[Objective] To retrospectively analyze the detection results of alanine aminotransferase (ALT) unqualified repeat blood donors in Guangzhou, so as to provide evidence for further expanding the repeat blood donor pool, reducing the rate of blood discarding and improving the qualified rate of blood test. [Methods] Blood donors with unqualified ALT in Guangzhou Blood Center from January 2018 to April 2024 were selected as the research objects. The past blood donation and population characteristics were analyzed according to the number of blood donations and ALT unqualified times. [Results] Among repeat blood donors with previous ALT disqualification, 99.5% to 99.7% did not have reactive markers for transfusion-transmitted diseases (TTD), which was higher than the rate among first-time blood donors with unqualified ALT (95.8%) (P<0.05). The rate of single-item ALT disqualification in repeat blood donors was higher in males than in females (P<0.05); it also varied by age (18-25 years > 26-35 years > 36-45 years > over 45 years) (P<0.05); and by quarter (third and fourth quarters > first and second quarters) (P<0.05). The ALT unqualified rate was significantly higher whole blood donors than that of platelet donors and returning blood donors (P<0.05). The overall ALT level (51.0 U/L), individual ALT level (56.0 U/L) and individual ALT unqualified rate (66.7%) of repeat blood donors with multiple ALT disqualifications were higher than those of repeat blood donors with single-item ALT disqualifications (26.0 U/L, 38.5 U/L, and 33.3%, respectively) (P<0.05). Moreover, as the number of ALT disqualifications increased, the overall level of ALT in repeat blood donors also increased (P<0.05), and the average level of individual ALT and individual ALT unqualified ratio tended to increase. Repeat blood donors with frequent ALT disqualifications had higher ALT levels (69.0 U/L). [Conclusion] The ALT unqualified rates of repeat blood donors were mostly non-specific elevation without TTD. Repeat blood donors with multiple ALT disqualifications tend to have continuous high ALT. Moreover, and with the increase of ALT disqualifications times, the overall ALT levels the average individual ALT levels and individual ALT unqualified rates showed an increasing trend.

[Objective] To investigate the factors associated with alanine aminotransferase (ALT) abnormalities in multi-ethnic blood donors across five Zang autonomous prefectures in the plateau regions of Qinghai Province, and to provide evidence for ensuring blood safety and formulating screening strategies. [Methods] A retrospective analysis was performed on the ALT abnormal test results of blood donors in the Zang autonomous prefectures of Qinghai from 2022 to 2024. The correlations between ALT levels and factors including gender, age, altitude, and infectious markers were investigated. [Results] The overall ALT unqualified rate among blood donors in this region was 9.01%. Significant differences in ALT levels were observed across genders and age groups (P<0.05). Variations in ALT abnormality rates were also noted among different plateau regions (P<0.05). Overall, ALT values exhibited an increasing trend with rising altitude. The average ALT unqualified rates were 11.19% in Zang donors, 7.96% in Han donors, and 4.79% in donors from other ethnic groups (P<0.05). No statistically significant association was observed between ALT abnormality and the presence of HBV/HCV infectious markers (P>0.05). [Conclusion] In the plateau areas of Qinghai, multi-ethnic blood donors have a relatively high ALT levels and ALT unqualified rates, showing distinct regional characteristics. ALT elevation in voluntary blood donors is related to non-pathological factors such as gender, age, and dietary habits, but not to infectious indicators.

