Effectiveness and Safety of Regorafenib and TAS-102 in Patients with Metastatic Colorectal Cancer: A Nationwide Population-Based Study in Taiwan.

Purpose: This study aimed to examine the real-world effectiveness and safety of regorafenib and trifluridine/tipiracil (TAS-102) in metastatic colorectal cancer (mCRC) patients in Taiwan.

Materials And Methods: Data were extracted from Taiwan's National Health Insurance Research Database to evaluate the clinical outcomes of mCRC patients treated with either regorafenib or TAS-102 between 2016 and 2019. Overall survival (OS) was compared using Kaplan-Meier curves and Cox's proportional hazard models, adjusting for age, gender, Quan-CCI score, liver metastases, number of metastatic sites, and the use of anti-EGFR medications.

Low antiviral uptake of nirmatrelvir/ritonavir and molnupiravir in adult patients with COVID-19 in Taiwan in 2022.

Background: Antivirals are effective in reducing hospitalisation and death in mild-to-moderate coronavirus 2019 (COVID-19) patients. We estimated the antiviral uptake of nirmatrelvir/ritonavir and molnupiravir in adult patients with a syndrome coronavirus 2 (SARS-CoV-2) infection during the Emergency Use Authorization (EUA) period in Taiwan.

Methods: A retrospective cohort study was conducted in Taiwan between January 2022 and December 2022.

Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.

Background: The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences.

Objective: This study aimed to develop a personalized predictive model, using artificial intelligence, to assess the 5-year and 10-year dementia risk among patients with type 2 diabetes mellitus (T2DM) who are prescribed antidiabetic medications.

Methods: This retrospective multicenter study used data from the Taipei Medical University Clinical Research Database, which comprises electronic medical records from 3 hospitals in Taiwan.

Comprehensive Evaluation of the Cardiovascular Protective Effects of Sodium-Glucose Cotransporter 2 Inhibitors in Patients with Advanced Chronic Kidney Disease: A Real-World Evidence.

Introduction: Diabetes, kidney disease, and cardiovascular disease have complex interactions and coexistences that significantly worsen a patient's overall health. Previous research results have shown that SGLT2i hypoglycemic drugs can not only effectively control blood sugar in diabetic patients but also protect the kidneys and heart. This study further focuses on diabetic patients with kidney disease to explore the effectiveness of using SGLT2i hypoglycemic drugs in avoiding heart-related complications or death.

Exploring disparities of teleconsultation readiness: A comparative analysis of healthcare facilities in Indonesia.

Objectives: To investigate the implementation of teleconsultation and assess the level of readiness for its adoption among various types of healthcare facilities.

Methods: This cross-sectional study involved medical doctors working in a public hospital, a private hospital, and community health centers in Yogyakarta, Indonesia. We recruited 29 medical specialists from various departments in two hospitals and 27 heads of community health centers.

Anti-osteoporosis drugs reduce mortality in cancer patients: A national cohort study of elderly with vertebral fractures.

Introduction: The most prevalent type of fragility fractures is osteoporotic vertebral fractures (OVFs). However, only a few studies have examined the relationship between anti-osteoporosis treatments and malignancy-related mortality following an OVF. The goal of this study is to determine the effect of anti-osteoporosis therapy on mortality in OVF patients with and without cancer.

Cost-effectiveness analysis of granulocyte colony-stimulating factors for the prophylaxis of chemotherapy-induced febrile neutropenia in patients with breast cancer in Taiwan.

Objectives: To examine the cost-effectiveness of using granulocyte colony-stimulating factor (G-CSF) for primary or secondary prophylaxis in patients with breast cancer from the perspective of Taiwan's National Health Insurance Administration.

Methods: A Markov model was constructed to simulate the events that may occur during and after a high-risk chemotherapy treatment. Various G-CSF prophylaxis strategies and medications were compared in the model.

Taipei Medical University Clinical Research Database: a collaborative hospital EHR database aligned with international common data standards.

Objective: The objective of this paper is to provide a comprehensive overview of the development and features of the Taipei Medical University Clinical Research Database (TMUCRD), a repository of real-world data (RWD) derived from electronic health records (EHRs) and other sources.

