OBJECTIVE: To assess the impact of albumin (Alb) administration on the prognosis of patients with acute kidney injury (AKI). METHODS: Clinical data of AKI patients in the intensive care unit (ICU) were retrospectively analyzed from the American Medical Information Mart of Intensive Care-IV (MIMIC-IV), including demographic data, acute physiology score (APS), comorbidities, vital signs, laboratory indicators, treatment status, ICU length of stay, and outcome indicators. The main outcome measure is ICU mortality. AKI patients were divided into Alb infusion group and Alb non infusion group based on whether they received Alb treatment. Multiple imputation was used to process missing data and eliminate variables that missing more than 30%. To ensure the stability of the results, propensity score matching (PSM) and inverse probability weighting (IPW) were used to correct the results. Using Kaplan-Meier survival curve and Cox proportional hazards regression model to evaluate the effect of Alb infusion on ICU survival rate in AKI patients. Perform subgroup analysis based on patient age, gender, and comorbidities to evaluate the prognostic effects of Alb on different patient subgroups. RESULTS: A total of 6 390 AKI patients were included, including 1 721 in the Alb infusion group and 4 669 in the Alb non infusion group. After adjusting for key covariates in the Cox regression model, compared with the Alb non infusion group, patients in the Alb infusion group were significantly younger in age, with APS III score, proportion of vasoactive drugs and continuous renal replacement therapy (CRRT) use, sepsis proportion, heart rate, respiratory frequency, aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine (Cr), lactic acid (Lac), and arterial partial pressure of carbon dioxide (PaCO₂) levels significantly higher. The proportion of hypertension, myocardial infarction, and congestive heart failure, as well as blood pressure, urine output, platelet count (PLT), and Alb levels were significantly lower. The results of univariate and multivariate Cox regression analysis on the raw data showed that the risk of death in the Alb infusion group was significantly lower than that in the Alb non infusion group [hazard ratio (HR) = 0.69, 95% confidence interval (95%CI) was 0.60-0.80, all P < 0.05]. The results after propensity score matching (PSM) and inverse probability weighting (IPW) processing are consistent with the original data trend (both P < 0.05). The Kaplan-Meier survival curve showed that the cumulative survival rate during ICU stay in the Alb infusion group was significantly higher than that in the Alb non infusion group (24.48% vs. 12.17%, Log-Rank test: χ² = 74.26, P < 0.05). Subgroup analysis shows that Alb infusion has a more significant survival benefit for AKI patients who use vasoactive drugs, have concurrent sepsis, and do not have liver disease. CONCLUSION Albumin infusion can decrease the ICU mortality of AKI patients.
Humans ; Retrospective Studies ; Acute Kidney Injury/mortality* ; Prognosis ; Male ; Female ; Middle Aged ; Aged ; Intensive Care Units ; Albumins/therapeutic use* ; Proportional Hazards Models ; Adult ; Databases, Factual

Objective To explore the correlation between serum homocysteine(Hcy),25-hydroxyvitamin D[25(OH)D]and frailty with type 2 diabites mellitus(T2DM)complicated with sarcopenia.Methods From September 2021 to March 2023,210 elderly T2DM patients were selected from the Department of Geriatrics of The First People's Hospital of Yunnan Province,and divided into simple T2DM(n=99)group,mild sarcopenia(M-Sar,n=59)group and severe sarcopenia(S-Sar,n=52)group.The"Elderly Comprehensive Assessment System"was used to evaluate subjects.The influencing factors of T2DM complicated with sarcopenia were analyzed by Logistic regression.The receiver operating characteristic(ROC)curve was used to analyze the predictive value of Hcy,25(OH)D combined with frailty in evaluating T2DM with sarcopenia.Results In T2DM,M-Sar and S-Sar groups,the age,Hcy,the risk rate of balance gait work falling and the rate of weakness increased in turn(P<0.05),while BMI,hemoglobin,25(OH)D,the rate of good nutrition,the normal rate of basic daily living,the low risk rate of falling,the rate of good balance gait function and the rate of no weakness decreased in turn(P<0.05).Logistic regression analysis showed that serum Hcy,frailty and 25(OH)D were the influencing factors of senile T2DM complicated with sarcopenia.Hcy,25(OH)D and frailty combined to predict T2DM with sarcopenia had an area under ROC carve of 0.815,with a sensitivity of 0.811 and a specificity of 0.717.Conclusions Serum Hcy,25(OH)D and frailty are closely related to T2DM combined with sarcopenia.Detection of Hcy and 25(OH)D combined with frailty score is helpful for early diagnosis of sarcopenia in primary hospitals.

