To investigate the clinical characteristics and prognosis of patients with diabetic ketoacidosis （DKA） combined with acute pancreatitis （AP），and to explore their predictive value for DKA combined with AP.
Methods
A total of 63 patients with DKA who were admitted to the Department of Critical Care Medicine of the Affiliated Hospital of Zunyi Medical University from January 2017 to April 2023 were enrolled.According to whether AP was combined，they were divided into a DKA group （40 cases） and a DKA + AP group （23 cases），and the clinical data and prognostic characteristics of the two groups were compared.Multivariate logistic regression analysis was used to evaluate the risk factors of DKA combined with AP； the receiver operating characteristic （ROC） curve was used to analyze their predictive value for DKA combined with AP and the area under the curve （AUC） was compared.
Results
There were statistically significant differences in diabetes diagnosis，C-reactive protein，triglyceride，serum potassium （K +），serum chloride （Cl -），non-invasive ventilator use，total hospitalization cost，and all-cause readmission within 3 months between the two groups （all P ＜0.05）.Compared with the DKA group，the DKA + AP group had more patients with unknown previous diabetes mellitus and fewer patients with type 1 diabetes （both P ＜0.017）.Multivariate logistic regression analysis showed that K+ ［odds ratio （OR）=0.134，95% confidence interval （CI）（0.028，0.645），P = 0.012］ was a protective factor for DKA combined with AP，while triglyceride was a risk factor ［OR=1.918，95%CI （1.229，2.994），P=0.004］.ROC analysis showed that the AUC of K+ was 0.697 ［95%CI （0.559，0.835），P=0.010］，the sensitivity was 0.739，the specificity was 0.650，and the cut-off value was 3.880 mmol/L.The AUC of triglyceride was 0.878 ［95%CI （0.786，0.970），P ＜0.001］，the sensitivity was 0.957，the specificity was 0.675，and the cut-off value was 1.940 mmol / L.The AUC of triglyceride for predicting DKA combined with AP was higher than that of K+ （Z=1.964，P=0.049）.
Conclusions
Patients with an unknown history of diabetes mellitus are more likely to have AP when DKA occurs.High triglycerides are risk factors for DKA combined with AP and thus have some value in predicting the concurrent AP in patients with DKA.
To investigate the incidence of enteral nutrition feeding intolerance（FI） in elderly critically ill patients，analyze its risk factors，and construct and validate a risk prediction nomogram.
Methods
Data of elderly critically ill patients admitted to the ICU of Jiangyin Clinical Medical College Affiliated to Jiangsu University between January and December 2023 were collected.Patients were divided into modeling and validation datasets.Univariate analysis and binary logistic regression were used to build the risk prediction model.The receiver operating characteristic （ROC） curve was employed to assess the model fit and determine the cut-off value.Sensitivity and specificity of the validation dataset were calculated.The R software "rms" package was applied to convert the prediction model formula into a nomogram.
Results
The modeling dataset included 316 patients，with an FI incidence of 42.4% （134/316）.Among those FI patients，88.8% （119 /134） occurred FI within 1-5 days after initiating enteral nutrition.Binary logistic regression identified age ［odds ratio （OR） = 1.107，95%confidence interval （CI） （1.073，1.141），P ＜0.001］，acute physiology and chronic health evaluation（APACHE） II ［OR = 1.056，95%CI （1.025，1.089），P ＜0.001］，albumin ［OR = 0.921，95%CI（0.874，0.971），P=0.002］，and high positive end-expiratory pressure （PEEP） ［OR = 3.366，95%CI（1.752，6.466），P ＜0.001］ as independent risk factors for FI during enteral nutrition in elderly critically ill patients.The prediction model formula was as follows： Z = -6.692 + 0.102 × age +0.055×APACHE II score-0.082×albumin+1.214×high PEEP （0，1）.Internal validation showed an area under the curve （AUC） of 0.884，sensitivity of 92.0%，and specificity of 54.4%.External validation yielded an AUC of 0.757，sensitivity of 78.1%，and specificity of 75.6%.
Conclusions
The incidence of FI in elderly critically ill patients is high.The constructed nomogram demonstrates strong predictive performance for FI，aiding clinicians in risk assessment and prognosis improvement during enteral nutrition.
To investigate the efficacy of hematopoietic stem cell transplantation （HSCT） in the treatment of acute leukemia and to analyze the factors affecting its recurrence.
Methods
A total of 172 acute leukemia patients admitted to the Hebei Yanda Ludaopei Hospital from August 2020 to August 2022 were selected as study subjects.According to different treatment methods，they were divided into an observation group and a control group，each with 86 cases.The observation group was treated with autologous hematopoietic stem cell transplantation （auto-HSCT），and the control group was treated with allogeneic hematopoietic stem cell transplantation （allo-HSCT）.The clinical data，therapeutic effect and recurrence rate of the two groups were compared.Patients were followed up for 1 year and divided into a recurrence group （38 cases） and a non-recurrence group （134 cases）according to their recurrence status.A generalized estimating equation （GEE） model was used to analyze the factors affecting the recurrence of patients.Then a prediction model was established and verified based on the influencing factors.
