULTS

mNGS-detected microorganisms in 91.7% (188/205) of the clinical samples, whereas CMTs demonstrated a lower detection rate, identifying microorganisms in only 37.6% (77/205) of samples. Compared to CMT results, mNGS exhibited a detection sensitivity of 93.5% and 95.4% in all 205 clinical samples and 180 bronchoalveolar lavage fluid (BALF) samples, respectively. A total of 114 patients (114/201; 56.7%) showed negative CMT results, among which 92 received treatment adjustments guided by their positive mNGS results. Notably, 67.4% (62/92) of patients demonstrated effective treatment, while 25% (23/92) experienced a stabilized condition. Subgroup analysis of cancer patients revealed that 41.9% (13/31) exhibited an effective response to treatment, and 35.5% (11/31) maintained a stable condition following medication adjustments guided by mNGS.

CONCLUSION

mNGS demonstrated great potential in identifying microorganisms of clinical significance in LRTIs. The rapid turnaround time and reduced susceptibility to the impact of antimicrobial administration make mNGS a valuable supplementary tool for diagnosis and treatment decision-making for suspected LRTIs in clinical practice.

Development of a Diagnostic Model for Differentiating Tuberculous Spondylitis and Pyogenic Spondylitis With MRI: A Multicenter Retrospective Observational Study

STUDY DESIGN

Multicenter retrospective observational study.

OBJECTIVE

This study aimed to distinguish tuberculous spondylitis (TS) from pyogenic spondylitis (PS) using magnetic resonance imaging (MRI). Further, a novel diagnostic model for differential diagnosis was developed.

SUMMARY OF BACKGROUND DATA

TS and PS are the two most common spinal infections. Distinguishing between these types clinically is challenging. Delayed diagnosis can lead to deficits or kyphosis. Currently, there is a lack of radiology-based diagnostic models for TS and PS.

METHODS

We obtained radiologic images from MRI imaging of patients with TS and PS and applied the least absolute shrinkage and selection operator regression to select the optimal features for a predictive model. Predictive models were built using multiple logistic regression analysis. Clinical utility was determined using decision curve analysis, and internal validation was performed using bootstrap resampling.

RESULTS

A total of 201 patients with TS (n=105) or PS (n=96) were enrolled. We identified significant differences in MRI features between both groups. We found that noncontiguous multivertebral and single-vertebral body involvement were common in TS and PS, respectively. Vertebral bone lesions were more severe in the TS group than in the PS group (Z=-4.553, P <0.001). The patients in the TS group were also more prone to vertebral intraosseous, epidural, and paraspinal abscesses ( P <0.001). A total of 8 predictors were included in the diagnostic model. Analysis of the calibration curve and area under the receiver operating characteristic curve suggested that the model was well-calibrated with high prediction accuracy.

CONCLUSIONS

This is the largest study comparing MRI features in TS and PS and the first to develop an MRI-based nomogram, which may help clinicians distinguish between TS and PS.

Diagnostic Efficacy of Metagenomic Next-Generation Sequencing in Patients with Spinal Infections: A Retrospective Study

Purpose

Early diagnosis of spinal infections remains challenging, and emerging metagenomic next-generation sequencing (mNGS) technology holds promise in addressing this issue. The aim of this study is to investigate the diagnostic efficacy of mNGS in spinal infections.

Patients and Methods

A total of 78 cases with suspected spinal infections were enrolled in this study, all of whom underwent laboratory, histopathological and mNGS examinations upon admission. Lesion samples were obtained by surgical or C-arm-guided puncture. Sensitivity, specificity, positive predictive value and negative predictive value of culture and mNGS were calculated for statistical analysis.

Results

With histopathological results as the reference, the included 78 patients were categorized into 50 cases in the spinal infection group and 28 cases in the aseptic group. The sensitivity (84%) and negative predictive value (77.14%) of mNGS were significantly higher than those of culture (32% and 44.26%, respectively), whereas no significant differences were observed in terms of specificity and positive predictive value. In the subgroup analysis for Mycobacterium tuberculosis, the sensitivity of mNGS (90.91%) and T-spot (90.91%) was significantly higher than that of culture (0). Additionally, mNGS demonstrated markedly higher specificity (100%) compared to T-spot (85.07%).

Conclusion

This study underscores the substantial advantages of mNGS in terms of diagnostic accuracy and bacterial coverage for spinal infections. The findings provide compelling clinical evidence that supports the enhanced diagnostic efficacy of mNGS.

Evaluation of different diagnostic methods for spinal tuberculosis infection

BACKGROUND AND PURPOSE

Tuberculosis (TB) is the most fatal infectious disease worldwide. Approximately 24.6% of tuberculosis cases are extrapulmonary and predominantly affect the spine. It is difficult to diagnose spinal TB (STB). We aimed to evaluate the diagnostic performance of the Mycobacteria Growth Indicator Tube (MGIT)-960 culture, T-SPOT.TB, Xpert Mycobacterium tuberculosis complex (MTB)/resistance to rifampin (RIF), and Metagenomic Next-Generation Sequencing (mNGS) to detect STB.