Objective To explore the correlation between serum homocysteine(Hcy),25-hydroxyvitamin D[25(OH)D]and frailty with type 2 diabites mellitus(T2DM)complicated with sarcopenia.Methods From September 2021 to March 2023,210 elderly T2DM patients were selected from the Department of Geriatrics of The First People's Hospital of Yunnan Province,and divided into simple T2DM(n=99)group,mild sarcopenia(M-Sar,n=59)group and severe sarcopenia(S-Sar,n=52)group.The"Elderly Comprehensive Assessment System"was used to evaluate subjects.The influencing factors of T2DM complicated with sarcopenia were analyzed by Logistic regression.The receiver operating characteristic(ROC)curve was used to analyze the predictive value of Hcy,25(OH)D combined with frailty in evaluating T2DM with sarcopenia.Results In T2DM,M-Sar and S-Sar groups,the age,Hcy,the risk rate of balance gait work falling and the rate of weakness increased in turn(P<0.05),while BMI,hemoglobin,25(OH)D,the rate of good nutrition,the normal rate of basic daily living,the low risk rate of falling,the rate of good balance gait function and the rate of no weakness decreased in turn(P<0.05).Logistic regression analysis showed that serum Hcy,frailty and 25(OH)D were the influencing factors of senile T2DM complicated with sarcopenia.Hcy,25(OH)D and frailty combined to predict T2DM with sarcopenia had an area under ROC carve of 0.815,with a sensitivity of 0.811 and a specificity of 0.717.Conclusions Serum Hcy,25(OH)D and frailty are closely related to T2DM combined with sarcopenia.Detection of Hcy and 25(OH)D combined with frailty score is helpful for early diagnosis of sarcopenia in primary hospitals.

Objective To investigate the risk factors of 28-day mortality in septic patients and develop optimizing clinical prediction model based on machine learning algorithms.Methods Data from patients admitted to the department of intensive care unit(ICU)of the Affiliated Hospital of Nanjing University of Chinese Medicine from January 2019 to December 2023 were retrospectively analyzed.The data extracted included①gender,age,history of hypertension,diabetes,coronary heart disease,chronic obstructive pulmonary disease(COPD)and chronic kidney disease(CKD);②Vital signs and results of laboratory examination at admission were also collected,then acute physiology and chronic health evaluationⅡ(APACHEⅡ)score and sequential organ failure assessment(SOFA)score were calculated;③The other laboratory test results not included in APACHEⅡscore and SOFA score,such as blood lactate acid(Lac),alanine aminotransferase(AST),hemoglobin(Hb),procalcitonin(PCT),brian natriuretic peptide(BNP),C-reactive protein(CRP),activated partial thromboplastin time(APTT),D-dimer and troponin I(TNI)were also gathered.According to the 28-day survival,the patients were divided into a survival group and a death group.The difference of the clinical data and related loboratory indicators between the two groups of sepsis patients were compared.LASSO regression and Boruta algorithm were used to screen predictive variables.Models of Logistic regression(LG),neural network(NN)and light gradient boosting machine(LightGBM)were constructed.The data was divided into training set and verification set under a ratio of 7:3,and fivefold cross-validation was used to evaluate the stability of the models.Confusion matrix,receiver operator characteristic curve(ROC curve)and calibration curve were also used to assess the recognition ability and accuracy of three models.Decision curve analysis(DCA)was conducted to evaluate the models'utility in decision-making.Shapley additive explanations(SHAP)analysis was used to explain the best-performing model.Results A total of 426 patients were included in the study,of which 256 survived and 170 died.Compared with death group,the age(72.09±14.08 vs.76.88±11.32,P<0.05),COPD[11.33%(29/256)vs.20.00%(34/170)],CKD[20.31%(52/256)vs.31.77%(54/170)],Lac on admission[mmol/L:1.72(1.20,2.66)vs.2.25(1.60,3.50)],AST[U/L:32.00(18.00,59.75)vs.37.00(24.00,76.50)],CRP[mg/L:71.23(22.51,151.79)vs.87.00(37.00,173.36)],APACHEⅡscore(19.96±6.55 vs.22.83±6.92)and SOFA score[7(5,10)vs.9(5,12)]in surrial group were significantly decreased,the difference were statistically significant(all P<0.05).Age,APACHEⅡscore,Lac,PCT and CRP were revealed as independent predictors of 28-day mortality in sepsis by LASSO regression and Boruta algorithm,the above 5 variables were incorporated into the LG,NN and LightGBM models,and the five-fold cross-validation showed that the LightGBM model had the best stability.The confusion matrix,ROC curve and calibration curves of the 3 models were plotted,and the results showed that the F1 score of the 3 models were 0.61,0.63 and 0.74,respectively;area under the curve(AUC)was 0.68,0.74 and 0.87,respectively;the Log Loss was 0.62,0.41 and 0.34,respectively;and the Brier scores were 0.22,0.13 and 0.09,respectively,indicating that LightGBM model was optimal.DCA showed that LightGBM model had the greatest clinical net benefit.SHAP showed that the predicted results were in good agreement with the actual results.Conclusion The LightGBM model exhibited the best performance in predicting 28-day mortality in septic patients and has the potential to help clinicians identify high-risk patients and guide clinical decision-making.

