Perspectives in Clinical Research最新文献

Background: Good clinical practice (GCP) ensures ethical, as well as scientific quality of clinical trials, thus safeguarding participant safety and data integrity. The drug controller general of India mandates GCP training for healthcare professionals who conduct clinical research. However, limited studies assess the effectiveness of such training programs in India.

Aim: This study evaluates the impact of educational intervention on the knowledge and awareness of GCP among healthcare professionals.

Settings and design: A prospective, interventional study was conducted at our tertiary care teaching hospital.

Materials and methods: A total of 180 healthcare professionals participated in a GCP workshop, with 172 completing pre- and post-intervention questionnaires. The workshop covered essential GCP topics, including ethical guidelines, informed consent, regulatory requirements, and serious adverse event reporting.

Statistical analysis used: Pre- and postintervention responses were analyzed using Fischer's exact test in GraphPad Prism 8.4.2. P < 0.05 was considered statistically significant.

Results: The study revealed a significant improvement in participants' knowledge across multiple GCP domains. However, gaps remained in understanding specific regulatory timelines.

Conclusion: Educational interventions, such as GCP workshops, significantly enhance healthcare professionals' knowledge and awareness, improving compliance with ethical and regulatory requirements in clinical research. Integrating GCP training into medical education may further strengthen research practices.

Context: Adverse drug reaction (ADR) reporting in pharmacovigilance is critical for patient safety but often limited by resource constraints and manual inefficiencies. The integration of artificial intelligence (AI) has the potential to address these challenges by streamlining the reporting process.

Aims: The aim of the study was to assess the performance of an AI-enabled system for audio-to-text transcription, translation, ADR form completion, and causality assessment based on the World Health Organization-Uppsala Monitoring Centre scale.

Settings and design: A computational comparative, cross-sectional study involving healthcare professionals and patients to evaluate the AI system's functionality in a real-world pharmacovigilance setting.

Methodology: A hundred participants (50 healthcare professionals and 50 patients) provided audio-recorded ADR reports. These recordings were processed through the AI system to generate transcriptions, translations, and ADR forms. The system's performance was assessed using transcription metrics (word error rate [WER], character error rate [CER], Sentence Error Rate [SER]), translation metrics (bilingual evaluation understudy [BLEU] score, Translation Edit Rate [TER]), and ADR form accuracy. Causality assessments by the AI were compared against expert evaluations.

Statistical analysis used: Descriptive and analytical statistics (unpaired t-test) were applied to evaluate the performance metrics and compare results between the two participant groups.

Results: The AI system demonstrated high accuracy in transcription (WER <0.05, CER <0.04, and SER <0.35) and translation (BLEU >0.85 and TER <0.05). ADR form completion achieved near-perfect accuracy with minor discrepancies. Causality assessments were consistent across healthcare professional and patient data (P = 1).

Conclusions: The AI-enabled system effectively streamlined ADR reporting, ensuring accuracy in transcription, translation, and causality assessment while maintaining consistency across groups. Its integration into pharmacovigilance processes can reduce workloads, enhance reporting rates, and improve global health outcomes.

Aim: The aim of this study was to evaluate the comparative efficacy and safety of fixed-dose combinations of amlodipine 5 mg + hydrochlorothiazide 12.5 mg (A+H) (Group 1), telmisartan 40 mg + hydrochlorothiazide 12.5 mg (T+H) (Group 2), and ramipril 5 mg + hydrochlorothiazide 12.5 mg (R+H) (Group 3) in patients of essential hypertension.

Materials and methods: A prospective, randomized, open-labeled study was conducted for a period of 12 months (April 2023-March 2024), at a single tertiary care center involving 327 patients that were newly diagnosed with essential hypertension without any comorbid conditions. Patients were assessed at baseline, 15 days, 1 month, and then followed up at monthly intervals up to 6 months.

Results: In the study, significant reductions in systolic blood pressure (SBP) were noted for A+H with R+H at 3 and 4 months and for T+H with R+H from 3 to 6 months. Diastolic blood pressure (DBP) reductions were significant for A+H with R+H at 15 days and 1 month. T+H was significantly more effective than A+H and R+H in reducing SBP, while all groups showed comparable efficacy in reducing DBP over 6 months. Adverse drug reactions (ADRs) were highest in the A+H group at 29.4% and lowest in the T+H group at 19.8%.

Conclusion: This real-world clinical study provided valuable insights into the comparative efficacy of different antihypertensive drug combinations, with T+H being most effective in reducing SBP; in terms of DBP, all the groups were equally efficacious.

