INAHTA member agency stories of engaging, adaptable, and impactful HTA.

Health technology assessment (HTA) agencies assess evidence to support decision making about which technologies to provide and pay for in the health system. HTA impact is understood as the influence that HTA report findings can have in the health system, including impacts on reimbursement decisions, changes to health outcomes, or broader system or societal impacts. The International Network of Agencies for Health Technology Assessment (INAHTA) is a global network of publicly funded HTA agencies.

Annonaceous acetogenins mimic AA005 targets mitochondrial trifunctional enzyme alpha subunit to treat obesity in male mice.

Obesity and related diseases pose a major health risk, yet current anti-obesity drugs inadequately addressing clinical needs. Here we show AA005, an annonaceous acetogenin mimic, resists obesity induced by high-fat diets and leptin mutations at non-toxic doses, with the alpha subunit of the mitochondrial trifunctional protein (HADHA) as a target identified through proteomics and in vitro validation. Pharmacokinetic analysis shows AA005 enriches in adipose tissue, prompting the creation of adipose-specific Hadha-deficient mice.

The risk factors determined by four machine learning methods for the change of difference of bone mineral density in post-menopausal women after three years follow-up.

The prevalence of osteoporosis has drastically increased recently. It is not only the most frequent but is also a major global public health problem due to its high morbidity. There are many risk factors associated with osteoporosis were identified.

Comparison of multiple linear regression and machine learning methods in predicting cognitive function in older Chinese type 2 diabetes patients.

Introduction: The prevalence of type 2 diabetes (T2D) has increased dramatically in recent decades, and there are increasing indications that dementia is related to T2D. Previous attempts to analyze such relationships principally relied on traditional multiple linear regression (MLR). However, recently developed machine learning methods (Mach-L) outperform MLR in capturing non-linear relationships.

Comparison between multiple logistic regression and machine learning methods in prediction of abnormal thallium scans in type 2 diabetes.

Background: The prevalence of type 2 diabetes (T2D) has been increasing dramatically in recent decades, and 47.5% of T2D patients will die of cardiovascular disease. Thallium-201 myocardial perfusion scan (MPS) is a precise and non-invasive method to detect coronary artery disease (CAD).

Adaptation behaviors modify the effects of body fat on heat-related symptoms among Taiwanese elderly.

Background: The aging process increases body fat and susceptibility to heat-related illnesses. The relationship between body composition and symptoms associated with exposure to extreme heat among the elderly is unclear. Additionally, the influence of individual adaptive behaviors in mitigating these risks has not been adequately explored.

Incidence, Risk Factors and Management of Postoperative Complications in Horizontal Strabismus Surgery.

Objective: To report the incidence, risk factors and management of postoperative complications after horizontal strabismus surgery.

Design: Retrospective Cohort study.

Participants: The study assessed 1,273 patients with 1,035 cases of exotropia and 238 cases of esotropia, with a minimum 18-month follow-up.

Ethical and legal considerations in social media research for health technology assessment: conclusions from a scoping review.

Objectives: The objective was to identify and describe the published guidance and current academic discourse of ethical issues and standards related to the use of for generating patient insights for the use by health technology assessment (HTA) or health policy decisions.

Methods: A scoping review of the literature was conducted in PubMed and Embase and identified 935 potential references published between January 2017 and June 2021. After title and abstract screening by three reviewers, 40 publications were included, the relevant information was extracted and data were collected in a mind map, which was then used to structure the output of the review.

Using social media research in health technology assessment: stakeholder perspectives and scoping review.

Objectives: The aim of this initiative was to examine collaboratively, in a multi-stakeholder team (health technology assessment (HTA) practitioners with patient involvement expertise, health technology industry, patient advocates, health policy experts, patient engagement experts), whether evidence generated through social media research (SMR) fills current information gaps relating to insights on specific aspects of patient experiences, preferences, or patient needs and delivers additional value to HTA.

Methods: The framing of the project was done in a co-creative, deliberative multi-stakeholder process. Challenge and refinement happened through discussions with 25 independent stakeholders from HTA bodies, industry, academia, and patient advocacy.

Comparison between linear regression and four different machine learning methods in selecting risk factors for osteoporosis in a Chinese female aged cohort.

Background: Population aging is emerging as an increasingly acute challenge for countries around the world. One particular manifestation of this phenomenon is the impact of osteoporosis on individuals and national health systems. Previous studies of risk factors for osteoporosis were conducted using traditional statistical methods, but more recent efforts have turned to machine learning approaches.

Changes in insulin resistance, glucose effectiveness, and first and second phases of insulin secretion in women aged 45-60 years old in Taiwan.