Objective:To explore the effect of psoas muscle index (PMI) and construct a machine learning model to validate the 180-day prognosis in patients with decompensated liver cirrhosis.Methods:Retrospective data were collected from patients with decompensated liver cirrhosis at Henan Provincial People's Hospital from January 2022 to November 2022. The area of the psoas muscle index (PMI) at the level of the third lumbar vertebra was measured and calculated based on the abdominal X-ray computed tomography images stored in the Eastern China Hospital Information System (HIS). Patients were divided into low PMI and normal PMI groups according to the receiver operating characteristic curve. Patients clinical data and complication status were collected.The general conditions of both groups were compared using a t-test, chi-square test, and Mann-Whitney U test. The Kaplan-Meier method was applied for survival analysis. The outcome variable was 180-day mortality, and variables were selected using Cox and LASSO regression. The dataset was divided into training and testing sets in a 7∶3 ratio. Machine learning algorithms were used to build models in the training set, and model performance was validated by the test set. The model for MELD-Na score was compared with the model for End-Stage Liver Disease score. Results:A total of 298 patients with decompensated liver cirrhosis were included.The MELD scores, Child-Pugh classification, and NRS2002 scores, along with the incidence rate of complications such as ascites, hepatic encephalopathy, infections, and gastrointestinal bleeding, were significantly higher in the low PMI than the normal PMI group, with statistically significant differences ( P<0.05). The area under a receiver operating characteristic curve for the extreme gradient boosting model was higher than traditional clinical scores (MELD score 0.658, MELD_Na score 0.719) in the machine learning model. Furthermore, the application of SHAP results model indicated that PMI, hemoglobin, NRS2002 score, direct bilirubin, and blood ammonia were important factors in predicting the prognosis of patients with decompensated liver cirrhosis. Conclusion:A low PMI is closely related to poorer survival rates and the development of complication rates in patients with decompensated liver cirrhosis. The machine learning prediction model based on this construction, especially extreme gradient boosting, has favorable predictive performance, which is superior to the traditional clinical scoring system and can provide patients with the most accurate risk assessment and individualized treatment plan.

Objective:To analyze the value of 18F-FDG PET/CT combined with MRI in the diagnosis and differential diagnosis of ductal carcinoma in situ (DCIS) and early stage invasive ductal carcinoma (IDC). Methods:From September 2019 to December 2023, 12 patients with DCIS (all females; age 36-67 years) and 34 patients with early stage IDC (all females; age 36-73 years) in Qingdao Central Hospital were retrospectively analyzed. The general clinical information, MRI features, and 18F-FDG PET/CT features of patients were analyzed. χ2 test, Fisher exact test, and Mann-Whitney U test were used to analyze the data. The independent predictors of DCIS were analyzed by logistic regression analysis. The value of different indicators in diagnosing DCIS was analyzed using ROC curves analysis, and Delong test was used to assess the differences among AUCs. Results:The differences in tumor metabolic volume (MTV; 18.55(10.90, 76.30) vs 4.00(2.00, 11.45)cm 3) and total lesion glycolysis (TLG; 44.85(25.30, 125.30) vs 9.40(6.68, 22.35)g) of breast lesion, enhancement pattern (non-mass enhancement (NME); 8/12 vs 29.4%(10/34)), lobulation sign (0/12 vs 58.8%(20/34)), and apparent diffusion coefficient (ADC; 1.33 (1.16, 1.63)×10 -3vs 1.08 (0.75, 1.28)×10 -3mm 2/s) between DCIS and early stage IDC groups were statistically significant ( Z values: from -3.91 to -2.56, χ2=5.17, all P<0.05). When differentiating DCIS from early stage IDC, NME (odds ratio ( OR)=36.50, 95% CI: 2.15-618.52, P=0.013), ADC ( OR=7.85, 95% CI: 1.11-55.46, P=0.044), and TLG ( OR=1.06, 95% CI: 1.02-1.11, P=0.007) were independent predictors. The AUC of the three predictors combination was 0.941, which was higher than those of single predictors ( Z values: 2.00-2.80, P values: 0.005-0.046). Conclusion:The combination of 18F-FDG PET/CT and MRI improves the efficacy of differential diagnosis between DCIS and early stage IDC, thereby providing a basis for developing personalized treatment plans for patients.

