Objective:To evaluate the value of peripheral blood systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), carcinoembryonic antigen (CEA), D-dimer, and albumin (ALB) alone or their combination in the diagnosis of early-onset colorectal cancer (EOCRC).Methods:From January 1, 2023 to November 30, 2024, 104 patients with EOCRC (EOCRC group) hospitalized at Renmin Hospital of Wuhan University were enrolled. During the same period, by simple random sampling method, 104 patients with benign colorectal polyps (benign polyp group) and 104 healthy individuals for health examinations (healthy control group) from outpatient department were enrolled. The peripheral blood parameters (including neutrophil count, lymphocyte count, CEA, and others) and pathological characteristics of EOCRC (including TNM stage, tumor differentiation grade, and depth of invasion) were collected. The relationship between peripheral blood parameters and EOCRC pathological features were analyzed. Receiver operating characteristic curves (ROC) were plotted, and the area under the curve (AUC) was calculated to evaluate the diagnostic value. Multivariate logistic regression analysis was performed to analyze the peripheral blood parameters which independently correlated with EOCRC and a combined diagnostic model was established. Simple random sampling method was used to divide the subjects in the negative control group (healthy control group + benign polyp group) and positive group (EOCRC group) into a training set (218 cases) and a validation set (94 cases) at a ratio of 7∶3, and the diagnostic performance of the combined diagnostic model in the training and validation sets was assessed. Hosmer-Lemeshow test and calibration curve were used to evaluate the fit and consistency of the model. Independent sample t-test, one-way ANOVA, Mann-Whitney U test and Kruskal-Wallis H test were used for statistical analysis. Results:EOCRC group had the highest levels of SII(744.03 (473.01, 1 246.28), 437.77 (342.28, 607.47), 497.31 (385.76, 721.63)×10 9/L), NLR(2.42 (1.76, 3.94), 1.96 (1.54, 2.52), 1.91 (1.55, 2.75)), CEA (3.58 (1.96, 20.85), 1.31 (0.95, 1.93), 1.21 (0.76, 2.11) μg/L) and D-dimer (0.36 (0.20, 0.90), 0.19 (0.12, 0.28), 0.18 (0.12, 0.30) mg/L), and the lowest levels of LMR(3.51±1.56, 4.38±1.37, 4.72±1.84) and ALB(42.40 (39.90, 44.70), 44.57 (42.83, 46.25), 44.95 (43.10, 46.58) g/L) than benign polyp group and healthy control group, and the differences were statistically significant ( H=31.18, 16.21, 76.72 and 47.72, F=15.40, H=34.19; all P<0.001). In EOCRC patients, there were statistically significant differences in SII and LMR between patients with different tumor invasion depth ( Z=-2.48, t=2.31; both P<0.05), in CEA between patients with different TNM stage, with or without lymph node metastasis and distant metastasis( Z=-2.68, -2.50 and -2.65; all P<0.05), in D-dimer between patients with different TNM stage, differentiation grade, invasion depth, and with or without lymph node metastasis and distant metastasis ( Z=-2.50, -2.60, -2.06, -2.14 and -3.33; all P<0.05), and in ALB between patients with or without distant metastasis ( Z=-2.52, P=0.012).The AUC of combination of SII, NLR, LMR, CEA, D-dimer, and ALB in differential diagnosis of the healthy control group and the EOCRC group was 0.914 (95% confidence interval (95% CI): 0.870 to 0.958, P<0.001), and the AUC of the combination in differential diagnosis of the benign polyp group and the EOCRC group was 0.904 (95% CI: 0.857 to 0.950, P<0.001). The results of multivariate logistic regression analysis revealed that SII, NLR, LMR, CEA, and ALB were all independently correlated with EOCRC (all P<0.05). The diagnostic model for EOCRC was established by the combination of SII, NLR, LMR, CEA, and ALB, and the AUC of the model in the training set and validation set was 0.911 and 0.883, respectively. The Hosmer-Lemeshow goodness-of-fit test indicated good model fit ( P=0.437). Calibration curve analysis showed strong consistency between predicted probabilities and actual probabilities, and the mean absolute error was 0.015. Conclusions:SII, NLR, LMR, CEA, D-dimer, and ALB all demonstrate diagnostic value in the diagnosis of EOCRC. The combined diagnostic model based on SII, NLR, LMR, CEA, and ALB demonstrates excellent diagnostic performance, which may serve as an adjunctive diagnostic approach for EOCRC.

