Objective:To investigate the value of systemic inflammatory response syndrome (SIRS), pediatric sequential organ failure assessment (pSOFA) and pediatric critical illness score (PCIS) in predicting mortality of pediatric sepsis in pediatric intensive care units (PICU) from Southwest China.Methods:This was a prospective multicenter observational study. A total of 447 children with sepsis admitted to 12 PICU in Southwest China from April 2022 to March 2023 were enrolled. Based on the prognosis, the patients were divided into survival group and non-survival group. The physiological parameters of SIRS, pSOFA and PCIS were recorded and scored within 24 h after PICU admission. The general clinical data and some laboratory results were recorded. The area under the curve (AUC) of the receiver operating characteristic curve was used to compare the predictive value of SIRS, pSOFA and PCIS in mortality of pediatric sepsis.Results:Amongst 447 children with sepsis, 260 patients were male and 187 patients were female, aged 2.5 (0.8, 7.0) years, 405 patients were in the survival group and 42 patients were in the non-survival group. 418 patients (93.5%) met the criteria of SIRS, and 440 patients (98.4%) met the criteria of pSOFA≥2. There was no significant difference in the number of items meeting the SIRS criteria between the survival group and the non-survival group (3(2, 4) vs. 3(3, 4) points, Z=1.30, P=0.192). The pSOFA score of the non-survival group was significantly higher than that of the survival group (9(6, 12) vs. 4(3, 7) points, Z=6.56, P<0.001), and the PCIS score was significantly lower than that of the survival group (72(68, 81) vs. 82(76, 88) points, Z=5.90, P<0.001). The predictive value of pSOFA (AUC=0.82) and PCIS (AUC=0.78) for sepsis mortality was significantly higher than that of SIRS (AUC=0.56) ( Z=6.59, 4.23, both P<0.001). There was no significant difference between pSOFA and PCIS ( Z=1.35, P=0.176). Platelet count, procalcitonin, lactic acid, albumin, creatinine, total bilirubin, activated partial thromboplastin time, prothrombin time and international normalized ratio were all able to predict mortality of sepsis to a certain degree (AUC=0.64, 0.68, 0.80, 0.64, 0.68, 0.60, 0.77, 0.75, 0.76, all P<0.05). Conclusion:Compared with SIRS, both pSOFA and PCIS had better predictive value in the mortality of pediatric sepsis in PICU.

Objective:To explore potential predictors of refractory Mycoplasma pneumoniae pneumonia (RMPP) in early stage. Methods:The prospective multicenter study was conducted in Zhejiang, China from May 1 st, 2019 to January 31 st, 2020. A total of 1 428 patients with fever >48 hours to <120 hours were studied. Their clinical data and oral pharyngeal swab samples were collected; Mycoplasma pneumoniae DNA in pharyngeal swab specimens was detected. Patients with positive Mycoplasma pneumoniae DNA results underwent a series of tests, including chest X-ray, complete blood count, C-reactive protein, lactate dehydrogenase (LDH), and procalcitonin. According to the occurrence of RMPP, the patients were divided into two groups, RMPP group and general Mycoplasma pneumoniae pneumonia (GMPP) group. Measurement data between the 2 groups were compared using Mann-Whitney U test. Logistic regression analyses were used to examine the associations between clinical data and RMPP. Receiver operating characteristic (ROC) curves were used to analyse the power of the markers for predicting RMPP. Results:A total of 1 428 patients finished the study, with 801 boys and 627 girls, aged 4.3 (2.7, 6.3) years. Mycoplasma pneumoniae DNA was positive in 534 cases (37.4%), of whom 446 cases (83.5%) were diagnosed with Mycoplasma pneumoniae pneumonia, including 251 boys and 195 girls, aged 5.2 (3.3, 6.9) years. Macrolides-resistant variation was positive in 410 cases (91.9%). Fifty-five cases were with RMPP, 391 cases with GMPP. The peak body temperature before the first visit and LDH levels in RMPP patients were higher than that in GMPP patients (39.6 (39.1, 40.0) vs. 39.2 (38.9, 39.7) ℃, 333 (279, 392) vs. 311 (259, 359) U/L, both P<0.05). Logistic regression showed the prediction probability π=exp (-29.7+0.667×Peak body temperature (℃)+0.004×LDH (U/L))/(1+exp (-29.7+0.667×Peak body temperature (℃)+0.004 × LDH (U/L))), the cut-off value to predict RMPP was 0.12, with a consensus of probability forecast of 0.89, sensitivity of 0.89, and specificity of 0.67; and the area under ROC curve was 0.682 (95% CI 0.593-0.771, P<0.01). Conclusion:In MPP patients with fever over 48 to <120 hours, a prediction probability π of RMPP can be calculated based on the peak body temperature and LDH level before the first visit, which can facilitate early identification of RMPP.

