1.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
2.A Case Report of Lupus Nephritis Initially Presenting As Membranous Nephropathy Treated With Sequential Obinutuzumab and Belimumab
Xin LEI ; Nan SHI ; Xiabing LANG ; Xiaohan HUANG ; Fei HAN
Medical Journal of Peking Union Medical College Hospital 2026;17(2):382-388
This article reports a case of an elderly male patient presenting with nephrotic syndrome. Renal biopsy pathology indicated membranous nephropathy, with both renal tissue staining for M-type phospholipase A2 receptor (PLA2R) and serum anti-PLA2R antibodies being negative. Nephrotic syndrome achieved remission following treatment with prednisone combined with tacrolimus; however, the patient relapsed during tacrolimus maintenance therapy. Subsequent laboratory evaluation revealed positive anti-nuclear antibodies and anti-double-stranded DNA antibodies, accompanied by decreased complement levels. Exostosin 1 and Exostosin 2 staining performed on the initial renal biopsy specimen yielded positive results, leading to a diagnosis of lupus nephritis. Due to the patient's history of rituximab-related allergic reactions, pulmonary infection, and acute kidney injury, the subsequent treatment regimen consisted of obinutuzumab sequentially combined with belimumab, in addition to prednisone 10 mg/d. During the two-year follow-up period, the patient's anti-double-stranded DNA antibodies converted to negative, complement levels normalized, proteinuria achieved complete remission, and no adverse events such as severe infection occurred. This article reviews the diagnosis, treatment, and relevant literature for this case, aiming to provide clinical insights for the early diagnosis and selection of therapeutic strategies for similar patients.
3.Three-dimensional Electrical Impedance Tomography for Monitoring Gastric Hemorrhage
Zi-Han ZHAO ; Bo SUN ; Jing-Shi HUANG ; Zhi-Wei LI ; Yang WU ; Nan LI ; Jia-Feng YAO ; Tong ZHAO
Progress in Biochemistry and Biophysics 2026;53(4):1062-1075
ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.
4.Establishment and validation of a model for femoral head necrosis after internal fixation of femoral neck fracture using logistic regression and SHAP analysis
Long LIAO ; Zepeng ZHAO ; Zongyuan LI ; Qinglong YU ; Tao ZHANG ; Jinyuan TANG ; Nan YE ; Han XU ; Bo SHI
Chinese Journal of Tissue Engineering Research 2026;30(3):626-633
BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95%Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2%and a specificity of 87.6%,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1%to 92%,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.
5.Establishment and validation of a model for femoral head necrosis after internal fixation of femoral neck fracture using logistic regression and SHAP analysis
Long LIAO ; Zepeng ZHAO ; Zongyuan LI ; Qinglong YU ; Tao ZHANG ; Jinyuan TANG ; Nan YE ; Han XU ; Bo SHI
Chinese Journal of Tissue Engineering Research 2026;30(3):626-633
BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95%Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2%and a specificity of 87.6%,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1%to 92%,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.
6.A Nomogram for End-Stage Renal Disease Prediction in Patients with Type 2 Diabetes Mellitus: A Nationwide Cohort Study in Korea
Inha JUNG ; Bong-Seong KIM ; So Young PARK ; Da Young LEE ; Ji Hee YU ; Ji A SEO ; Kyung-Do HAN ; Nan Hee KIM
Endocrinology and Metabolism 2026;41(2):245-255
Background:
Despite the rising incidence of end-stage renal disease (ESRD) among individuals with type 2 diabetes mellitus (T2DM) in Korea, no predictive model or nomogram has been developed using a nationwide cohort. In this study, we developed a nomogram to predict the long-term risk of ESRD in patients with T2DM using a large-scale, population-based Korean database.
Methods:
Using the Korean National Health Insurance Database, patients with T2DM who underwent health examinations between 2015 and 2016 were assigned as development (n=1,744,277) and validation (n=747,407) cohorts. New ESRD cases were identified using codes for renal replacement therapy. A Cox proportional hazards regression model was used to derive a risk-scoring system, and 13 variables were selected. A risk score nomogram was then created to estimate the risk of ESRD.