For rare real-world data involving off-label drug use or comorbidity-associated polypharmacy,researchers have increasingly adopted target trial emulation to investigate drug repurposing for target indications.The success of such studies hinges on rigorous trial design and strict adherence to predefined protocols and standardized pipelines.Key elements in the trial design include the precise definition of inclusion and exclusion criteria,the selection of trial and control drugs and determination of treatment allocation time,the determination of appropriate efficacy endpoints for the target indication,the identification of causal estimands,and the development of robust strategies for confounding adjustment.The execution of the trial follows a structured process:screening eligible subjects,extracting relevant drug exposure data,constructing treatment and control groups,emulating the target trial,and ultimately generating hypotheses for drug repurposing through statistical inference.Propensity score methods,including stratification,matching and weighting techniques,are critical tools for addressing confounding bias and ensuring accurate estimation of causal effects.In recent years,creative progress has been made in target trial emulation,particularly in the calculation of propensity scores.Researchers have adopted advanced machine learning techniques,to enhance variable selection and have actively explored the use of innovative methods of digital intelligence technology like classification and regression trees,support vector machines,and deep learning for the application of propensity score calculation.Target trial emulation based on real-world data has achieved remarkable advancements in drug repurposing,demonstrating broad application prospects,particularly in cardiovascular diseases,metabolic disorders,Alzheimer's disease,and cancer.

Objective:To explore the clinical utility of peripheral immune-inflammatory markers in predicting late-life depression with cognitive impairment(LLD+ CI + ). Methods:A cross-sectional study was conducted between January 2020 and December 2021, collecting demographic data, peripheral blood inflammatory markers, and cognitive function scores from 40 patients with LLD+ CI + , 38 patients with late-life depression without cognitive impairment(LLD+ CI -), and 26 healthy controls(HCs). Logistic regression analysis and receiver operating characteristic(ROC)curve analysis were employed to assess the value of peripheral blood inflammatory markers in differentiating LLD+ CI + . Results:Patients with LLD+ CI + exhibited significantly different levels of lymphocytes, C-reactive protein(CRP), systemic immune-inflammation index(SII), systemic inflammation response index(SIRI), neutrophil-to-high-density lipoprotein cholesterol ratio(NHR), and neutrophil-to-lymphocyte ratio (NLR)compared with the LLD+ CI - group and the HGs group( F=4.000, 11.642, 13.541, 10.441, 6.623, 4.193; P=0.022, 0.003, 0.001, 0.005, 0.036, 0.018). The multivariate logistic regression analysis of factors influencing LLD+ CI + revealed that elevated levels of CRP( OR=4.933, 95% CI: 1.385-17.563, P=0.014), SII( OR=5.534, 95% CI: 1.336-22.927, P=0.018), and NLR( OR=3.386, 95% CI: 1.470-7.797, P=0.004)constitute risk factors for geriatric depression with cognitive impairment, while an increased lymphocyte count( OR=0.206, 95% CI: 0.058-0.725, P=0.014)serves as a protective factor.Further analysis identified CRP, lymphocytes, SII, and NLR as significant predictors for LLD+ CI + , with areas under the curve (AUC) values of 0.849(95% CI: 0.760-0.934), 0.847(95% CI: 0.761-0.933), 0.860(95% CI: 0.777-0.943), and 0.857(95% CI: 0.777-0.938), respectively, in distinguishing LLD with or without cognitive impairment. Conclusions:Peripheral immune-inflammatory markers represent an economical and effective approach for investigating the pathophysiological changes and predictive factors associated with LLD+ CI + .These findings provide valuable insights into the underlying mechanisms and potential therapeutic avenues.