Objective:To observe the recurrence condition of hepatitis B in different risk groups after liver transplantation in an attempt to provide useful information on whether to discontinue hepatitis B immunoglobulin (HBIG) in the future at an early stage.Methods:The patient population was divided into high, low-risk, and special groups [especially primary hepatocellular carcinoma (HCC)] according to the guidelines for the prevention and treatment of hepatitis B recurrence after liver transplantation. The recurrence condition and risk factors in this population were observed for hepatitis B. Measurement data were analyzed using a t-test and a rank-sum test. Count data were compared using a χ2 test between groups. Results:This study finally included 532 hepatitis B-related liver transplant cases. A total of 35 cases had HBV recurrence after liver transplantation, including 34 cases that were HBsAg positive, one case that was HBsAg negative, and 10 cases that were hepatitis B virus (HBV) DNA positive. The overall HBV recurrence rate was 6.6%. The recurrence rate of HBV was 9.2% and 4.8% in the high- and low-risk HBV DNA positive and negative groups before surgery ( P = 0.057). Among the 293 cases diagnosed with HCC before liver transplantation, 30 had hepatitis B recurrence after surgery, with a recurrence rate of 10.2%. The independent related factors for the recurrence of hepatitis B in patients with HCC after liver transplantation were HCC recurrence ( HR =181.92, 95% CI 15.99~2 069.96, P < 0.001), a high postoperative dose of mycophenolate mofetil dispersible tablets (MMF) ( HR =5.190, 95% CI 1.289~20.889, P = 0.020), and a high dosage of HBIG ( HR = 1.012, 95% CI 1.001~1.023, P = 0.035). Among the 239 cases who were non-HCC before liver transplantation, five cases (recurrence rate of 2.1%) arouse postoperative hepatitis B recurrence. Lamivudine was used in all cases, combined with on-demand HBIG prophylaxis after surgery. There was no hepatitis B recurrence in non-HCC patients who treated with entecavir combined with HBIG after surgery. Conclusion:High-barrier-to-resistance nucleotide analogues combined with long-term HBIG have a good effect on preventing the recurrence of hepatitis B after liver transplantation. The discontinuation of HBIG may be considered at an early stage after administration of a high-barrier-to-resistance nucleotide analogue in low-risk patients. Domestically, the HBV infection rate is high, so further research is still required to explore the timing of HBIG discontinuation for high-risk patients, especially those with HCC.

BACKGROUND:Trauma-induced coagulopathy(TIC)due to serious injuries significantly leads to increased mortality and morbidity among elderly patients.However,the risk factors of TIC are not well elucidated.This study aimed to explore the risk factors of TIC in elderly patients who have major trauma. METHODS:In this retrospective study,the risk factors for TIC in elderly trauma patients at a single trauma center were investigated between January 2015 and September 2020.The demographic information including gender,age,trauma parts,injury severity,use of blood products,use of vasopressors,need of emergency surgery,duration of mechanical ventilation,length of stay in the intensive care unit(ICU)and hospital,and clinical outcomes were extracted from electric medical records.Multivariate logistic regression analysis was performed to differentiate risk factors,and the performance of the model was evaluated using receiver operating characteristics(ROC)curves. RESULTS:Among the 371 elderly trauma patients,248(66.8%)were male,with the age of 72.5±6.8 years,median injury severity score(ISS)of 24(IQR:17-29),and Glasgow coma score(GCS)of 14(IQR:7-15).Of these patients,129(34.8%)were diagnosed with TIC,whereas 242(65.2%)were diagnosed with non-TIC.The severity scores such as ISS(25[20-34]vs.21[16-29],P<0.001)and shock index(SI),(0.90±0.66 vs.0.58±0.18,P<0.001)was significantly higher in the TIC group than in the non-TIC group.Serum calcium levels(1.97±0.19 mmol/L vs.2.15±0.16 mmol/L,P<0.001),fibrinogen levels(1.7±0.8 g/L vs.2.8±0.9 g/L,P<0.001),and base excess(BE,-4.9±4.6 mmol/L vs.-1.2±3.1 mmol/L,P<0.001)were significantly lower in the TIC group than in the non-TIC group.Multivariate logistic regression analysis revealed that ISS>16(OR:3.404,95%CI:1.471-7.880;P=0.004),SI>1(OR:5.641,95%CI:1.700-18.719;P=0.005),low BE(OR:0.868,95%CI:0.760-0.991;P=0.037),hypocalcemia(OR:0.060,95%CI:0.009-0.392;P=0.003),and hypofibrinogenemia(OR:0.266,95%CI:0.168-0.419;P<0.001)were independent risk factors for TIC in elderly trauma patients.The AUC of the prediction model included all these risk factors was 0.887(95%CI:0.851-0.923)with a sensitivity and specificity of 83.6%and 82.6%,respectively. CONCLUSION:Higher ISS(more than 16),higher SI(more than 1),acidosis,hypocalcemia,and hypofibrinogenemia emerged as independent risk factors for TIC in elderly trauma patients.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.

