[Objective] To validate and optimize the platelet transfusion refractoriness (PTR) prediction model for patients with hematological disorders established by our center. [Methods] The data of patients with hematological diseases who received platelet transfusions from December 2021 to December 2022 were used as the training set, and data from January 2023 to December 2023 as the validation set. The validation set data was used to validate the predictive model constructed on the training set. Relevant risk factors for PTR were collected through literature review and preliminary studies。 The patients were divided into effective and ineffective groups according to the corrected count increment (CCI) of platelet counts. Predictive factors were screened using univariate and multivariate logistic regression. The calibration of the model were assessed via calibration curves, while discrimination, accuracy, sensitivity, and specificity were evaluated using receiver operating characteristic (ROC) curves Clinical utility was further analyzed with decision curve analysis (DCA). [Results] The Hosmer-Lemeshow (H-L) goodness-of-fit test for the validation set yielded S: P=0.000, indicating that the original model needs optimization. Baseline comparisons and logistic regression identified the number of red blood cell units (RBCU) and platelet units (PLT-U) transfused as key predictors for the optimized model. The H-L goodness-of-fit test S: P values for the training and validation sets were 0.930 and 0.056, respectively; the ROC areas were 0.793 5 and 0.809 4, specificities 90.95% and 84.21%, sensitivities 59.26% and 70.04%, and accuracies 78.14% and 74.10%, respectively. DCA demonstrated clinical net benefit within a prediction probability threshold range of 0.2-0.8. [Conclusion] Transfusion volumes of RBC-U and PLT-U were inversely associated with PTR in hematological patients. The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.

[This corrects the article DOI: 10.1016/j.apsb.2021.10.012.].

Objective:To explore the risk factors for severe acute kidney injury (AKI) in children with sepsis in the pediatric intensive care unit (PICU) and construct a prediction model to assist early clinical identification.Methods:A retrospective analysis was performed on clinical data of 987 children with sepsis admitted to the PICU of Hunan Children′s Hospital from July 1, 2018 to January 31, 2021. Children who developed severe AKI during hospitalization were included in the AKI stage 2-3 group ( n=228), and the remaining were included in the No-AKI/AKI stage 1 group ( n=759). General information and biochemical indicators were compared between the two groups. Logistic regression analysis was used to identify risk factors for severe AKI in children with sepsis, and a prediction model and nomogram were established. Results:The mortality rate in the AKI stage 2-3 group was 2.49 times that of the No-AKI/AKI stage 1 group [31.1%(71/228) vs 12.5%(95/759), P<0.05]. Compared with the No-AKI/AKI stage 1 group, the AKI stage 2-3 group had lower levels of platelet count (PLT), total protein (TP), albumin (ALB), antithrombin Ⅲ (AT3), and fibrinogen (FIB), but higher levels of lactate dehydrogenase (LDH), serum creatinine (SCr), blood urea nitrogen (BUN), magnesium ion (Mg 2+ ), activated partial thromboplastin time (APTT), fibrinogen degradation products (FDP), and D-dimer (D-D) (all P<0.05), with no significant difference in total bile acid (TBAC) ( P>0.05). Multivariate logistic regression analysis showed that decreased AT3 ( OR=0.989, 95% CI: 0.980-0.997, P=0.007), increased LDH ( OR=1.001, 95% CI: 1.000-1.001, P<0.001), increased SCr ( OR=1.051, 95% CI: 1.037-1.066, P<0.001), and increased BUN ( OR=1.099, 95% CI: 1.028-1.174, P=0.005) were risk factors for severe AKI in children with sepsis. The prediction model was Logist Pr=-3.184-0.012 X1+ 0.001 X2+ 0.050 X3+ 0.094 X4 ( X1=AT3, X2=LDH, X3=SCr, X4=BUN), with the optimal cut-off value of 0.374 (Youden index=0.560). A nomogram was constructed by binary assignment of predictive variables, with an area under the curve of 0.826 (95% CI: 0.790-0.861, P<0.001). Conclusions:The mortality rate of septic children with severe AKI in PICU is significantly increased. Decreased AT3, and increased LDH, SCr, and BUN are risk factors for severe AKI in children with sepsis. Clinicians should be alert to severe AKI when the predicted probability of the early warning model exceeds 0.374.