Objective To analyze the causes and compensation characteristics of medical damage disputes in Anhui Province in recent years,and provide reference suggestions for effectively controlling and reducing the incidence of medical errors and doctor-patient conflicts.Methods The 1 876 cases of medical damage disputes in Anhui Province from 2017 to 2022 were included in the judgment documents network,and their occurrence years and causes of disputes were analyzed.Results The number of medical malpractice cases did not decrease significantly,and the average amount of compensation continued to increase;the top three causes of disputes were improper treatment or surgery(54.6%),and the average first place of actual compensation was improper medication or adverse drug reactions,and in terms of hospital level,1 009 cases(53.8%)were concentrated in tertiary public hospitals,the average actual compensation amount of private hospitals ranked first;the top three departments were surgery(44.62%);the highest incidence of damage was death(40.2%),and the average compensation amount for first-class disability was the highest.Hospitals were mainly responsible for secondary responsibilities(38.7%).Conclusion The contradiction between doctors and patients is still serious,so it is necessary to promote the construction of tight medical association and medical community,guide the allocation of medical resources,pay attention to risk sharing and management optimization,and reduce the incidence of medical damage disputes.

Objective:To establish graded forecast models of pollen concentration in spring and summer-autumn in northern China, based on long-term data of pollen and allergic rhinitis (AR) medical visits in 8 cities of northern China.Methods:Pollen concentration and the characteristics of AR patients from 8 cities of northern China, including Beijing, Baotou, Hohhot, Xi′an, Xining, Cangzhou, Liaocheng and Zibo, were analyzed. Spearman′s correlation was used to examine the relationship between pollen concentration and daily AR patient visits. A pollen concentration grading was establish, and a pollen forecast model was created using the eXtreme gradient boosting (XGBoost) algorithm. The model incorporated meteorological factors and the 3-day moving average of pollen concentrations.Results:The spring pollen period started early and lasted long in Beijing and Xi ′an, while the summer-autumn pollen period started earlier and persisted longer in Xining, Baotou and Hohhot. During summer-autumn pollen period, and the spring period in most cities (except Baotou and Cangzhou), average daily patient visits were significantly higher than those in non-pollen periods. A strong correlation was observed between daily AR patient visits and the 3-day moving average of pollen concentrations in both the spring and summer-autumn periods across all cities. Based on the correlation, a pollen concentration grading standard of northern China was established. The accuracy evaluation of pollen concentration prediction model showed that the percentage of forecasts with either completely accurate or within one level difference exceeded 91% in spring and 95% in summer-autumn. The most important predictive variable in the model was the pollen level from previous day, followed by the temperature and humidity.Conclusion:The grading prediction model for pollen concentration provides guidance for AR patients in term of travel, early defense and treatment, as well as the determining medication schedules for clinical drug research and specific immunotherapy.

