Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Nowadays,the one hospital with multiple districts has become a common model for the development of large public hospitals at present.Through the analysis of the common problems in the development of one hospital with multiple districts,the homogeneous management of one hospital with multiple districts has practical problems,it reflected in difficulties in space management,difficulties,difficulties in staff management,difficulties in system management,difficulties in collaborative development of medical service,difficulties in assessment,difficulties in cost management,difficulties in culture integrations.The case of the scientific management of one hospital with multiple districts in a tertiary public hospitals of provincial state-owned is analyzed,the experience are summarized in terms of organizational structure level,development orientation level,personnel level,performance pay level,cost control level,basic facilities level,culture level,to expected to provide references for promoting the construction of one hospital with multiple districts in public hospitals.

Urine carries rich information of human metabolism, while urine examination facilitates the diagnosis, classification and efficacy observation for acute kidney injury (AKI) and chronic kidney disease (CKD). Urine sediment has characteristics of convenience, screening, qualitation, localization, which provides important basis for distinguishing the source of RBC, assisting in the diagnosis of renal glomerular diseases, urinary infection and various causes of renal parenchymal injury. The urine sediment microscopy based on renal tubular epithelial cell (RTEC) and granular tubular (GC) counts mainly includes urinary sediment score (USS), tubular scoring index (CSI), urine microscopy score (UMS), and continuous urine sediment microscopy score (MicrExUrSed), which can provide laboratory information for early diagnosis, etiological differentiation, staging evaluation, and prognosis assessment of AKI.

Objective:To establish a set of artificial intelligence (AI) verification rules for blood routine analysis.Methods:Blood routine analysis data of 18 474 hospitalized patients from the First Hospital of Jilin University during August 1st to 31st, 2019, were collected as training group for establishment of the AI verification rules,and the corresponding patient age, microscopic examination results, and clinical diagnosis information were collected. 92 laboratory parameters, including blood analysis report parameters, research parameters and alarm information, were used as candidate conditions for AI audit rules; manual verification combining microscopy was considered as standard, marked whether it was passed or blocked. Using decision tree algorithm, AI audit rules are initially established through high-intensity, multi-round and five-fold cross-validation and AI verification rules were optimized by setting important mandatory cases. The performance of AI verification rules was evaluated by comparing the false negative rate, precision rate, recall rate, F1 score, and pass rate with that of the current autoverification rules using Chi-square test. Another cohort of blood routine analysis data of 12 475 hospitalized patients in the First Hospital of Jilin University during November 1sr to 31st, 2023, were collected as validation group for validation of AI verification rules, which underwent simulated verification via the preliminary AI rules, thus performance of AI rules were analyzed by the above indicators. Results:AI verification rules consist of 15 rules and 17 parameters and do distinguish numeric and morphological abnormalities. Compared with auto-verification rules, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score of AI rules in training group were 22.7%, 1.6%, 74.5%, 1.3%, 75.7%, 97.2%, 93.5%, 94.7%, 94.1, respectively.All of them were better than auto-verification rules, and the difference was statistically significant ( P<0.001), and with no important case missed. In validation group, the true positive rate, the false positive rate, the true negative rate, the false negative rate, the pass rate, the accuracy, the precision rate, the recall rate and F1 score were 19.2%, 8.2%, 70.1%, 2.5%, 72.6%, 89.2%, 70.0%, 88.3%, 78.1, respectively, Compared with the auto-verification rules, The false negative rate was lower, the false positive rate and the recall rate were slightly higher, and the difference was statistically significant ( P<0.001). Conclusion:A set of the AI verification rules are established and verified by using decision tree algorithm of machine learning, which can identify, intercept and prompt abnormal results stably, and is moresimple, highly efficient and more accurate in the report of blood analysis test results compared with auto-vefication.

