[Establishing a prognostic prediction model for patients with septic shock based on the completion time of fluid resuscitation and the negative fluid balance volumes].

OBJECTIVE: To explore the relationship between the completion time of fluid resuscitation as well as negative fluid balance volumes and the prognosis of patients with septic shock, and to try to construct a prediction model based on the completion time of fluid resuscitation and negative fluid balance volumes, and to verify the predictive efficacy of the model on the prognosis of patients with septic shock. METHODS: Patients with septic shock admitted to Wuxi People's Hospital from April 2020 to April 2023 were selected. The general data (gender, age, body mass index, infection site), pathological indicators on admission, the difference of acute physiology and chronic health evaluation II (APACHE II) and sequential organ failure assessment (SOFA) between admission and 24 hours after fluid resuscitation, the completion time of fluid resuscitation and negative fluid balance volume were recorded. Multivariate Logistic analysis was used to screen the influencing factors of the prognosis of patients with septic shock, and a nomogram model was established. Bootstrap method was used for internal validation of the model. The consistency index, calibration curve and receiver operator characteristic curve (ROC curve) were used to evaluate the accuracy and prediction efficiency of the model. RESULTS: A total of 96 patients with septic shock were enrolled, 38 patients died and 58 patients survived at 28 days. Compared with the survival group, the difference of APACHE II score, SOFA score, the proportion of fluid resuscitation completed within 1 to 3 hours, and the proportion of negative fluid balance volume -500 to -250 mL per day in the death group were lower, and the differences were statistically significant (all P < 0.05). Multivariate Logistic analysis showed that the completion time of fluid resuscitation was a risk factor for the prognosis of patients with septic shock [odds ratio (OR) = 26.285, 95% confidence interval (95%CI) was 9.984-76.902, P < 0.05]. The difference of APACHE II score (OR = 0.045, 95%CI was 0.015-0.131), SOFA score (OR = 0.056, 95%CI was 0.019-0.165) between admission and 24 hours after fluid resuscitation, and negative fluid balance volume (OR = 0.043, 95%CI was 0.015-0.127) were protective factors for the prognosis of patients with septic shock (all P < 0.05). The model validation results showed that the consistency index was 0.681 (95%CI was 0.596-0.924), indicating good discrimination. The calibration curve showed that the calibration curve fitted well with the ideal curve. The ROC curve showed that the sensitivity of the nomogram model for predicting the death of patients with septic shock was 83.7%, the specificity was 97.2%, and the area under the ROC curve (AUC) was 0.931 (95%CI was 0.846-0.985), indicating that the model had good prediction efficiency. CONCLUSIONS: The completion time of fluid resuscitation and negative fluid balance volumes are related to the prognosis of septic shock patients, and the alignment diagram model improve the identification of the risk of death in septic shock patients.

[Ultrasound cardiac output monitor and thermodilution for cardiac function monitoring in critical patients: a Meta-analysis].

OBJECTIVE: To assess the differences between ultrasound cardiac output monitor (USCOM) and thermodilution (TD) systematically in cardiac function monitoring of critically ill patients. METHODS: The Chinese and English literatures about the clinical trials which using USCOM and TD to monitor cardiac function published in CNKI, Wanfang database, China biomedical literature database, VIP database, China Clinical Trial Registration Center, PubMed, Embase and Cochrane Library were searched by computer from the establishment to December 2018. Some indicators, like cardiac output (CO), cardiac index (CI), stroke volume (SV) and other parameters were used to evaluate cardiac function. Literature search, quality evaluation and data extraction were conducted independently by two authors. The tailored Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used for literature quality evaluation. EndNote X6 was used for literature screening and management. RevMan 5.3 was used for Meta-analysis. Funnel chart analysis was used for publication bias. RESULTS: A total of 26 studies involving 772 patients were included. Among them, there were 5 literatures found that the agreements of cardiac function between the USCOM and TD methods were poor. Meta-analysis showed that there was no significant difference between the two methods in CO and CI monitoring [CO: mean difference (MD) = -0.06, 95% confidence interval (95%CI) was -0.17 to 0.05, P = 0.31; CI: MD = -0.04, 95%CI was -0.13 to 0.05, P = 0.38]. Subgroup analysis of different TD methods [pulmonary artery catheter (PAC), pulse indicator continuous cardiac output (PiCCO)] and different windows of USCOM ultrasonic probe [aorta (AA), pulmonary artery (PA)] in CO monitoring was not shown significant difference yet (PAC: MD = -0.07, 95%CI was -0.18 to 0.04, P = 0.23; PiCCO: MD = 0.09, 95%CI was -0.31 to 0.50, P = 0.65; AA windows: MD = -0.14, 95%CI was -0.31 to 0.02, P = 0.09; PA windows: MD = -0.00, 95%CI was -0.15 to 0.14, P = 0.95; AA/PA windows: MD = 0.23, 95%CI was -0.40 to 0.86, P = 0.47). However, the difference in SV was statistically significant between the USCOM and TD method (MD = 1.48, 95%CI was 0.04 to 2.92, P = 0.04). Funnel chart showed that the literature distribution of CO and CI monitoring were basically symmetrical, indicating that the bias of literature publication is small. CONCLUSIONS: USCOM has good consistency with TD method in monitoring the cardiac function parameters of CO and CI, and different windows of ultrasonic probe of USCOM have no significant influence on the monitoring results, but there is significant difference in the consistency of the two methods in SV monitoring.