Patient-Reported Questionnaires to Identify Adverse Drug Reactions: A Systematic Review

Real-World Effectiveness of Biologics in Patients With Severe Asthma: Analysis of the KoSAR

PURPOSE

Severe asthma is associated with high morbidity and healthcare utilization; however, treatment options for these patients are limited. This study aimed to determine the therapeutic effects of biologics in clinical practice.

METHODS

This multicenter, retrospective cohort study included 136 patients who received biologics for at least 4 months between September 2017 and July 2022 at 25 medical centers affiliated with the Korean Severe Asthma Registry (KoSAR). The study evaluated the treatment effects, including acute exacerbation rates, maintenance of oral corticosteroid dosages, lung function, quality of life, blood eosinophil count, and fractional exhaled nitric oxide (FeNO) levels, by comparing measurements before and after 4 months of biologic treatment. Responses for each medication was evaluated based on the Global Evaluation of Treatment Effectiveness score, and any adverse reactions were summarized.

RESULTS

With the administration of biologics over the course of 4 months, there was a reduction in asthma acute exacerbations, a significant improvement in lung function, and a significant decrease in daily maintenance dose of oral steroid. Blood eosinophil counts decreased in the mepolizumab and reslizumab groups, while FeNO levels decreased only in the dupilumab group. The Asthma Control Test, Quality of Life Questionnaire for Adult Korean Asthmatics, and the EuroQol-visual analogue scale scores showed a significant improvement. Most patients (80.15%) responded to the biologic treatment. Meanwhile, non-responders often had chronic rhinosinusitis as a comorbidity, exhibited lower lung function, and required higher doses of oral steroids. No severe adverse events were reported.

CONCLUSIONS

Biologics are highly effective in Korean patients with Type 2 severe asthma, significantly reducing acute exacerbation rates and doses of oral corticosteroids, while also improving lung function. Therefore, it seems beneficial to administer biologics without any restrictions to patients exhibiting Type 2 severe asthma.

Retrospective Analysis of Patient-Reported Adverse Drug Reactions in an Italian Allergy Unit: ALLERG-RAF Study

INTRODUCTION

The Italian Medicines Agency indicates that about 5% of hospital admissions are due to adverse drug reactions (ADRs). Several factors are recognized to be associated with an increased risk for ADRs, such as the female gender and polytherapy. The aim of this study was to retrospectively analyze the suspected ADRs reported by patients during the anamnestic interview at the Allergy Unit.

PATIENTS AND METHODS

ALLERG-RAF study is a retrospective analysis of the medical records of patients evaluated in the Allergy Unit of ASST Spedali Civili and the University of Brescia from 2000 to 2016. The inclusion criteria were age ≥18 years and medical consultation requested for suspected ADRs. Data relating to the patient's intrinsic characteristics, the drug supposed to be the cause, and the prescribed pharmacological therapy were collected. Pseudonymized data from each patient were collected in an informatics database.

RESULTS

From 2000 to 2016, 35,817 accesses to the Allergy Unit were made, and 2,171 unique events related to a suspected ADR were collected in 1,840 patients. More than two-thirds of the reports concerned females (70.4%). Antibiotics were involved in the majority of the self-reported suspected ADRs (48.7%), particularly beta-lactams (61.1%). Anti-inflammatory drugs, mainly NSAIDs, were second in incidence and suspected in 25.2% of reports. As a site of ADR manifestation, most of the reported reactions involve the skin. No clinical sequelae were reported.

CONCLUSIONS

Our results underline the importance of patient reporting in pharmacovigilance. Furthermore, gender gap data emphasizes the importance of the gender-specific medicine approach.

Clinical Application of an Artificial Intelligence System for Diagnosing Thyroid Disease Based on a Computer Neural Network Deep Learning Model

Purpose

This study aimed to establish a stereoscopic neural learning network through deep learning and construct an artificial intelligence (AI) diagnosis system for the prediction of benign and malignant thyroid diseases, as well as repeatedly verified the diagnosis system and adjusted the data, in order to develop a type of AI-assisted thyroid diagnosis software with a low false negative rate and high sensitivity for clinical practice.

Patients and Methods

From July 2020 to April 2023, A total of 36 patients with thyroid nodules in our hospital were selected for diagnosis of thyroid nodules based on the Expert Consensus on Thyroid Ultrasound; samples were taken by aspiration biopsy or surgically and sent for pathological diagnosis. The ultrasonic diagnosis results were compared with the pathological results, a database was established based on the ultrasonic diagnostic characteristics and was entered in the AI-assisted diagnosis software for judgment of benign and malignant conditions. The data in the software were corrected based on the conformity rate and the reasons for misjudgment, and the corrected software was used to evaluate the benign and malignant conditions of the 36 patients, until the conformity rate exceeded 90%.

Results

The initial conformity rate of the AI software for identifying benign and malignant conditions was 88%, while that of the software utilizing the database was 94%.

Conclusion

We established a stereoscopic neural learning network and construct an AI diagnosis system for the prediction of benign and malignant thyroid diseases, with a low false negative rate and high sensitivity for clinical practice.

Systematic Review of Psychotropic Adverse Drug Event Monitoring Tools for Use in Long-Term Care Facilities

OBJECTIVES

To evaluate properties of psychotropic adverse drug event (ADE) monitoring tools intended for use in long-term care facilities.

DESIGN

Systematic review.

SETTING AND PARTICIPANTS

Adults aged 18 years and older in nursing homes and other long-term care facilities.

