Infectious Medicine最新文献

Background

To summarize the diagnosis and treatment of a patient with nasopharyngeal carcinoma and cerebrospinal fluid (CSF) Epstein-Barr virus (EBV) positivity (determined by next-generation sequencing), review the relevant literature, and explore the significance of EBV presence in the CSF of patients with nasopharyngeal carcinoma.

Methods

A patient presenting with headache as the initial symptom was diagnosed with nasopharyngeal carcinoma and admitted to the Eighth Medical Center of Chinese PLA General Hospital on March 3, 2021. Available databases were screened for reports on nasopharyngeal carcinoma with EBV-positive CSF and analyzed. The patients’ general information, initial symptoms, treatment, and prognosis were subsequently evaluated.

Results

EBV-positive CSF is commonly observed in patients with recurrent nasopharyngeal carcinoma. However, no reports of EBV-positive CSF in patients with primary nasopharyngeal carcinoma have been published to date.

Conclusion

The presence of EBV in the CSF of patients with recurrent nasopharyngeal carcinoma is indicative of a poor prognosis. Thus, newly diagnosed nasopharyngeal carcinoma patients should undergo a lumbar puncture as soon as possible to have their CSF tested for EBV. Such a measure would promptly predict the prognosis and facilitate the development of a personalized treatment strategy.

Background

In this study, we present a case of Japanese spotted fever (JSF) caused by Rickettsia japonica and use this case to investigate the process of diagnosing and reintegrating traceability of infectious diseases via metagenomic next-generation sequencing (mNGS).

Methods

From data relating to epidemiological history, clinical and laboratory examinations, and mNGS sequencing, a diagnosis of severe JSF was concluded.

Results

A detailed field epidemiological investigation discovered parasitic Haemaphysalis longicornis from a host animal (dog) in the domicile of the patient, within which R. japonica was detected, along with a diverse array of other potentially pathogenic microorganisms that could cause other infectious diseases.

Conclusion

The mNGS provided an efficient method to diagnose JSF infection. This methodology could also be applied to field epidemiological investigations to establish the traceability of infectious diseases.

The COVID-19 pandemic has created unprecedented challenges worldwide. Artificial intelligence (AI) technologies hold tremendous potential for tackling key aspects of pandemic management and response. In the present review, we discuss the tremendous possibilities of AI technology in addressing the global challenges posed by the COVID-19 pandemic. First, we outline the multiple impacts of the current pandemic on public health, the economy, and society. Next, we focus on the innovative applications of advanced AI technologies in key areas such as COVID-19 prediction, detection, control, and drug discovery for treatment. Specifically, AI-based predictive analytics models can use clinical, epidemiological, and omics data to forecast disease spread and patient outcomes. Additionally, deep neural networks enable rapid diagnosis through medical imaging. Intelligent systems can support risk assessment, decision-making, and social sensing, thereby improving epidemic control and public health policies. Furthermore, high-throughput virtual screening enables AI to accelerate the identification of therapeutic drug candidates and opportunities for drug repurposing. Finally, we discuss future research directions for AI technology in combating COVID-19, emphasizing the importance of interdisciplinary collaboration. Though promising, barriers related to model generalization, data quality, infrastructure readiness, and ethical risks must be addressed to fully translate these innovations into real-world impacts. Multidisciplinary collaboration engaging diverse expertise and stakeholders is imperative for developing robust, responsible, and human-centered AI solutions against COVID-19 and future public health emergencies.

A 68-year-old-gentleman presented with left hip pain, night sweats, fatigue, and weight loss. He had previously experienced pain with white discharge until he underwent an arthroscopic washout and reduction. The left lower limb was shortened and wasted with limited hip movements. He had recently travelled to Zambia, his country of origin. Imaging demonstrated a large mass with chronic erosions of the acetabulum and femoral head. Synovial biopsy grew Mycobacterium tuberculosis, which was treated with rifampicin, isoniazid, pyrazinamide, and ethambutol for 2 months then 4 months of rifampicin and isoniazid. Whole genome sequencing indicated full sensitivity. Complex reconstructive surgery is scheduled, with a custom femoral head and acetabulum. This case illustrates the importance of considering tuberculosis in patients with erosive joint pathology and a multidisciplinary approach as delayed diagnosis results in high morbidity. Prompt diagnosis using newer modalities such as whole genome sequencing on synovial fluid can enable timely treatment.

