Analysis of risk factors associated with fatal outcome among severe fever with thrombocytopenia syndrome patients from 2015 to 2019 in Shandong, China

Increased cTnI Predicts Early Death in Patients with Severe Fever with Thrombocytopenia: A Multicenter Study in North China

Background

Myocardial injury is common in severe fever with thrombocytopenia syndrome (SFTS) patients. Currently, research on the prognostic value of cardiac troponin I (cTnI) for predicting the mortality of SFTS patients, especially death within 7 days is limited.

Methods

Between May 2011 and October 2022, clinical and laboratory data on admission of consecutive SFTS cases were collected from six medical centres in China. The clinical endpoint was in-hospital all-cause death within seven days. Risk factors of myocardial injury and death were analysed using multivariable regression models. Prognostic models were established using Cox regression and performance of indicators was evaluated in terms of calibration, discrimination.

Results

A total of 1379 laboratory-confirmed patients were enrolled, in which 686 subjects were included for analysis. The median age was 66 years, with 48.1% of male. Eighty-seven patients died within seven days and 396 patients diagnosed with myocardial injury during hospitalization. Non-survivors had significant higher levels of cardiac indices than survivors, including cTnI, aspartic transaminase (AST) and lactate dehydrogenase (LDH). Elevated levels of cTnI (HR = 1.058, 95% CI:1.032-1.085), AST (HR = 1.191, 95% CI:1.150-1.234) and LDH (HR = 1.019, 95% CI:1.009-1.029) predicted risk of early in-hospital mortality. cTnI model performed best, with area under curve of 0.850 (0.774-0.926) and concordance index of 0.842, respectively. Statistical differences were found between high and low levels of cTnI for mortality (P<0.001) using 0.35 ng/mL as the optimal cut-off.

Conclusion

The risk of early in-hospital death can be predicted by cTnI. Clinical doctors should remind vigilant concerning the elevation of cardiac enzyme as soon as possible.

Activated partial thromboplastin time predicts mortality in patients with severe fever with thrombocytopenia syndrome: A multicenter study in north China

Background

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with high lethality. This study aimed to determine whether prolonged activated partial thromboplastin time (APTT) predicted SFTS mortality.

Methods

SFTS patients were enrolled from 6 hospitals in the north China. Subjects were divided into training cohort and 5 externally validation cohorts. The least absolute shrinkage and selection operator Cox regression model was performed to screen potential prognostic factors. Risk factors were analyzed using multivariable regression models. Prognostic models were established by Cox regression and random survival forest (RSF) methods, and evaluated regarding discrimination, validity and clinical benefit. Time-dependent receiver operating characteristic (ROC) curve was used to evaluate the predictive effectiveness of variables.

Results

1332 SFTS cases were included, in which 211 patients died. Six potential prognostic factors were screened, and pulse, breath, APTT and aspartic transaminase (AST) were independently associated with mortality in both training cohort (Yantai, N = 791) and external validation cohort (N = 541). APTT was steadily correlated with the fatality (HR: 1.039-1.144; all P < 0.01) in each five sub-validation cohorts (Dandong, Dalian, Tai'an, Qingdao and Beijing). RSF model with variables of APTT, AST, pulse and breath had considerable prognostic effectiveness, which APTT showed the highest prognostic ability with the area under the curve of 0.848 and 0.787 for 7-day and 14-day survival, respectively. Survival differences were found between high and low levels of APTT for mortality using 50s as the optimal cut-off.

Conclusions

SFTS patients have prolonged APTT, which is an independent risk factor for fatality. APTT≥50s was recommended as a biomarker to remind physicians to monitor and treat patients more aggressively to improve clinical prognosis.

