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Yen-Hao Chen,1– 4 Wan-Ting Huang,5 Wen-Chin Lee,6 Ching-Mei Chen,5 Fu-Jen Cheng,7 Chia-Te Kung,7 Chin-Chou Wang,8 Liang-Jen Wang,9 Yu-Che Ou,10 Shau-Hsuan Li1 1Division of Hematology-Oncology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan; 2School of Medicine, College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan; 3School of Medicine, Chung Shan Medical University, Taichung, 402, Taiwan; 4Department of Nursing, School of Nursing, Fooyin University, Kaohsiung, 831, Taiwan; 5Department of Laboratory Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan; 6Division of Nephrology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan; 7Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan; 8Department of Occupational Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan; 9Department of Child and Adolescent Psychiatry, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan; 10Department of Obstetrics and Gynecology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, TaiwanCorrespondence: Shau-Hsuan Li, Division of Hematology-Oncology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung City, 833, Taiwan, Email lee.a0928@msa.hinet.netBackground: The aim of this study was to investigate the role of phthalate in patients with esophageal squamous cell carcinoma (ESCC).Methods: A total of 116 ESCC patients and 58 controls without any known histories of malignancies were enrolled. All eight urine phthalate metabolites were measured to assess phthalate levels. Clinical and urine phthalate metabolite profiles were compared between subgroups to identify differences, and the effects of phthalates on clinical ESCC outcomes were also examined.Results: The concentrations of some urine phthalate metabolites were higher in the ESCC group than in the control group, including mono-(3-carboxypropyl) phthalate (MCPP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono-n-butyl phthalate (MnBP). Higher concentrations of urine phthalate metabolites were associated with clinical T3–T4 status. Patients with higher concentration of mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono-2-ethylhexyl phthalate (MEHP), and MEOHP had lower 1-year and 2-year overall survival (OS) rates than those with lower concentrations of these metabolites in our univariate analysis. Multivariate analysis showed that urinary MEHP of ≥ 3 μg/L and clinical stage IVB were independent prognostic factors for worse OS.Conclusion: The results of our study showed that urine phthalate metabolites are elevated in ESCC patients and associated with advanced tumor stage, and that a high urinary concentration of MEHP is an independent prognostic factor of worse OS.Keywords: phthalate, esophageal cancer, squamous cell carcinoma, survival

Ting-Yu Hsu,1 Chi-Yung Cheng,1,2,* I-Min Chiu,1,2 Chun-Hung Richard Lin,2 Fu-Jen Cheng,1 Hsiu-Yung Pan,1 Yu-Jih Su,3 Chao-Jui Li1,* 1Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; 2Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan; 3Department of Internal Medicine, Division of Rheumatology, Allergy and Immunology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan*These authors contributed equally to this workCorrespondence: Chi-Yung Cheng; Chao-Jui Li, Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, 123 Ta-Pei Road, Niao-Sung, Kaohsiung, 833, Taiwan, Tel +886-7-7317123 ext. 8415, Email qzsecawsxd@gmail.com; chaojui@cgmh.org.twBackground: The global aging population presents a significant challenge, with older adults experiencing declining physical and cognitive abilities and increased vulnerability to chronic diseases and adverse health outcomes. This study aims to develop an interpretable deep learning (DL) model to predict adverse events in geriatric patients within 72 hours of hospitalization.Methods: The study used retrospective data (2017– 2020) from a major medical center in Taiwan. It included non-trauma geriatric patients who visited the emergency department and were admitted to the general ward. Data preprocessing involved collecting prognostic factors like vital signs, lab results, medical history, and clinical management. A deep feedforward neural network was developed, and performance was evaluated using accuracy, sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC). Model interpretation utilized the Shapley Additive Explanation (SHAP) technique.Results: The analysis included 127,268 patients, with 2.6% experiencing imminent intensive care unit transfer, respiratory failure, or death during hospitalization. The DL model achieved AUCs of 0.86 and 0.84 in the validation and test sets, respectively, outperforming the Sequential Organ Failure Assessment (SOFA) score. Sensitivity and specificity values ranged from 0.79 to 0.81. The SHAP technique provided insights into feature importance and interactions.Conclusion: The developed DL model demonstrated high accuracy in predicting serious adverse events in geriatric patients within 72 hours of hospitalization. It outperformed the SOFA score and provided valuable insights into the model’s decision-making process. Keywords: explainable machine learning, deep learning algorithm, adverse events, mortality