Objective:To investigate the accuracy and clinical utility of a newly designed acetabular bone defect classification system based on the ischial-gluteal pillar in assessing the severity of acetabular bone defects and guiding hip revision surgery.Methods:A retrospective analysis was conducted on 474 patients who underwent hip revision surgery for prosthetic loosening after total hip arthroplasty at our institution from January 2010 to December 2020, including 296 males and 178 females with a mean age of 70.4±8.9 years (range: 52-86 years). The accuracy of our classification system in guiding surgical procedures was evaluated by comparing preoperative defect classifications with intraoperative findings. Clinical outcomes were evaluated using preoperative and final follow-up Harris hip scores (HHS) and Oxford hip scores (OHS), as well as the incidence of complications.Results:Preoperative classifications included 143 Type I, 192 Type II (Type IIa: 86 cases, Type IIb: 59 cases, Type IIc: 47 cases), 93 Type III (Type IIIa: 54 cases, Type IIIb: 27 cases, Type IIIc: 12 cases), and 46 Type IV cases (Type IVa: 32 cases, Type IVb: 9 cases, Type IVc: 5 cases). Compared with intraoperative findings, classification accuracy was 99.3% for Type I (1 errors), 98.4% for Type II (3 errors), 97.8% for Type III (2 errors), and 97.8% for Type IV (1 misclassified as Type III). The mean follow-up was 5.8±4.4 years (range: 2-12 years). At final follow-up, mean HHS improved from 36.65±10.27 to 91.36±7.53, and mean OHS increased from 11.35±4.36 to 44.6±5.27 with significant difference ( P<0.001). Complications included one Type IV periprosthetic infection, one Type II hip dislocation, one Type I and two Type IV re-revisions (due to femoral loosening or graft resorption), one Type II and one Type III death unrelated to surgery, and one Type I postoperative thigh hematoma. No neurovascular injuries occurred. Conclusions:This novel 3D acetabular bone defect classification system, based on ischial-gluteal pillar integrity, provides accurate preoperative assessment and effectively guides surgical planning. Its application demonstrates favorable mid-term outcomes in hip revision surgery.

Objective:To investigate the accuracy and clinical utility of a newly designed acetabular bone defect classification system based on the ischial-gluteal pillar in assessing the severity of acetabular bone defects and guiding hip revision surgery.Methods:A retrospective analysis was conducted on 474 patients who underwent hip revision surgery for prosthetic loosening after total hip arthroplasty at our institution from January 2010 to December 2020, including 296 males and 178 females with a mean age of 70.4±8.9 years (range: 52-86 years). The accuracy of our classification system in guiding surgical procedures was evaluated by comparing preoperative defect classifications with intraoperative findings. Clinical outcomes were evaluated using preoperative and final follow-up Harris hip scores (HHS) and Oxford hip scores (OHS), as well as the incidence of complications.Results:Preoperative classifications included 143 Type I, 192 Type II (Type IIa: 86 cases, Type IIb: 59 cases, Type IIc: 47 cases), 93 Type III (Type IIIa: 54 cases, Type IIIb: 27 cases, Type IIIc: 12 cases), and 46 Type IV cases (Type IVa: 32 cases, Type IVb: 9 cases, Type IVc: 5 cases). Compared with intraoperative findings, classification accuracy was 99.3% for Type I (1 errors), 98.4% for Type II (3 errors), 97.8% for Type III (2 errors), and 97.8% for Type IV (1 misclassified as Type III). The mean follow-up was 5.8±4.4 years (range: 2-12 years). At final follow-up, mean HHS improved from 36.65±10.27 to 91.36±7.53, and mean OHS increased from 11.35±4.36 to 44.6±5.27 with significant difference ( P<0.001). Complications included one Type IV periprosthetic infection, one Type II hip dislocation, one Type I and two Type IV re-revisions (due to femoral loosening or graft resorption), one Type II and one Type III death unrelated to surgery, and one Type I postoperative thigh hematoma. No neurovascular injuries occurred. Conclusions:This novel 3D acetabular bone defect classification system, based on ischial-gluteal pillar integrity, provides accurate preoperative assessment and effectively guides surgical planning. Its application demonstrates favorable mid-term outcomes in hip revision surgery.

For rare real-world data involving off-label drug use or comorbidity-associated polypharmacy,researchers have increasingly adopted target trial emulation to investigate drug repurposing for target indications.The success of such studies hinges on rigorous trial design and strict adherence to predefined protocols and standardized pipelines.Key elements in the trial design include the precise definition of inclusion and exclusion criteria,the selection of trial and control drugs and determination of treatment allocation time,the determination of appropriate efficacy endpoints for the target indication,the identification of causal estimands,and the development of robust strategies for confounding adjustment.The execution of the trial follows a structured process:screening eligible subjects,extracting relevant drug exposure data,constructing treatment and control groups,emulating the target trial,and ultimately generating hypotheses for drug repurposing through statistical inference.Propensity score methods,including stratification,matching and weighting techniques,are critical tools for addressing confounding bias and ensuring accurate estimation of causal effects.In recent years,creative progress has been made in target trial emulation,particularly in the calculation of propensity scores.Researchers have adopted advanced machine learning techniques,to enhance variable selection and have actively explored the use of innovative methods of digital intelligence technology like classification and regression trees,support vector machines,and deep learning for the application of propensity score calculation.Target trial emulation based on real-world data has achieved remarkable advancements in drug repurposing,demonstrating broad application prospects,particularly in cardiovascular diseases,metabolic disorders,Alzheimer's disease,and cancer.