Objective:To explore the risk factors for severe acute kidney injury (AKI) in children with sepsis in the pediatric intensive care unit (PICU) and construct a prediction model to assist early clinical identification.Methods:A retrospective analysis was performed on clinical data of 987 children with sepsis admitted to the PICU of Hunan Children′s Hospital from July 1, 2018 to January 31, 2021. Children who developed severe AKI during hospitalization were included in the AKI stage 2-3 group ( n=228), and the remaining were included in the No-AKI/AKI stage 1 group ( n=759). General information and biochemical indicators were compared between the two groups. Logistic regression analysis was used to identify risk factors for severe AKI in children with sepsis, and a prediction model and nomogram were established. Results:The mortality rate in the AKI stage 2-3 group was 2.49 times that of the No-AKI/AKI stage 1 group [31.1%(71/228) vs 12.5%(95/759), P<0.05]. Compared with the No-AKI/AKI stage 1 group, the AKI stage 2-3 group had lower levels of platelet count (PLT), total protein (TP), albumin (ALB), antithrombin Ⅲ (AT3), and fibrinogen (FIB), but higher levels of lactate dehydrogenase (LDH), serum creatinine (SCr), blood urea nitrogen (BUN), magnesium ion (Mg 2+ ), activated partial thromboplastin time (APTT), fibrinogen degradation products (FDP), and D-dimer (D-D) (all P<0.05), with no significant difference in total bile acid (TBAC) ( P>0.05). Multivariate logistic regression analysis showed that decreased AT3 ( OR=0.989, 95% CI: 0.980-0.997, P=0.007), increased LDH ( OR=1.001, 95% CI: 1.000-1.001, P<0.001), increased SCr ( OR=1.051, 95% CI: 1.037-1.066, P<0.001), and increased BUN ( OR=1.099, 95% CI: 1.028-1.174, P=0.005) were risk factors for severe AKI in children with sepsis. The prediction model was Logist Pr=-3.184-0.012 X1+ 0.001 X2+ 0.050 X3+ 0.094 X4 ( X1=AT3, X2=LDH, X3=SCr, X4=BUN), with the optimal cut-off value of 0.374 (Youden index=0.560). A nomogram was constructed by binary assignment of predictive variables, with an area under the curve of 0.826 (95% CI: 0.790-0.861, P<0.001). Conclusions:The mortality rate of septic children with severe AKI in PICU is significantly increased. Decreased AT3, and increased LDH, SCr, and BUN are risk factors for severe AKI in children with sepsis. Clinicians should be alert to severe AKI when the predicted probability of the early warning model exceeds 0.374.

To explore the application of humanistic care in children's fever clinics,the children's fever clinics of Guangzhou Women and Children's Medical Center conducted relevant research using narrative medicine as a guiding concept.This paper elaborated on the medical humanistic dilemmas and narrative care needs in children's fever clinics,and focused on exploring the practice paths of narrative medicine in pediatric with Chinese characteristics from five dimensions,including the cultivation of nursing staff's abilities of professional narrative and humanistic care,the establishment of health lectures featuring narrative patient education,the alleviation of medical anxiety for children and their families,related support of narrative nursing,and caring services.The aim was to improve the narrative care ability of nurses in children's fever clinics,develop methods for pediatric patients that can eliminate the fear of seeking medical treatment,and protect children's physical and mental health.A carrier of care,support,and emotional expression can be provided for parents.The foundation for nursing staff to achieve professional growth through narrative reflection can be laid.Thus,it can assist in establishing a life narrative community relationship between doctors and patients,and jointly explore the meaning of life.