Objective:To construct a risk prediction model for diabetes kidney disease (DKD).Methods:Patients newly diagnosed with type 2 diabetes mellitus (T2DM) between January 1, 2015, and December 31, 2022, were selected as study subjects from the Yinzhou Regional Health Information Platform in Ningbo City. The Lasso method was used to screen the risk factors, and the DKD risk prediction model was established using Cox proportional hazard regression models. Bootstrap 500 resampling was applied for internal validation.Results:The study included 49 706 subjects, with an median ( Q1, Q3) age of 60.00 (50.00, 68.00) years old, and 55% were male. A total of 4 405 subjects eventually developed DKD. Age at first diagnosis of T2DM, BMI, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, past medical history (hyperuricemia, rheumatic diseases), triglycerides, and estimated glomerular filtration rate were included in the final model. The final model's C-index was 0.653, with an average of 0.654 after Bootstrap correction. The final model's area under the receiver operating characteristic curve for predicting 4-year, 5-year, and 6-year was 0.657, 0.659, and 0.664, respectively. The calibration curve was closely aligned with the ideal curve. Conclusions:This study constructed a DKD risk prediction model for newly diagnosed T2DM patients based on real-world data that is simple, easy to use, and highly practical. It provides a reliable basis for screening high-risk groups for DKD.

BACKGROUND:Trauma-induced coagulopathy(TIC)due to serious injuries significantly leads to increased mortality and morbidity among elderly patients.However,the risk factors of TIC are not well elucidated.This study aimed to explore the risk factors of TIC in elderly patients who have major trauma. METHODS:In this retrospective study,the risk factors for TIC in elderly trauma patients at a single trauma center were investigated between January 2015 and September 2020.The demographic information including gender,age,trauma parts,injury severity,use of blood products,use of vasopressors,need of emergency surgery,duration of mechanical ventilation,length of stay in the intensive care unit(ICU)and hospital,and clinical outcomes were extracted from electric medical records.Multivariate logistic regression analysis was performed to differentiate risk factors,and the performance of the model was evaluated using receiver operating characteristics(ROC)curves. RESULTS:Among the 371 elderly trauma patients,248(66.8%)were male,with the age of 72.5±6.8 years,median injury severity score(ISS)of 24(IQR:17-29),and Glasgow coma score(GCS)of 14(IQR:7-15).Of these patients,129(34.8%)were diagnosed with TIC,whereas 242(65.2%)were diagnosed with non-TIC.The severity scores such as ISS(25[20-34]vs.21[16-29],P<0.001)and shock index(SI),(0.90±0.66 vs.0.58±0.18,P<0.001)was significantly higher in the TIC group than in the non-TIC group.Serum calcium levels(1.97±0.19 mmol/L vs.2.15±0.16 mmol/L,P<0.001),fibrinogen levels(1.7±0.8 g/L vs.2.8±0.9 g/L,P<0.001),and base excess(BE,-4.9±4.6 mmol/L vs.-1.2±3.1 mmol/L,P<0.001)were significantly lower in the TIC group than in the non-TIC group.Multivariate logistic regression analysis revealed that ISS>16(OR:3.404,95%CI:1.471-7.880;P=0.004),SI>1(OR:5.641,95%CI:1.700-18.719;P=0.005),low BE(OR:0.868,95%CI:0.760-0.991;P=0.037),hypocalcemia(OR:0.060,95%CI:0.009-0.392;P=0.003),and hypofibrinogenemia(OR:0.266,95%CI:0.168-0.419;P<0.001)were independent risk factors for TIC in elderly trauma patients.The AUC of the prediction model included all these risk factors was 0.887(95%CI:0.851-0.923)with a sensitivity and specificity of 83.6%and 82.6%,respectively. CONCLUSION:Higher ISS(more than 16),higher SI(more than 1),acidosis,hypocalcemia,and hypofibrinogenemia emerged as independent risk factors for TIC in elderly trauma patients.