Results:
In the development cohort, 8,631 patients with T2DM developed ESRD during a follow-up period of 4.8±0.9 years. After multivariable adjustment, significant predictors of ESRD included male sex, current smoking, physical inactivity, low income, low body mass index, hypertension, low-density lipoprotein cholesterol ≥160 mg/dL, chronic kidney disease, insulin use, and longer duration of T2DM. A final nomogram incorporating 13 variables was developed to estimate the individual probability of ESRD. The concordance index for ESRD prediction in the validation cohort was 0.906 (95% confidence interval, 0.9 to 0.912).
Conclusion
This 13-variable nomogram provides a simple tool for identifying patients with T2DM at high risk of ESRD and may aid in early intervention.
7.Statistical analysis of vector monitoring in port areas of Shandong Province from 2017 to 2023
Huan-mei HAN ; Tao ZHANG ; Zhi-ping SU ; Rong-jun YAN ; Wei HUANG ; Wen-wen ZHANG
Acta Parasitologica et Medica Entomologica Sinica 2026;33(2):121-127
Objective To provide a scientific basis for vector prevention and control in port areas, vector monitoring has been conducted continuously to characterize the composition, density, and seasonal fluctuations of vectors across 21 port-areas of Shandong province from 2017 to 2023. Methods In accordance with the Regional Vector Monitoring Plan for Frontier Ports, vector surveillance of mosquitoes, flies, cockroaches, rodents, and other disease vectors was performed. Data were analyzed to describe vector community composition and identify seasonal fluctuations. Results A total of 601 rodents belonging to 1 family, 4 genera, and 4 species were captured. Three dominant rodent species inhabit port areas. In addition, 88 104 mosquitoes were captured and classified into 3 subfamilies, 4 genera, and 12 species; 38 959 flies were trapped and classified into 8 families,31 genera, and 51 species, including 9 dominant fly species in port-areas; and 54 672 captured cockroaches were classified into 2 families,4 genera, and 4 species, with Blattella germanica as the dominant species. Conclusions Significant vector community changes(P<0.005)have been identified after the epidemic. To improve the pertinence and efficacy of port health quarantine work, continuous and strong attention should be paid to vector compositions and population densities at Shandong ports.
8.Research Progress of Multidimensional Immunomodulatory Factor ZG16 in Enhancing Antitumor Immune Responses
Longyan NIE ; Xiongchao FANG ; Peng GAO ; Zhuo HAN ; Zhibo FENG ; Tianshuo SONG ; Xiaomeng HAN ; Nan WANG
Cancer Research on Prevention and Treatment 2026;53(9):727-732
The introduction of immunotherapy has changed the traditional paradigms in cancer treatment and has demonstrated substantial clinical benefits across various malignancies. However, this progress is accompanied with emerging challenges, such as immune evasion and low response rates to immunotherapy. As an immunomodulatory molecule, zymogen granule protein 16 (ZG16) plays a crucial role in immunotherapy by inhibiting the binding of programmed death 1 (PD-1) to its ligand PD-L1, preventing immune evasion and restoring the immune system's ability to recognize and eliminate tumor cells. ZG16 is downregulated in multiple gastrointestinal tumors, and its regulatory mechanisms vary depending on the tumor type. ZG16 expression is closely associated with patient prognosis, and it has been identified as a favorable prognostic marker in colorectal cancer. This article provides a systematic overview of the structural characteristics, expression regulation mechanisms, and antitumor immune functions of ZG16.
