Background: The aim of this study is to establish a clinical diagnosis model as a new evaluation indicator for the differentiation of adult-onset Still's disease (AOSD) and other fever of unknown origin disease (FUO).Methods: This is an observational case-control study between January 2010 and December 2018.Laboratory parameters of AOSD group (N=91), FUO group (N=89) and control group (N=81) including procalcitonin, C-reactive protein (CRP), ferritin, leukocyte, lymphocyte, neutrophil, lymphocyte proportion, neutrophil proportion, red blood cell distribution width (RDW), platelet and platelet parameters were collected. Descriptive statistics and logistic regression were performed to establish a model based on these laboratory variables.Results: After univariate screening, the variables including CRP, leukocyte, neutrophil, lymphocyte proportion, neutrophil proportion, ferritin and mean platelet volume (MPV) showed significant difference between AOSD and FUO groups, then a stepwise regression analysis was performed to establish a model based on these screened variables, at last ferritin, neutrophil and MPV were significantly different in the model. The results suggested that the higher value of ferritin and neutrophil, the lower value of MPV in the model indicated the higher risk to diagnose AOSD. Area under the curve (AUC) of the model was 0.909 (95% CI: 0.855-0.947), which showed high differential diagnostic value (sensitivity: 86.6%, specificity: 82.0%). Conclusions:The diagnosis model of AOSD and other FUO was established, with an outstanding performance for differential diagnosis.

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Background. The prognosis of Infective endocarditis (IE) is poor, and we conducted this investigation to evaluate the worth of admission lymphocyte-to-white blood cell ratio (LWR) for prediction of short-term outcome in IE patients. Methods. We retrospectively assessed the medical records of 147 IE patients from January 2017 to December 2019. Patients were divided into the survivor group and nonsurvivor group. Univariate and multivariate analyses were applied to estimate the independent factors contribution to in-hospital death, and receiver-operator characteristic (ROC) curve was utilized to check the performance. Results. The levels of LWR (0.17 ± 0.08 vs. 0.10 ± 0.06) were significantly increased among the survivor group compared with the nonsurvivor group ( P  = 0.001). Multivariate analysis displayed that LWR (hazard ratio (HR): 1.755, 1.304–2.362, P  < 0.001) was not interfered by other confounding factors for early death. Moreover, ROC analysis suggested that LWR (cutoff value = 0.10) performed the best among assessed indexes for the forecast of primary outcome (area under curve (AUC) = 0.750, 95% confidence interval (CI) = 0.634–0.867, P  < 0.001, sensitivity = 70.0%, specificity = 76.4%), and the proportion of in-hospital mortality was remarkably inferior in patients with LWR > 0.10 than in those with LWR ≤ 0.10. (5.83% vs. 31.8%, P  < 0.001). Conclusions. LMR is an independent, simple, universal, inexpensive, and reliable prognostic parameter to identify high-risk IE patients for in-hospital mortality.

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Objective: Acute type A aortic dissection (AAD) is a serious life-threatening cardiovascular emergency with high in-hospital mortality without aggressive clinical treatment. The study intended to identify the relationship between platelet (PLT) to platelet distribution width (PDW) ratio (PPR) and in-hospital mortality in postoperative patients with type A AAD. Methods: A total of 171 type A AAD patients were recruited in this retrospective study from January 2017 to December 2019. Receiver operating characteristics (ROC) were exploited to determine the best cut-off value of PPR, and then patients were sub-grouped into the low-PPR group and high-PPR group, according to the optimal value of PPR. Finally, univariate, and multivariate analyses were carried out to examine the prognostic value of PPR. Results: The value of PPR was 9.76, and the mortality was statistically higher in the low-PPR group than in the high-PPR group (29.1% vs. 6.0%, P < 0.01). The area under the ROC curve (AUC) of PPR was 0.724 (95% CI, 0.633-0.815; P < 0.001) with a 56.4% sensitivity and 80.6% specificity. Multivariate analysis showed that serum PPR was an independent factor associated with in-hospital mortality (hazard ratio (HR): 1.151; 95% confidence interval (CI): 1.035 -1.297; P = 0.010). Conclusion: Serum PPR can be used as an independent predictor of in-hospital mortality in postoperative patients with type A AAD.