Objective:To identify factors influencing treatment-free remission (TFR) outcomes in children and adolescent patients with chronic myeloid leukemia (CML) after imatinib (IM) discontinuation.Methods:This multicenter retrospective study analyzed 36 children and adolescent patients with CML from eight hematology centers in China (December 1, 2016, to September 27, 2024) who discontinued IM therapy with documented post-cessation outcomes. Clinical characteristics and molecular response dynamics were assessed. Univariate analysis and multivariate Cox proportional hazards regression models were employed to assess factors associated with TFR outcomes.Results:A total of 36 patients were documented, comprising 17 males and 19 females. The median ages at CML diagnosis and IM discontinuation were 11 years ( IQR: 5,16) and 20 years ( IQR: 14,25), respectively. The median time from IM initiation to first deep molecular response (DMR) was 21 months ( IQR: 13, 38). Pre-discontinuation, patients received IM for a median duration of 96 months ( IQR: 84, 121) and maintained DMR for 74 months ( IQR: 63, 89). With a median post-discontinuation follow-up of 38 months ( IQR: 15, 68), cumulative TFR rates at 6, 12, 24, and 36 months were 74.1%, 60.7%, 60.7%, and 56.0%, respectively, generating an overall TFR rate of 58.3%. Fifteen patients lost major molecular response at a median of 5 months post-discontinuation ( IQR: 3, 11). All 15 patients resumed tyrosine kinase inhibitor therapy, comprising 13 who restarted IM and 2 who switched to dasatinib. By the last follow-up, 13 (86.7% ) patients regained DMR after a median treatment duration of 5 months ( IQR: 3, 17), and no disease progression occurred in any patient. Withdrawal syndrome occurred in 2 (5.6% ) patients. Univariate analysis revealed significantly higher TFR rates in patients with pre-discontinuation IM duration of ≥100 months vs <100 months (82.4% vs 36.8%, P=0.017) and pre-discontinuation DMR duration of ≥72 months vs <72 months (84.2% vs 29.4%, P=0.003). Multivariate Cox analysis identified pre-discontinuation DMR duration as an independent protective factor for TFR ( HR=5.419, 95% CI: 1.524–19.272, P=0.009) . Conclusion:DMR duration was identified as an independent protective factor influencing TFR outcomes in children and adolescent patients with CML after IM discontinuation. Patients who maintained DMR for ≥72 months before IM discontinuation demonstrated a significantly higher TFR rate.

Objective:To analyze the value of 18F-FDG PET/CT combined with MRI in the diagnosis and differential diagnosis of ductal carcinoma in situ (DCIS) and early stage invasive ductal carcinoma (IDC). Methods:From September 2019 to December 2023, 12 patients with DCIS (all females; age 36-67 years) and 34 patients with early stage IDC (all females; age 36-73 years) in Qingdao Central Hospital were retrospectively analyzed. The general clinical information, MRI features, and 18F-FDG PET/CT features of patients were analyzed. χ2 test, Fisher exact test, and Mann-Whitney U test were used to analyze the data. The independent predictors of DCIS were analyzed by logistic regression analysis. The value of different indicators in diagnosing DCIS was analyzed using ROC curves analysis, and Delong test was used to assess the differences among AUCs. Results:The differences in tumor metabolic volume (MTV; 18.55(10.90, 76.30) vs 4.00(2.00, 11.45)cm 3) and total lesion glycolysis (TLG; 44.85(25.30, 125.30) vs 9.40(6.68, 22.35)g) of breast lesion, enhancement pattern (non-mass enhancement (NME); 8/12 vs 29.4%(10/34)), lobulation sign (0/12 vs 58.8%(20/34)), and apparent diffusion coefficient (ADC; 1.33 (1.16, 1.63)×10 -3vs 1.08 (0.75, 1.28)×10 -3mm 2/s) between DCIS and early stage IDC groups were statistically significant ( Z values: from -3.91 to -2.56, χ2=5.17, all P<0.05). When differentiating DCIS from early stage IDC, NME (odds ratio ( OR)=36.50, 95% CI: 2.15-618.52, P=0.013), ADC ( OR=7.85, 95% CI: 1.11-55.46, P=0.044), and TLG ( OR=1.06, 95% CI: 1.02-1.11, P=0.007) were independent predictors. The AUC of the three predictors combination was 0.941, which was higher than those of single predictors ( Z values: 2.00-2.80, P values: 0.005-0.046). Conclusion:The combination of 18F-FDG PET/CT and MRI improves the efficacy of differential diagnosis between DCIS and early stage IDC, thereby providing a basis for developing personalized treatment plans for patients.

