Objective:We try to screen out predictive indicators with higher value by analyzing the differences in clinical and laboratory indicators between severe fever with thrombocytopenia syndrome (SFTS) patients in the intensive care unit (ICU) group and non-ICU group.Methods:The clinical and laboratory index data of 69 SFTS patients diagnosed in the laboratory in a hospital from June to December 2019 were retrospectively collected. According to the clinical outcome of the patients, they were divided into ICU and non-ICU groups. The differences in clinical manifestations and laboratory indicators between the two groups were analyzed. The receiver operating characteristic curve (ROC) was used to screen the more valuable predictive indicators.Results:Compared with the non-ICU group, ICU group SFTS patients had significantly higher procalcitonin (PCT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), glutamyl transpeptidase (GGT), leucine aminopeptidase (LAP), glutamate dehydrogenase (GDH), adenosine deaminase (ADA), cystatin C (Cys C), α-hydroxybutyrate dehydrogenase (α-HBDH), creatine kinase (CK), lactate dehydrogenase (LDH) levels ( W=530.0, P=0.003; W=496.5, P=0.015; W=496.0, P=0.015; W=535.5, P=0.002; W=545.5, P=0.001; W=498.5, P=0.013; W=537.0, P=0.002; W=523.0, P=0.004; W=512.0, P=0.007; W=502.0, P=0.012; W=486.0, P=0.023; W=509.0, P=0.008; W=541.0, P=0.002) and significantly lower platelet count (PLT), indirect bilirubin (IBIL), albumin/globulin ratio(A/G) and superoxide dismutase (SOD) levels ( W=199.0, P=0.024; W=175.5.5, P=0.009; t=-2.9, P=0.004; W=209.5, P=0.036; t=-3.0, P=0.004). ROC result showed that ALP [area under the curve (AUC)=0.804, 95% confidence interval ( CI) (0.679~0.929)] and LDH [AUC=0.805, 95% CI (0.680~ 0.930)] have a higher value for predicting the risk of severe illness. Conclusions:Abnormal liver function, heart function, and renal function indicators in SFTS patients indicate that patients are at risk of exacerbation. Among them, ALP and LDH levels have higher predictive value for risk of severe disease, suggesting that the monitoring of patients with the above symptoms should be strengthened in the clinical nursing process.

Patients with acute heart failure (AHF) often experience dyspnea, and monitoring and quantifying their breathing patterns can provide reference information for disease and prognosis assessment. In this study, 39 AHF patients and 24 healthy subjects were included. Nighttime chest-abdominal respiratory signals were collected using wearable devices, and the differences in nocturnal breathing patterns between the two groups were quantitatively analyzed. Compared with the healthy group, the AHF group showed a higher mean breathing rate (BR_mean) [(21.03 ± 3.84) beat/min vs. (15.95 ± 3.08) beat/min, P < 0.001], and larger R_RSBI_cv [70.96% (54.34%-104.28)% vs. 58.48% (45.34%-65.95)%, P = 0.005], greater AB_ratio_cv [(22.52 ± 7.14)% vs. (17.10 ± 6.83)%, P = 0.004], and smaller SampEn (0.67 ± 0.37 vs. 1.01 ± 0.29, P < 0.001). Additionally, the mean inspiratory time (TI_mean) and expiration time (TE_mean) were shorter, TI_cv and TE_cv were greater. Furthermore, the LBI_cv was greater, while SD1 and SD2 on the Poincare plot were larger in the AHF group, all of which showed statistically significant differences. Logistic regression calibration revealed that the TI_mean reduction was a risk factor for AHF. The BR_ mean demonstrated the strongest ability to distinguish between the two groups, with an area under the curve (AUC) of 0.846. Parameters such as breathing period, amplitude, coordination, and nonlinear parameters effectively quantify abnormal breathing patterns in AHF patients. Specifically, the reduction in TI_mean serves as a risk factor for AHF, while the BR_mean distinguishes between the two groups. These findings have the potential to provide new information for the assessment of AHF patients.
Humans ; Heart Failure/diagnosis* ; Prognosis ; Respiration ; Wearable Electronic Devices ; Acute Disease