Background

Hepatitis C, caused by the Hepatitis C Virus (HCV), is the second most common form of viral hepatitis. The geographical distribution of HCV genotypes can be quite complex, making it challenging to ascertain the most prevalent genotype in a specific area.

Methods

To address this, a review was conducted to determine the prevalence of HCV genotypes across various provinces and as a whole in Pakistan. The scientific literature regarding the prevalence, distribution, genotyping, and epidemiology of HCV was gathered from published articles spanning the years 1996–2020.

Results

Genotype 1 accounted for 5.1% of the patients, with its predominant subtype being 1a at 4.38%. The frequencies of its other subtypes, 1b and 1c, were observed to be 1.0% and 0.31% respectively. Genotype 2 had a frequency of 2.66%, with the most widely distributed subtype being 2a at 2.11% of the patients. Its other subtypes, 2b and 2c, had frequencies of 0.17% and 0.36% respectively. The most prevalent genotype among all isolates was 3 (65.35%), with the most frequent subtype being 3a (55.15%), followed by 3b (7.18%). The prevalence of genotypes 4, 5, and 6 were scarce in Pakistan, with frequencies of 0.97%, 0.08%, and 0.32% respectively. The prevalence of untypeable and mixed genotypes was 21.34% and 3.53% respectively. Estimating genotypes proves to be a productive method in assisting with the duration and selection of antiviral treatment. Different HCV genotypes can exhibit variations in their response to specific antiviral treatments. Different genotypes may have distinct natural histories, including variations in disease progression and severity. Some genotypes may lead to more rapid liver damage, while others progress more slowly.

Conclusions

This information can guide screening and testing strategies, helping to identify individuals at higher risk of developing severe complications. Studying the distribution of HCV genotypes in a population can provide valuable insights into the transmission dynamics of the virus.

Here we describe the first case of abscess infection caused by Nocardia beijingensis in China. The patient was immunocompetent but suffered from postoperative abscess for 6 years. This study highlights the necessity of long-term infected foci to be thoroughly examined to identify the pathogen, as well as the importance of accurate Nocardia identification and antimicrobial susceptibility tests for understanding the pathogen's epidemiology, clinical significance, and treatment strategy.

Background

Some COVID-19 patients deteriorate to severe cases with relatively higher case-fatality rates, which increases the medical burden. This necessitates identification of patients at risk of severe disease. Early assessment plays a crucial role in identifying patients at risk of severe disease. This study is to assess the effectiveness of SUPER score as a predictor of severe COVID-19 cases.

Methods

We consecutively enrolled COVID-19 patients admitted to a comprehensive medical center in Wuhan, China, and recorded clinical characteristics and laboratory indexes. The SUPER score was calculated using parameters including oxygen saturation, urine volume, pulse, emotional state, and respiratory rate. In addition, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity of the SUPER score for the diagnosis of severe COVID-19 were calculated and compared with the National Early Warning Score 2 (NEWS2).

Results

The SUPER score at admission, with a threshold of 4, exhibited good predictive performance for early identification of severe COVID-19 cases, yielding an AUC of 0.985 (95% confidence interval [CI] 0.897–1.000), sensitivity of 1.00 (95% CI 0.715–1.000), and specificity of 0.92 (95% CI 0.775–0.982), similar to NEWS2 (AUC 0.984; 95% CI 0.895–1.000, sensitivity 0.91; 95% CI 0.587–0.998, specificity 0.97; 95% CI 0.858–0.999). Compared with patients with a SUPER score<4, patients in the high-risk group exhibited lower lymphocyte counts, interleukin-2, interleukin-4 and higher fibrinogen, C-reactive protein, aspartate aminotransferase, and lactate dehydrogenase levels.

Conclusions

In conclusion, the SUPER score demonstrated equivalent accuracy to the NEWS2 score in predicting severe COVID-19. Its application in prognostic assessment therefore offers an effective early warning system for critical management and facilitating efficient allocation of health resources.