Background: In women after menopause, the incidence of diabetes mellitus increases. Increased insulin resistance (IR), decreased glucose effectiveness (GE), and the first and second phases of insulin secretion (FPIS and SPIS), are the four most important factors that trigger glucose intolerance and diabetes (diabetogenic factor [DF]). In the cross-sectional study, we enrolled nondiabetic women between the ages of 45 and 60 years to observe the changes in DFs during the perimenopausal period and to elucidate the underlying mechanisms of diabetes in menopausal women.

[Determination of three plant growth regulators in and by three-phase hollow fiber liquid phase microextraction- high performance liquid chromatography].

() and () are precious raw materials for traditional Chinese medicine. The growing demand for and cannot be met by current production techniques. Hence, the widespread artificial cultivation of and using substantial amounts of plant growth regulators (PGRs) has emerged.

Aging Affects Insulin Resistance, Insulin Secretion, and Glucose Effectiveness in Subjects with Normal Blood Glucose and Body Weight.

Aim: Several studies have demonstrated that factors including diabetes, including insulin resistance (IR), glucose effectiveness (GE), and the first and second phase of insulin secretion (FPIS, SPIS) could easily be calculated using basic characteristics and biochemistry profiles. Aging is accompanied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging in the different phases of insulin secretion (ISEC), i.

Using Machine Learning to Predict Abnormal Carotid Intima-Media Thickness in Type 2 Diabetes.

Carotid intima-media thickness (c-IMT) is a reliable risk factor for cardiovascular disease risk in type 2 diabetes (T2D) patients. The present study aimed to compare the effectiveness of different machine learning methods and traditional multiple logistic regression in predicting c-IMT using baseline features and to establish the most significant risk factors in a T2D cohort. We followed up with 924 patients with T2D for four years, with 75% of the participants used for model development.

Gasdermin A Is Required for Epidermal Cornification during Skin Barrier Regeneration and in an Atopic Dermatitis-Like Model.

Atopic dermatitis is featured with impaired skin barrier. The stratum corneum and the intercellular tight junctions constitute the permeability barrier, which is essential to protect water loss in the host and prevent pathogen entry. The epidermal barrier is constantly renewed by differentiating keratinocytes through cornification, during which autophagy contributes to elimination of organelles and nucleus.

Corneal Complications after COVID-19 Vaccination: A Systemic Review.

Multiple vaccines are now being used across the world, and several studies have described cases of corneal graft rejection following the administration of the COVID-19 vaccine. The purpose of this article is to review the corneal adverse event that occurred following COVID-19 vaccine administration. The literature search was conducted in March 2022 using MEDLINE, PubMed, and the Cochrane Database of Systematic Reviews.

Comparing Multiple Linear Regression and Machine Learning in Predicting Diabetic Urine Albumin-Creatinine Ratio in a 4-Year Follow-Up Study.

The urine albumin-creatinine ratio (uACR) is a warning for the deterioration of renal function in type 2 diabetes (T2D). The early detection of ACR has become an important issue. Multiple linear regression (MLR) has traditionally been used to explore the relationships between risk factors and endpoints.

Intelligent and thermo-responsive Au-pluronic® F127 nanocapsules for Raman-enhancing detection of biomolecules.

Thermo-responsive Raman-enhanced nanocapsules were successfully fabricated by Pluronic® F127 (F127) decorated with gold nanoparticles (AuNPs) for surface-enhanced Raman scattering (SERS) detection of biomolecules. F127 nanocapsules changes from hydrophilicity (swelling) to hydrophobicity (de-swelling) when the temperature increases from 15 °C to 37 °C, owing to the lower critical solution temperature (LCST) of F127 is about 26.5 °C.

Disruptive technologies in health care disenchanted: a systematic review of concepts and examples.

Objectives: To clarify the concept of disruptive technologies in health care, provide examples and consider implications of potentially disruptive technologies for health technology assessment (HTA).

Methods: We conducted a systematic review of conceptual and empirical papers on healthcare technologies that are described as "" We searched MEDLINE and Embase from 2013 to April 2019 (updated in December 2021). Data extraction was done in duplicate by pairs of reviewers utilizing a data extraction form.

The reimbursement coverage decisions and pricing rules for medical devices in Taiwan.

Medical technology is undergoing rapid transformations, and the classifications of medical devices have also expanded greatly; therefore, it is necessary to develop appropriate reimbursement policies and pricing mechanisms in a timely manner. This paper aims to introduce the reimbursement coverage and pricing rules for medical devices in Taiwan. In addition, this paper identifies and evaluates available health technology assessments (HTA) and literature on published websites concerning medical device decision-making processes and pricing systems in South Korea and Japan, which are near Taiwan and have similar reimbursement coverage processes.