Objective:To explore the clinical utility of peripheral immune-inflammatory markers in predicting late-life depression with cognitive impairment(LLD+ CI + ). Methods:A cross-sectional study was conducted between January 2020 and December 2021, collecting demographic data, peripheral blood inflammatory markers, and cognitive function scores from 40 patients with LLD+ CI + , 38 patients with late-life depression without cognitive impairment(LLD+ CI -), and 26 healthy controls(HCs). Logistic regression analysis and receiver operating characteristic(ROC)curve analysis were employed to assess the value of peripheral blood inflammatory markers in differentiating LLD+ CI + . Results:Patients with LLD+ CI + exhibited significantly different levels of lymphocytes, C-reactive protein(CRP), systemic immune-inflammation index(SII), systemic inflammation response index(SIRI), neutrophil-to-high-density lipoprotein cholesterol ratio(NHR), and neutrophil-to-lymphocyte ratio (NLR)compared with the LLD+ CI - group and the HGs group( F=4.000, 11.642, 13.541, 10.441, 6.623, 4.193; P=0.022, 0.003, 0.001, 0.005, 0.036, 0.018). The multivariate logistic regression analysis of factors influencing LLD+ CI + revealed that elevated levels of CRP( OR=4.933, 95% CI: 1.385-17.563, P=0.014), SII( OR=5.534, 95% CI: 1.336-22.927, P=0.018), and NLR( OR=3.386, 95% CI: 1.470-7.797, P=0.004)constitute risk factors for geriatric depression with cognitive impairment, while an increased lymphocyte count( OR=0.206, 95% CI: 0.058-0.725, P=0.014)serves as a protective factor.Further analysis identified CRP, lymphocytes, SII, and NLR as significant predictors for LLD+ CI + , with areas under the curve (AUC) values of 0.849(95% CI: 0.760-0.934), 0.847(95% CI: 0.761-0.933), 0.860(95% CI: 0.777-0.943), and 0.857(95% CI: 0.777-0.938), respectively, in distinguishing LLD with or without cognitive impairment. Conclusions:Peripheral immune-inflammatory markers represent an economical and effective approach for investigating the pathophysiological changes and predictive factors associated with LLD+ CI + .These findings provide valuable insights into the underlying mechanisms and potential therapeutic avenues.

Objective To analyze the causes and compensation characteristics of medical damage disputes in Anhui Province in recent years,and provide reference suggestions for effectively controlling and reducing the incidence of medical errors and doctor-patient conflicts.Methods The 1 876 cases of medical damage disputes in Anhui Province from 2017 to 2022 were included in the judgment documents network,and their occurrence years and causes of disputes were analyzed.Results The number of medical malpractice cases did not decrease significantly,and the average amount of compensation continued to increase;the top three causes of disputes were improper treatment or surgery(54.6%),and the average first place of actual compensation was improper medication or adverse drug reactions,and in terms of hospital level,1 009 cases(53.8%)were concentrated in tertiary public hospitals,the average actual compensation amount of private hospitals ranked first;the top three departments were surgery(44.62%);the highest incidence of damage was death(40.2%),and the average compensation amount for first-class disability was the highest.Hospitals were mainly responsible for secondary responsibilities(38.7%).Conclusion The contradiction between doctors and patients is still serious,so it is necessary to promote the construction of tight medical association and medical community,guide the allocation of medical resources,pay attention to risk sharing and management optimization,and reduce the incidence of medical damage disputes.