【Objective】 To explore the effectiveness of PDCA (Plan-Do-Check-Act Cycle Management) in clinical emergency blood management. 【Methods】 The data of emergency blood-using cases from January 2021 to June 2022 in each clinical department of our hospital were collected to observe the blood matching time, blood retrieving time, and emergency bloodusing rate. They were divided into PDCA experimental group (Experimental group, July to December 2021, n=287), pre-PDCA experimental group (Control group 1, January to June 2021, n=516) and post-PDCA experimental cessation group (Control group 2, January to June 2022, n=277). Subgroup analysis was performed according to different departments, which were Internal Medicine Department, Surgery Depatment, and ICU. The situation of non-emergency blood use occupying emergency lanes in the pre-implementation period was continuously improved using PDCA, and the differences in blood matching time, blood retrieving time, and emergency blood-using rate among the three groups were compared and analyzed by Kruskal-Wallis test and chi-square test. 【Results】 The blood matching time and blood retrieving time (M, min) in the experimental group, control group 1 and control group 2 were 19.00 vs 45.50 vs 23.00 and 22.00 vs 44.00 vs 25.00, respectively (P< 0.05), and were 19.00 vs 47.00 vs 24.00 and 23.00 vs 56.00 vs 30. 50 in Internal Medicine Department, 18.00 vs 57.50 vs 14.00 and 32.00 vs 41.00 vs 24.00 in Surgery Department, 20.00 vs 42.00 vs 23.00 and 16.50 vs 34.00 vs 12.50 in ICU (P<0.05). The rate of emergency blood use in the experimental group, control group 1, and control group 2 were 6.9%(287/4 141) vs 11.0%(516/4 689) vs 6.8%(277/4 089), respectively (P< 0.05), and were 6.3%(175/2 769) vs 11.8% (297/2 512) vs 6.7% (186/2 789) in Internal Medicine Department, 5.9%(24/405) vs 3.6 %(44/1 213) vs 7.4% (37/501) in Surgery Department, and 9.1% (88/967) vs 18% (175/973) vs 6.8%(54/799) in ICU (P<0.05). 【Conclusion】 The adoption of PDCA in Blood Transfusion Department can effectively shorten the blood matching time and blood retrieving time for clinical emergencies and improve the success rate of emergency blood transfusion.

【Objective】 To observe the effect of platelet transfusion in inpatients with haematological diseases, analyze the possible causes of platelet transfusion refractoriness (PTR), in order to further improve the efficacy of platelet transfusion. 【Methods】 A total of 310 patients with blood disease in our hospital from August 2020 to November 2021 who received platelet transfusion were retrospectively analyzed. Possible influencing factors of platelet transfusion, including gender, age, platelet preservation time, number of platelet transfusions, complication and red blood cell product transfusion were analyzed. 【Results】 Patients were divided into effective group and refractory group according to percentage platelet recovery (PPR) and corrected count increment (CCI). PTR was defined as PPR <20% or CCI <5 000 after two consecutive transfusions in 24 h or clinical bleeding symptoms or tendency not significantly controlled. Statistical differences were noticed between the two groups in terms of gender, pretransfusion white blood cell count, anemia, and whether antibiotics were used (P<0.05). The type of disease, gender, anemia and number of comorbidities were associated with PTR. The incidence of PTR was the highest in patients with myelodysplastic syndrome, and the incidence of PTR was higher in men than in women. Transfusion units of suspended red blood cells and the number of comorbidities were negatively correlated with the transfusion efficacy (P<0.05). 【Conclusion】 Possible influencing factors of platelet transfusion included the level of white blood cells before transfusion, use of antibiotics, anemia and transfusion of red blood cells, number of comorbidities, and type of disease, while no significant differences were found in age, hemolysis, hypersplenism, platelet preservation time, and number of platelet transfusions on transfusion efficacy.