METHODS

Medline, CINAHL, Embase, and PsycInfo were searched from inception to August 2022 for studies reporting the development, validation, or application of tools to monitor psychotropic ADEs. Screening, data extraction, and quality assessment were performed independently by 2 authors. Each tool was assessed under the domains of test-retest reliability, interrater reliability, content validity, and construct validity.

RESULTS

Eight studies that described 6 tools were included. Tools were developed in Wales (n = 2), United States (n = 1), Ireland (n = 1), Canada (n = 1), and Singapore (n = 1). Tools monitored 4 to 95 items related to antipsychotics (n = 6 tools), antidepressants (n = 4), benzodiazepines or hypnotics (n = 4), antiepileptics (n = 4), and dementia medications (n = 1). Tools commonly monitored sedation, tiredness, or sleepiness (n = 6); falls (n = 4); and tremor or extrapyramidal symptoms (n = 4). Tools were designed for application by nurses (n = 4), during family conferences (n = 1), and by general medical practitioners before repeat prescribing (n = 1). Two tools were reported to require 10 to 60 minutes to administer. Four tools were determined to have adequate content validity and 2 tools adequate interrater reliability. No tools reported test-retest reliability or construct validity.

CONCLUSIONS AND IMPLICATIONS

Six published psychotropic ADE monitoring tools are heterogeneous in design and intended application. Existing tools are predominately designed for application by nurses with or without direct involvement of the wider multidisciplinary team. Further research is needed into models of care that facilitate psychotropic ADE monitoring in the long-term care facility setting, and the extent to which application of specific tools is associated with reduced medication-related harm.

Application of a WeChat-based mini-app as a patient reminder in Helicobacter pylori eradication: a prospective multi-center randomized controlled study

BACKGROUND

To improve the eradication rate of H. pylori, researchers have investigated the role of WeChat-based mini-app as an electronic reminding system in H. pylori treatment.

METHODS

Subjects from three medical centers were divided into two groups. Patients in the daily mini-app-based notification system group received daily notifications via the WeChat mini-app. Patients in the control group received one-time verbal education on the first clinical visit. Both groups received a 14-day quadruple therapy to eradicate H. pylori infection. Eradication rate, compliance, adverse events and satisfaction were evaluated.

RESULTS

Both intention-to-treat (ITT) and per-protocol (PP) analyses were conducted. The eradication rate in the daily mini-app-based notification system group was slightly higher compared with the control group (ITT analysis: 76.70% vs. 70.73%, p = 0.312; PP analysis: 85.87% vs. 82.86%, p = 0.562). The compliance was significantly higher in the daily mini-app-based notification system group (ITT analysis: 85.52% vs. 70.48%, p = 0.028; PP analysis: 92.39% vs. 81.90%, p = 0.030). The adverse event rates were similar between the two groups (PP analysis: 36.96% vs. 40.95%, p = 0.566). No significant difference in eradication rate was seen in each subgroup analysis by age, place of residence, grade of education, or endoscopic findings.

CONCLUSION

The study showed that daily mini-app-based notification improved patient compliance but not H. pylori eradication rate. Trial registration The research was registered in the Chinese Clinical Trial Registry (ChiCTR2000031011, 21/03/2020).

Correction: Lim et al. Patient-Reported Questionnaires to Identify Adverse Drug Reactions: A Systematic Review. Int. J. Environ. Res. Public Health 2021, 18, 11877

There was an error in the original publication [...].

Development of a web-based system to report medication-related adverse effects: a design and usability study (Preprint)

Background

Medicine use is the most common intervention in health care. The frequency with which medicines are used means medication-related problems are very common. One common type of medication-related problems is adverse drug events, which are unintended and harmful effects associated with use of medicines. Reporting of adverse drug events to regulatory authorities is important for evaluation of safety of medicines; however, these adverse effects are frequently unreported due to various factors, including lack of consumer-friendly reporting tools.

Objective

The aim of this study was to develop a user-friendly digital tool for consumers to report medication-related adverse effects.

Methods

The project consisted of 3 parts: (1) content development, including a systematic literature search; (2) iterative system development; and (3) usability testing. The project was guided by participatory design principles, which suggest involving key stakeholders throughout the design process. The first 2 versions were developed as a mobile app and were tested with end users in 2 workshops. The third version was developed as a web application and was tested with consumers who were taking regular medicines. Consumers were asked to complete a modified version of the mHealth app usability questionnaire (MAUQ), an 18-item questionnaire with each item scored using a 7-point Likert scale ranging from 0 (strongly disagree) to 7 (strongly agree). The MAUQ assessed 3 subscales including ease of use (5 items), interface and satisfaction (7 items), and usefulness (6 items). Continuous variables were reported as mean (SD) values, whereas categorical variables were presented as frequencies (percentages). Data analysis was conducted in Microsoft Excel.

Results

The content for the system was based on a systematic literature search and short-listing of questions, followed by feedback from project team members and consumers. Feedback from consumers in the 2 workshops were incorporated to improve the functionality, visual design, and stability of the third (current) version. The third version of the system was tested with 26 consumers. A total of 79% (N=307/390) of all responses on the MAUQ were scored 6 or 7, indicating that users generally strongly agree with the usability of the system. When looking at the individual domains, the system had an average score of 6.3 (SD 0.9) for “ease of use,” 6.3 (SD 0.8) for “interface and satisfaction,” and 5.2 (SD 1.4) for “usefulness.”

Conclusions

The web-based system for medicine adverse effects reporting is a user-friendly tool developed using an iterative participatory design approach. Future research includes further improving the system, particularly the usefulness of the system, as well as testing the scalability and performance of the system in practice.