High C-reactive protein to lymphocyte ratio predicts mortality outcomes of patients with severe fever with thrombocytopenia syndrome: A multicenter study in China

Antiviral immunity of severe fever with thrombocytopenia syndrome: current understanding and implications for clinical treatment

Dabie Banda virus (DBV), a tick-borne pathogen, was first identified in China in 2009 and causes profound symptoms including fever, leukopenia, thrombocytopenia and multi-organ dysfunction, which is known as severe fever with thrombocytopenia syndrome (SFTS). In the last decade, global incidence and mortality of SFTS increased significantly, especially in East Asia. Though previous studies provide understandings of clinical and immunological characteristics of SFTS development, comprehensive insight of antiviral immunity response is still lacking. Here, we intensively discuss the antiviral immune response after DBV infection by integrating previous ex- and in-vivo studies, including innate and adaptive immune responses, anti-viral immune responses and long-term immune characters. A comprehensive overview of potential immune targets for clinical trials is provided as well. However, development of novel strategies for improving the prognosis of the disease remains on challenge. The current review may shed light on the establishment of immunological interventions for the critical disease SFTS.

Novel nomograms to predict risk and prognosis in hospitalized patients with severe fever with thrombocytopenia syndrome

Background

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging and life-threatening infectious disease caused by SFTS virus. Although recent studies have reported the use of nomograms based on demographic and laboratory data to predict the prognosis of SFTS, no study has included viral load, which is an important factor that influences the prognosis, when compared with other risk factors. Therefore, this study aimed to develop a model that predicts SFTS prognosis before it reaches the critical illness stage and to compare the predictive ability of groups with and without viral load.

Methods

Two hundred patients with SFTS were enrolled between June 2018 and August 2023. Data were sourced from the first laboratory results at admission, and two nomograms for mortality risk were developed using multivariate logistic regression to identify the risk variables for poor prognosis in these patients. We calculated the area under the receiver operating characteristic curve (AUC) for the two nomograms to assess their discrimination, and predictive abilities were compared using net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

Results

The multivariate logistic regression analysis identified four independent risk factors: age, bleeding manifestations, prolonged activated partial thromboplastin time, and viral load. Based on these factors, a final nomogram predicting mortality risk in patients with SFTS was constructed; in addition, a simplified nomogram was constructed excluding the viral load. The AUC [0.926, 95% confidence interval (CI): 0.882-0.970 vs. 0.882, 95% CI: 35 0.823-0.942], NRI (0.143, 95% CI, 0.036-0.285), and IDI (0.124, 95% CI, 0.061-0.186) were calculated and compared between the two models. The calibration curves of the two models showed excellent concordance, and decision curve analysis was used to quantify the net benefit at different threshold probabilities.

Conclusion

Two critical risk nomograms were developed based on the indicators for early prediction of mortality risk in patients with SFTS, and enhanced predictive accuracy was observed in the model that incorporated the viral load. The models developed will provide frontline clinicians with a convenient tool for early identification of critically ill patients and initiation of a better personalized treatment in a timely manner.

The relationship between C-reactive protein to lymphocyte ratio and the prevalence of myocardial infarction in US adults: A cross-sectional study

Objective

C-reactive protein to lymphocyte ratio (CLR) has been identified as a novel inflammatory biomarker. However, the role of CLR in myocardial infarction is unclear. Thus, this study designs to investigate the association of CLR with the prevalence of myocardial infarction in a large multiracial population in the United States.

Methods

Participants from the National Health and Nutrition Examination Survey (NHANES) 2017-March 2020 Pre-pandemic were included in this cross-sectional study. Multivariable regression and subgroup analyses, controlling for demographic variables, were performed to examine the association between CLR and its quintiles and myocardial infarction. A smooth curve fitting was used to model the non-linear relationship between them.

Results

A total of 12,615 participants aged ≥18 years were recruited, of whom 609 (4.83%) self-reported a history of myocardial infarction. Compared to those in the lowest quartile of ln-transformed CLR (Q1), the myocardial infarction risks for subjects in Q2, Q3, and Q4 were 1.64, 1.71, and 1.79 times, respectively. Obvious upward trends were observed when ln-transformed CLR increased (P for trend <0.01). In continuous analyses, the fully adjusted odds ratios (OR) for myocardial infarction prevalence per ln-transformed increment in CLR was 1.46 (95% CI: 1.16-1.84, P < 0.01). Furthermore, a linear association was detected for ln-transformed CLR with the risk of myocardial infarction. Interaction test showed that the effect of CLR on myocardial infarction was significantly affected by age (P for interaction = 0.04).

Conclusions

Data from a large, cross-sectional cohort program show that CLR is positively associated with myocardial infarction prevalence. Our findings highlight that CLR may be a novel inflammation warning biomarker for myocardial infarction.