METHODS

We assessed 126 patients presumed to have STB using these four methods. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated using clinical diagnosis as a reference.

RESULTS

Of the patients, 41 were diagnosed with STB and 85 with non-STB. In the STB group, the sensitivity, specificity, PPV, and NPV of the MGIT-960 culture were 29.3% (12/41), 100% (85/85), 100% (12/12), and 74.6% (85/114), respectively. The sensitivity, specificity, PPV, and NPV of T-SPOT.TB were 92.7% (38/41), 82.4% (70/85), 58.5% (31/53), and 95.9% (70/73), respectively. The sensitivity, specificity, PPV, and NPV of the Xpert MTB/RIF assay were 53.7% (22/41), 100% (85/85), 100% (22/22), and 81.7% (85/104), respectively. The sensitivity, specificity, PPV, and NPV of mNGS were 39.0% (16/41), 98.8% (84/85), 94.1% (16/17), and 77.1% (84/109), respectively. The sensitivity, specificity, PPV, and NPV of mNGS + Xpert MTB/RIF were 73.2% (30/41), 100% (85/85), 96.8% (30/31), and 72.0% (85/118), respectively. The sensitivity, specificity, PPV, and NPV of the mNGS + T-spot assay were 97.6% (40/41), 100% (85/85), 67.9% (38/56), and 75.9% (85/113), respectively. Moreover, the sensitivity, specificity, PPV, and NPV of T-spot + Xpert MTB/RIF were 95.1% (39/41), 100% (85/85), 72.2% (39/54), and 81.0% (85/105), respectively.

CONCLUSIONS

T-SPOT.TB is the most effective method for diagnosing STB; however, Xpert MTB/RIF is more reliable and can detect RIF resistance. Clinicians can use mNGS to identify pathogens in patients with spinal infections; these pathogens appeared to be more meaningful in guiding the clinical management of patients in the non-STB group. The combination of Xpert MTB/RIF and mNGS can improve the early diagnosis rate and drug resistance detection, reduce the diagnostic cycle, and provide early targeted anti-TB treatment for patients with STB.

Metagenomic next-generation sequencing for Mycobacterium tuberculosis complex detection: a meta-analysis

Objective

Metagenomic next-generation sequencing (mNGS) has been gradually applied to the diagnosis of tuberculosis (TB) due to its rapid and highly sensitive characteristics. Despite numerous studies on this subject, their results vary significantly. Thus, the current meta-analysis was performed to assess the performance of the mNGS on tuberculosis.

Methods

PubMed, Embase, Web of Science, and The Cochrane Library were searched up to June 21, 2023. Studies utilizing the mNGS for tuberculosis detection were included. The risk of bias was assessed by QUADAS-2, and a meta-analysis was performed with STATA14.0 software.

Results

Seventeen studies comprising 3,205 specimens were included. The combined sensitivity and specificity of mNGS for clinical specimens were 0.69[0.58-0.79] and 1.00[0.99-1.00], respectively. Subgroup analysis identified sequencing platform, diagnostic criteria, study type, sample size, and sample types as potential sources of heterogeneity. Cerebrospinal Fluid (CSF) has a lower sensitivity of 0.58 (0.39-0.75). In a population with a 10% prevalence rate, the accuracy of sensitivity reached 94%.

Conclusion

Metagenomic next-generation sequencing technology exhibits high sensitivity and speed in diagnosing Mycobacterium tuberculosis. Its application in mono and mixed infections peoples shows promise, and mNGS is likely to be increasingly used to address challenges posed by Mycobacterium tuberculosis complexes in the future.

Clinical Value of Metagenomic Next-Generation Sequencing Using Spinal Tissue in the Rapid Diagnosis of Spinal Tuberculosis

Purpose

To evaluate the accuracy of metagenomic next-generation sequencing (mNGS) for rapid diagnosis of spinal tuberculosis using spinal tissue specimens.

Methods

Medical data regarding suspected spinal tuberculosis were retrospectively analyzed. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of mNGS were calculated to determine its diagnostic efficacy, and these values were compared with culture and composite reference standard (CRS).

Results

Two hundred and three cases of spinal tuberculosis were included for analysis. The sensitivity, specificity, PPV, NPV, and AUC of mNGS compared with culture were all very good. When CRS was used for the comparison, the sensitivity of mNGS and culture were 71.2% and 73.0%; the specificity and PPV were 100% in all cases; the NPV were 74.2% and 75.4%; the AUCs were all 0.86. The sensitivity and NPV of culture were slightly higher than that of mNGS; however, the diagnostic efficacy of mNGS and culture was consistent (P > 0.05).

Conclusion

Spinal tissue specimens for mNGS testing had very good accuracy for diagnosing spinal tuberculosis.