Objective:To investigate the prognostic value of early serum lactate, albumin, and lactate/albumin ratio (L/A) on the 28-day prognosis of adult patients with sepsis.Methods:A retrospective cohort study was conducted among adult patients with sepsis admitted to the First Affiliated Hospital of Xinjiang Medical University from January to December in 2020. Gender, age, comorbidities, lactate within 24 hours of admission, albumin, L/A, interleukin-6 (IL-6), procalcitonin (PCT), C-reactive protein (CRP) and 28-day prognosis were recorded. The receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of lactate, albumin and L/A for 28-day mortality in patients with sepsis. Subgroup analysis of patients was performed according to the best cut-off value, Kaplan-Meier survival curves were drawn, and the 28-day cumulative survival of patients with sepsis was analyzed.Results:A total of 274 patients with sepsis were included, and 122 patients died at 28 days, with a 28-day mortality of 44.53%. Compared with the survival group, the age, the proportion of pulmonary infection, the proportion of shock, lactate, L/A and IL-6 in the death group were significantly increased, and albumin was significantly decreased [age (years): 65 (51, 79) vs. 57 (48, 73), pulmonary infection: 75.4% vs. 53.3%, shock: 37.7% vs. 15.1%, lactate (mmol/L): 4.76 (2.95, 9.23) vs. 2.21 (1.44, 3.19), L/A: 0.18 (0.10, 0.35) vs. 0.08 (0.05, 0.11), IL-6 (ng/L): 337.00 (97.73, 2 318.50) vs. 55.88 (25.26, 150.65), albumin (g/L): 27.68 (21.02, 33.03) vs. 29.62 (25.25, 34.23), all P < 0.05]. The area under the ROC curve (AUC) and 95% confidence interval (95% CI) of lactate, albumin, and L/A were 0.794 (95% CI was 0.741-0.840), 0.589 (95% CI was 0.528-0.647), 0.807 (95% CI was 0.755-0.852) for predicting 28-day mortality in sepsis patients. The optimal diagnostic cut-off value of lactate was 4.07 mmol/L, the sensitivity was 57.38%, the specificity was 92.76%. The optimal diagnostic cut-off value of albumin was 22.28 g/L, the sensitivity was 31.15%, the specificity was 92.76%. The optimal diagnostic cut-off of L/A was 0.16, the sensitivity was 54.92%, and the specificity was 95.39%. Subgroup analysis showed that the 28-day mortality of sepsis patients in the L/A > 0.16 group was significantly higher than that in the L/A ≤ 0.16 group [90.5% (67/74) vs. 27.5% (55/200), P < 0.001]. The 28-day mortality of sepsis patients in the albumin ≤ 22.28 g/L group was significantly higher than that in the albumin > 22.28 g/L group [77.6% (38/49) vs. 37.3% (84/225), P < 0.001]. The 28-day mortality in the group with lactate > 4.07 mmol/L was significantly higher than that in the group with lactate ≤ 4.07 mmol/L [86.4% (70/81) vs. 26.9% (52/193), P < 0.001]. The three were consistent with the analysis results of Kaplan-Meier survival curve. Conclusion:The early serum lactate, albumin, and L/A were all valuable in predicting the 28-day prognosis of patients with sepsis, and L/A was better than lactate and albumin.

Objective:The predictive model of cardiac arrest in the emergency room was constructed and validated based on Logistic regression.Methods:This study was a retrospective cohort study. Patients admitted to the emergency room of the First Affiliated Hospital of Xinjiang Medical University from January 2020 to July 2021 were included. The general information, vital signs, clinical symptoms, and laboratory examination results of the patients were collected, and the outcome was cardiac arrest within 24 hours. The patients were randomly divided into modeling and validation group at a ratio of 7:3. LASSO regression and multivariable logistic regression were used to select predictive factors and construct a prediction model for cardiac arrest in the emergency room. The value of the prediction model was evaluated using the area under the receiver operator characteristic curve (AUC), calibration curve, and decision curve analysis (DCA).Results:A total of 784 emergency room patients were included in the study, 384 patients occurred cardiac arrest. The 10 variables were ultimately selected to construct a risk prediction model for cardiac arrest: Logit( P)= -4.503+2.159×modified early warning score (MEWS score)+2.095×chest pain+1.670×abdominal pain+ 2.021×hematemesis+2.015×cold extremities+5.521×endotracheal intubation+0.388×venous blood lactate-0.100×albumin+0.768×K ++0.001×D-dimer. The AUC of the model group was 0.984 (95% CI: 0.976-0.993) and that of the validation group was 0.972 (95% CI: 0.951-0.993). This prediction model demonstrates good calibration, discrimination, and clinical applicability. Conclusions:Based on the MEWS score, chest pain, abdominal pain, hematemesis, cold extremities, tracheal intubation, venous blood lactate, albumin, K +, and D-dimer, a predictive model for cardiac arrest in the in-hospital emergency room was constructed to predict the probability of cardiac arrest in emergency room patients and adjust the treatment strategy in time.