Blood urea nitrogen to albumin ratio is a novel predictor of fatal outcome for patients with severe fever with thrombocytopenia syndrome

Severe fever with thrombocytopenia syndrome (SFTS) is associated with a high death rate and lacks a targeted therapy plan. The ratio of blood urea nitrogen to albumin, known as BAR, is a valuable method for assessing the outlook of various infectious diseases. The objective of this research was to evaluate the effectiveness of BAR in forecasting the outcome of individuals with SFTS. Four hundred and thirty-seven patients with SFTS from two clinical centers were included in this study according to inclusion and exclusion criteria. Clinical characteristics and test parameters of SFTS patients were analyzed between survival and fatal groups. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression suggested that BAR might serve as a standalone prognostic indicator for patients with SFTS in the initial phase (hazard ratio = 18.669, 95% confidence interval [CI]: 8.558-40.725, p < 0.001). And BAR had a better predictive effectiveness in clinical outcomes in patients with SFTS with an AUC of 0.832 (95% CI: 0.788-0.876, p < 0.001), a cutoff value of 0.19, a sensitivity of 0.812, and a specificity of 0.726 compared to C-reactive protein, procalcitonin, and platelet to lymphocyte ratio via receiver operating characteristic curve. KM (Kaplan Meier) curves demonstrated that high level of BAR was associated with poor survival condition in patients with SFTS. Furthermore, the high level of BAR was associated with long hospital stays and test paraments of kidney, liver, and coagulation function in survival patients. So, BAR could be used as a promising early warning biomarker of adverse outcomes in patients with 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.

Cardiac Abnormalities in Patients With Severe Fever With Thrombocytopenia Syndrome: A Systematic Review

Since the identification of severe fever with thrombocytopenia syndrome virus (SFTSV) in 2010, there has been an increase in reported cases in China and other Asian countries. Cardiac abnormalities are highly prevalent in SFTS patients. We searched 5 Chinese and international databases for published SFTS articles and extracted patient characteristics, cardiac complications, electrocardiography findings, and imaging findings. Twenty-seven studies were identified, covering 1938 patients and 621 cardiac abnormalities. Arrhythmia was the most prevalent, reported in 24 studies and 525 cases, with a prevalence of 27.09%. The 2 major types of arrhythmias were bradycardia and atrial fibrillation. Heart failure was the second most prevalent abnormality, with 77 cases. Changes in the ST segment and T wave were the most common. Valve regurgitation, reduced ejection fraction, and pericardial effusion were also documented. We recommend that physicians pay close attention to newly onset arrhythmia and structural heart disease in SFTS patients.

Investigation of predictors for invasive pulmonary aspergillosis in patients with severe fever with thrombocytopenia syndrome

Patients with severe fever with thrombocytopenia syndrome (SFTS) had been confirmed to have immune dysfunction and were prone to invasive pulmonary aspergillosis (IPA), which was directly related to the increased mortality. The aim of this study was to investigate the predictors for IPA in SFTS patients, and the results were expected to be helpful for early identification of IPA and initiation of anti-fungal therapy. The study was performed to review laboratory confirmed SFTS patients in two tertiary hospitals in Shandong province (Qilu Hospital of Shandong University and Shandong Public Health Clinical Center) from April 2021 to August 2022. The enrolled patients were further divided into IPA group and non-IPA group. Demographic characteristics, clinical manifestations and laboratory parameters between IPA group and non-IPA group patients were analyzed and compared to identify the independent predictors for IPA by univariate analysis and multivariable logistic regression analysis. Sensitivity and specificity of independent predictors were evaluated by receiver operating characteristic (ROC) curve analysis. In total, 67 SFTS patients were enrolled with an average age of 64.7 (± 8.4) years old. The incidence of IPA was 32.8% (22/67). Mortality of patients in IPA group was 27.3% (6/22), which was significantly higher than that in non-IPA group. Results of univariate analysis showed that uncontrolled diabetes, central nervous system symptoms, platelet < 40 × 10⁹/L, CD4⁺ T cell < 300/μL and CD8⁺ T cell < 400/μL were risk factors for development of IPA. These factors were further analyzed by multivariable logistic regression analysis and the results indicated that uncontrolled diabetes, platelet < 40 × 10⁹/L, CD4⁺ T cell < 300/μL and CD8⁺ T cell < 400/μL could be recognized as independent predictors for IPA in SFTS patients. In conclusion, IPA is a serious complication for SFTS patients and increases mortality. It is necessary to early identify predictors of IPA for improving survival of SFTS patients.