This article reviews the overview, impact and intervention measures of adult attachment of main caregivers of dementia patients, in order to provide a basis for my country to carry out targeted intervention measures to improve the health outcomes of the main caregivers.

Objectives To determine the risk factors of ventilator-associated pneumonia (VAP) in the pediatric intensive care unit and to explore effective strategies to reduce the morbidity of VAP. Methods A retrospective analysis was conducted on 455 children admitted into the PICU of Hunan Children's Hospital from June 2014 to June 2017. The 455 children were divided into VAP group (n=43) and non-VAP group (n=412). The incidence of VAP was identified and risk factors were compared using the logistic regression analysis via SPSS 19.0 software.Results There were 311 males and 144 females with a median age of 11 months old (29 days to 9 years and 4 months). The incidence of VAP was 9.45% (43/455). Congenital laryngeal and trachea malformation with pulmonary infection was the first reason for the occurrence of VAP (23.3%), followed by congenital heart diseases with pulmonary infection (18.6%). Via univariate analysis, types of endotracheal intubation (χ2=45.33, P<0.001), duration of mechanical ventilation (Z=1.21, P=0.034), re-intubation (χ2=20.22, P=0.004), early usage of antibiotics (χ2=4.98, P=0.026),and methods of nutritional support(χ2=10.15,P=0.006)were identified as risk factors of VAP in the pediatric intensive care unit patients (P<0.05). Based on the multivariate logistic regression analysis, the followings were all independent predictor for VAP:types of endotracheal intubation(OR=1.87,95%CI:1.48~9.75),duration of mechanical ventilation(OR=1.14, 95%CI:1.08~2.35), re-intubation (OR=3.42, 95%CI:1.26~5.57), early usage of antibiotics (OR=4.55, 95%CI:2.21~8.77). Conclusions Many risk factors were found related with the occurrence of VAP. A comprehensive analysis of the host factors and iatrogenic factors should be conducted. Rational use of antibiotics and daily assessment of extubation might help reduce the incidence of VAP.

Objective To investigate the prevalence of pulmonary fungal infection and drug resist-ance of the pathogenic fungi among children with severe diseases in pediatric intensive care unit(PICU). Methods From July 2013 to June 2017,the complete clinical data,results of fungal culture and drug sensi-tivity of bronchoalveolar lavage fluid in 112 critically ill children with pulmonary fungus infection of PICU hospitalization in our hospital were collected. Samples of peripheral venous blood were collected meantime, including blood routine examination,C reactive protein,G test and GM test. Results One hundred and twen-ty-six fungi were isolated from sputum samples in 112 critically ill children. Severe pulmonary infection (30. 36%,34/112) was the most common form of the primary diseases, the next were severe sepsis (16. 07%,18/112)and severe malnutrition(15. 18%,17/112). Classified based on age difference,the first one was ＜1 year old (43. 75%,49/112),the second one was 1 to 3 years old(29. 46%,33/112). The fun-gal strains were predominantly Candida albicans (61. 90%) and Candida tropicalis (16. 67%),among the infectious cases 14 were diagnosed as mixed infection. Two cases of 3 cryptococcal infectious children were HIV infection,another one was malignant tumor,Cryptococcus was cultured in both sputum,pleural effusion and cerebrospinal fluid. The drug resistance rate of fluconazol in 126 strains of fungi was 12. 70%,the rate of itraconazole was 7. 14%. Generally,the fungi cultured were with very low resistance to 5-fluorocytosine,vori-conazole and amphotericin B. However,the strains of Aspergillus fumigates,Candida kruse,Candida parapsi-losis and Cryptococcus were highly resistant to fluconazol and itraconazole,but with very low resistance to 5-fluorocytosine and amphotericin B. Conclusion Candida albicans is the main pathogenic fungus of pulmo-nary fungal infection among children in PICU,and we could choose voriconazole and amphotericin B as treat-ment of critically ill children with pulmonaty fungal infection.