In an evolving healthcare ecosystem, it can be challenging to consistently deliver the most effective and efficient care. Design thinking can be an enabler to improve clinical outcomes in healthcare by potentially benefitting the design of new health products, processes, and devices. Clinical trials are vital for enhancing medical knowledge and development of new therapies. However, one of the most persistent challenges faced by sponsors and researchers is the process of patient recruitment in clinical trials. Effective recruitment strategies are crucial for the success of clinical trials, as inadequate enrollment can lead to delays, increased costs, and trial abandonment. Despite decades of efforts to address this issue, the struggle to find eligible patients, high screen failure rates, and competing sites for the same patient pool continue to plague the industry. Patient-centric activities to streamline study recruitment and enroll diverse patient populations have been explored. However, the outcomes of these initiatives have not been as expected, highlighting the need to explore these innovations further. Design thinking is a human-centered approach to problem-solving that emphasizes empathy, collaboration, and iterative testing. We feel it can offer novel insights into patients' needs and behaviors, leading to more engaging and effective recruitment strategies. This article explores the potential of design thinking as a transformative approach to tackle the challenge of patient recruitment in clinical trials, by examining its principles, processes, and benefits. Through this article, we aim to enable sponsors, patients, sites, and contract research organizations (CROs), to enhance enrollment in clinical trials by humanizing the patient trial experience.

This article deals with the various aspects of health-related quality of life (QoL) assessments, building upon a previous discussion of the concept and its measurement types. Specifically, the article will delve into number and timing of QoL assessments, calculating scores from QoL instruments, determining clinically meaningful changes in QoL, sample size calculation when QoL is an endpoint and handling missing data in QoL assessments.

Purpose/aim: Primary goal of epilepsy management is to completely eradicate the disease without causing much adverse effects. However, physicians are not achieving this despite availability of antiseizure medicines and therapeutic drug monitoring (TDM) services. The objective was to evaluate 3 years' time trend of antiseizure medications (ASMs) use and primarily compare TDM requisitions for older versus newer ASMs.

Materials and methods: This is an analytical, observational time-trend analysis (TTA) of TDM services. The author retrospectively assessed TDM records of 122 statistically computed patients receiving a total of 448 ASMs over 3 years period from January 2019 to December 2021 stored in the department. Z-test, Chi-square test for trend, and trendline were plotted to establish trend.

Results: Significant portion of the sample comprised older ASMs (252 of 448, 56.25% [95% confidence interval 46%-65%]). Comparison between monotherapy and polytherapy showed a statistically significant difference (P < 0.05) with trend for polytherapy. The minimum number of ASMs used in polytherapy was two, prescribed to 43.24% of people living with epilepsy. Of the two ASMs combined, the most common combination was of phenytoin and levetiracetam, prescribed to 31.25% of patients receiving two ASMs. Maximum number of ASMs prescribed to patients were five and seen in 2/74 of patients receiving polytherapy. Eighteen percent of referrals cited therapeutic failures with four adverse drug reactions (ADRs) documented at the therapeutic level.

Conclusion: TTA of ASMs showed that in between 2019 and 2021, there was rising trend for use of newer ASMs. Overall, TDM requisitions for older drugs were more in number than newer drugs. The majority were treated with >1 ASMs, and seizure control was satisfactory with few ADRs documented.

The placebo effect, observed when inert substances produce measurable health outcomes, has long intrigued researchers and clinicians. Traditionally attributed to psychological factors, recent evidence suggests neurobiological mechanisms may also contribute, though the exact pathways remain unclear. This review aims to provide an updated understanding of the placebo effect, exploring its underlying mechanisms, the factors influencing its variability, and its implications in both clinical research and practice. A comprehensive review of the literature was conducted, focusing on studies that examined psychological, genetic, and neurobiological contributions to the placebo effect. The review also considered the use of placebos in research, including their types, characteristics, and ethical considerations. Placebos can activate psychological mechanisms like expectation and conditioning, while neurobiological pathways involving the opioid and dopamine systems may also play a role. Genetic polymorphisms, such as those affecting the COMT enzyme, have been identified as potential predictors of placebo response. The scale of the placebo effect extends beyond subjective symptoms to physiological outcomes, including changes in heart rate, blood pressure, and brain activity. The placebo effect is influenced by multiple factors, including study design, disease type, and participant characteristics. High placebo response rates in certain conditions (e.g., pain, depression) raise questions about the reliability of test interventions. The ethical use of placebos, particularly in surgical and behavioral trials, remains a subject of debate. An improved understanding of placebo mechanisms is essential for optimizing its use in both research and clinical practice. Standardized reporting and ethical guidelines are necessary to ensure the integrity of placebo-controlled trials and the ethical application of placebo effects in patient care.