Results
The remission rate of the observation group was significantly higher than that of the control group ［96.51%（83 / 86） vs.88.37% （76/86），χ2=4.077，P=0.043］，while the recurrence rate was lower ［13.95% （12/86） vs.30.23% （26/86），χ2=6.621，P=0.010］.Through GEE model analysis，it was found that gender（male），age ＞45 years old，lymphocyte count ≤3 × 109/ L，white blood cell count ＞40 × 109/ L，platelet count ≤200×109/L，monocyte count ＞3 × 108/kg，CD34+ cell count ＞3 × 106/kg and type of acute leukemia （acute lymphoblastic leukemia） were risk factors for recurrence of acute leukemia （all P ＜0.05）.The regression equation was as follows： P = 1 /［1 + exp （0.835 + male ×1.032+age ＞45 years old×0.921+lymphocyte count ≤3×109/L×1.103+white blood cell count ＞40×109/L×0.503+platelet count ≤200×109/L×0.883+monocyte count ＞3 ×108/kg×0.868+CD34+ cell count ＞3 × 106 / kg × 0.799 + acute lymphoblastic leukemia × 1.013）］； the predicted model agreement rate was 82.56%.
Conclusions
HSCT is effective in the treatment of acute leukemia.Compared with allo-HSCT，auto-HSCT has higher remission rate and lower recurrence rate.Relapse is affected by many factors，and the prediction model can provide clinical decision support.
To investigate the expression levels of serum angiopoietin-like protein 4 （ANGPTL-4） and syndecan-1 （SDC-1） in neonatal respiratory distress syndrome （NRDS）and their value in prognostic assessment.
Methods
A total of 135 children with NRDS admitted to Hainan Hospital，Shanghai Children's Medical Center，Shanghai Jiao Tong University School of Medicine from January 2022 to March 2024 were divided into a survival group （120 cases） and a death group （15 cases） according to their survival conditions within 28 days，and 60 healthy newborns born in the same period were selected as a control group.General information and levels of serum ANGPTL-4 and SDC-1 were detected in all subjects.According to the oxygenation index （OI），the children with NRDS were divided into a mild group （44 cases，4 mmHg ≤OI ＜8 mmHg），a moderate group （60 cases，8 mmHg ≤OI ＜16 mmHg），and a severe group （31 cases，OI ≥16 mmHg）.The receiver operating characteristic （ROC） curve was drawn to analyze the value of serum ANGPTL-4 and SDC-1 levels in predicting NRDS death.Pearson correlation was used to analyze the correlation between serum ANGPTL-4 and SDC-1 levels and clinical indexes in NRDS.
Results
The levels of serum ANGPTL-4 and SDC-1 of children among three groups were statistically significantly different （F = 29.716，34.825； both P ＜0.001），and they were significantly higher in the death group than in the survival group （both P ＜0.05）.The levels of serum ANGPTL-4 and SDC-1 in the control group，mild group，moderate group，and severe group were compared，and the differences were statistically significant （F = 21.615，27.318； both P ＜0.001）； they were significantly higher in the severe group than in the mild and moderate groups （all P ＜0.05）.The ROC curve showed that the combination of ANGPTL-4（326.40 μg/L） and SDC-1 （373.18 μg/L） had the largest area under the curve （AUC） ［AUC=0.938，95% confidence interval （CI） （0.879，0.991）］ for determining mortality in NRDS children，with a sensitivity of 96.8% and a specificity of 80.3%.Pearson correlation analysis showed that the levels of serum ANGPTL-4 and SDC-1 in NRDS were positively correlated with interlukin-6（IL-6） （r=0.451，0.527； P = 0.005，＜0.001），IL-17 （r = 0.736，0.815； both P ＜0.001），IL-33 （r =0.784，0.773； both P ＜0.001），acute physiology and chronic health evaluation （APACHE） II score（r = 0.704，0.682； P = 0.006，＜0.001），and score for neonatal acute physiology with perinatal extension （SNAPPE） II （r=0.663，0.718； both P ＜0.001）.
Conclusion
The increase of serum ANGPTL-4 and SDC-1 levels is related to the severity of NRDS，and has good value in predicting its prognosis.
To systematically review the risk prediction models for incontinenceassociated dermatitis （IAD） in ICU patients.
Methods
The databases of CNKI，Wanfang，VIP，CBM，PubMed，Embase，Web of Science and the Cochrane Library were searched for the literature on risk prediction models for IAD in ICU patients published up to July 23，2023.Two researchers independently screened the literature，extracted relevant data，and evaluated the risk of bias and applicability of involved literature.Meta-analysis of the predictive value of predictors in the model was performed using Revman5.4.
Results
A total of eight studies were involved，including six model development studies and two external validation studies for the perineal assessment tool （PAT）.Six studies used logistic regression models，two used external validation，and three used internal validation.The area under the receiver operating characteristic curve of the involved models ranged from 0.795 to 0.974.Meta-analysis showed that serum albumin ［odds ratio （OR） = 2.45，95% confidence interval （CI） （1.68，3.59），Z = 4.62，P ＜0.001］，fever （body temperature ≥38 ℃） ［OR=2.29，95%CI （1.39，3.79），Z=3.23，P=0.001］，loose stools ［OR=6.93，95%CI （4.50，10.65），Z=8.81，P ＜0.001］ and PAT ［OR=2.56，95%CI （1.23，5.30），Z = 2.53，P = 0.01］ were influential factors for the risk of IAD in ICU patients.
Conclusions
The existing predictive models for IAD in ICU patients are not ideal，as they exhibit bias in the development，design，statistical analysis and reporting.In the future，model validation and updates should be conducted to improve their performance through large-scale and multi-center studies.
