Objective To investigate the effect of enteral nutrition (EN) start time on pH value of gastric juice and ventilator-associated pneumonia (VAP) in critically ill patients with invasive mechanical ventilation, so as to provide reference for the rational selection of EN timing.Methods Patients with mechanical ventilation who underwent EN treatment admitted to the intensive care unit (ICU) of the First Affiliated Hospital of Zhengzhou University from January 1st, 2016 to November 30th, 2017 were enrolled, and the inclusion criteria were age ≥ 18 years, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) ≤ 15, and nutritional risk screening (NRS 2002) ≥ 3. Patients were divided into two groups according to the start time of EN: early EN group (implementation of EN within 48 hours after mechanical ventilation) and late EN group (implementation of EN after 48 hours after mechanical ventilation). The pH value of gastric juice, VAP incidence, mechanical ventilation time, and the length of ICU stay were compared between the two groups.Results A total of 108 patients were included, 54 in the early EN group and 54 in the late EN group respectively. The pH value of gastric juice in early EN group was lower than that in late EN group [4.8 (3.8, 5.8) vs. 5.6 (4.6, 6.6),P < 0.01]. There were 8 patients with VAP in the early EN group, 3 of whom were early onset VAP. There were 17 patients with VAP in the late EN group, 10 of whom were early onset VAP. The incidence of VAP and the incidence of premature VAP in the early EN group were significantly lower than those in the late EN group (14.8％ vs. 31.5％, 5.6％ vs. 18.5％, bothP < 0.05). The mechanical ventilation time [days: 7.5 (5.7, 9.0) vs. 8.6 (6.8, 10.7) and the length of ICU stay [days: 10.0 (8.5, 11.7) vs. 11.0 (9.5, 12.6)] in the early EN group were significantly shorter than those in the late EN group (allP < 0.05).Conclusion At the same time of protecting gastric mucosa, early EN is helpful to reduce the incidence of VAP, reduce the duration of mechanical ventilation and the length of ICU stay, and improve the prognosis.

Objective:To establish a predictive model for the progression of acute kidney injury (AKI) to stage 3 AKI (renal failure) in the intensive care unit (ICU), so as to assist physicians to make early and timely decisions on whether to intervene in advance.Methods:A retrospective analysis was conducted. Thirty-eight patients with AKI admitted to the intensive care medicine of the Third People's Hospital of Henan Province from January 2018 to May 2023 were enrolled. Patient data including acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) upon admission, serum creatinine (SCr), blood urea nitrogen (BUN), daily urine output during hospitalization, and the timing of continuous renal replacement therapy (CRRT) intervention were recorded. Based on clinically collected pathological data, standardized creatinine value ratio mean polynomial fitting models were established as the first criterion for judging the progression to stage 3 AKI after data cleansing, screening, and normalization. Additionally, standardized creatinine value ratio index fitting models were established as the second criterion for predicting progression to stage 3 AKI.Results:A total of 38 AKI patients were included, including 25 males and 13 females. The average age was (58.45±12.94) years old. The APACHEⅡ score was 24.13±4.17 at admission. The intervention node was (4.42±0.95) days. Using a dual regression model approach, statistical modeling was performed with a relatively small sample size of statistical data samples, yielding a scatter index non-linear regression model for standardized creatinine value ratio data relative to day " n", with y = 1.246?2 x1.164?9 and an R2 of 0.860?1, indicating reasonable statistical fitting. Additionally, a quadratic non-linear regression model was obtained for the mean standardized creatinine value ratio relative to day " n", with y = -0.260?6 x2+3.010?7 x-1.612 and an R2 of 0.998?9, indicating an excellent statistical fit. For example, using a baseline SCr value of 66 μmol/L for a healthy individual, the dual regression model predicted that the patient would progress to stage 3 AKI within 3-5 days. This prediction was consistent when applied to other early intervention renal injury patients. Conclusion:The established model effectively predicts the time interval of the progression of AKI to stage 3 AKI (renal failure), which assist intensive care physicians to intervene AKI as early as possible to prevent disease progression.