Objective To investigate the risk factors of 28-day mortality in septic patients and develop optimizing clinical prediction model based on machine learning algorithms.Methods Data from patients admitted to the department of intensive care unit(ICU)of the Affiliated Hospital of Nanjing University of Chinese Medicine from January 2019 to December 2023 were retrospectively analyzed.The data extracted included①gender,age,history of hypertension,diabetes,coronary heart disease,chronic obstructive pulmonary disease(COPD)and chronic kidney disease(CKD);②Vital signs and results of laboratory examination at admission were also collected,then acute physiology and chronic health evaluationⅡ(APACHEⅡ)score and sequential organ failure assessment(SOFA)score were calculated;③The other laboratory test results not included in APACHEⅡscore and SOFA score,such as blood lactate acid(Lac),alanine aminotransferase(AST),hemoglobin(Hb),procalcitonin(PCT),brian natriuretic peptide(BNP),C-reactive protein(CRP),activated partial thromboplastin time(APTT),D-dimer and troponin I(TNI)were also gathered.According to the 28-day survival,the patients were divided into a survival group and a death group.The difference of the clinical data and related loboratory indicators between the two groups of sepsis patients were compared.LASSO regression and Boruta algorithm were used to screen predictive variables.Models of Logistic regression(LG),neural network(NN)and light gradient boosting machine(LightGBM)were constructed.The data was divided into training set and verification set under a ratio of 7:3,and fivefold cross-validation was used to evaluate the stability of the models.Confusion matrix,receiver operator characteristic curve(ROC curve)and calibration curve were also used to assess the recognition ability and accuracy of three models.Decision curve analysis(DCA)was conducted to evaluate the models'utility in decision-making.Shapley additive explanations(SHAP)analysis was used to explain the best-performing model.Results A total of 426 patients were included in the study,of which 256 survived and 170 died.Compared with death group,the age(72.09±14.08 vs.76.88±11.32,P<0.05),COPD[11.33%(29/256)vs.20.00%(34/170)],CKD[20.31%(52/256)vs.31.77%(54/170)],Lac on admission[mmol/L:1.72(1.20,2.66)vs.2.25(1.60,3.50)],AST[U/L:32.00(18.00,59.75)vs.37.00(24.00,76.50)],CRP[mg/L:71.23(22.51,151.79)vs.87.00(37.00,173.36)],APACHEⅡscore(19.96±6.55 vs.22.83±6.92)and SOFA score[7(5,10)vs.9(5,12)]in surrial group were significantly decreased,the difference were statistically significant(all P<0.05).Age,APACHEⅡscore,Lac,PCT and CRP were revealed as independent predictors of 28-day mortality in sepsis by LASSO regression and Boruta algorithm,the above 5 variables were incorporated into the LG,NN and LightGBM models,and the five-fold cross-validation showed that the LightGBM model had the best stability.The confusion matrix,ROC curve and calibration curves of the 3 models were plotted,and the results showed that the F1 score of the 3 models were 0.61,0.63 and 0.74,respectively;area under the curve(AUC)was 0.68,0.74 and 0.87,respectively;the Log Loss was 0.62,0.41 and 0.34,respectively;and the Brier scores were 0.22,0.13 and 0.09,respectively,indicating that LightGBM model was optimal.DCA showed that LightGBM model had the greatest clinical net benefit.SHAP showed that the predicted results were in good agreement with the actual results.Conclusion The LightGBM model exhibited the best performance in predicting 28-day mortality in septic patients and has the potential to help clinicians identify high-risk patients and guide clinical decision-making.