9.Application and effectiveness evaluation of a streamlined case teaching method based on Occam's Razor principle in ophthalmology education
Xiaona* NING ; Chenjun* GUO ; Jing HAN ; Wei LEI ; Jinbo ZHAO ; Nan MA
International Eye Science 2026;26(11):2026-2031
AIM: To address the problem of cognitive overload and deviation from core teaching objectives caused by information redundancy in traditional case-based teaching in ophthalmology, Occam's Razor principle was innovatively applied to construct a set of streamlined case-based teaching resources, and their effectiveness was subsequently validated.METHODS:This was a prospective randomized controlled trial. Intern students from the 2019 and 2020 cohorts of the five-year clinical medicine program who completed their ophthalmology clerkship at the Department of Ophthalmology, Tangdu Hospital, Air Force Medical University between June 2023 and May 2025 were enrolled. By using a random number table, they were randomly assigned to an experimental group and a control group. Cases refined by Occam's Razor principle(removing irrelevant information and focusing on core principles, clinical reasoning, and the diagnostic and therapeutic workflow)were adopted for the experimental group, whereas the original complete cases were used for the control group. Teaching effectiveness was assessed through knowledge tests, classroom performance evaluation, teaching case assessment, and student satisfaction.RESULTS:Totally 120 students were included in this study and all of them completed the research. There were 60 students in the experimental group(43 males and 17 females, mean age 21.72±0.76 y)and 60 students in control group(41 males and 19 females, mean age 21.68±0.57 y)(all P>0.05). The score rates on the ocular trauma section and on the case analysis questions were significantly higher in the experimental group than in the control group(83.21%±7.96% vs 74.25%±11.01%; 84.31%±8.08% vs 67.62%±11.63%; both P<0.001). Teacher evaluations indicated that the experimental group achieved better scores than the control group in aspects such as identification of key case points and logical clinical reasoning(all P<0.001). A significantly lower cognitive load score was observed in the experimental group, whereas higher scores were obtained for clarity of case structure, thought-provoking quality, and teaching value(all P<0.001). The teaching satisfaction rate reached 95% in the experimental group, which was higher than the 83% observed in the control group(P<0.05).CONCLUSION: Refined cases guided by Occam's Razor principle can significantly reduce cognitive load, enhance medical students' efficiency in mastering core diagnostic and therapeutic principles, improve the precision of clinical reasoning, and strengthen execution of clinical procedures, thereby providing an innovative pathway for clinical teaching reform.
10.LI Diangui's Experience in Treating Vitiligo from the Perspective of Turbid Toxins Latent in the Collaterals
Yuxin ZHANG ; Nan JIANG ; Qian YANG ; Wenzhao HAN ; Jiaqi LI ; Wenwen ZHOU ; Weiye LI ; Xiang LIU ;
Journal of Traditional Chinese Medicine 2026;67(21):2275-2279
This paper summarizes Professor LI Diangui's experience in treating vitiligo from the perspective of turbid toxins latent in the collaterals. Based on the theory of turbid-toxin, professor LI proposes that turbid toxins latent in the collaterals and qi-blood disharmony constitute the core pathogenesis of the onset and progression of the disease, and that resolving turbidity and removing toxins while harmonizing qi and blood should serve as the fundamental therapeutic principles. In clinical practice, treatment is tailored according to the evolution of the pathogenesis and syndrome differentiation. When stagnation of qi movement leads to the endogenous accumulation of turbid pathogens, treatment focuses on relieving constraint, dispersing turbidity, soothing the liver, and regulating qi, with a modified self-formulated Kaiyu Sanzhuo Decoction (开郁散浊汤). When turbid pathogens overflow to the superficial tissues and obstruct the cutaneous collaterals, treatment aims to resolve blood stasis, disperse turbidity, regulate qi, and unblock the collaterals, using a modified self-formulated Tongluo Huazhuo Decoction (通络化浊汤). When deficiency of healthy qi allows toxins to remain latent and the disease becomes prolonged, treatment emphasizes reinforcing healthy qi, eliminating turbidity, tonifying qi, and nourishing blood, with a modified self-formulated Fuzheng Quzhuo Decoction (扶正祛浊汤).


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