MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1080/07853890.2024.2337738

Медицинская библиотека · Annals of medicine · 2024

Identification of pathogen composition in a Chinese population with iatrogenic and native vertebral osteomyelitis by using mNGS.

Gao Qile, Liu Qianfei, Zhang Guang, Lu Yingqing, Li Yanbing, Tang Mingxing, Liu Shaohua, Zhang Hongqi, Hu Xiaojiang

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

BACKGROUND

Early antimicrobial therapy is crucial regarding the prognosis of vertebral osteomyelitis, but early pathogen diagnosis remains challenging.

OBJECTIVE

In this study, we aimed to differentiate the types of pathogens in iatrogenic vertebral osteomyelitis (IVO) and native vertebral osteomyelitis (NVO) to guide early antibiotic treatment.

METHODS

A total of 145 patients, who had confirmed spinal infection and underwent metagenomic next-generation sequencing (mNGS) testing, were included, with 114 in the NVO group and 31 in the IVO group. Using mNGS, we detected and classified 53 pathogens in the 31 patients in the IVO group and 169 pathogens in the 114 patients in the NVO group. To further distinguish IVO from NVO, we employed machine learning algorithms to select serum biomarkers and developed a nomogram model.

RESULTS

The results revealed that the proportion of the Actinobacteria phylum in the NVO group was approximately 28.40%, which was significantly higher than the 15.09% in the IVO group. Conversely, the proportion of the Firmicutes phylum (39.62%) in the IVO group was markedly increased compared to the 21.30% in the NVO group. Further genus-level classification demonstrated that Staphylococcus was the most common pathogen in the IVO group, whereas Mycobacterium was predominant in the NVO group. Through LASSO regression and random forest algorithms, we identified 5 serum biomarkers including percentage of basophils (BASO%), percentage of monocytes (Mono%), platelet volume (PCT), globulin (G), activated partial thromboplastin time (APTT) for distinguishing IVO from NVO. Based on these biomarkers, we established a nomogram model capable of accurately discriminating between the two conditions.

CONCLUSION

The results of this study hold promise in providing valuable guidance to clinical practitioners for the differential diagnosis and early antimicrobial treatment of vertebral osteomyelitis.

Для цитирования: Gao Qile, Liu Qianfei, Zhang Guang, Lu Yingqing, Li Yanbing, Tang Mingxing, Liu Shaohua, Zhang Hongqi, Hu Xiaojiang. Identification of pathogen composition in a Chinese population with iatrogenic and native vertebral osteomyelitis by using mNGS.. Annals of medicine. 2024. DOI: 10.1080/07853890.2024.2337738.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.