Objective:To investigate the effect of heat shock protein 60 (HSP60) overexpression on the ability of bone marrow mesenchymal stem cells (MSCs) and its therapeutic effect on rats with phosgene induced acute lung injury.Methods:HSP60 was transfected into MSCs by adenovirus. Western blot was used to measure the expressions of HSP60 before and after transfection. CCK-8 assay was used to detect the activity of MSCs, flow cytometry was used to detect the apoptotic ability of MSCs, and Transwell assay was used to observe the migration ability of MSCs. Sixty SPF grade male SD rats were randomly divided into control group, phosgene exposure group (inhalation of phosgene for 5 min) , MSCs group (phosgene exposure, MSCs treatment group) and transfected MSCs group (phosgene exposure, overexpression of HSP60 MSCs treatment group) . The pathological changes of lung were observed by lung pathological section, lung wet dry ratio, the degree of pulmonary edema, the total cell count and total protein content of alveolar lavage fluid, the inflammatory changes of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in BALF and serum were observed. The data were analyzed by Graphpad Prism 8.0 software. Paired comparisons were performed by non paired t-test. One way ANOVA was used for comparison between groups. Results:The proliferation ability of MSCs transfected with HSP60[ A= (0.69±0.05) ] was significantly higher than that of MSCs not transfected with HSP60[ A= (0.27±0.02) ] ( P<0.05) . Compared with the phosgene exposure group, the pulmonary edema and inflammatory factor infiltration of MSCs group and MSCs transfected group were reduced. However, compared with MSCs group, the degree of pulmonary edema in MSCs transfected group was significantly improved, the levels of inflammatory factors IL-6 and TNF-α were significantly decreased, and the total protein content and total cell count in bronchoalveolar lavage fluid were less ( P<0.05) . Conclusion:MSCs transfected with HSP60 can enhance the ability of proliferation, anti apoptosis, migration and the curative effect in rats with phosgene induced acute lung injury.

Objective:To investigate the effect of heat shock protein 60 (HSP60) overexpression on the ability of bone marrow mesenchymal stem cells (MSCs) and its therapeutic effect on rats with phosgene induced acute lung injury.Methods:HSP60 was transfected into MSCs by adenovirus. Western blot was used to measure the expressions of HSP60 before and after transfection. CCK-8 assay was used to detect the activity of MSCs, flow cytometry was used to detect the apoptotic ability of MSCs, and Transwell assay was used to observe the migration ability of MSCs. Sixty SPF grade male SD rats were randomly divided into control group, phosgene exposure group (inhalation of phosgene for 5 min) , MSCs group (phosgene exposure, MSCs treatment group) and transfected MSCs group (phosgene exposure, overexpression of HSP60 MSCs treatment group) . The pathological changes of lung were observed by lung pathological section, lung wet dry ratio, the degree of pulmonary edema, the total cell count and total protein content of alveolar lavage fluid, the inflammatory changes of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in BALF and serum were observed. The data were analyzed by Graphpad Prism 8.0 software. Paired comparisons were performed by non paired t-test. One way ANOVA was used for comparison between groups. Results:The proliferation ability of MSCs transfected with HSP60[ A= (0.69±0.05) ] was significantly higher than that of MSCs not transfected with HSP60[ A= (0.27±0.02) ] ( P<0.05) . Compared with the phosgene exposure group, the pulmonary edema and inflammatory factor infiltration of MSCs group and MSCs transfected group were reduced. However, compared with MSCs group, the degree of pulmonary edema in MSCs transfected group was significantly improved, the levels of inflammatory factors IL-6 and TNF-α were significantly decreased, and the total protein content and total cell count in bronchoalveolar lavage fluid were less ( P<0.05) . Conclusion:MSCs transfected with HSP60 can enhance the ability of proliferation, anti apoptosis, migration and the curative effect in rats with phosgene induced acute lung injury.

Objective To probe into the role of nursing classification and marking management in ICU nursing management. Methods According to the admission date,the first 87 patients hospitalized in our department were assigned into the control group and another 84 into the intervention group.Then the human resources were divided based on the ABCD nursing classification and marking management for ICU.The two groups were compared in terms of adverse events.Results The incidences of pressure sores, non-planned extubation,improper clinostatism for using respirator,hypoglucycaemia during reinforced treatment with insulin, respirator-associated pulmonary pneumonia,tube-associated infection,and multidrug resistant bacteria in the intervention group were all significantly lower than those in the control group (allP<0.05).Conclusion The nursing classification and marking management for ICU nursing management can enhance the nursing quality.

Objective To observe the effect of intelligent trunk intensive training on motor and balance for patients with stroke. Methods 80 stroke patients were divided into treatment group (n=40) and control group (n=40) randomly. Both groups accepted routine rehabilitation,and the treatment group accepted intelligence trunk intensive training in addition for 6 weeks. They were assessed with Rivermead Movement Index (RMI), the Berg Balance Scale (BBS), Sheikh trunk control ability evaluation before and after treatment. Results All the scores improved after treatment in both groups (P<0.001), and improved more in the treatment group than in the control group (P<0.001).The score of trunk control positively correlated with the score of RMI and BBS respectively (r=0.576, r=0.592, P<0.05). Conclusion Intelligent trunk intensive training can further improve the motor and balance of patients with stroke.