BACKGROUND:Trauma-induced coagulopathy(TIC)due to serious injuries significantly leads to increased mortality and morbidity among elderly patients.However,the risk factors of TIC are not well elucidated.This study aimed to explore the risk factors of TIC in elderly patients who have major trauma. METHODS:In this retrospective study,the risk factors for TIC in elderly trauma patients at a single trauma center were investigated between January 2015 and September 2020.The demographic information including gender,age,trauma parts,injury severity,use of blood products,use of vasopressors,need of emergency surgery,duration of mechanical ventilation,length of stay in the intensive care unit(ICU)and hospital,and clinical outcomes were extracted from electric medical records.Multivariate logistic regression analysis was performed to differentiate risk factors,and the performance of the model was evaluated using receiver operating characteristics(ROC)curves. RESULTS:Among the 371 elderly trauma patients,248(66.8%)were male,with the age of 72.5±6.8 years,median injury severity score(ISS)of 24(IQR:17-29),and Glasgow coma score(GCS)of 14(IQR:7-15).Of these patients,129(34.8%)were diagnosed with TIC,whereas 242(65.2%)were diagnosed with non-TIC.The severity scores such as ISS(25[20-34]vs.21[16-29],P<0.001)and shock index(SI),(0.90±0.66 vs.0.58±0.18,P<0.001)was significantly higher in the TIC group than in the non-TIC group.Serum calcium levels(1.97±0.19 mmol/L vs.2.15±0.16 mmol/L,P<0.001),fibrinogen levels(1.7±0.8 g/L vs.2.8±0.9 g/L,P<0.001),and base excess(BE,-4.9±4.6 mmol/L vs.-1.2±3.1 mmol/L,P<0.001)were significantly lower in the TIC group than in the non-TIC group.Multivariate logistic regression analysis revealed that ISS>16(OR:3.404,95%CI:1.471-7.880;P=0.004),SI>1(OR:5.641,95%CI:1.700-18.719;P=0.005),low BE(OR:0.868,95%CI:0.760-0.991;P=0.037),hypocalcemia(OR:0.060,95%CI:0.009-0.392;P=0.003),and hypofibrinogenemia(OR:0.266,95%CI:0.168-0.419;P<0.001)were independent risk factors for TIC in elderly trauma patients.The AUC of the prediction model included all these risk factors was 0.887(95%CI:0.851-0.923)with a sensitivity and specificity of 83.6%and 82.6%,respectively. CONCLUSION:Higher ISS(more than 16),higher SI(more than 1),acidosis,hypocalcemia,and hypofibrinogenemia emerged as independent risk factors for TIC in elderly trauma patients.

BACKGROUND:Trauma-induced coagulopathy(TIC)due to serious injuries significantly leads to increased mortality and morbidity among elderly patients.However,the risk factors of TIC are not well elucidated.This study aimed to explore the risk factors of TIC in elderly patients who have major trauma. METHODS:In this retrospective study,the risk factors for TIC in elderly trauma patients at a single trauma center were investigated between January 2015 and September 2020.The demographic information including gender,age,trauma parts,injury severity,use of blood products,use of vasopressors,need of emergency surgery,duration of mechanical ventilation,length of stay in the intensive care unit(ICU)and hospital,and clinical outcomes were extracted from electric medical records.Multivariate logistic regression analysis was performed to differentiate risk factors,and the performance of the model was evaluated using receiver operating characteristics(ROC)curves. RESULTS:Among the 371 elderly trauma patients,248(66.8%)were male,with the age of 72.5±6.8 years,median injury severity score(ISS)of 24(IQR:17-29),and Glasgow coma score(GCS)of 14(IQR:7-15).Of these patients,129(34.8%)were diagnosed with TIC,whereas 242(65.2%)were diagnosed with non-TIC.The severity scores such as ISS(25[20-34]vs.21[16-29],P<0.001)and shock index(SI),(0.90±0.66 vs.0.58±0.18,P<0.001)was significantly higher in the TIC group than in the non-TIC group.Serum calcium levels(1.97±0.19 mmol/L vs.2.15±0.16 mmol/L,P<0.001),fibrinogen levels(1.7±0.8 g/L vs.2.8±0.9 g/L,P<0.001),and base excess(BE,-4.9±4.6 mmol/L vs.-1.2±3.1 mmol/L,P<0.001)were significantly lower in the TIC group than in the non-TIC group.Multivariate logistic regression analysis revealed that ISS>16(OR:3.404,95%CI:1.471-7.880;P=0.004),SI>1(OR:5.641,95%CI:1.700-18.719;P=0.005),low BE(OR:0.868,95%CI:0.760-0.991;P=0.037),hypocalcemia(OR:0.060,95%CI:0.009-0.392;P=0.003),and hypofibrinogenemia(OR:0.266,95%CI:0.168-0.419;P<0.001)were independent risk factors for TIC in elderly trauma patients.The AUC of the prediction model included all these risk factors was 0.887(95%CI:0.851-0.923)with a sensitivity and specificity of 83.6%and 82.6%,respectively. CONCLUSION:Higher ISS(more than 16),higher SI(more than 1),acidosis,hypocalcemia,and hypofibrinogenemia emerged as independent risk factors for TIC in elderly trauma patients.