Urinary paraquat concentration and white blood cell count as prognostic factors in paraquat poisoning

Purpose: To investigate the effect of white blood cell (WBC) and urinary paraquat (PQ) levels on prognostic factors in patients exposed to PQ intoxication using multivariate logistic regression analysis.Methods: A total of 104 subjects intoxicated with PQ between December 2015 and July 2016 were used in this retrospective study. They comprised patients who survived (n = 78), and patients who died (n = 26). Clinical features and prognostic parameters were analyzed in both groups. Multivariate logistic regression analysis was used to establish a prognostic correlation model based on results from single factor variables.Results: Comparison of demographic and clinical attributes between the two groups, survivors (n = 78) and non-survivors (n = 26), revealed that those who survived were not as old (33.3 ± 9.9 years) as nonsurvivors (41.5 ± 12.9 years). In addition, on admission, it was found that the survivors ingested lower amounts of PQ (31.6 ± 13.8 ml) than non-survivors (67.88 ± 31.2 ml). There were significant differences between the two groups with respect to WBC, neutrophils, lymphocytes, lactate dehydrogenase (LDH), creatine kinase (CK), amylase, uric acid (UA), pH, partial pressure of oxygen (PaO2), base excess (BE), lactic acid, and D-dimer levels (p < 0.05).Conclusion: WBC and urine PQ concentration have strong correlation with prognostic factors in PQ poisoning.Keywords: Paraquat intoxication, Dithionite test, Multivariate logistic analysis, Prognosis, Predictor

Estimated plasma volume status as a simple and accessible predictor of 28-day mortality in septic shock: insights from a retrospective study of the MIMIC-IV database

BackgroundAssessing volume status in septic shock patients is crucial for tailored fluid resuscitation. Estimated plasma volume status (ePVS) has emerged as a simple and effective tool for evaluating patient volume status. However, the prognostic value of ePVS in septic shock patients remains underexplored.MethodsThe study cohort consisted of septic shock patients admitted to the ICU, sourced from the MIMIC-IV database. Patients were categorized into two groups based on 28-day survival outcomes, and their baseline characteristics were compared. According to the ePVS (6.52 dL/g) with a hazard ratio of 1 in the restricted cubic spline (RCS) analysis, patients were further divided into high and low ePVS groups. A multivariable Cox regression model was utilized to evaluate the association between ePVS and 28-day mortality rate. The Kaplan–Meier survival curve was plotted, and all-cause mortality was compared between the high and low groups using the log-rank test.ResultsA total of 7,607 septic shock patients were included in the study, among whom 2,144 (28.2%) died within 28 days. A J-shaped relationship was observed between ePVS at ICU admission and 28-day mortality, with an increase in mortality risk noted when ePVS exceeded 6.52 dL/g. The high ePVS group exhibited notably higher mortality rates compared to the low ePVS group (28-day mortality: 26.2% vs. 30.2%; 90-day mortality: 35% vs. 42.3%). After adjustment for confounding factors, ePVS greater than 6.52 dL/g independently correlated with an increased risk of 28-day mortality (HR: 1.20, 95% CI: 1.10–1.31, p < 0.001) and 90-day mortality (HR: 1.25, 95% CI: 1.15–1.35, p < 0.001). Kaplan–Meier curves demonstrated a heightened risk of mortality associated with ePVS values exceeding 6.52 dL/g.ConclusionA J-shaped association was observed between ePVS and 28-day mortality in septic shock patients, with higher ePVS levels associated with increased risk of mortality

STUDY ON ANFIS CONTROL STRATEGY OF ENGINEERING VEHICLE SEAT SUSPENSION (MT)

Taking the seat vibration system of a certain type of engineering vehicle as an object, using the characteristics of adaptive network-based fuzzy inference system（ANFIS） self-learning and fuzzy reasoning, a semiactive control method of seat suspension vibration based on ANFIS was proposed, which solved the problem of excessive seat vibration in the working process of engineering vehicles. Firstly, the vibration process of the seat suspension of engineering vehicles was analyzed, and the dynamic model of the seat suspension was established. Then, the fuzzy neural control system of seat suspension was designed by adding feed-forward and feedback links. Finally, the control effects of different vibration excitation frequencies, different controller control objects and the input of measured seat signals were observed respectively. The results show that the fuzzy neural control system reduces the vibration energy and frequency of the seat, and the root mean square value of the seat vibration displacement is 52% to 66% of the passive suspension seat