Objective:To evaluate the clinical application of urine sediment score (USS) in early diagnosis, etiological differentiation, staging and prognosis of acute kidney injury (AKI), and to investigate the diagnostic efficacy of independent USS and its combination with blood urea nitrogen(Bun) serum creatinine(sCr) and uric acid(UA) in AKI.Methods:From August 23 to September 28, 2023, 9 020 morning urine samples of hospitalized patients in the First Hospital of Jilin University were detected by Sysmex UF5000.A total of 3 226 ssamples with small and round cell (SRC) > 1/μl and/or CAST>1/μl were screened for microscopic examination, and 404 cases with positive renal tubular epithelial cells and/or cast were enrolled in this study. There were 218 males and 186 females, aged 59.5 (49.0, 71.0) years. The 404 cases were divided into the USS AKI group (345 cases) and the USS non-AKI group (59 cases) according to the USS results based on the microscopic findings. According to Kidney Disease: Improving Global Outcomes (KDIGO) criteria, they were divided into KDIGO criteria AKI group (63 cases) and KDIGO criteria non-AKI group (341 cases), and the AKI group was divided into renal AKI group (33 cases) and non-renal AKI group (30 cases). According to the clinical diagnosis recorded in the medical records, they were divided into clinically diagnosed AKI group (29 cases) and clinically diagnosed non-AKI group (375 cases).The χ 2 test or Fisher exact test was used to compare USS in different AKI causes and stages. Logistic regression was used to calculate the odds ratio of renal AKI and stage 3 AKI. The area under the receiver operating characteristic curve was used to evaluate the sensitivity and specificity of USS, sCr, UA and Bun alone and in combination in the diagnosis of AKI, and the best cut-off value, sensitivity and specificity in the diagnosis of AKI were calculated. P < 0.05 was considered statistically significant. Results:The USS was used to identify the etiology of KDIGO standard AKI group,and there were significant differences in USS between renal AKI group and non-renal AKI group (χ 2=11.070, P<0.001). Compared to USS=1, the odds ratio of renal AKI was 8.125 when USS≥2 (95% CI 2.208—29.901). There was a statistically significant difference in the comparison of USS between groups in each stage of the AKI staging study based on USS (χ 2=15.724, P<0.05). Compared to USS=1, the odds ratio of stage 3 AKI was 9.714 when USS≥2 (95% CI 1.145-82.390). The AUC of independent USS in the diagnosis of AKI was 0.687 (95% CI 0.618-0.757, P<0.001), the specificity was 65.7% and the sensitivity was 61.9%. The AUC of USS combined with Bun, sCr, UA in the diagnosis of AKI was 0.794 (95% CI 0.608-0.980, P<0.05), the specificity was 82.4%, and the sensitivity was 88.9%. Conclusions:There wasan increased likelihood of renal AKI or stage 3 AKI while USS≥2,and whose combination with Bun, sCr and UA will improve the diagnostic efficiency of AKI.

Objective:Clot waveform analysis (CWA) of activated partial thromboplastin time (APTT) was used to rapidly identify patients with hemophilia A (HA) and lupus anticoagulant (LA) positive, and to explore the diagnostic efficacy of APTT-CWA in HA and LA-positive patients.Methods:From July 25, 2022, to December 28, 2023, 145 patients with APTT prolongation were admitted to the First Hospital of Jilin University. This group comprised 106 males and 39 females, with an average age of (29.3±15.8) years, among whom there were 94 clinically confirmed HA cases and 51 LA-positive cases. The retrospective analysis employed the Mann-Whitney U test to compare APTT results and CWA parameters between HA patients and LA-positive individuals.CWA parameters including the first derivative of maximum reaction velocity (|min1|), the second derivative of maximum acceleration (|min2|), and maximum deceleration (|max2|) were investigated. Patients were classified based on the duration of APTT prolongation into mild (33 s53 s) groups. A comparison of APTT seconds and CWA parameters |min1|, |min2|, and |max2| was conducted for HA and LA-positive patients between each group. Furthermore, receiver operating characteristic (ROC) curves and area under the curve (AUC) were utilized to assess the diagnostic efficacy of CWA parameters and determine cut-off values. Results:The APTT results for HA and LA-positive patients were 70.2 s and 41.5 s, respectively, exhibiting a statistically significant difference ( P<0.001). CWA parameters |min1| were 1.459 %/s vs 3.868 %/s, |min2| were 0.124 %/s2 vs 0.502 %/s2, and |max2| were 0.054 %/s2 vs 0.388 %/s2in HA and LA patients, respectively ( P<0.001). In all APTT prolongation groups, the CWA parameters |min1|, |min2|and |max2| for HA were significantly lower than those for LA-positive patients ( P<0.05). CWA graph analysis revealed that the peak heights of |min1|, |min2|, and |max2| in HA were lower compared to LA patients. In the severe extension group, HA displayed significantly decreased peak values and a flatter, incomplete curve. ROC curve analysis indicated AUC values were greater than 0.8 ( P<0.01) for |min1|, |min2|, and |max2| in all APTT prolongation groups. Cut-off values for |min1|, |min2|, and |max2| were established for each prolongation group: mild (3.205 %/s, 0.423 %/s2, and 0.300 %/s2), moderate (2.884 %/s, 0.340 %/s2, 0.231 %/s2), and severe (2.209 %/s, 0.190 %/s2, 0.095 %/s2). Conclusion:When APTT was extended within the same range, there were significant differences in CWA parameters between HA patients and LA patients, ROC curve analysis demonstrated the effectiveness of CWA parameters in distinguishing HA from LA-positive patients,APTT-CWA can serve as a low-cost, efficient, and specific method for the rapid identification of hemophilia and lupus anticoagulant-positive patients.