Objective:To identify factors influencing treatment-free remission (TFR) outcomes in children and adolescent patients with chronic myeloid leukemia (CML) after imatinib (IM) discontinuation.Methods:This multicenter retrospective study analyzed 36 children and adolescent patients with CML from eight hematology centers in China (December 1, 2016, to September 27, 2024) who discontinued IM therapy with documented post-cessation outcomes. Clinical characteristics and molecular response dynamics were assessed. Univariate analysis and multivariate Cox proportional hazards regression models were employed to assess factors associated with TFR outcomes.Results:A total of 36 patients were documented, comprising 17 males and 19 females. The median ages at CML diagnosis and IM discontinuation were 11 years ( IQR: 5,16) and 20 years ( IQR: 14,25), respectively. The median time from IM initiation to first deep molecular response (DMR) was 21 months ( IQR: 13, 38). Pre-discontinuation, patients received IM for a median duration of 96 months ( IQR: 84, 121) and maintained DMR for 74 months ( IQR: 63, 89). With a median post-discontinuation follow-up of 38 months ( IQR: 15, 68), cumulative TFR rates at 6, 12, 24, and 36 months were 74.1%, 60.7%, 60.7%, and 56.0%, respectively, generating an overall TFR rate of 58.3%. Fifteen patients lost major molecular response at a median of 5 months post-discontinuation ( IQR: 3, 11). All 15 patients resumed tyrosine kinase inhibitor therapy, comprising 13 who restarted IM and 2 who switched to dasatinib. By the last follow-up, 13 (86.7% ) patients regained DMR after a median treatment duration of 5 months ( IQR: 3, 17), and no disease progression occurred in any patient. Withdrawal syndrome occurred in 2 (5.6% ) patients. Univariate analysis revealed significantly higher TFR rates in patients with pre-discontinuation IM duration of ≥100 months vs <100 months (82.4% vs 36.8%, P=0.017) and pre-discontinuation DMR duration of ≥72 months vs <72 months (84.2% vs 29.4%, P=0.003). Multivariate Cox analysis identified pre-discontinuation DMR duration as an independent protective factor for TFR ( HR=5.419, 95% CI: 1.524–19.272, P=0.009) . Conclusion:DMR duration was identified as an independent protective factor influencing TFR outcomes in children and adolescent patients with CML after IM discontinuation. Patients who maintained DMR for ≥72 months before IM discontinuation demonstrated a significantly higher TFR rate.

Objective:To explore the effect of psoas muscle index (PMI) and construct a machine learning model to validate the 180-day prognosis in patients with decompensated liver cirrhosis.Methods:Retrospective data were collected from patients with decompensated liver cirrhosis at Henan Provincial People's Hospital from January 2022 to November 2022. The area of the psoas muscle index (PMI) at the level of the third lumbar vertebra was measured and calculated based on the abdominal X-ray computed tomography images stored in the Eastern China Hospital Information System (HIS). Patients were divided into low PMI and normal PMI groups according to the receiver operating characteristic curve. Patients clinical data and complication status were collected.The general conditions of both groups were compared using a t-test, chi-square test, and Mann-Whitney U test. The Kaplan-Meier method was applied for survival analysis. The outcome variable was 180-day mortality, and variables were selected using Cox and LASSO regression. The dataset was divided into training and testing sets in a 7∶3 ratio. Machine learning algorithms were used to build models in the training set, and model performance was validated by the test set. The model for MELD-Na score was compared with the model for End-Stage Liver Disease score. Results:A total of 298 patients with decompensated liver cirrhosis were included.The MELD scores, Child-Pugh classification, and NRS2002 scores, along with the incidence rate of complications such as ascites, hepatic encephalopathy, infections, and gastrointestinal bleeding, were significantly higher in the low PMI than the normal PMI group, with statistically significant differences ( P<0.05). The area under a receiver operating characteristic curve for the extreme gradient boosting model was higher than traditional clinical scores (MELD score 0.658, MELD_Na score 0.719) in the machine learning model. Furthermore, the application of SHAP results model indicated that PMI, hemoglobin, NRS2002 score, direct bilirubin, and blood ammonia were important factors in predicting the prognosis of patients with decompensated liver cirrhosis. Conclusion:A low PMI is closely related to poorer survival rates and the development of complication rates in patients with decompensated liver cirrhosis. The machine learning prediction model based on this construction, especially extreme gradient boosting, has favorable predictive performance, which is superior to the traditional clinical scoring system and can provide patients with the most accurate risk assessment and individualized treatment plan.

Purpose/Significance To strengthen the construction of intelligent primary health information systems,and to provide ref-erences for improving the level of primary health services.Method/Process The paper systematically summarizes the current construction of primary health information systems at home and abroad,focuses on analyzing the current technical architectures and intelligent applica-tions of the existing systems,and puts forward improvement suggestions for the shortcomings in the construction mode,data connectivity and intelligent application.Result/Conclusion Countermeasures such as strengthening top-level design,promoting multi-source heter-ogeneous data fusion and strengthening intelligent applications are proposed to provide references for the construction of intelligent primary health information systems.