Methods: TMUCRD was developed by integrating EHRs from three affiliated hospitals, including Taipei Medical University Hospital, Wan-Fang Hospital and Shuang-Ho Hospital. The data cover over 15 years and include diverse patient care information.

Machine-Learning Based Risk Assessment for Cancer Therapy-Related Cardiac Adverse Events Among Breast Cancer Patients.

The study aims to develop machine-learning models to predict cardiac adverse events in female breast cancer patients who receive adjuvant therapy. We selected breast cancer patients from a retrospective dataset of the Taipei Medical University Clinical Research Database and Taiwan Cancer Registry between January 2004 and December 2020. Patients were monitored at the date of prescribed chemo- and/or -target therapies until cardiac adverse events occurred during a year.

Unveiling the future of COVID-19 patient care: groundbreaking prediction models for severe outcomes or mortality in hospitalized cases.

Background: Previous studies have identified COVID-19 risk factors, such as age and chronic health conditions, linked to severe outcomes and mortality. However, accurately predicting severe illness in COVID-19 patients remains challenging, lacking precise methods.

Objective: This study aimed to leverage clinical real-world data and multiple machine-learning algorithms to formulate innovative predictive models for assessing the risk of severe outcomes or mortality in hospitalized patients with COVID-19.

Near infrared imaging system for preventing blood vision obstruction in endoscopy.

Spinal endoscopy procedure is commonly used in the diagnosis and treatment of various health problems and is effective. Bleeding is one of the most common complications of spinal endoscopy procedures. Blood vision obstruction (BVO), that is, obstruction of the endoscopic camera lens caused by the accumulation of blood in the surgical field, is a serious problem in endoscopic procedures.

A novel prediction model of the risk of pancreatic cancer among diabetes patients using multiple clinical data and machine learning.

Introduction: Pancreatic cancer is associated with poor prognosis. Considering the increased global incidence of diabetes cases and that individuals with diabetes are considered a high-risk subpopulation for pancreatic cancer, it is critical to detect the risk of pancreatic cancer within populations of person living = with diabetes. This study aimed to develop a novel prediction model for pancreatic cancer risk among patients with diabetes, using = a real-world database containing clinical features and employing numerous artificial intelligent approach algorithms.

Machine learning approaches for predicting 5-year breast cancer survival: A multicenter study.

The study used clinical data to develop a prediction model for breast cancer survival. Breast cancer prognostic factors were explored using machine learning techniques. We conducted a retrospective study using data from the Taipei Medical University Clinical Research Database, which contains electronic medical records from three affiliated hospitals in Taiwan.

Prescription patterns of granulocyte colony-stimulating factors in patients with breast cancer: A real-world study.

Background And Objectives: Myelosuppressive chemotherapy is effective for breast cancer but carries a potential risk of febrile neutropenia (FN). Clinical practice guidelines have recommended prophylaxis with granulocyte colony-stimulating factor (G-CSF) to reduce the incidence of FN in patients receiving chemotherapy. We aimed to examine the use of G-CSFs for primary prophylaxis for FN and to see whether it follows the guidelines.

Emotion recognition in doctor-patient interactions from real-world clinical video database: Initial development of artificial empathy.

Background And Objective: The promising use of artificial intelligence (AI) to emulate human empathy may help a physician engage with a more empathic doctor-patient relationship. This study demonstrates the application of artificial empathy based on facial emotion recognition to evaluate doctor-patient relationships in clinical practice.

Methods: A prospective study used recorded video data of doctor-patient clinical encounters in dermatology outpatient clinics, Taipei Municipal Wanfang Hospital, and Taipei Medical University Hospital collected from March to December 2019.

Advantages of DES over BMS in Preventing the Risk of Myocardial Infarction, Ischemic Stroke, and Mortality in Various Populations.

Previous studies have demonstrated that drug-eluting stents (DESs) are more effective than bare metal stents (BMSs) in reducing the risk of myocardial infarction in the short term, but the long-term preventive benefits for myocardial infarction, ischemic stroke, and mortality are not clear. This study deeply analyzed the long-term (within 3 years) advantages of the use of DESs in preventing the risk of myocardial infarction, ischemic stroke, and mortality in various populations compared with those of using BMSs. This was a retrospective observational cohort study.